Release v2.8.0

Implements extensible provider registry allowing users to register custom providers (e.g., Cloudflare, Ollama) alongside built-in providers. Updates `providers` CLI command to show registered/builtin/custom providers with `list` and `info` subcommands. Enhances `createProvider()` to accept provider instances, spec objects, or strings. Updates `hasApiKey()` to support provider aliases and custom env vars. Exports registry functions (`register

docker/Dockerfile.chat

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.7.8" \
+    "praisonai>=2.8.0" \
     "praisonai[chat]" \
     "embedchain[github,youtube]"
 

docker/Dockerfile.dev

@@ -20,7 +20,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.7.8" \
+    "praisonai>=2.8.0" \
     "praisonai[ui]" \
     "praisonai[chat]" \
     "praisonai[realtime]" \

docker/Dockerfile.ui

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     praisonai_tools \
-    "praisonai>=2.7.8" \
+    "praisonai>=2.8.0" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/js/ai-sdk/README.md

@@ -0,0 +1,41 @@
+# AI SDK Examples
+
+Examples demonstrating the AI SDK integration in PraisonAI TypeScript.
+
+## Prerequisites
+
+```bash
+npm install praisonai ai @ai-sdk/openai @ai-sdk/anthropic @ai-sdk/google zod
+```
+
+## Environment Variables
+
+```bash
+export OPENAI_API_KEY=sk-...
+export ANTHROPIC_API_KEY=sk-ant-...
+export GOOGLE_API_KEY=AIza...
+```
+
+## Examples
+
+| File | Description |
+|------|-------------|
+| `basic-chat.ts` | Simple text generation |
+| `streaming.ts` | Streaming text output |
+| `tool-calling.ts` | Function/tool calling |
+| `multi-provider.ts` | Using multiple providers |
+| `structured-output.ts` | JSON schema output |
+| `multi-agent.ts` | Multi-agent attribution |
+
+## Running Examples
+
+```bash
+npx ts-node basic-chat.ts
+npx ts-node streaming.ts
+npx ts-node tool-calling.ts
+```
+
+## More Information
+
+- [AI SDK Documentation](https://docs.praisonai.com/docs/js/ai-sdk)
+- [AI SDK CLI](https://docs.praisonai.com/docs/js/ai-sdk-cli)

examples/js/ai-sdk/basic-chat.ts

@@ -0,0 +1,39 @@
+/**
+ * AI SDK Basic Chat Example
+ * 
+ * Demonstrates simple text generation using the AI SDK backend.
+ * 
+ * Usage:
+ *   npx ts-node basic-chat.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from 'praisonai';
+
+async function main() {
+  // Create backend with model string
+  const backend = createAISDKBackend('openai/gpt-4o-mini');
+
+  console.log('Sending message to OpenAI...\n');
+
+  // Generate text
+  const result = await backend.generateText({
+    messages: [
+      { role: 'system', content: 'You are a helpful assistant.' },
+      { role: 'user', content: 'What are the three primary colors?' }
+    ],
+    maxTokens: 200,
+    temperature: 0.7,
+  });
+
+  console.log('Response:', result.text);
+  console.log('\nFinish reason:', result.finishReason);
+  
+  if (result.usage) {
+    console.log('Token usage:', result.usage);
+  }
+}
+
+main().catch(console.error);

examples/js/ai-sdk/multi-agent.ts

@@ -0,0 +1,96 @@
+/**
+ * AI SDK Multi-Agent Attribution Example
+ * 
+ * Demonstrates how to propagate attribution context (agentId, runId, traceId)
+ * to LLM calls for multi-agent observability and safety.
+ * 
+ * Usage:
+ *   npx ts-node multi-agent.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from 'praisonai';
+
+// Simulate a multi-agent system with attribution
+interface AgentContext {
+  agentId: string;
+  runId: string;
+  traceId: string;
+  sessionId?: string;
+}
+
+async function runAgent(name: string, task: string, context: AgentContext) {
+  console.log(`\n[${name}] Starting task: ${task}`);
+  console.log(`  Attribution: agentId=${context.agentId}, runId=${context.runId}`);
+
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    attribution: context,
+    timeout: 30000,
+  });
+
+  const result = await backend.generateText({
+    messages: [
+      { role: 'system', content: `You are ${name}, a specialized AI agent.` },
+      { role: 'user', content: task }
+    ],
+    maxTokens: 100,
+  });
+
+  console.log(`  Response: ${result.text.slice(0, 100)}...`);
+  return result.text;
+}
+
+async function main() {
+  // Create a shared trace ID for the entire workflow
+  const traceId = `trace-${Date.now().toString(36)}`;
+  const sessionId = 'session-user123';
+
+  console.log('Multi-Agent Workflow with Attribution');
+  console.log('=====================================');
+  console.log(`Trace ID: ${traceId}`);
+  console.log(`Session ID: ${sessionId}`);
+
+  // Agent 1: Research Agent
+  const researchResult = await runAgent(
+    'ResearchAgent',
+    'What are the key benefits of TypeScript?',
+    {
+      agentId: 'agent-research',
+      runId: `run-${Date.now().toString(36)}-1`,
+      traceId,
+      sessionId,
+    }
+  );
+
+  // Agent 2: Summary Agent
+  const summaryResult = await runAgent(
+    'SummaryAgent',
+    `Summarize this in one sentence: ${researchResult}`,
+    {
+      agentId: 'agent-summary',
+      runId: `run-${Date.now().toString(36)}-2`,
+      traceId,
+      sessionId,
+    }
+  );
+
+  // Agent 3: Review Agent
+  await runAgent(
+    'ReviewAgent',
+    `Review this summary for accuracy: ${summaryResult}`,
+    {
+      agentId: 'agent-review',
+      runId: `run-${Date.now().toString(36)}-3`,
+      traceId,
+      sessionId,
+    }
+  );
+
+  console.log('\n\nWorkflow complete!');
+  console.log('All requests were tagged with the same trace ID for observability.');
+  console.log('Check your LLM provider dashboard to see the correlated requests.');
+}
+
+main().catch(console.error);

examples/js/ai-sdk/multi-provider.ts

@@ -0,0 +1,59 @@
+/**
+ * AI SDK Multi-Provider Example
+ * 
+ * Demonstrates using multiple LLM providers with the same interface.
+ * 
+ * Usage:
+ *   npx ts-node multi-provider.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ *   ANTHROPIC_API_KEY - Your Anthropic API key
+ *   GOOGLE_API_KEY - Your Google API key
+ */
+
+import { createAISDKBackend } from 'praisonai';
+
+const PROMPT = 'Explain what an API is in one sentence.';
+
+async function testProvider(modelString: string) {
+  try {
+    const backend = createAISDKBackend(modelString, {
+      timeout: 30000,
+    });
+
+    const startTime = Date.now();
+    const result = await backend.generateText({
+      messages: [{ role: 'user', content: PROMPT }],
+      maxTokens: 100,
+    });
+    const duration = Date.now() - startTime;
+
+    console.log(`\n${modelString}:`);
+    console.log(`  Response: ${result.text}`);
+    console.log(`  Duration: ${duration}ms`);
+    return true;
+  } catch (error: any) {
+    console.log(`\n${modelString}:`);
+    console.log(`  Error: ${error.message}`);
+    return false;
+  }
+}
+
+async function main() {
+  console.log('Testing multiple providers with the same prompt...');
+  console.log(`Prompt: "${PROMPT}"`);
+
+  const providers = [
+    'openai/gpt-4o-mini',
+    'anthropic/claude-3-haiku-20240307',
+    'google/gemini-1.5-flash',
+  ];
+
+  const results = await Promise.all(providers.map(testProvider));
+  
+  const successful = results.filter(Boolean).length;
+  console.log(`\n\nSummary: ${successful}/${providers.length} providers succeeded`);
+}
+
+main().catch(console.error);

examples/js/ai-sdk/streaming.ts

@@ -0,0 +1,39 @@
+/**
+ * AI SDK Streaming Example
+ * 
+ * Demonstrates streaming text generation with real-time output.
+ * 
+ * Usage:
+ *   npx ts-node streaming.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from 'praisonai';
+
+async function main() {
+  const backend = createAISDKBackend('openai/gpt-4o-mini');
+
+  console.log('Streaming response from OpenAI...\n');
+
+  const stream = await backend.streamText({
+    messages: [
+      { role: 'user', content: 'Write a short poem about coding.' }
+    ],
+    maxTokens: 200,
+  });
+
+  // Stream chunks as they arrive
+  for await (const chunk of stream) {
+    if (chunk.text) {
+      process.stdout.write(chunk.text);
+    }
+    
+    if (chunk.finishReason) {
+      console.log('\n\nFinish reason:', chunk.finishReason);
+    }
+  }
+}
+
+main().catch(console.error);

examples/js/ai-sdk/structured-output.ts

@@ -0,0 +1,72 @@
+/**
+ * AI SDK Structured Output Example
+ * 
+ * Demonstrates generating typed JSON objects with Zod schemas.
+ * 
+ * Usage:
+ *   npx ts-node structured-output.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { generateObject } from 'ai';
+import { openai } from '@ai-sdk/openai';
+import { z } from 'zod';
+
+// Define schema for a person profile
+const PersonSchema = z.object({
+  name: z.string().describe('Full name'),
+  age: z.number().describe('Age in years'),
+  occupation: z.string().describe('Job title'),
+  city: z.string().describe('City of residence'),
+  interests: z.array(z.string()).describe('List of hobbies/interests'),
+  bio: z.string().describe('Short biography'),
+});
+
+// Define schema for a recipe
+const RecipeSchema = z.object({
+  name: z.string().describe('Recipe name'),
+  cuisine: z.string().describe('Type of cuisine'),
+  prepTime: z.number().describe('Preparation time in minutes'),
+  cookTime: z.number().describe('Cooking time in minutes'),
+  servings: z.number().describe('Number of servings'),
+  ingredients: z.array(z.object({
+    item: z.string(),
+    amount: z.string(),
+  })).describe('List of ingredients'),
+  instructions: z.array(z.string()).describe('Step-by-step instructions'),
+});
+
+async function main() {
+  console.log('Generating structured output with Zod schemas...\n');
+
+  // Generate a person profile
+  console.log('1. Generating a fictional person profile...');
+  const personResult = await generateObject({
+    model: openai('gpt-4o-mini'),
+    schema: PersonSchema,
+    prompt: 'Generate a fictional software engineer profile.',
+  });
+
+  console.log('Person:', JSON.stringify(personResult.object, null, 2));
+
+  // Generate a recipe
+  console.log('\n2. Generating a recipe...');
+  const recipeResult = await generateObject({
+    model: openai('gpt-4o-mini'),
+    schema: RecipeSchema,
+    prompt: 'Generate a simple pasta recipe.',
+  });
+
+  console.log('Recipe:', JSON.stringify(recipeResult.object, null, 2));
+
+  // Type-safe access
+  console.log('\n3. Type-safe access:');
+  console.log(`  Person name: ${personResult.object.name}`);
+  console.log(`  Person age: ${personResult.object.age}`);
+  console.log(`  Recipe name: ${recipeResult.object.name}`);
+  console.log(`  Total time: ${recipeResult.object.prepTime + recipeResult.object.cookTime} minutes`);
+}
+
+main().catch(console.error);

examples/js/ai-sdk/tool-calling.ts

@@ -0,0 +1,75 @@
+/**
+ * AI SDK Tool Calling Example
+ * 
+ * Demonstrates function/tool calling with Zod schemas.
+ * 
+ * Usage:
+ *   npx ts-node tool-calling.ts
+ * 
+ * Environment:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { generateText, tool } from 'ai';
+import { openai } from '@ai-sdk/openai';
+import { z } from 'zod';
+
+// Define tools with Zod schemas
+const tools = {
+  get_weather: tool({
+    description: 'Get the current weather for a city',
+    inputSchema: z.object({
+      city: z.string().describe('The city name'),
+      unit: z.enum(['celsius', 'fahrenheit']).optional().describe('Temperature unit'),
+    }),
+    execute: async ({ city, unit = 'celsius' }) => {
+      // Mock weather data
+      const weather = {
+        city,
+        temperature: unit === 'celsius' ? 22 : 72,
+        unit,
+        condition: 'sunny',
+        humidity: 45,
+      };
+      return weather;
+    },
+  }),
+  
+  get_time: tool({
+    description: 'Get the current time in a timezone',
+    inputSchema: z.object({
+      timezone: z.string().describe('Timezone like "America/New_York"'),
+    }),
+    execute: async ({ timezone }) => {
+      const time = new Date().toLocaleString('en-US', { timeZone: timezone });
+      return { timezone, time };
+    },
+  }),
+};
+
+async function main() {
+  console.log('Asking about weather with tool calling...\n');
+
+  const result = await generateText({
+    model: openai('gpt-4o-mini'),
+    messages: [
+      { role: 'user', content: 'What is the weather in Paris and what time is it in New York?' }
+    ],
+    tools,
+    maxSteps: 5, // Allow multiple tool calls
+  });
+
+  console.log('Tool Calls:');
+  for (const toolCall of result.toolCalls) {
+    console.log(`  - ${toolCall.toolName}:`, toolCall.args);
+  }
+
+  console.log('\nTool Results:');
+  for (const toolResult of result.toolResults) {
+    console.log(`  - ${toolResult.toolName}:`, toolResult.result);
+  }
+
+  console.log('\nFinal Response:', result.text);
+}
+
+main().catch(console.error);

examples/provider-registry/custom_provider_example.py

@@ -0,0 +1,225 @@
+"""
+Custom Provider Registry Example (Python)
+
+This example demonstrates how to register and use custom LLM providers
+with the PraisonAI Python wrapper.
+
+Note: The Python provider registry is for custom provider extensions.
+Built-in providers (OpenAI, Anthropic, Google) are handled by LiteLLM
+in praisonaiagents automatically.
+"""
+
+import sys
+sys.path.insert(0, '../../src/praisonai')
+
+from praisonai.llm import (
+    LLMProviderRegistry,
+    register_llm_provider,
+    unregister_llm_provider,
+    has_llm_provider,
+    list_llm_providers,
+    create_llm_provider,
+    get_default_llm_registry,
+    parse_model_string
+)
+
+
+# Example 1: Simple Custom Provider
+# ---------------------------------
+
+class SimpleCustomProvider:
+    """A minimal custom provider example."""
+    
+    provider_id = "simple-custom"
+    
+    def __init__(self, model_id: str, config: dict = None):
+        self.model_id = model_id
+        self.config = config or {}
+        self.api_endpoint = self.config.get('api_endpoint', 'https://api.example.com')
+    
+    def generate(self, prompt: str) -> str:
+        """Generate a response (simulated)."""
+        print(f"[SimpleCustomProvider] Generating with model: {self.model_id}")
+        print(f"[SimpleCustomProvider] Prompt: {prompt[:50]}...")
+        return f"Response from {self.provider_id}/{self.model_id}: Hello! This is a simulated response."
+
+
+# Example 2: Ollama Provider
+# --------------------------
+
+class OllamaProvider:
+    """Custom provider for local Ollama integration."""
+    
+    provider_id = "ollama"
+    
+    def __init__(self, model_id: str, config: dict = None):
+        self.model_id = model_id
+        self.config = config or {}
+        self.base_url = self.config.get('base_url', 'http://localhost:11434')
+    
+    def generate(self, prompt: str) -> str:
+        """Generate a response using Ollama API."""
+        import requests
+        
+        response = requests.post(
+            f"{self.base_url}/api/generate",
+            json={
+                "model": self.model_id,
+                "prompt": prompt,
+                "stream": False
+            }
+        )
+        
+        if response.status_code != 200:
+            raise Exception(f"Ollama API error: {response.text}")
+        
+        return response.json().get("response", "")
+    
+    def generate_stream(self, prompt: str):
+        """Generate a streaming response using Ollama API."""
+        import requests
+        
+        response = requests.post(
+            f"{self.base_url}/api/generate",
+            json={
+                "model": self.model_id,
+                "prompt": prompt,
+                "stream": True
+            },
+            stream=True
+        )
+        
+        for line in response.iter_lines():
+            if line:
+                import json
+                data = json.loads(line)
+                yield data.get("response", "")
+                if data.get("done"):
+                    break
+
+
+# Example 3: Cloudflare Workers AI Provider
+# -----------------------------------------
+
+class CloudflareProvider:
+    """Custom provider for Cloudflare Workers AI."""
+    
+    provider_id = "cloudflare"
+    
+    def __init__(self, model_id: str, config: dict = None):
+        self.model_id = model_id
+        self.config = config or {}
+        self.account_id = self.config.get('account_id')
+        self.api_token = self.config.get('api_token')
+    
+    def generate(self, prompt: str) -> str:
+        """Generate a response using Cloudflare Workers AI."""
+        import requests
+        
+        if not self.account_id or not self.api_token:
+            raise ValueError("Cloudflare account_id and api_token are required")
+        
+        response = requests.post(
+            f"https://api.cloudflare.com/client/v4/accounts/{self.account_id}/ai/run/{self.model_id}",
+            headers={
+                "Authorization": f"Bearer {self.api_token}",
+                "Content-Type": "application/json"
+            },
+            json={"prompt": prompt}
+        )
+        
+        if response.status_code != 200:
+            raise Exception(f"Cloudflare API error: {response.text}")
+        
+        return response.json().get("result", {}).get("response", "")
+
+
+def main():
+    print("=== Provider Registry Example (Python) ===\n")
+    
+    # Check initial state
+    print("Initial providers:", list_llm_providers())
+    print()
+    
+    # Register custom providers
+    print("Registering custom providers...")
+    register_llm_provider("simple-custom", SimpleCustomProvider)
+    register_llm_provider("ollama", OllamaProvider, aliases=["local"])
+    register_llm_provider("cloudflare", CloudflareProvider, aliases=["cf", "workers-ai"])
+    print()
+    
+    # Check providers after registration
+    print("Providers after registration:", list_llm_providers())
+    print("Has ollama:", has_llm_provider("ollama"))
+    print("Has local (alias):", has_llm_provider("local"))
+    print("Has cloudflare:", has_llm_provider("cloudflare"))
+    print("Has cf (alias):", has_llm_provider("cf"))
+    print()
+    
+    # Parse model strings
+    print("=== Model String Parsing ===\n")
+    
+    test_strings = [
+        "openai/gpt-4o-mini",
+        "gpt-4o-mini",
+        "claude-3-5-sonnet-latest",
+        "gemini-2.0-flash",
+        "ollama/llama2",
+        "cloudflare/workers-ai-model"
+    ]
+    
+    for model_str in test_strings:
+        parsed = parse_model_string(model_str)
+        print(f"  '{model_str}' -> provider={parsed['provider_id']}, model={parsed['model_id']}")
+    print()
+    
+    # Create and use providers
+    print("=== Using Custom Providers ===\n")
+    
+    # Use simple custom provider
+    provider = create_llm_provider("simple-custom/test-model")
+    print(f"Created provider: {provider.provider_id}/{provider.model_id}")
+    response = provider.generate("Hello, world!")
+    print(f"Response: {response}")
+    print()
+    
+    # Use ollama provider via alias
+    provider = create_llm_provider("local/llama2", config={"base_url": "http://localhost:11434"})
+    print(f"Created provider: {provider.provider_id}/{provider.model_id}")
+    print()
+    
+    # Demonstrate error handling
+    print("=== Error Handling ===\n")
+    try:
+        create_llm_provider("unknown-provider/model")
+    except ValueError as e:
+        print(f"Expected error: {e}")
+    print()
+    
+    # Demonstrate isolated registries
+    print("=== Isolated Registries ===\n")
+    
+    # Create isolated registry
+    isolated_registry = LLMProviderRegistry()
+    isolated_registry.register("isolated-provider", SimpleCustomProvider)
+    
+    print(f"Default registry providers: {list_llm_providers()}")
+    print(f"Isolated registry providers: {isolated_registry.list()}")
+    
+    # Use isolated registry
+    provider = create_llm_provider("isolated-provider/model", registry=isolated_registry)
+    print(f"Created from isolated registry: {provider.provider_id}/{provider.model_id}")
+    print()
+    
+    # Cleanup
+    print("=== Cleanup ===\n")
+    unregister_llm_provider("simple-custom")
+    unregister_llm_provider("ollama")
+    unregister_llm_provider("cloudflare")
+    print(f"Providers after cleanup: {list_llm_providers()}")
+    
+    print("\n=== Example Complete ===")
+
+
+if __name__ == "__main__":
+    main()

examples/provider-registry/custom_provider_example.ts

@@ -0,0 +1,239 @@
+/**
+ * Custom Provider Registry Example
+ * 
+ * This example demonstrates how to register and use custom LLM providers
+ * with the PraisonAI TypeScript SDK.
+ */
+
+import {
+  registerProvider,
+  createProvider,
+  BaseProvider,
+  listProviders,
+  hasProvider,
+  type ProviderConfig,
+  type GenerateTextOptions,
+  type GenerateTextResult,
+  type StreamTextOptions,
+  type StreamChunk,
+  type GenerateObjectOptions,
+  type GenerateObjectResult,
+  type Message,
+  type ToolDefinition
+} from 'praisonai';
+
+// Example 1: Simple Custom Provider
+// ---------------------------------
+// A minimal custom provider that wraps a hypothetical API
+
+class SimpleCustomProvider extends BaseProvider {
+  readonly providerId = 'simple-custom';
+  private apiEndpoint: string;
+
+  constructor(modelId: string, config?: ProviderConfig) {
+    super(modelId, config);
+    this.apiEndpoint = (config as any)?.apiEndpoint || 'https://api.example.com';
+  }
+
+  async generateText(options: GenerateTextOptions): Promise<GenerateTextResult> {
+    // In a real implementation, you would call your API here
+    console.log(`[SimpleCustomProvider] Generating text with model: ${this.modelId}`);
+    console.log(`[SimpleCustomProvider] Messages:`, options.messages);
+    
+    // Simulated response
+    return {
+      text: `Response from ${this.providerId}/${this.modelId}: Hello! This is a simulated response.`,
+      usage: {
+        promptTokens: 10,
+        completionTokens: 20,
+        totalTokens: 30
+      }
+    };
+  }
+
+  async *streamText(options: StreamTextOptions): AsyncGenerator<StreamChunk> {
+    const words = ['Hello', 'from', 'streaming', 'response!'];
+    for (const word of words) {
+      yield { text: word + ' ', done: false };
+      await new Promise(resolve => setTimeout(resolve, 100));
+    }
+    yield { text: '', done: true };
+  }
+
+  async generateObject<T>(options: GenerateObjectOptions<T>): Promise<GenerateObjectResult<T>> {
+    // Simulated structured output
+    return {
+      object: { message: 'Structured response' } as T,
+      usage: {
+        promptTokens: 10,
+        completionTokens: 20,
+        totalTokens: 30
+      }
+    };
+  }
+
+  formatTools(tools: ToolDefinition[]): any[] {
+    return tools;
+  }
+
+  formatMessages(messages: Message[]): any[] {
+    return messages;
+  }
+}
+
+// Example 2: Ollama Provider
+// --------------------------
+// A more realistic example for local Ollama integration
+
+class OllamaProvider extends BaseProvider {
+  readonly providerId = 'ollama';
+  private baseUrl: string;
+
+  constructor(modelId: string, config?: ProviderConfig) {
+    super(modelId, config);
+    this.baseUrl = (config as any)?.baseUrl || 'http://localhost:11434';
+  }
+
+  async generateText(options: GenerateTextOptions): Promise<GenerateTextResult> {
+    const response = await fetch(`${this.baseUrl}/api/generate`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        model: this.modelId,
+        prompt: options.messages.map(m => `${m.role}: ${m.content}`).join('\n'),
+        stream: false
+      })
+    });
+
+    if (!response.ok) {
+      throw new Error(`Ollama API error: ${response.statusText}`);
+    }
+
+    const data = await response.json();
+    return {
+      text: data.response,
+      usage: {
+        promptTokens: data.prompt_eval_count || 0,
+        completionTokens: data.eval_count || 0,
+        totalTokens: (data.prompt_eval_count || 0) + (data.eval_count || 0)
+      }
+    };
+  }
+
+  async *streamText(options: StreamTextOptions): AsyncGenerator<StreamChunk> {
+    const response = await fetch(`${this.baseUrl}/api/generate`, {
+      method: 'POST',
+      headers: { 'Content-Type': 'application/json' },
+      body: JSON.stringify({
+        model: this.modelId,
+        prompt: options.messages.map(m => `${m.role}: ${m.content}`).join('\n'),
+        stream: true
+      })
+    });
+
+    if (!response.ok) {
+      throw new Error(`Ollama API error: ${response.statusText}`);
+    }
+
+    const reader = response.body?.getReader();
+    if (!reader) throw new Error('No response body');
+
+    const decoder = new TextDecoder();
+    while (true) {
+      const { done, value } = await reader.read();
+      if (done) break;
+      
+      const chunk = decoder.decode(value);
+      const lines = chunk.split('\n').filter(line => line.trim());
+      
+      for (const line of lines) {
+        try {
+          const data = JSON.parse(line);
+          yield { text: data.response || '', done: data.done || false };
+        } catch {
+          // Skip invalid JSON
+        }
+      }
+    }
+  }
+
+  async generateObject<T>(options: GenerateObjectOptions<T>): Promise<GenerateObjectResult<T>> {
+    const result = await this.generateText({
+      messages: [
+        ...options.messages,
+        { role: 'system', content: `Respond with valid JSON matching this schema: ${JSON.stringify(options.schema)}` }
+      ]
+    });
+
+    return {
+      object: JSON.parse(result.text) as T,
+      usage: result.usage
+    };
+  }
+
+  formatTools(tools: ToolDefinition[]): any[] {
+    return tools;
+  }
+
+  formatMessages(messages: Message[]): any[] {
+    return messages;
+  }
+}
+
+// Main Example
+// ------------
+
+async function main() {
+  console.log('=== Provider Registry Example ===\n');
+
+  // Check initial providers
+  console.log('Initial providers:', listProviders());
+  console.log('Has openai:', hasProvider('openai'));
+  console.log('Has ollama:', hasProvider('ollama'));
+  console.log();
+
+  // Register custom providers
+  console.log('Registering custom providers...');
+  registerProvider('simple-custom', SimpleCustomProvider);
+  registerProvider('ollama', OllamaProvider, { aliases: ['local'] });
+  console.log();
+
+  // Check providers after registration
+  console.log('Providers after registration:', listProviders());
+  console.log('Has ollama:', hasProvider('ollama'));
+  console.log('Has local (alias):', hasProvider('local'));
+  console.log();
+
+  // Create and use providers
+  console.log('=== Using Custom Providers ===\n');
+
+  // Use simple custom provider
+  const simpleProvider = createProvider('simple-custom/test-model');
+  console.log(`Created provider: ${simpleProvider.providerId}/${simpleProvider.modelId}`);
+  
+  const simpleResult = await simpleProvider.generateText({
+    messages: [{ role: 'user', content: 'Hello!' }]
+  });
+  console.log('Response:', simpleResult.text);
+  console.log('Usage:', simpleResult.usage);
+  console.log();
+
+  // Use ollama provider via alias
+  const ollamaProvider = createProvider('local/llama2', {
+    baseUrl: 'http://localhost:11434'
+  } as any);
+  console.log(`Created provider: ${ollamaProvider.providerId}/${ollamaProvider.modelId}`);
+  console.log();
+
+  // Demonstrate error handling for unknown provider
+  console.log('=== Error Handling ===\n');
+  try {
+    createProvider('unknown-provider/model');
+  } catch (error: any) {
+    console.log('Expected error:', error.message);
+  }
+
+  console.log('\n=== Example Complete ===');
+}
+
+main().catch(console.error);

examples/provider-registry/isolated_registry_example.py

@@ -0,0 +1,197 @@
+"""
+Isolated Registry Example - Multi-Agent Safety
+
+This example demonstrates how to use isolated registries to prevent
+provider registration collisions in multi-agent scenarios.
+
+Key concepts:
+- Each agent/context can have its own registry
+- No global state mutation
+- Safe for concurrent/parallel runs
+- Different agents can use different provider implementations
+
+Requirements:
+- pip install praisonai
+"""
+
+import sys
+sys.path.insert(0, '../../src/praisonai')
+
+from praisonai.llm import (
+    LLMProviderRegistry,
+    create_llm_provider,
+    register_llm_provider,
+    get_default_llm_registry,
+    _reset_default_registry
+)
+
+
+# Define two different provider implementations with the same name
+class Agent1Provider:
+    """Provider implementation for Agent 1."""
+    provider_id = "custom"
+    
+    def __init__(self, model_id, config=None):
+        self.model_id = model_id
+        self.config = config or {}
+        self.agent_name = "Agent1"
+    
+    def generate(self, prompt):
+        return f"[{self.agent_name}] Response to: {prompt}"
+
+
+class Agent2Provider:
+    """Provider implementation for Agent 2 - different behavior."""
+    provider_id = "custom"
+    
+    def __init__(self, model_id, config=None):
+        self.model_id = model_id
+        self.config = config or {}
+        self.agent_name = "Agent2"
+    
+    def generate(self, prompt):
+        return f"[{self.agent_name}] Different response to: {prompt}"
+
+
+def demonstrate_collision_problem():
+    """Show what happens with global registry collisions."""
+    print("=== Problem: Global Registry Collision ===\n")
+    
+    # Reset to clean state
+    _reset_default_registry()
+    
+    # Agent 1 registers "custom" provider
+    register_llm_provider("custom", Agent1Provider)
+    print("Agent 1 registered 'custom' provider")
+    
+    # Agent 2 tries to register same name - ERROR!
+    try:
+        register_llm_provider("custom", Agent2Provider)
+        print("Agent 2 registered 'custom' provider")
+    except ValueError as e:
+        print(f"Agent 2 FAILED: {e}")
+    
+    print()
+    print("Problem: Both agents want to use 'custom' but with different implementations.")
+    print("Solution: Use isolated registries.\n")
+
+
+def demonstrate_isolated_solution():
+    """Show how isolated registries solve the collision problem."""
+    print("=== Solution: Isolated Registries ===\n")
+    
+    # Create isolated registries for each agent
+    agent1_registry = LLMProviderRegistry()
+    agent2_registry = LLMProviderRegistry()
+    
+    # Each agent registers its own "custom" provider
+    agent1_registry.register("custom", Agent1Provider)
+    agent2_registry.register("custom", Agent2Provider)
+    
+    print("Agent 1 registry providers:", agent1_registry.list())
+    print("Agent 2 registry providers:", agent2_registry.list())
+    print()
+    
+    # Create providers from each registry
+    provider1 = create_llm_provider("custom/model-v1", registry=agent1_registry)
+    provider2 = create_llm_provider("custom/model-v1", registry=agent2_registry)
+    
+    # They have different implementations!
+    print("Provider 1 response:", provider1.generate("Hello"))
+    print("Provider 2 response:", provider2.generate("Hello"))
+    print()
+    
+    # Verify isolation
+    print("Verification:")
+    print(f"  provider1.agent_name = {provider1.agent_name}")
+    print(f"  provider2.agent_name = {provider2.agent_name}")
+    print(f"  Same class? {type(provider1) == type(provider2)}")
+    print()
+
+
+def demonstrate_parallel_agents():
+    """Simulate parallel agent execution with isolated registries."""
+    print("=== Parallel Agent Simulation ===\n")
+    
+    def run_agent(agent_id, registry):
+        """Simulate an agent run with its own registry."""
+        provider = create_llm_provider("custom/model", registry=registry)
+        result = provider.generate(f"Query from agent {agent_id}")
+        return result
+    
+    # Setup registries
+    registries = {}
+    for i in range(3):
+        reg = LLMProviderRegistry()
+        # Each agent gets a slightly different provider
+        class DynamicProvider:
+            provider_id = "custom"
+            def __init__(self, model_id, config=None):
+                self.model_id = model_id
+                self.agent_id = i  # Capture agent ID
+            def generate(self, prompt):
+                return f"Agent-{self.agent_id} processed: {prompt}"
+        
+        reg.register("custom", DynamicProvider)
+        registries[i] = reg
+    
+    # Simulate parallel execution
+    print("Simulating parallel agent runs:")
+    for agent_id, registry in registries.items():
+        result = run_agent(agent_id, registry)
+        print(f"  {result}")
+    
+    print()
+    print("Each agent used its own isolated registry - no collisions!")
+    print()
+
+
+def demonstrate_shared_vs_isolated():
+    """Compare shared (global) vs isolated registry patterns."""
+    print("=== Shared vs Isolated Patterns ===\n")
+    
+    # Reset global registry
+    _reset_default_registry()
+    
+    # Pattern 1: Shared (global) registry
+    print("Pattern 1: Shared Registry (use for app-wide providers)")
+    register_llm_provider("shared-provider", Agent1Provider)
+    
+    # All code sees the same provider
+    global_reg = get_default_llm_registry()
+    print(f"  Global registry has 'shared-provider': {global_reg.has('shared-provider')}")
+    
+    # Pattern 2: Isolated registry
+    print("\nPattern 2: Isolated Registry (use for per-agent/per-run providers)")
+    isolated = LLMProviderRegistry()
+    isolated.register("isolated-provider", Agent2Provider)
+    
+    # Only code with reference to this registry sees it
+    print(f"  Isolated registry has 'isolated-provider': {isolated.has('isolated-provider')}")
+    print(f"  Global registry has 'isolated-provider': {global_reg.has('isolated-provider')}")
+    
+    print()
+    print("Recommendation:")
+    print("  - Use global registry for app-wide, stable providers")
+    print("  - Use isolated registries for per-agent or per-run customization")
+    print()
+
+
+def main():
+    print("=" * 60)
+    print("Isolated Registry Example - Multi-Agent Safety")
+    print("=" * 60)
+    print()
+    
+    demonstrate_collision_problem()
+    demonstrate_isolated_solution()
+    demonstrate_parallel_agents()
+    demonstrate_shared_vs_isolated()
+    
+    print("=" * 60)
+    print("Example Complete")
+    print("=" * 60)
+
+
+if __name__ == "__main__":
+    main()

src/praisonai-ts/examples/ai-sdk/basic-chat.ts

@@ -0,0 +1,42 @@
+/**
+ * AI SDK Basic Chat Example
+ * 
+ * Demonstrates basic text generation using the AI SDK backend.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/basic-chat.ts
+ * 
+ * Required environment variables:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from '../../src/llm/providers/ai-sdk';
+
+async function main() {
+  console.log('AI SDK Basic Chat Example\n');
+
+  // Create a backend for OpenAI
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    timeout: 30000,
+    maxRetries: 2,
+  });
+
+  console.log(`Provider: ${backend.providerId}`);
+  console.log(`Model: ${backend.modelId}\n`);
+
+  // Generate text
+  const result = await backend.generateText({
+    messages: [
+      { role: 'system', content: 'You are a helpful assistant.' },
+      { role: 'user', content: 'What is the capital of France? Answer in one sentence.' }
+    ],
+    temperature: 0.7,
+    maxTokens: 100,
+  });
+
+  console.log('Response:', result.text);
+  console.log('\nUsage:', result.usage);
+  console.log('Finish Reason:', result.finishReason);
+}
+
+main().catch(console.error);

src/praisonai-ts/examples/ai-sdk/multi-agent.ts

@@ -0,0 +1,123 @@
+/**
+ * AI SDK Multi-Agent Example
+ * 
+ * Demonstrates multi-agent safety with attribution context.
+ * Each agent has its own ID and the context is propagated to LLM calls.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/multi-agent.ts
+ * 
+ * Required environment variables:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from '../../src/llm/providers/ai-sdk';
+import type { AttributionContext } from '../../src/llm/providers/ai-sdk/types';
+
+// Simulate multiple agents running in parallel
+async function runAgent(
+  agentId: string,
+  task: string,
+  attribution: AttributionContext
+): Promise<{ agentId: string; result: string; duration: number }> {
+  console.log(`[${agentId}] Starting task: "${task}"`);
+  
+  // Create backend with attribution context
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    timeout: 30000,
+    attribution,
+  });
+
+  const startTime = Date.now();
+  
+  const result = await backend.generateText({
+    messages: [
+      { role: 'system', content: `You are agent ${agentId}. Be concise.` },
+      { role: 'user', content: task }
+    ],
+    temperature: 0.7,
+    maxTokens: 100,
+  });
+
+  const duration = Date.now() - startTime;
+  
+  console.log(`[${agentId}] Completed in ${duration}ms`);
+  
+  return {
+    agentId,
+    result: result.text,
+    duration
+  };
+}
+
+async function main() {
+  console.log('AI SDK Multi-Agent Example\n');
+  console.log('Running multiple agents in parallel with attribution tracking...\n');
+
+  // Shared run context
+  const runId = `run-${Date.now()}`;
+  const traceId = `trace-${Math.random().toString(36).slice(2, 10)}`;
+  const sessionId = 'session-demo';
+
+  console.log(`Run ID: ${runId}`);
+  console.log(`Trace ID: ${traceId}`);
+  console.log(`Session ID: ${sessionId}\n`);
+  console.log('---\n');
+
+  // Define agents with their tasks
+  const agents = [
+    {
+      id: 'researcher',
+      task: 'What is the population of Tokyo? Just the number.',
+      attribution: {
+        agentId: 'researcher',
+        runId,
+        traceId,
+        sessionId,
+      }
+    },
+    {
+      id: 'analyst',
+      task: 'What is 15% of 1000? Just the number.',
+      attribution: {
+        agentId: 'analyst',
+        runId,
+        traceId,
+        sessionId,
+      }
+    },
+    {
+      id: 'writer',
+      task: 'Write a one-sentence tagline for a coffee shop.',
+      attribution: {
+        agentId: 'writer',
+        runId,
+        traceId,
+        sessionId,
+      }
+    }
+  ];
+
+  // Run all agents in parallel
+  const startTime = Date.now();
+  const results = await Promise.all(
+    agents.map(agent => runAgent(agent.id, agent.task, agent.attribution))
+  );
+  const totalDuration = Date.now() - startTime;
+
+  console.log('\n---\n');
+  console.log('Results:\n');
+
+  for (const result of results) {
+    console.log(`[${result.agentId}] (${result.duration}ms)`);
+    console.log(`  ${result.result.trim()}\n`);
+  }
+
+  console.log('---');
+  console.log(`Total parallel execution time: ${totalDuration}ms`);
+  console.log(`Sum of individual times: ${results.reduce((sum, r) => sum + r.duration, 0)}ms`);
+  console.log('\nNote: Attribution headers (X-Agent-Id, X-Run-Id, X-Trace-Id, X-Session-Id)');
+  console.log('are automatically injected into each LLM request for tracing and debugging.');
+}
+
+main().catch(console.error);

src/praisonai-ts/examples/ai-sdk/multi-provider.ts

@@ -0,0 +1,68 @@
+/**
+ * AI SDK Multi-Provider Example
+ * 
+ * Demonstrates using multiple AI providers with the same interface.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/multi-provider.ts
+ * 
+ * Required environment variables (set at least one):
+ *   OPENAI_API_KEY - Your OpenAI API key
+ *   ANTHROPIC_API_KEY - Your Anthropic API key
+ *   GOOGLE_API_KEY - Your Google API key
+ */
+
+import { createAISDKBackend, validateProviderApiKey } from '../../src/llm/providers/ai-sdk';
+
+const PROVIDERS = [
+  { id: 'openai', model: 'gpt-4o-mini' },
+  { id: 'anthropic', model: 'claude-3-haiku-20240307' },
+  { id: 'google', model: 'gemini-1.5-flash' },
+];
+
+async function main() {
+  console.log('AI SDK Multi-Provider Example\n');
+  console.log('Testing multiple providers with the same prompt...\n');
+
+  const prompt = 'What is 2 + 2? Answer with just the number.';
+  console.log(`Prompt: "${prompt}"\n`);
+  console.log('---\n');
+
+  for (const provider of PROVIDERS) {
+    // Check if API key is available
+    if (!validateProviderApiKey(provider.id)) {
+      console.log(`${provider.id}: Skipped (no API key)`);
+      continue;
+    }
+
+    try {
+      const modelString = `${provider.id}/${provider.model}`;
+      console.log(`${provider.id} (${provider.model}):`);
+
+      const backend = createAISDKBackend(modelString, {
+        timeout: 30000,
+        maxRetries: 1,
+      });
+
+      const startTime = Date.now();
+      const result = await backend.generateText({
+        messages: [
+          { role: 'user', content: prompt }
+        ],
+        temperature: 0,
+        maxTokens: 10,
+      });
+      const duration = Date.now() - startTime;
+
+      console.log(`  Response: ${result.text.trim()}`);
+      console.log(`  Duration: ${duration}ms`);
+      console.log(`  Tokens: ${result.usage?.totalTokens || 'N/A'}`);
+      console.log();
+    } catch (error) {
+      console.log(`  Error: ${error instanceof Error ? error.message : 'Unknown error'}`);
+      console.log();
+    }
+  }
+}
+
+main().catch(console.error);

src/praisonai-ts/examples/ai-sdk/streaming.ts

@@ -0,0 +1,56 @@
+/**
+ * AI SDK Streaming Example
+ * 
+ * Demonstrates streaming text generation using the AI SDK backend.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/streaming.ts
+ * 
+ * Required environment variables:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from '../../src/llm/providers/ai-sdk';
+
+async function main() {
+  console.log('AI SDK Streaming Example\n');
+
+  // Create a backend for OpenAI
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    timeout: 60000,
+  });
+
+  console.log(`Provider: ${backend.providerId}`);
+  console.log(`Model: ${backend.modelId}\n`);
+  console.log('Streaming response:\n');
+
+  // Stream text
+  const stream = await backend.streamText({
+    messages: [
+      { role: 'system', content: 'You are a helpful assistant.' },
+      { role: 'user', content: 'Write a short poem about programming.' }
+    ],
+    temperature: 0.8,
+    maxTokens: 200,
+    onToken: (token) => {
+      // This callback is called for each token
+      process.stdout.write(token);
+    },
+  });
+
+  // Consume the stream
+  let totalTokens = 0;
+  for await (const chunk of stream) {
+    if (chunk.text) {
+      // Text is already printed via onToken callback
+    }
+    if (chunk.usage) {
+      totalTokens = chunk.usage.totalTokens || 0;
+    }
+  }
+
+  console.log('\n\n---');
+  console.log(`Total tokens: ${totalTokens}`);
+}
+
+main().catch(console.error);

src/praisonai-ts/examples/ai-sdk/structured-output.ts

@@ -0,0 +1,129 @@
+/**
+ * AI SDK Structured Output Example
+ * 
+ * Demonstrates generating structured JSON output using schemas.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/structured-output.ts
+ * 
+ * Required environment variables:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from '../../src/llm/providers/ai-sdk';
+
+// Define the schema for structured output
+const recipeSchema = {
+  type: 'object',
+  properties: {
+    name: {
+      type: 'string',
+      description: 'Name of the recipe'
+    },
+    ingredients: {
+      type: 'array',
+      items: {
+        type: 'object',
+        properties: {
+          name: { type: 'string' },
+          amount: { type: 'string' },
+          unit: { type: 'string' }
+        },
+        required: ['name', 'amount']
+      },
+      description: 'List of ingredients'
+    },
+    steps: {
+      type: 'array',
+      items: { type: 'string' },
+      description: 'Cooking steps'
+    },
+    prepTime: {
+      type: 'number',
+      description: 'Preparation time in minutes'
+    },
+    cookTime: {
+      type: 'number',
+      description: 'Cooking time in minutes'
+    },
+    servings: {
+      type: 'number',
+      description: 'Number of servings'
+    }
+  },
+  required: ['name', 'ingredients', 'steps']
+};
+
+interface Recipe {
+  name: string;
+  ingredients: Array<{
+    name: string;
+    amount: string;
+    unit?: string;
+  }>;
+  steps: string[];
+  prepTime?: number;
+  cookTime?: number;
+  servings?: number;
+}
+
+async function main() {
+  console.log('AI SDK Structured Output Example\n');
+
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    timeout: 30000,
+  });
+
+  console.log(`Provider: ${backend.providerId}`);
+  console.log(`Model: ${backend.modelId}\n`);
+
+  console.log('Generating a recipe in structured JSON format...\n');
+
+  const result = await backend.generateObject<Recipe>({
+    messages: [
+      { 
+        role: 'system', 
+        content: 'You are a helpful cooking assistant. Generate recipes in the requested format.' 
+      },
+      { 
+        role: 'user', 
+        content: 'Give me a simple recipe for chocolate chip cookies.' 
+      }
+    ],
+    schema: recipeSchema,
+    temperature: 0.7,
+  });
+
+  console.log('Generated Recipe:');
+  console.log('================\n');
+  
+  const recipe = result.object;
+  
+  console.log(`📝 ${recipe.name}`);
+  console.log();
+  
+  if (recipe.prepTime || recipe.cookTime) {
+    console.log(`⏱️  Prep: ${recipe.prepTime || 'N/A'} min | Cook: ${recipe.cookTime || 'N/A'} min`);
+  }
+  if (recipe.servings) {
+    console.log(`🍽️  Servings: ${recipe.servings}`);
+  }
+  console.log();
+  
+  console.log('Ingredients:');
+  for (const ing of recipe.ingredients) {
+    const unit = ing.unit ? ` ${ing.unit}` : '';
+    console.log(`  • ${ing.amount}${unit} ${ing.name}`);
+  }
+  console.log();
+  
+  console.log('Steps:');
+  recipe.steps.forEach((step, i) => {
+    console.log(`  ${i + 1}. ${step}`);
+  });
+  
+  console.log('\n---');
+  console.log('Usage:', result.usage);
+}
+
+main().catch(console.error);

src/praisonai-ts/examples/ai-sdk/tool-calling.ts

@@ -0,0 +1,144 @@
+/**
+ * AI SDK Tool Calling Example
+ * 
+ * Demonstrates tool calling using the AI SDK backend.
+ * 
+ * Usage:
+ *   npx ts-node examples/ai-sdk/tool-calling.ts
+ * 
+ * Required environment variables:
+ *   OPENAI_API_KEY - Your OpenAI API key
+ */
+
+import { createAISDKBackend } from '../../src/llm/providers/ai-sdk';
+import type { ToolDefinition, Message } from '../../src/llm/providers/types';
+
+// Define tools
+const tools: ToolDefinition[] = [
+  {
+    name: 'get_weather',
+    description: 'Get the current weather for a location',
+    parameters: {
+      type: 'object',
+      properties: {
+        location: {
+          type: 'string',
+          description: 'The city and country, e.g., "London, UK"'
+        },
+        unit: {
+          type: 'string',
+          enum: ['celsius', 'fahrenheit'],
+          description: 'Temperature unit'
+        }
+      },
+      required: ['location']
+    }
+  },
+  {
+    name: 'get_time',
+    description: 'Get the current time for a timezone',
+    parameters: {
+      type: 'object',
+      properties: {
+        timezone: {
+          type: 'string',
+          description: 'The timezone, e.g., "America/New_York"'
+        }
+      },
+      required: ['timezone']
+    }
+  }
+];
+
+// Mock tool execution
+function executeTool(name: string, args: Record<string, unknown>): string {
+  switch (name) {
+    case 'get_weather':
+      return JSON.stringify({
+        location: args.location,
+        temperature: 22,
+        unit: args.unit || 'celsius',
+        condition: 'Partly cloudy'
+      });
+    case 'get_time':
+      return JSON.stringify({
+        timezone: args.timezone,
+        time: new Date().toLocaleTimeString('en-US', { 
+          timeZone: args.timezone as string 
+        })
+      });
+    default:
+      return JSON.stringify({ error: 'Unknown tool' });
+  }
+}
+
+async function main() {
+  console.log('AI SDK Tool Calling Example\n');
+
+  const backend = createAISDKBackend('openai/gpt-4o-mini', {
+    timeout: 30000,
+  });
+
+  console.log(`Provider: ${backend.providerId}`);
+  console.log(`Model: ${backend.modelId}\n`);
+
+  // Initial conversation
+  const messages: Message[] = [
+    { role: 'system', content: 'You are a helpful assistant with access to weather and time tools.' },
+    { role: 'user', content: 'What is the weather in London and what time is it in New York?' }
+  ];
+
+  console.log('User:', messages[1].content);
+  console.log('\n--- First LLM Call ---\n');
+
+  // First call - model should request tool calls
+  let result = await backend.generateText({
+    messages,
+    tools,
+    toolChoice: 'auto',
+  });
+
+  console.log('Finish Reason:', result.finishReason);
+
+  // Handle tool calls
+  if (result.toolCalls && result.toolCalls.length > 0) {
+    console.log(`\nTool Calls: ${result.toolCalls.length}`);
+    
+    // Add assistant message with tool calls
+    messages.push({
+      role: 'assistant',
+      content: null,
+      tool_calls: result.toolCalls
+    });
+
+    // Execute each tool and add results
+    for (const toolCall of result.toolCalls) {
+      const args = JSON.parse(toolCall.function.arguments);
+      console.log(`\n  Executing: ${toolCall.function.name}`);
+      console.log(`  Arguments: ${JSON.stringify(args)}`);
+      
+      const toolResult = executeTool(toolCall.function.name, args);
+      console.log(`  Result: ${toolResult}`);
+      
+      messages.push({
+        role: 'tool',
+        content: toolResult,
+        tool_call_id: toolCall.id,
+        name: toolCall.function.name
+      });
+    }
+
+    console.log('\n--- Second LLM Call (with tool results) ---\n');
+
+    // Second call with tool results
+    result = await backend.generateText({
+      messages,
+      tools,
+    });
+  }
+
+  console.log('Final Response:', result.text);
+  console.log('\nUsage:', result.usage);
+}
+
+main().catch(console.error);

src/praisonai-ts/package.json

@@ -1,6 +1,6 @@
 {
   "name": "praisonai",
-  "version": "1.3.2",
+  "version": "1.3.3",
   "description": "PraisonAI TypeScript AI Agents Framework - Node.js, npm, and Javascript AI Agents Framework",
   "main": "dist/index.js",
   "types": "dist/index.d.ts",
@@ -46,11 +46,15 @@
   "author": "Mervin Praison",
   "license": "MIT",
   "devDependencies": {
+    "@ai-sdk/anthropic": "^3.0.1",
+    "@ai-sdk/google": "^3.0.1",
+    "@ai-sdk/openai": "^3.0.1",
     "@types/figlet": "^1.7.0",
     "@types/jest": "^29.5.14",
     "@types/node": "^22.12.0",
     "@typescript-eslint/eslint-plugin": "^8.22.0",
     "@typescript-eslint/parser": "^8.22.0",
+    "ai": "^6.0.3",
     "eslint": "^9.19.0",
     "jest": "^29.7.0",
     "rimraf": "^5.0.5",
@@ -60,12 +64,12 @@
     "typescript": "^5.7.3"
   },
   "dependencies": {
+    "@modelcontextprotocol/sdk": "^1.12.1",
     "axios": "^1.7.9",
     "dotenv": "^16.4.7",
     "fast-xml-parser": "^4.5.1",
     "node-fetch": "^2.6.9",
-    "openai": "^4.81.0",
-    "@modelcontextprotocol/sdk": "^1.12.1"
+    "openai": "^4.81.0"
   },
   "optionalDependencies": {
     "boxen": "^7.1.1",
@@ -74,6 +78,26 @@
     "figlet": "^1.7.0",
     "ora": "^5.4.1"
   },
+  "peerDependencies": {
+    "@ai-sdk/anthropic": ">=1.0.0",
+    "@ai-sdk/google": ">=1.0.0",
+    "@ai-sdk/openai": ">=1.0.0",
+    "ai": ">=4.0.0"
+  },
+  "peerDependenciesMeta": {
+    "ai": {
+      "optional": true
+    },
+    "@ai-sdk/openai": {
+      "optional": true
+    },
+    "@ai-sdk/anthropic": {
+      "optional": true
+    },
+    "@ai-sdk/google": {
+      "optional": true
+    }
+  },
   "overrides": {
     "whatwg-url": "^14.1.0",
     "node-fetch": "^2.6.9"

src/praisonai-ts/src/cli/commands/llm.ts

@@ -0,0 +1,777 @@
+/**
+ * LLM Command - AI SDK provider management and testing
+ * 
+ * Subcommands:
+ * - providers: List available AI SDK providers
+ * - test: Test connectivity to a provider
+ * - validate: Validate provider configuration
+ * - run: Run a prompt with a specific model
+ */
+
+import { outputJson, formatSuccess, formatError } from '../output/json';
+import * as pretty from '../output/pretty';
+import { ERROR_CODES } from '../output/errors';
+
+export interface LLMOptions {
+  verbose?: boolean;
+  output?: 'json' | 'text' | 'pretty';
+  json?: boolean;
+  model?: string;
+  stream?: boolean;
+  timeout?: number;
+  provider?: string;
+  schema?: string;
+  tool?: string;
+}
+
+// Exit codes specific to LLM commands
+const LLM_EXIT_CODES = {
+  SUCCESS: 0,
+  GENERAL_ERROR: 1,
+  INVALID_ARGS: 2,
+  AUTH_ERROR: 3,
+  PROVIDER_NOT_FOUND: 4,
+  NETWORK_ERROR: 5,
+  TIMEOUT: 6,
+} as const;
+
+export async function execute(args: string[], options: LLMOptions): Promise<void> {
+  const subcommand = args[0] || 'providers';
+  const outputFormat = options.json ? 'json' : (options.output || 'pretty');
+
+  switch (subcommand) {
+    case 'providers':
+      await providersCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'test':
+      await testCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'validate':
+      await validateCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'run':
+      await runCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'models':
+      await modelsCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'config':
+      await configCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'trace':
+      await traceCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'tools':
+      await toolsCommand(args.slice(1), options, outputFormat);
+      break;
+    case 'json':
+      await jsonCommand(args.slice(1), options, outputFormat);
+      break;
+    default:
+      if (outputFormat === 'json') {
+        outputJson(formatError(ERROR_CODES.INVALID_ARGS, `Unknown subcommand: ${subcommand}`));
+      } else {
+        await pretty.error(`Unknown subcommand: ${subcommand}`);
+        await pretty.info('Available subcommands: providers, test, validate, run, models, config, trace, tools, json');
+      }
+      process.exit(LLM_EXIT_CODES.INVALID_ARGS);
+  }
+}
+
+/**
+ * List available AI SDK providers
+ */
+async function providersCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const { 
+      listSupportedProviders, 
+      AISDK_PROVIDERS, 
+      validateProviderApiKey,
+      isAISDKAvailable,
+      getAISDKVersion
+    } = await import('../../llm/providers/ai-sdk');
+    
+    const providers = listSupportedProviders();
+    const aiSdkAvailable = await isAISDKAvailable();
+    const aiSdkVersion = await getAISDKVersion();
+    
+    const providerDetails = providers.map((id: string) => {
+      const info = AISDK_PROVIDERS[id as keyof typeof AISDK_PROVIDERS];
+      const hasApiKey = validateProviderApiKey(id);
+      return {
+        id,
+        package: info?.package || 'custom',
+        envKey: info?.envKey || 'N/A',
+        hasApiKey,
+        status: hasApiKey ? 'ready' : 'missing_key'
+      };
+    });
+
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess({
+        ai_sdk_available: aiSdkAvailable,
+        ai_sdk_version: aiSdkVersion,
+        providers: providerDetails,
+        total: providers.length
+      }));
+    } else {
+      await pretty.heading('AI SDK Providers');
+      
+      if (aiSdkAvailable) {
+        await pretty.success(`AI SDK: ${aiSdkVersion || 'installed'}`);
+      } else {
+        await pretty.warn('AI SDK not installed. Run: npm install ai');
+      }
+      
+      await pretty.newline();
+      await pretty.plain('  Available Providers:');
+      
+      for (const p of providerDetails) {
+        const status = p.hasApiKey ? '✅' : '⚠️';
+        const keyInfo = p.hasApiKey ? '🔑' : `Missing ${p.envKey}`;
+        await pretty.plain(`    ${status} ${p.id.padEnd(20)} ${keyInfo}`);
+        
+        if (options.verbose) {
+          await pretty.dim(`        Package: ${p.package}`);
+        }
+      }
+      
+      await pretty.newline();
+      await pretty.info('Set API keys via environment variables');
+      await pretty.dim('  Example: export OPENAI_API_KEY=sk-...');
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to list providers');
+  }
+}
+
+/**
+ * Test connectivity to a provider
+ */
+async function testCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  const providerId = args[0] || options.provider;
+  
+  if (!providerId) {
+    if (outputFormat === 'json') {
+      outputJson(formatError(ERROR_CODES.MISSING_ARG, 'Provider ID required'));
+    } else {
+      await pretty.error('Provider ID required. Usage: llm test <provider>');
+      await pretty.dim('  Example: praisonai-ts llm test openai');
+    }
+    process.exit(LLM_EXIT_CODES.INVALID_ARGS);
+    return;
+  }
+
+  try {
+    const { 
+      createAISDKBackend, 
+      validateProviderApiKey,
+      getMissingApiKeyMessage,
+      isProviderSupported
+    } = await import('../../llm/providers/ai-sdk');
+    
+    // Check if provider is supported
+    if (!isProviderSupported(providerId)) {
+      if (outputFormat === 'json') {
+        outputJson(formatError('PROVIDER_NOT_FOUND', `Provider '${providerId}' is not supported`));
+      } else {
+        await pretty.error(`Provider '${providerId}' is not supported`);
+      }
+      process.exit(LLM_EXIT_CODES.PROVIDER_NOT_FOUND);
+      return;
+    }
+    
+    // Check API key
+    if (!validateProviderApiKey(providerId)) {
+      const msg = getMissingApiKeyMessage(providerId);
+      if (outputFormat === 'json') {
+        outputJson(formatError('AUTH_ERROR', msg));
+      } else {
+        await pretty.error(msg);
+      }
+      process.exit(LLM_EXIT_CODES.AUTH_ERROR);
+      return;
+    }
+    
+    // Determine test model based on provider
+    const testModels: Record<string, string> = {
+      openai: 'gpt-4o-mini',
+      anthropic: 'claude-3-haiku-20240307',
+      google: 'gemini-1.5-flash',
+      groq: 'llama-3.1-8b-instant',
+      mistral: 'mistral-small-latest',
+      cohere: 'command-light',
+      deepseek: 'deepseek-chat',
+    };
+    
+    const modelId = options.model || testModels[providerId] || 'default';
+    const modelString = `${providerId}/${modelId}`;
+    
+    if (outputFormat !== 'json') {
+      await pretty.info(`Testing ${modelString}...`);
+    }
+    
+    const startTime = Date.now();
+    const backend = createAISDKBackend(modelString, {
+      timeout: options.timeout || 30000,
+      maxRetries: 0, // No retries for test
+    });
+    
+    const result = await backend.generateText({
+      messages: [
+        { role: 'user', content: 'Say "OK" and nothing else.' }
+      ],
+      maxTokens: 10,
+      temperature: 0,
+    });
+    
+    const duration = Date.now() - startTime;
+    
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess({
+        provider: providerId,
+        model: modelId,
+        status: 'success',
+        duration_ms: duration,
+        response: result.text,
+        usage: result.usage
+      }));
+    } else {
+      await pretty.success(`Connection successful! (${duration}ms)`);
+      await pretty.plain(`  Provider: ${providerId}`);
+      await pretty.plain(`  Model: ${modelId}`);
+      await pretty.plain(`  Response: ${result.text.trim()}`);
+      if (result.usage) {
+        await pretty.dim(`  Tokens: ${result.usage.totalTokens}`);
+      }
+    }
+  } catch (error) {
+    handleError(error, outputFormat, `Failed to test provider '${providerId}'`);
+  }
+}
+
+/**
+ * Validate provider configuration
+ */
+async function validateCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  const providerId = args[0] || options.provider;
+  
+  if (!providerId) {
+    if (outputFormat === 'json') {
+      outputJson(formatError(ERROR_CODES.MISSING_ARG, 'Provider ID required'));
+    } else {
+      await pretty.error('Provider ID required. Usage: llm validate --provider <id>');
+    }
+    process.exit(LLM_EXIT_CODES.INVALID_ARGS);
+    return;
+  }
+
+  try {
+    const { 
+      isProviderSupported,
+      validateProviderApiKey,
+      getProviderEnvKey,
+      getProviderPackage,
+      isAISDKAvailable
+    } = await import('../../llm/providers/ai-sdk');
+    
+    const checks: Array<{ name: string; passed: boolean; message: string }> = [];
+    
+    // Check AI SDK availability
+    const aiSdkAvailable = await isAISDKAvailable();
+    checks.push({
+      name: 'AI SDK Installed',
+      passed: aiSdkAvailable,
+      message: aiSdkAvailable ? 'AI SDK is installed' : 'AI SDK not found. Run: npm install ai'
+    });
+    
+    // Check provider support
+    const isSupported = isProviderSupported(providerId);
+    checks.push({
+      name: 'Provider Supported',
+      passed: isSupported,
+      message: isSupported ? `Provider '${providerId}' is supported` : `Provider '${providerId}' is not supported`
+    });
+    
+    if (isSupported) {
+      // Check provider package
+      const pkg = getProviderPackage(providerId);
+      if (pkg) {
+        let pkgInstalled = false;
+        try {
+          require.resolve(pkg);
+          pkgInstalled = true;
+        } catch {
+          pkgInstalled = false;
+        }
+        checks.push({
+          name: 'Provider Package',
+          passed: pkgInstalled,
+          message: pkgInstalled ? `${pkg} is installed` : `${pkg} not found. Run: npm install ${pkg}`
+        });
+      }
+      
+      // Check API key
+      const hasApiKey = validateProviderApiKey(providerId);
+      const envKey = getProviderEnvKey(providerId);
+      checks.push({
+        name: 'API Key',
+        passed: hasApiKey,
+        message: hasApiKey 
+          ? `${envKey} is set` 
+          : `${envKey} is not set`
+      });
+    }
+    
+    const allPassed = checks.every(c => c.passed);
+    
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess({
+        provider: providerId,
+        valid: allPassed,
+        checks
+      }));
+    } else {
+      await pretty.heading(`Validation: ${providerId}`);
+      
+      for (const check of checks) {
+        const icon = check.passed ? '✅' : '❌';
+        await pretty.plain(`  ${icon} ${check.name}: ${check.message}`);
+      }
+      
+      await pretty.newline();
+      if (allPassed) {
+        await pretty.success('All checks passed!');
+      } else {
+        await pretty.warn('Some checks failed. Fix the issues above.');
+        process.exit(LLM_EXIT_CODES.GENERAL_ERROR);
+      }
+    }
+  } catch (error) {
+    handleError(error, outputFormat, `Failed to validate provider '${providerId}'`);
+  }
+}
+
+/**
+ * Run a prompt with a specific model
+ */
+async function runCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  const prompt = args.join(' ');
+  
+  if (!prompt) {
+    if (outputFormat === 'json') {
+      outputJson(formatError(ERROR_CODES.MISSING_ARG, 'Prompt required'));
+    } else {
+      await pretty.error('Prompt required. Usage: llm run "<prompt>" --model <provider/model>');
+      await pretty.dim('  Example: praisonai-ts llm run "Hello!" --model openai/gpt-4o-mini');
+    }
+    process.exit(LLM_EXIT_CODES.INVALID_ARGS);
+    return;
+  }
+  
+  const modelString = options.model || 'openai/gpt-4o-mini';
+
+  try {
+    const { createAISDKBackend } = await import('../../llm/providers/ai-sdk');
+    
+    const backend = createAISDKBackend(modelString, {
+      timeout: options.timeout || 60000,
+    });
+    
+    if (options.stream) {
+      // Streaming mode
+      if (outputFormat === 'json') {
+        // JSON streaming - output each chunk as JSON line
+        const stream = await backend.streamText({
+          messages: [{ role: 'user', content: prompt }],
+        });
+        
+        process.stdout.write('{"type":"stream_start"}\n');
+        
+        let fullText = '';
+        for await (const chunk of stream) {
+          if (chunk.text) {
+            fullText += chunk.text;
+            process.stdout.write(JSON.stringify({ type: 'text', text: chunk.text }) + '\n');
+          }
+          if (chunk.finishReason) {
+            process.stdout.write(JSON.stringify({ 
+              type: 'finish', 
+              finishReason: chunk.finishReason,
+              usage: chunk.usage 
+            }) + '\n');
+          }
+        }
+        
+        process.stdout.write(JSON.stringify({ type: 'stream_end', fullText }) + '\n');
+      } else {
+        // Pretty streaming - output text directly
+        const stream = await backend.streamText({
+          messages: [{ role: 'user', content: prompt }],
+        });
+        
+        for await (const chunk of stream) {
+          if (chunk.text) {
+            process.stdout.write(chunk.text);
+          }
+        }
+        process.stdout.write('\n');
+      }
+    } else {
+      // Non-streaming mode
+      const startTime = Date.now();
+      const result = await backend.generateText({
+        messages: [{ role: 'user', content: prompt }],
+      });
+      const duration = Date.now() - startTime;
+      
+      if (outputFormat === 'json') {
+        outputJson(formatSuccess({
+          model: modelString,
+          text: result.text,
+          usage: result.usage,
+          finishReason: result.finishReason,
+          duration_ms: duration
+        }));
+      } else {
+        await pretty.plain(result.text);
+        
+        if (options.verbose) {
+          await pretty.newline();
+          await pretty.dim(`Model: ${modelString}`);
+          await pretty.dim(`Duration: ${duration}ms`);
+          if (result.usage) {
+            await pretty.dim(`Tokens: ${result.usage.totalTokens} (prompt: ${result.usage.promptTokens}, completion: ${result.usage.completionTokens})`);
+          }
+        }
+      }
+    }
+  } catch (error) {
+    handleError(error, outputFormat, `Failed to run prompt with model '${modelString}'`);
+  }
+}
+
+/**
+ * Handle errors with proper exit codes and formatting
+ */
+/**
+ * List common models for each provider
+ */
+async function modelsCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const { listSupportedProviders, AISDK_PROVIDERS } = await import('../../llm/providers/ai-sdk');
+    
+    // Common models per provider (not exhaustive)
+    const commonModels: Record<string, string[]> = {
+      openai: ['gpt-4o', 'gpt-4o-mini', 'gpt-4-turbo', 'gpt-3.5-turbo', 'o1', 'o1-mini'],
+      anthropic: ['claude-3-5-sonnet-latest', 'claude-3-5-haiku-latest', 'claude-3-opus-latest'],
+      google: ['gemini-2.0-flash', 'gemini-1.5-pro', 'gemini-1.5-flash'],
+      groq: ['llama-3.3-70b-versatile', 'llama-3.1-8b-instant', 'mixtral-8x7b-32768'],
+      mistral: ['mistral-large-latest', 'mistral-small-latest', 'codestral-latest'],
+      cohere: ['command-r-plus', 'command-r', 'command-light'],
+      deepseek: ['deepseek-chat', 'deepseek-coder'],
+      xai: ['grok-2', 'grok-2-mini'],
+    };
+
+    const providers = listSupportedProviders();
+    const modelsData = providers.map((id: string) => ({
+      provider: id,
+      models: commonModels[id] || ['(check provider docs)'],
+      package: AISDK_PROVIDERS[id as keyof typeof AISDK_PROVIDERS]?.package || 'custom'
+    }));
+
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess({
+        note: 'This is not an exhaustive list. Check provider documentation for all available models.',
+        providers: modelsData
+      }));
+    } else {
+      await pretty.heading('Common Models by Provider');
+      await pretty.dim('Note: This is not exhaustive. Check provider docs for all models.\n');
+      
+      for (const p of modelsData) {
+        await pretty.plain(`  ${p.provider}:`);
+        for (const model of p.models) {
+          await pretty.dim(`    - ${model}`);
+        }
+      }
+      
+      await pretty.newline();
+      await pretty.info('Usage: praisonai-ts llm run "prompt" --model provider/model');
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to list models');
+  }
+}
+
+/**
+ * Show resolved configuration (redacted)
+ */
+async function configCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const { SAFE_DEFAULTS, AISDK_PROVIDERS, PROVIDER_ALIASES } = await import('../../llm/providers/ai-sdk');
+    
+    // Gather environment config (redacted)
+    const envConfig: Record<string, string> = {};
+    for (const [id, info] of Object.entries(AISDK_PROVIDERS)) {
+      const envKey = (info as any).envKey;
+      if (envKey && process.env[envKey]) {
+        envConfig[envKey] = '****' + process.env[envKey]!.slice(-4);
+      }
+    }
+
+    const config = {
+      defaults: SAFE_DEFAULTS,
+      aliases: PROVIDER_ALIASES,
+      environment: envConfig,
+      model: options.model || 'openai/gpt-4o-mini',
+      timeout: options.timeout || SAFE_DEFAULTS.timeout,
+    };
+
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess(config));
+    } else {
+      await pretty.heading('AI SDK Configuration');
+      
+      await pretty.plain('  Defaults:');
+      await pretty.dim(`    timeout: ${SAFE_DEFAULTS.timeout}ms`);
+      await pretty.dim(`    maxRetries: ${SAFE_DEFAULTS.maxRetries}`);
+      await pretty.dim(`    maxOutputTokens: ${SAFE_DEFAULTS.maxOutputTokens}`);
+      await pretty.dim(`    redactLogs: ${SAFE_DEFAULTS.redactLogs}`);
+      
+      await pretty.newline();
+      await pretty.plain('  Provider Aliases:');
+      for (const [alias, target] of Object.entries(PROVIDER_ALIASES)) {
+        await pretty.dim(`    ${alias} → ${target}`);
+      }
+      
+      await pretty.newline();
+      await pretty.plain('  Environment (redacted):');
+      if (Object.keys(envConfig).length === 0) {
+        await pretty.dim('    No API keys detected');
+      } else {
+        for (const [key, value] of Object.entries(envConfig)) {
+          await pretty.dim(`    ${key}: ${value}`);
+        }
+      }
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to show config');
+  }
+}
+
+/**
+ * Demo trace/attribution headers
+ */
+async function traceCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const { createAISDKBackend, createAttributionMiddleware } = await import('../../llm/providers/ai-sdk');
+    
+    const modelString = options.model || 'openai/gpt-4o-mini';
+    
+    // Generate demo attribution context
+    const attribution = {
+      agentId: `agent-${Date.now().toString(36)}`,
+      runId: `run-${Math.random().toString(36).slice(2, 10)}`,
+      traceId: `trace-${Math.random().toString(36).slice(2, 10)}`,
+      sessionId: options.verbose ? `session-demo` : undefined,
+    };
+    
+    if (outputFormat !== 'json') {
+      await pretty.heading('Attribution Trace Demo');
+      await pretty.info(`Running with model: ${modelString}`);
+      await pretty.newline();
+      await pretty.plain('  Attribution Context:');
+      await pretty.dim(`    agentId: ${attribution.agentId}`);
+      await pretty.dim(`    runId: ${attribution.runId}`);
+      await pretty.dim(`    traceId: ${attribution.traceId}`);
+      if (attribution.sessionId) {
+        await pretty.dim(`    sessionId: ${attribution.sessionId}`);
+      }
+      await pretty.newline();
+      await pretty.plain('  Headers injected:');
+      await pretty.dim(`    X-Agent-Id: ${attribution.agentId}`);
+      await pretty.dim(`    X-Run-Id: ${attribution.runId}`);
+      await pretty.dim(`    X-Trace-Id: ${attribution.traceId}`);
+      await pretty.newline();
+    }
+    
+    const backend = createAISDKBackend(modelString, {
+      timeout: options.timeout || 30000,
+      attribution,
+    });
+    
+    const startTime = Date.now();
+    const result = await backend.generateText({
+      messages: [{ role: 'user', content: 'Say "Trace OK" and nothing else.' }],
+      maxTokens: 10,
+    });
+    const duration = Date.now() - startTime;
+    
+    if (outputFormat === 'json') {
+      outputJson(formatSuccess({
+        attribution,
+        headers: {
+          'X-Agent-Id': attribution.agentId,
+          'X-Run-Id': attribution.runId,
+          'X-Trace-Id': attribution.traceId,
+        },
+        response: result.text,
+        duration_ms: duration,
+      }));
+    } else {
+      await pretty.success(`Response: ${result.text.trim()} (${duration}ms)`);
+      await pretty.newline();
+      await pretty.info('Attribution headers are automatically injected into LLM requests.');
+      await pretty.dim('Use --verbose for session ID.');
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to run trace demo');
+  }
+}
+
+/**
+ * Demo tool calling - shows how tools work with AI SDK
+ * Note: AI SDK requires Zod schemas for tools, which requires runtime setup
+ */
+async function toolsCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const modelString = options.model || 'openai/gpt-4o-mini';
+    
+    if (outputFormat !== 'json') {
+      await pretty.heading('Tool Calling Demo');
+      await pretty.info(`Model: ${modelString}`);
+      await pretty.newline();
+      await pretty.plain('  AI SDK Tool Calling requires Zod schemas.');
+      await pretty.newline();
+      await pretty.plain('  Example code:');
+      await pretty.dim(`    import { generateText, tool } from 'ai';`);
+      await pretty.dim(`    import { openai } from '@ai-sdk/openai';`);
+      await pretty.dim(`    import { z } from 'zod';`);
+      await pretty.newline();
+      await pretty.dim(`    const tools = {`);
+      await pretty.dim(`      get_weather: tool({`);
+      await pretty.dim(`        description: 'Get weather for a city',`);
+      await pretty.dim(`        inputSchema: z.object({`);
+      await pretty.dim(`          city: z.string().describe('City name'),`);
+      await pretty.dim(`        }),`);
+      await pretty.dim(`      }),`);
+      await pretty.dim(`    };`);
+      await pretty.newline();
+      await pretty.dim(`    const result = await generateText({`);
+      await pretty.dim(`      model: openai('gpt-4o-mini'),`);
+      await pretty.dim(`      messages: [{ role: 'user', content: 'Weather in Paris?' }],`);
+      await pretty.dim(`      tools,`);
+      await pretty.dim(`    });`);
+      await pretty.newline();
+      await pretty.info('See examples/ai-sdk/tool-calling.ts for a complete example.');
+    } else {
+      outputJson(formatSuccess({
+        model: modelString,
+        note: 'AI SDK tool calling requires Zod schemas at runtime',
+        example: {
+          import: "import { generateText, tool } from 'ai'; import { z } from 'zod';",
+          tool: "tool({ description: '...', inputSchema: z.object({ city: z.string() }) })",
+        },
+        docs: 'See examples/ai-sdk/tool-calling.ts',
+      }));
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to run tools demo');
+  }
+}
+
+/**
+ * Demo structured output (JSON schema) - shows how to use generateObject
+ * Note: AI SDK requires Zod schemas for structured output
+ */
+async function jsonCommand(args: string[], options: LLMOptions, outputFormat: string): Promise<void> {
+  try {
+    const modelString = options.model || 'openai/gpt-4o-mini';
+    
+    if (outputFormat !== 'json') {
+      await pretty.heading('Structured Output (JSON) Demo');
+      await pretty.info(`Model: ${modelString}`);
+      await pretty.newline();
+      await pretty.plain('  AI SDK Structured Output requires Zod schemas.');
+      await pretty.newline();
+      await pretty.plain('  Example code:');
+      await pretty.dim(`    import { generateObject } from 'ai';`);
+      await pretty.dim(`    import { openai } from '@ai-sdk/openai';`);
+      await pretty.dim(`    import { z } from 'zod';`);
+      await pretty.newline();
+      await pretty.dim(`    const schema = z.object({`);
+      await pretty.dim(`      name: z.string(),`);
+      await pretty.dim(`      age: z.number(),`);
+      await pretty.dim(`      city: z.string(),`);
+      await pretty.dim(`    });`);
+      await pretty.newline();
+      await pretty.dim(`    const result = await generateObject({`);
+      await pretty.dim(`      model: openai('gpt-4o-mini'),`);
+      await pretty.dim(`      schema,`);
+      await pretty.dim(`      prompt: 'Generate a fictional person profile.',`);
+      await pretty.dim(`    });`);
+      await pretty.newline();
+      await pretty.dim(`    console.log(result.object); // { name: '...', age: 25, city: '...' }`);
+      await pretty.newline();
+      await pretty.info('See examples/ai-sdk/structured-output.ts for a complete example.');
+    } else {
+      outputJson(formatSuccess({
+        model: modelString,
+        note: 'AI SDK structured output requires Zod schemas at runtime',
+        example: {
+          import: "import { generateObject } from 'ai'; import { z } from 'zod';",
+          schema: "z.object({ name: z.string(), age: z.number(), city: z.string() })",
+        },
+        docs: 'See examples/ai-sdk/structured-output.ts',
+      }));
+    }
+  } catch (error) {
+    handleError(error, outputFormat, 'Failed to run JSON demo');
+  }
+}
+
+/**
+ * Handle errors with proper exit codes and formatting
+ */
+async function handleError(error: unknown, outputFormat: string, context: string): Promise<never> {
+  const { AISDKError } = await import('../../llm/providers/ai-sdk');
+  
+  let exitCode: number = LLM_EXIT_CODES.GENERAL_ERROR;
+  let errorCode = 'UNKNOWN_ERROR';
+  let message = context;
+  
+  if (error instanceof AISDKError) {
+    message = `${context}: ${error.message}`;
+    errorCode = error.code;
+    
+    switch (error.code) {
+      case 'AUTHENTICATION':
+        exitCode = 3; // AUTH_ERROR
+        break;
+      case 'PROVIDER_NOT_FOUND':
+      case 'MODEL_NOT_FOUND':
+        exitCode = 4; // PROVIDER_NOT_FOUND
+        break;
+      case 'NETWORK':
+        exitCode = 5; // NETWORK_ERROR
+        break;
+      case 'TIMEOUT':
+        exitCode = 6; // TIMEOUT
+        break;
+      case 'INVALID_REQUEST':
+        exitCode = 2; // INVALID_ARGS
+        break;
+    }
+  } else if (error instanceof Error) {
+    message = `${context}: ${error.message}`;
+  }
+  
+  if (outputFormat === 'json') {
+    outputJson(formatError(errorCode, message));
+  } else {
+    await pretty.error(message);
+  }
+  
+  process.exit(exitCode);
+}

src/praisonai-ts/src/cli/commands/providers.ts

@@ -1,11 +1,23 @@
 /**
- * Providers command - List available LLM providers
+ * Providers command - List and manage LLM providers
+ * 
+ * Supports:
+ * - list: List all registered providers
+ * - register: Register a custom provider (programmatic only)
+ * - info: Show provider details
  */
 
-import { getAvailableProviders } from '../../llm/providers';
+import { 
+  getAvailableProviders, 
+  listProviders, 
+  hasProvider,
+  getDefaultRegistry,
+  isProviderAvailable 
+} from '../../llm/providers';
 import { hasApiKey } from '../runtime/env';
-import { outputJson, formatSuccess } from '../output/json';
+import { outputJson, formatSuccess, formatError } from '../output/json';
 import * as pretty from '../output/pretty';
+import { ERROR_CODES } from '../output/errors';
 
 export interface ProvidersOptions {
   verbose?: boolean;
@@ -15,11 +27,15 @@ export interface ProvidersOptions {
 
 interface ProviderInfo {
   name: string;
+  registered: boolean;
   available: boolean;
   hasApiKey: boolean;
+  isBuiltin: boolean;
   models?: string[];
 }
 
+const BUILTIN_PROVIDERS = ['openai', 'anthropic', 'google', 'gemini', 'oai', 'claude'];
+
 const PROVIDER_MODELS: Record<string, string[]> = {
   openai: ['gpt-4o', 'gpt-4o-mini', 'gpt-4-turbo', 'gpt-4', 'gpt-3.5-turbo'],
   anthropic: ['claude-sonnet-4-20250514', 'claude-3-5-sonnet-20241022', 'claude-3-opus-20240229', 'claude-3-haiku-20240307'],
@@ -27,58 +43,128 @@ const PROVIDER_MODELS: Record<string, string[]> = {
 };
 
 export async function execute(args: string[], options: ProvidersOptions): Promise<void> {
+  const subcommand = args[0] || 'list';
   const outputFormat = options.json ? 'json' : (options.output || 'pretty');
+
+  switch (subcommand) {
+    case 'list':
+      await listProvidersCommand(options, outputFormat);
+      break;
+    case 'info':
+      await providerInfoCommand(args[1], options, outputFormat);
+      break;
+    default:
+      await listProvidersCommand(options, outputFormat);
+  }
+}
+
+async function listProvidersCommand(options: ProvidersOptions, outputFormat: string): Promise<void> {
+  const registry = getDefaultRegistry();
+  const registeredProviders = registry.list();
   
-  const availableProviders = getAvailableProviders();
-  
-  const providers: ProviderInfo[] = [
-    {
-      name: 'openai',
-      available: availableProviders.includes('openai'),
-      hasApiKey: hasApiKey('openai'),
-      models: PROVIDER_MODELS.openai
-    },
-    {
-      name: 'anthropic',
-      available: availableProviders.includes('anthropic'),
-      hasApiKey: hasApiKey('anthropic'),
-      models: PROVIDER_MODELS.anthropic
-    },
-    {
-      name: 'google',
-      available: availableProviders.includes('google'),
-      hasApiKey: hasApiKey('google'),
-      models: PROVIDER_MODELS.google
-    }
-  ];
+  const providers: ProviderInfo[] = registeredProviders.map(name => {
+    const isBuiltin = BUILTIN_PROVIDERS.includes(name);
+    return {
+      name,
+      registered: true,
+      available: isProviderAvailable(name),
+      hasApiKey: hasApiKey(name),
+      isBuiltin,
+      models: PROVIDER_MODELS[name]
+    };
+  });
 
   if (outputFormat === 'json') {
     outputJson(formatSuccess({
       providers: providers.map(p => ({
         name: p.name,
+        registered: p.registered,
         available: p.available,
         has_api_key: p.hasApiKey,
+        is_builtin: p.isBuiltin,
         models: options.verbose ? p.models : undefined
-      }))
+      })),
+      total: providers.length,
+      builtin_count: providers.filter(p => p.isBuiltin).length,
+      custom_count: providers.filter(p => !p.isBuiltin).length
     }));
   } else {
-    await pretty.heading('Available Providers');
+    await pretty.heading('Registered LLM Providers');
     
-    for (const provider of providers) {
-      const status = provider.available ? '✅' : '❌';
-      const keyStatus = provider.hasApiKey ? '🔑' : '⚠️ No API key';
-      
-      await pretty.plain(`  ${status} ${provider.name} ${keyStatus}`);
-      
-      if (options.verbose && provider.models) {
-        for (const model of provider.models) {
-          await pretty.dim(`      - ${model}`);
+    // Built-in providers
+    const builtinProviders = providers.filter(p => p.isBuiltin);
+    if (builtinProviders.length > 0) {
+      await pretty.plain('\n  Built-in:');
+      for (const provider of builtinProviders) {
+        const status = provider.available ? '✅' : '❌';
+        const keyStatus = provider.hasApiKey ? '🔑' : '⚠️ No API key';
+        await pretty.plain(`    ${status} ${provider.name} ${keyStatus}`);
+        
+        if (options.verbose && provider.models) {
+          for (const model of provider.models) {
+            await pretty.dim(`        - ${model}`);
+          }
         }
       }
     }
     
+    // Custom providers
+    const customProviders = providers.filter(p => !p.isBuiltin);
+    if (customProviders.length > 0) {
+      await pretty.plain('\n  Custom:');
+      for (const provider of customProviders) {
+        const status = provider.available ? '✅' : '❌';
+        await pretty.plain(`    ${status} ${provider.name}`);
+      }
+    }
+    
+    await pretty.newline();
+    await pretty.info('Register custom providers with registerProvider():');
+    await pretty.dim('  import { registerProvider } from "praisonai";');
+    await pretty.dim('  registerProvider("cloudflare", CloudflareProvider);');
     await pretty.newline();
     await pretty.info('Set API keys via environment variables:');
     await pretty.dim('  OPENAI_API_KEY, ANTHROPIC_API_KEY, GOOGLE_API_KEY');
   }
 }
+
+async function providerInfoCommand(name: string | undefined, options: ProvidersOptions, outputFormat: string): Promise<void> {
+  if (!name) {
+    if (outputFormat === 'json') {
+      outputJson(formatError(ERROR_CODES.MISSING_ARG, 'Provider name required'));
+    } else {
+      await pretty.error('Provider name required. Usage: providers info <name>');
+    }
+    return;
+  }
+
+  const registry = getDefaultRegistry();
+  const isRegistered = registry.has(name);
+  const isBuiltin = BUILTIN_PROVIDERS.includes(name.toLowerCase());
+  const available = isProviderAvailable(name);
+  const models = PROVIDER_MODELS[name.toLowerCase()];
+
+  if (outputFormat === 'json') {
+    outputJson(formatSuccess({
+      name,
+      registered: isRegistered,
+      available,
+      is_builtin: isBuiltin,
+      has_api_key: hasApiKey(name),
+      models: models || []
+    }));
+  } else {
+    await pretty.heading(`Provider: ${name}`);
+    await pretty.plain(`  Registered: ${isRegistered ? '✅ Yes' : '❌ No'}`);
+    await pretty.plain(`  Available: ${available ? '✅ Yes' : '❌ No'}`);
+    await pretty.plain(`  Type: ${isBuiltin ? 'Built-in' : 'Custom'}`);
+    await pretty.plain(`  API Key: ${hasApiKey(name) ? '🔑 Set' : '⚠️ Not set'}`);
+    
+    if (models && models.length > 0) {
+      await pretty.plain('\n  Models:');
+      for (const model of models) {
+        await pretty.dim(`    - ${model}`);
+      }
+    }
+  }
+}

src/praisonai-ts/src/cli/runtime/env.ts

@@ -29,16 +29,22 @@ export function loadEnvConfig(): EnvConfig {
   return config;
 }
 
-export function hasApiKey(provider: 'openai' | 'anthropic' | 'google'): boolean {
-  switch (provider) {
+export function hasApiKey(provider: string): boolean {
+  const normalizedProvider = provider.toLowerCase();
+  switch (normalizedProvider) {
     case 'openai':
+    case 'oai':
       return !!process.env[ENV_VARS.OPENAI_API_KEY];
     case 'anthropic':
+    case 'claude':
       return !!process.env[ENV_VARS.ANTHROPIC_API_KEY];
     case 'google':
+    case 'gemini':
       return !!process.env[ENV_VARS.GOOGLE_API_KEY];
     default:
-      return false;
+      // For custom providers, check for provider-specific env var
+      const envVarName = `${normalizedProvider.toUpperCase()}_API_KEY`;
+      return !!process.env[envVarName];
   }
 }
 

src/praisonai-ts/src/cli/spec/cli-spec.ts

@@ -97,6 +97,30 @@ export const COMMANDS: Record<string, Command> = {
     description: 'List available LLM providers',
     flags: []
   },
+  llm: {
+    description: 'AI SDK provider management and testing',
+    subcommands: {
+      providers: { description: 'List available AI SDK providers' },
+      test: { 
+        description: 'Test connectivity to a provider',
+        args: [{ name: 'provider', type: 'string', required: false, position: 0 }]
+      },
+      validate: {
+        description: 'Validate provider configuration',
+        args: [{ name: 'provider', type: 'string', required: false, position: 0 }]
+      },
+      run: {
+        description: 'Run a prompt with a specific model',
+        args: [{ name: 'prompt', type: 'string', required: true, position: 0 }]
+      }
+    },
+    flags: [
+      { name: 'model', short: 'm', type: 'string', description: 'Model to use (provider/model format)' },
+      { name: 'stream', short: 's', type: 'boolean', default: false, description: 'Enable streaming output' },
+      { name: 'timeout', type: 'integer', description: 'Request timeout in milliseconds' },
+      { name: 'provider', short: 'p', type: 'string', description: 'Provider ID' }
+    ]
+  },
   tools: {
     description: 'List or manage tools',
     subcommands: {

src/praisonai-ts/src/index.ts

@@ -225,18 +225,36 @@ export {
 
 // Export providers with explicit names to avoid conflicts
 export {
+  // Provider factory and utilities
   createProvider,
   getDefaultProvider,
   parseModelString,
   isProviderAvailable,
   getAvailableProviders,
+  // Provider classes
   OpenAIProvider,
   AnthropicProvider,
   GoogleProvider,
   BaseProvider,
+  // Provider registry (extensibility API)
+  ProviderRegistry,
+  registerProvider,
+  unregisterProvider,
+  hasProvider,
+  listProviders,
+  getDefaultRegistry,
+  createProviderRegistry,
+  registerBuiltinProviders,
+  // Types
   type LLMProvider,
   type ProviderConfig,
   type ProviderFactory,
+  type ProviderConstructor,
+  type ProviderLoader,
+  type RegisterOptions,
+  type IProviderRegistry,
+  type ProviderInput,
+  type CreateProviderOptions,
   type GenerateTextOptions,
   type GenerateTextResult,
   type StreamTextOptions,

src/praisonai-ts/src/llm/providers/ai-sdk/adapter.ts

@@ -0,0 +1,457 @@
+/**
+ * AI SDK Adapter
+ * 
+ * Converts between praisonai-ts message/tool formats and AI SDK formats.
+ * Handles prompt construction, tool definitions, and result parsing.
+ */
+
+import type { Message, ToolDefinition, ToolCall, GenerateTextResult, TokenUsage as PraisonTokenUsage } from '../types';
+import type { 
+  AISDKToolDefinition, 
+  AISDKToolCall, 
+  AISDKToolResult,
+  TokenUsage,
+  FinishReason,
+  PraisonStreamChunk
+} from './types';
+
+/**
+ * AI SDK prompt message types (simplified for compatibility)
+ */
+export interface AISDKSystemMessage {
+  role: 'system';
+  content: string;
+}
+
+export interface AISDKUserMessage {
+  role: 'user';
+  content: Array<{ type: 'text'; text: string }>;
+}
+
+export interface AISDKAssistantMessage {
+  role: 'assistant';
+  content: Array<
+    | { type: 'text'; text: string }
+    | { type: 'tool-call'; toolCallId: string; toolName: string; args: unknown }
+  >;
+}
+
+export interface AISDKToolMessage {
+  role: 'tool';
+  content: Array<{
+    type: 'tool-result';
+    toolCallId: string;
+    toolName: string;
+    result: unknown;
+  }>;
+}
+
+export type AISDKMessage = 
+  | AISDKSystemMessage 
+  | AISDKUserMessage 
+  | AISDKAssistantMessage 
+  | AISDKToolMessage;
+
+/**
+ * Convert praisonai-ts messages to AI SDK prompt format
+ */
+export function toAISDKPrompt(messages: Message[]): AISDKMessage[] {
+  return messages.map(msg => {
+    switch (msg.role) {
+      case 'system':
+        return {
+          role: 'system' as const,
+          content: msg.content || ''
+        };
+        
+      case 'user':
+        return {
+          role: 'user' as const,
+          content: [{ type: 'text' as const, text: msg.content || '' }]
+        };
+        
+      case 'assistant':
+        if (msg.tool_calls && msg.tool_calls.length > 0) {
+          return {
+            role: 'assistant' as const,
+            content: msg.tool_calls.map(tc => ({
+              type: 'tool-call' as const,
+              toolCallId: tc.id,
+              toolName: tc.function.name,
+              args: safeParseJSON(tc.function.arguments)
+            }))
+          };
+        }
+        return {
+          role: 'assistant' as const,
+          content: [{ type: 'text' as const, text: msg.content || '' }]
+        };
+        
+      case 'tool':
+        return {
+          role: 'tool' as const,
+          content: [{
+            type: 'tool-result' as const,
+            toolCallId: msg.tool_call_id || '',
+            toolName: msg.name || '',
+            result: safeParseJSON(msg.content || '')
+          }]
+        };
+        
+      default:
+        // Fallback to user message for unknown roles
+        return {
+          role: 'user' as const,
+          content: [{ type: 'text' as const, text: msg.content || '' }]
+        };
+    }
+  });
+}
+
+/**
+ * Convert praisonai-ts tool definitions to AI SDK format
+ * AI SDK expects tools created with the tool() helper from @ai-sdk/provider-utils
+ */
+export async function toAISDKTools(tools: ToolDefinition[]): Promise<Record<string, any>> {
+  const result: Record<string, any> = {};
+  
+  // Import the tool helper from @ai-sdk/provider-utils
+  let toolHelper: any;
+  let jsonSchemaHelper: any;
+  try {
+    const providerUtils = await import('@ai-sdk/provider-utils');
+    toolHelper = providerUtils.tool;
+    jsonSchemaHelper = providerUtils.jsonSchema;
+  } catch {
+    toolHelper = null;
+    jsonSchemaHelper = null;
+  }
+  
+  for (const toolDef of tools) {
+    // Build a proper JSON Schema for the tool parameters
+    const params = toolDef.parameters || {};
+    const schema = {
+      type: 'object' as const,
+      properties: params.properties || {},
+      required: params.required || [],
+      ...(params.additionalProperties !== undefined 
+        ? { additionalProperties: params.additionalProperties } 
+        : {}),
+    };
+    
+    if (toolHelper && jsonSchemaHelper) {
+      // Use AI SDK's tool() helper for proper tool creation
+      result[toolDef.name] = toolHelper({
+        description: toolDef.description || '',
+        parameters: jsonSchemaHelper(schema),
+      });
+    } else {
+      // Fallback format - create tool-like object manually
+      result[toolDef.name] = {
+        description: toolDef.description || '',
+        parameters: schema,
+      };
+    }
+  }
+  
+  return result;
+}
+
+/**
+ * Convert AI SDK tool call to praisonai-ts format
+ */
+export function fromAISDKToolCall(toolCall: AISDKToolCall): ToolCall {
+  return {
+    id: toolCall.toolCallId,
+    type: 'function',
+    function: {
+      name: toolCall.toolName,
+      arguments: typeof toolCall.args === 'string' 
+        ? toolCall.args 
+        : JSON.stringify(toolCall.args)
+    }
+  };
+}
+
+/**
+ * Convert praisonai-ts tool result to AI SDK format
+ */
+export function toAISDKToolResult(
+  toolCallId: string,
+  toolName: string,
+  result: unknown
+): AISDKToolResult {
+  return {
+    toolCallId,
+    toolName,
+    result
+  };
+}
+
+/**
+ * Extract text content from AI SDK response content
+ */
+export function extractTextFromContent(content: unknown[]): string {
+  if (!Array.isArray(content)) {
+    return '';
+  }
+  
+  return content
+    .filter((part): part is { type: 'text'; text: string } => 
+      typeof part === 'object' && 
+      part !== null && 
+      'type' in part && 
+      part.type === 'text' &&
+      'text' in part
+    )
+    .map(part => part.text)
+    .join('');
+}
+
+/**
+ * Extract tool calls from AI SDK response content
+ */
+export function extractToolCallsFromContent(content: unknown[]): ToolCall[] {
+  if (!Array.isArray(content)) {
+    return [];
+  }
+  
+  return content
+    .filter((part): part is { type: 'tool-call'; toolCallId: string; toolName: string; args: unknown } =>
+      typeof part === 'object' &&
+      part !== null &&
+      'type' in part &&
+      part.type === 'tool-call'
+    )
+    .map(part => fromAISDKToolCall({
+      toolCallId: part.toolCallId,
+      toolName: part.toolName,
+      args: part.args
+    }));
+}
+
+/**
+ * Convert AI SDK generate result to praisonai-ts format
+ */
+export function fromAISDKResult(result: {
+  text?: string;
+  content?: unknown[];
+  toolCalls?: AISDKToolCall[];
+  usage?: { promptTokens: number; completionTokens: number };
+  finishReason?: string;
+}): GenerateTextResult {
+  // Extract text from content or use text directly
+  let text = result.text || '';
+  if (!text && result.content) {
+    text = extractTextFromContent(result.content);
+  }
+  
+  // Extract tool calls
+  let toolCalls: ToolCall[] = [];
+  if (result.toolCalls && result.toolCalls.length > 0) {
+    toolCalls = result.toolCalls.map(fromAISDKToolCall);
+  } else if (result.content) {
+    toolCalls = extractToolCallsFromContent(result.content);
+  }
+  
+  // Map usage - provide defaults if not available
+  const usage: PraisonTokenUsage = result.usage ? {
+    promptTokens: result.usage.promptTokens,
+    completionTokens: result.usage.completionTokens,
+    totalTokens: result.usage.promptTokens + result.usage.completionTokens
+  } : {
+    promptTokens: 0,
+    completionTokens: 0,
+    totalTokens: 0
+  };
+  
+  // Map finish reason to praisonai-ts format
+  const finishReason = mapFinishReasonToProvider(result.finishReason);
+  
+  return {
+    text,
+    toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
+    usage,
+    finishReason,
+    raw: result
+  };
+}
+
+/**
+ * Map AI SDK finish reason to internal format
+ */
+export function mapFinishReason(reason?: string): FinishReason {
+  if (!reason) return 'unknown';
+  
+  switch (reason.toLowerCase()) {
+    case 'stop':
+    case 'end_turn':
+    case 'end':
+      return 'stop';
+    case 'length':
+    case 'max_tokens':
+      return 'length';
+    case 'tool_calls':
+    case 'tool-calls':
+    case 'function_call':
+      return 'tool-calls';
+    case 'content_filter':
+    case 'content-filter':
+      return 'content-filter';
+    case 'error':
+      return 'error';
+    case 'cancelled':
+    case 'canceled':
+      return 'cancelled';
+    default:
+      return 'unknown';
+  }
+}
+
+/**
+ * Map AI SDK finish reason to praisonai-ts provider format
+ * Uses underscore format for tool_calls as expected by GenerateTextResult
+ */
+export function mapFinishReasonToProvider(reason?: string): 'stop' | 'length' | 'tool_calls' | 'content_filter' | 'error' {
+  if (!reason) return 'stop';
+  
+  switch (reason.toLowerCase()) {
+    case 'stop':
+    case 'end_turn':
+    case 'end':
+      return 'stop';
+    case 'length':
+    case 'max_tokens':
+      return 'length';
+    case 'tool_calls':
+    case 'tool-calls':
+    case 'function_call':
+      return 'tool_calls';
+    case 'content_filter':
+    case 'content-filter':
+      return 'content_filter';
+    case 'error':
+    case 'cancelled':
+    case 'canceled':
+    default:
+      return 'error';
+  }
+}
+
+/**
+ * Convert AI SDK stream chunk to praisonai-ts format
+ */
+export function fromAISDKStreamChunk(chunk: {
+  type: string;
+  textDelta?: string;
+  toolCallId?: string;
+  toolName?: string;
+  argsTextDelta?: string;
+  args?: unknown;
+  finishReason?: string;
+  usage?: { promptTokens: number; completionTokens: number };
+}): PraisonStreamChunk | null {
+  switch (chunk.type) {
+    case 'text-delta':
+      if (chunk.textDelta) {
+        return { type: 'text', text: chunk.textDelta };
+      }
+      return null;
+      
+    case 'tool-call':
+      if (chunk.toolCallId && chunk.toolName) {
+        return {
+          type: 'tool-call-end',
+          toolCallId: chunk.toolCallId,
+          args: chunk.args
+        };
+      }
+      return null;
+      
+    case 'tool-call-streaming-start':
+      if (chunk.toolCallId && chunk.toolName) {
+        return {
+          type: 'tool-call-start',
+          toolCallId: chunk.toolCallId,
+          toolName: chunk.toolName
+        };
+      }
+      return null;
+      
+    case 'tool-call-delta':
+      if (chunk.toolCallId && chunk.argsTextDelta) {
+        return {
+          type: 'tool-call-delta',
+          toolCallId: chunk.toolCallId,
+          argsTextDelta: chunk.argsTextDelta
+        };
+      }
+      return null;
+      
+    case 'finish':
+    case 'step-finish':
+      return {
+        type: 'finish',
+        finishReason: mapFinishReason(chunk.finishReason),
+        usage: chunk.usage ? {
+          promptTokens: chunk.usage.promptTokens,
+          completionTokens: chunk.usage.completionTokens,
+          totalTokens: chunk.usage.promptTokens + chunk.usage.completionTokens
+        } : undefined
+      };
+      
+    default:
+      return null;
+  }
+}
+
+/**
+ * Map praisonai-ts tool choice to AI SDK format
+ */
+export function toAISDKToolChoice(
+  toolChoice?: 'auto' | 'none' | 'required' | { type: 'tool'; toolName: string }
+): 'auto' | 'none' | 'required' | { type: 'tool'; toolName: string } | undefined {
+  if (!toolChoice) return undefined;
+  
+  if (typeof toolChoice === 'string') {
+    return toolChoice;
+  }
+  
+  return toolChoice;
+}
+
+/**
+ * Safely parse JSON, returning the original string if parsing fails
+ */
+function safeParseJSON(str: string): unknown {
+  if (typeof str !== 'string') {
+    return str;
+  }
+  
+  try {
+    return JSON.parse(str);
+  } catch {
+    return str;
+  }
+}
+
+/**
+ * Create a simple prompt from a string
+ */
+export function createSimplePrompt(prompt: string, systemPrompt?: string): AISDKMessage[] {
+  const messages: AISDKMessage[] = [];
+  
+  if (systemPrompt) {
+    messages.push({
+      role: 'system',
+      content: systemPrompt
+    });
+  }
+  
+  messages.push({
+    role: 'user',
+    content: [{ type: 'text', text: prompt }]
+  });
+  
+  return messages;
+}

src/praisonai-ts/src/llm/providers/ai-sdk/backend.ts

@@ -0,0 +1,549 @@
+/**
+ * AI SDK Backend
+ * 
+ * Main implementation of the AI SDK backend for praisonai-ts.
+ * Provides generateText, streamText, and generateObject methods
+ * with retry logic, timeouts, and attribution support.
+ */
+
+import type { 
+  LLMProvider, 
+  GenerateTextOptions, 
+  GenerateTextResult,
+  StreamTextOptions,
+  StreamChunk,
+  GenerateObjectOptions,
+  GenerateObjectResult,
+  Message,
+  ToolDefinition
+} from '../types';
+
+import type {
+  AISDKBackendConfig,
+  AttributionContext,
+  AISDKProviderOptions,
+  PraisonStreamChunk,
+  TokenUsage
+} from './types';
+
+import { AISDKError, SAFE_DEFAULTS } from './types';
+import { parseModelString, createAISDKProvider, validateProviderApiKey, getMissingApiKeyMessage } from './provider-map';
+import { toAISDKPrompt, toAISDKTools, fromAISDKResult, fromAISDKStreamChunk, toAISDKToolChoice, mapFinishReasonToProvider } from './adapter';
+import { createStandardMiddleware, createAttributionMiddleware, composeMiddleware, type AISDKMiddleware } from './middleware';
+
+/**
+ * Lazy-loaded AI SDK modules
+ * These are only imported when actually used to avoid startup cost
+ * 
+ * Note: We use 'any' type here because the 'ai' package is an optional
+ * peer dependency. The actual types are checked at runtime.
+ */
+let _aiModule: any = null;
+
+async function getAIModule(): Promise<any> {
+  if (!_aiModule) {
+    try {
+      // Dynamic import - 'ai' is an optional peer dependency
+      // Use variable to prevent TypeScript from resolving the module at compile time
+      const moduleName = 'ai';
+      _aiModule = await import(moduleName);
+    } catch (error) {
+      throw new AISDKError(
+        'AI SDK is not installed. Install it with: npm install ai',
+        'MISSING_DEPENDENCY',
+        false,
+        error
+      );
+    }
+  }
+  return _aiModule;
+}
+
+/**
+ * AI SDK Backend - implements LLMProvider interface
+ */
+export class AISDKBackend implements LLMProvider {
+  public readonly providerId: string;
+  public readonly modelId: string;
+  
+  private readonly config: AISDKBackendConfig;
+  private readonly attribution?: AttributionContext;
+  private provider: unknown | null = null;
+  private model: unknown | null = null;
+  
+  constructor(
+    modelString: string,
+    config: AISDKBackendConfig = {}
+  ) {
+    const parsed = parseModelString(modelString, config.defaultProvider);
+    this.providerId = parsed.providerId;
+    this.modelId = parsed.modelId;
+    
+    // Merge with safe defaults
+    this.config = {
+      ...SAFE_DEFAULTS,
+      ...config
+    };
+    
+    this.attribution = config.attribution;
+  }
+  
+  /**
+   * Initialize the AI SDK provider and model (lazy)
+   */
+  private async ensureInitialized(): Promise<void> {
+    if (this.model) {
+      return;
+    }
+    
+    // Validate API key
+    if (!validateProviderApiKey(this.providerId)) {
+      throw new AISDKError(
+        getMissingApiKeyMessage(this.providerId),
+        'AUTHENTICATION',
+        false
+      );
+    }
+    
+    // Get provider options from config
+    const providerOptions: AISDKProviderOptions = 
+      this.config.providers?.[this.providerId] || {};
+    
+    // Create the AI SDK provider
+    this.provider = await createAISDKProvider(this.providerId, providerOptions);
+    
+    // Get the language model from the provider
+    if (typeof this.provider === 'function') {
+      // Provider is callable (e.g., openai('gpt-4o'))
+      this.model = (this.provider as Function)(this.modelId);
+    } else if (this.provider && typeof (this.provider as any).languageModel === 'function') {
+      // Provider has languageModel method
+      this.model = (this.provider as any).languageModel(this.modelId);
+    } else if (this.provider && typeof (this.provider as any).chat === 'function') {
+      // Provider has chat method (OpenAI style)
+      this.model = (this.provider as any).chat(this.modelId);
+    } else {
+      throw new AISDKError(
+        `Could not get language model from provider '${this.providerId}'`,
+        'PROVIDER_ERROR',
+        false
+      );
+    }
+  }
+  
+  /**
+   * Generate text (non-streaming)
+   */
+  async generateText(options: GenerateTextOptions): Promise<GenerateTextResult> {
+    await this.ensureInitialized();
+    
+    const ai = await getAIModule();
+    
+    // Convert messages to AI SDK format
+    const prompt = toAISDKPrompt(options.messages);
+    
+    // Convert tools if provided (now async)
+    const tools = options.tools ? await toAISDKTools(options.tools) : undefined;
+    
+    // Build call options
+    const callOptions: Record<string, unknown> = {
+      model: this.model,
+      messages: prompt,
+      maxTokens: options.maxTokens || this.config.maxOutputTokens,
+      temperature: options.temperature,
+      topP: options.topP,
+      frequencyPenalty: options.frequencyPenalty,
+      presencePenalty: options.presencePenalty,
+      stopSequences: options.stop,
+      maxRetries: this.config.maxRetries,
+    };
+    
+    if (tools && Object.keys(tools).length > 0) {
+      callOptions.tools = tools;
+      callOptions.toolChoice = toAISDKToolChoice(options.toolChoice as any);
+    }
+    
+    // Add telemetry settings if configured
+    if (this.config.telemetry) {
+      callOptions.experimental_telemetry = this.config.telemetry;
+    }
+    
+    // Execute with retry logic
+    let lastError: unknown;
+    const maxRetries = this.config.maxRetries || SAFE_DEFAULTS.maxRetries;
+    
+    for (let attempt = 0; attempt <= maxRetries; attempt++) {
+      try {
+        // Create abort controller for timeout
+        const controller = new AbortController();
+        const timeoutId = setTimeout(() => {
+          controller.abort();
+        }, this.config.timeout || SAFE_DEFAULTS.timeout);
+        
+        try {
+          callOptions.abortSignal = controller.signal;
+          
+          const result = await ai.generateText(callOptions as any);
+          
+          clearTimeout(timeoutId);
+          
+          return fromAISDKResult({
+            text: result.text,
+            toolCalls: result.toolCalls?.map((tc: any) => ({
+              toolCallId: tc.toolCallId,
+              toolName: tc.toolName,
+              args: tc.args
+            })),
+            usage: result.usage,
+            finishReason: result.finishReason
+          });
+        } finally {
+          clearTimeout(timeoutId);
+        }
+      } catch (error) {
+        lastError = error;
+        
+        const classifiedError = classifyError(error);
+        
+        // Don't retry non-retryable errors
+        if (!classifiedError.isRetryable || attempt === maxRetries) {
+          throw classifiedError;
+        }
+        
+        // Exponential backoff
+        const delay = Math.min(1000 * Math.pow(2, attempt), 10000);
+        await sleep(delay);
+      }
+    }
+    
+    throw classifyError(lastError);
+  }
+  
+  /**
+   * Stream text generation
+   */
+  async streamText(options: StreamTextOptions): Promise<AsyncIterable<StreamChunk>> {
+    await this.ensureInitialized();
+    
+    const ai = await getAIModule();
+    
+    // Convert messages to AI SDK format
+    const prompt = toAISDKPrompt(options.messages);
+    
+    // Convert tools if provided (now async)
+    const tools = options.tools ? await toAISDKTools(options.tools) : undefined;
+    
+    // Build call options
+    const callOptions: Record<string, unknown> = {
+      model: this.model,
+      messages: prompt,
+      maxTokens: options.maxTokens || this.config.maxOutputTokens,
+      temperature: options.temperature,
+      topP: options.topP,
+      frequencyPenalty: options.frequencyPenalty,
+      presencePenalty: options.presencePenalty,
+      stopSequences: options.stop,
+    };
+    
+    if (tools && Object.keys(tools).length > 0) {
+      callOptions.tools = tools;
+      callOptions.toolChoice = toAISDKToolChoice(options.toolChoice as any);
+    }
+    
+    // Add telemetry settings if configured
+    if (this.config.telemetry) {
+      callOptions.experimental_telemetry = this.config.telemetry;
+    }
+    
+    // Create abort controller for timeout
+    const controller = new AbortController();
+    const timeoutId = setTimeout(() => {
+      controller.abort();
+    }, this.config.timeout || SAFE_DEFAULTS.timeout);
+    
+    callOptions.abortSignal = controller.signal;
+    
+    const self = this;
+    const onToken = options.onToken;
+    const onToolCall = options.onToolCall;
+    
+    // Return async iterable
+    return {
+      async *[Symbol.asyncIterator](): AsyncGenerator<StreamChunk, void, unknown> {
+        try {
+          const result = await ai.streamText(callOptions as any);
+          
+          let accumulatedText = '';
+          const toolCalls: Map<string, { id: string; name: string; args: string }> = new Map();
+          
+          for await (const chunk of result.textStream) {
+            // AI SDK streamText returns text chunks directly
+            if (typeof chunk === 'string') {
+              accumulatedText += chunk;
+              
+              if (onToken) {
+                onToken(chunk);
+              }
+              
+              yield {
+                text: chunk
+              };
+            }
+          }
+          
+          // Get final result for usage and tool calls
+          const finalResult = await result;
+          
+          // Yield tool calls if any
+          if (finalResult.toolCalls && finalResult.toolCalls.length > 0) {
+            for (const tc of finalResult.toolCalls) {
+              const toolCall = {
+                id: tc.toolCallId,
+                type: 'function' as const,
+                function: {
+                  name: tc.toolName,
+                  arguments: typeof tc.args === 'string' ? tc.args : JSON.stringify(tc.args)
+                }
+              };
+              
+              if (onToolCall) {
+                onToolCall(toolCall);
+              }
+              
+              yield {
+                toolCalls: [toolCall]
+              };
+            }
+          }
+          
+          // Yield final chunk with usage
+          yield {
+            usage: finalResult.usage ? {
+              promptTokens: finalResult.usage.promptTokens,
+              completionTokens: finalResult.usage.completionTokens,
+              totalTokens: finalResult.usage.promptTokens + finalResult.usage.completionTokens
+            } : undefined,
+            finishReason: finalResult.finishReason
+          };
+          
+        } catch (error) {
+          throw classifyError(error);
+        } finally {
+          clearTimeout(timeoutId);
+        }
+      }
+    };
+  }
+  
+  /**
+   * Generate structured object output
+   */
+  async generateObject<T = unknown>(options: GenerateObjectOptions<T>): Promise<GenerateObjectResult<T>> {
+    await this.ensureInitialized();
+    
+    const ai = await getAIModule();
+    
+    // Convert messages to AI SDK format
+    const prompt = toAISDKPrompt(options.messages);
+    
+    // Build call options
+    const callOptions: Record<string, unknown> = {
+      model: this.model,
+      messages: prompt,
+      schema: options.schema,
+      maxTokens: options.maxTokens || this.config.maxOutputTokens,
+      temperature: options.temperature,
+      maxRetries: options.maxRetries || this.config.maxRetries,
+    };
+    
+    // Add telemetry settings if configured
+    if (this.config.telemetry) {
+      callOptions.experimental_telemetry = this.config.telemetry;
+    }
+    
+    // Create abort controller for timeout
+    const controller = new AbortController();
+    const timeoutId = setTimeout(() => {
+      controller.abort();
+    }, this.config.timeout || SAFE_DEFAULTS.timeout);
+    
+    try {
+      callOptions.abortSignal = controller.signal;
+      
+      const result = await ai.generateObject(callOptions as any);
+      
+      return {
+        object: result.object as T,
+        usage: result.usage ? {
+          promptTokens: result.usage.promptTokens,
+          completionTokens: result.usage.completionTokens,
+          totalTokens: result.usage.promptTokens + result.usage.completionTokens
+        } : {
+          promptTokens: 0,
+          completionTokens: 0,
+          totalTokens: 0
+        },
+        raw: result
+      };
+    } catch (error) {
+      throw classifyError(error);
+    } finally {
+      clearTimeout(timeoutId);
+    }
+  }
+  
+  /**
+   * Get the underlying AI SDK model (for advanced use)
+   */
+  async getModel(): Promise<unknown> {
+    await this.ensureInitialized();
+    return this.model;
+  }
+  
+  /**
+   * Get the underlying AI SDK provider (for advanced use)
+   */
+  async getProvider(): Promise<unknown> {
+    await this.ensureInitialized();
+    return this.provider;
+  }
+}
+
+/**
+ * Create an AI SDK backend instance
+ */
+export function createAISDKBackend(
+  modelString: string,
+  config?: AISDKBackendConfig
+): AISDKBackend {
+  return new AISDKBackend(modelString, config);
+}
+
+/**
+ * Classify an error into an AISDKError
+ */
+function classifyError(error: unknown): AISDKError {
+  if (error instanceof AISDKError) {
+    return error;
+  }
+  
+  const message = error instanceof Error ? error.message : String(error);
+  const lowerMessage = message.toLowerCase();
+  
+  // Check for timeout/abort
+  if (lowerMessage.includes('abort') || lowerMessage.includes('timeout')) {
+    return new AISDKError(
+      `Request timed out: ${message}`,
+      'TIMEOUT',
+      true,
+      error
+    );
+  }
+  
+  // Check for rate limit
+  if (lowerMessage.includes('rate limit') || lowerMessage.includes('429') || lowerMessage.includes('too many')) {
+    return new AISDKError(
+      `Rate limit exceeded: ${message}`,
+      'RATE_LIMIT',
+      true,
+      error,
+      429
+    );
+  }
+  
+  // Check for authentication
+  if (lowerMessage.includes('unauthorized') || lowerMessage.includes('401') || 
+      lowerMessage.includes('forbidden') || lowerMessage.includes('403') ||
+      lowerMessage.includes('api key') || lowerMessage.includes('authentication')) {
+    return new AISDKError(
+      `Authentication failed: ${message}`,
+      'AUTHENTICATION',
+      false,
+      error,
+      401
+    );
+  }
+  
+  // Check for invalid request
+  if (lowerMessage.includes('bad request') || lowerMessage.includes('400') ||
+      lowerMessage.includes('invalid')) {
+    return new AISDKError(
+      `Invalid request: ${message}`,
+      'INVALID_REQUEST',
+      false,
+      error,
+      400
+    );
+  }
+  
+  // Check for model not found
+  if (lowerMessage.includes('model not found') || lowerMessage.includes('404') ||
+      lowerMessage.includes('does not exist')) {
+    return new AISDKError(
+      `Model not found: ${message}`,
+      'MODEL_NOT_FOUND',
+      false,
+      error,
+      404
+    );
+  }
+  
+  // Check for network errors
+  if (lowerMessage.includes('network') || lowerMessage.includes('econnrefused') ||
+      lowerMessage.includes('enotfound') || lowerMessage.includes('socket')) {
+    return new AISDKError(
+      `Network error: ${message}`,
+      'NETWORK',
+      true,
+      error
+    );
+  }
+  
+  // Check for cancelled
+  if (lowerMessage.includes('cancel')) {
+    return new AISDKError(
+      `Request cancelled: ${message}`,
+      'CANCELLED',
+      false,
+      error
+    );
+  }
+  
+  // Check for missing dependency
+  if (lowerMessage.includes('cannot find module') || lowerMessage.includes('module_not_found')) {
+    return new AISDKError(
+      `Missing dependency: ${message}`,
+      'MISSING_DEPENDENCY',
+      false,
+      error
+    );
+  }
+  
+  // Check for server errors (retryable)
+  if (lowerMessage.includes('500') || lowerMessage.includes('502') ||
+      lowerMessage.includes('503') || lowerMessage.includes('504') ||
+      lowerMessage.includes('server error')) {
+    return new AISDKError(
+      `Server error: ${message}`,
+      'PROVIDER_ERROR',
+      true,
+      error,
+      500
+    );
+  }
+  
+  // Default to unknown error
+  return new AISDKError(
+    message,
+    'UNKNOWN',
+    false,
+    error
+  );
+}
+
+/**
+ * Sleep for a given number of milliseconds
+ */
+function sleep(ms: number): Promise<void> {
+  return new Promise(resolve => setTimeout(resolve, ms));
+}

src/praisonai-ts/src/llm/providers/ai-sdk/index.ts

@@ -0,0 +1,195 @@
+/**
+ * AI SDK Integration for praisonai-ts
+ * 
+ * This module provides integration with Vercel's AI SDK for multi-provider LLM support.
+ * All imports are lazy-loaded to avoid startup cost when AI SDK is not used.
+ * 
+ * @example Basic usage
+ * ```typescript
+ * import { createAISDKBackend, registerAISDKProviders } from 'praisonai';
+ * 
+ * // Register AI SDK providers (one-time)
+ * registerAISDKProviders();
+ * 
+ * // Create a backend for any supported provider
+ * const backend = createAISDKBackend('anthropic/claude-3-5-sonnet');
+ * const result = await backend.generateText({ messages: [...] });
+ * ```
+ */
+
+// Re-export types (these don't cause runtime imports)
+export type {
+  AISDKBackendConfig,
+  AISDKProviderOptions,
+  AttributionContext,
+  AISDKTelemetrySettings,
+  AISDKErrorCode,
+  PraisonStreamChunk,
+  TokenUsage,
+  FinishReason,
+  AISDKToolDefinition,
+  AISDKToolCall,
+  AISDKToolResult,
+} from './types';
+
+export { AISDKError, SAFE_DEFAULTS, AISDK_PROVIDERS, PROVIDER_ALIASES } from './types';
+
+// Re-export provider map functions
+export {
+  parseModelString,
+  resolveProviderAlias,
+  isProviderSupported,
+  getProviderPackage,
+  getProviderEnvKey,
+  listSupportedProviders,
+  registerCustomProvider,
+  unregisterCustomProvider,
+  getCustomProvider,
+  createAISDKProvider,
+  validateProviderApiKey,
+  getMissingApiKeyMessage,
+  type ParsedModel,
+  type ProviderFactory,
+} from './provider-map';
+
+// Re-export adapter functions
+export {
+  toAISDKPrompt,
+  toAISDKTools,
+  fromAISDKToolCall,
+  toAISDKToolResult,
+  fromAISDKResult,
+  fromAISDKStreamChunk,
+  mapFinishReason,
+  mapFinishReasonToProvider,
+  toAISDKToolChoice,
+  createSimplePrompt,
+  type AISDKMessage,
+  type AISDKSystemMessage,
+  type AISDKUserMessage,
+  type AISDKAssistantMessage,
+  type AISDKToolMessage,
+} from './adapter';
+
+// Re-export middleware functions
+export {
+  createAttributionMiddleware,
+  createLoggingMiddleware,
+  createTimeoutMiddleware,
+  composeMiddleware,
+  createStandardMiddleware,
+  redactSensitiveData,
+  type AISDKMiddleware,
+} from './middleware';
+
+// Lazy-loaded backend exports
+// These use getters to avoid importing the backend module until needed
+
+let _AISDKBackend: typeof import('./backend').AISDKBackend | null = null;
+let _createAISDKBackend: typeof import('./backend').createAISDKBackend | null = null;
+
+/**
+ * Get the AISDKBackend class (lazy loaded)
+ */
+export function getAISDKBackendClass(): typeof import('./backend').AISDKBackend {
+  if (!_AISDKBackend) {
+    const backend = require('./backend');
+    _AISDKBackend = backend.AISDKBackend;
+  }
+  return _AISDKBackend!;
+}
+
+/**
+ * Create an AI SDK backend instance
+ * 
+ * @param modelString - Model string in format "provider/model" or just "model"
+ * @param config - Optional configuration
+ * @returns AISDKBackend instance implementing LLMProvider
+ * 
+ * @example
+ * ```typescript
+ * const backend = createAISDKBackend('openai/gpt-4o');
+ * const backend = createAISDKBackend('anthropic/claude-3-5-sonnet');
+ * const backend = createAISDKBackend('google/gemini-2.0-flash');
+ * ```
+ */
+export function createAISDKBackend(
+  modelString: string,
+  config?: import('./types').AISDKBackendConfig
+): import('./backend').AISDKBackend {
+  if (!_createAISDKBackend) {
+    const backend = require('./backend');
+    _createAISDKBackend = backend.createAISDKBackend;
+  }
+  return _createAISDKBackend!(modelString, config);
+}
+
+// Re-export the class for direct instantiation
+export { AISDKBackend } from './backend';
+
+/**
+ * Register AI SDK providers with the praisonai-ts provider registry
+ * This allows using AI SDK providers via the standard createProvider() function
+ * 
+ * @param customProviders - Optional map of custom provider factories
+ * 
+ * @example
+ * ```typescript
+ * import { registerAISDKProviders, createProvider } from 'praisonai';
+ * 
+ * // Register all AI SDK providers
+ * registerAISDKProviders();
+ * 
+ * // Now you can use AI SDK providers via createProvider
+ * const provider = createProvider('aisdk:anthropic/claude-3-5-sonnet');
+ * ```
+ */
+export function registerAISDKProviders(
+  customProviders?: Record<string, import('./provider-map').ProviderFactory>
+): void {
+  // Register custom providers if provided
+  if (customProviders) {
+    const { registerCustomProvider } = require('./provider-map');
+    for (const [id, factory] of Object.entries(customProviders)) {
+      registerCustomProvider(id, factory);
+    }
+  }
+  
+  // Note: Integration with main provider registry is done in ../index.ts
+  // This function is mainly for registering custom AI SDK providers
+}
+
+/**
+ * Check if AI SDK is available (installed)
+ */
+export async function isAISDKAvailable(): Promise<boolean> {
+  try {
+    // Use variable to prevent TypeScript from resolving at compile time
+    const moduleName = 'ai';
+    await import(moduleName);
+    return true;
+  } catch {
+    return false;
+  }
+}
+
+/**
+ * Get AI SDK version if available
+ */
+export async function getAISDKVersion(): Promise<string | null> {
+  try {
+    // Use variable to prevent TypeScript from resolving at compile time
+    const moduleName = 'ai';
+    await import(moduleName);
+    // AI SDK doesn't export version directly, so we check package.json
+    try {
+      const pkgPath = 'ai/package.json';
+      const pkg = require(pkgPath);
+      return pkg.version;
+    } catch {
+      return 'installed';
+    }
+  } catch {
+    return null;
+  }
+}

src/praisonai-ts/src/llm/providers/ai-sdk/middleware.ts

@@ -0,0 +1,316 @@
+/**
+ * AI SDK Middleware
+ * 
+ * Provides middleware for injecting attribution context into AI SDK calls.
+ * Supports multi-agent safety with agent_id, run_id, trace_id, session_id.
+ */
+
+import type { AttributionContext, AISDKBackendConfig } from './types';
+
+/**
+ * Middleware interface for AI SDK language models
+ * Compatible with AI SDK's LanguageModelMiddleware type
+ */
+export interface AISDKMiddleware {
+  transformParams?: (options: {
+    params: Record<string, unknown>;
+    type: 'generate' | 'stream';
+    model: unknown;
+  }) => Promise<Record<string, unknown>> | Record<string, unknown>;
+  
+  wrapGenerate?: (options: {
+    doGenerate: () => Promise<unknown>;
+    doStream: () => Promise<unknown>;
+    params: Record<string, unknown>;
+    model: unknown;
+  }) => Promise<unknown>;
+  
+  wrapStream?: (options: {
+    doGenerate: () => Promise<unknown>;
+    doStream: () => Promise<unknown>;
+    params: Record<string, unknown>;
+    model: unknown;
+  }) => Promise<unknown>;
+}
+
+/**
+ * Create attribution middleware that injects agent context into requests
+ * 
+ * Injects:
+ * - Headers: X-Agent-Id, X-Run-Id, X-Trace-Id, X-Session-Id
+ * - Provider options metadata where supported
+ */
+export function createAttributionMiddleware(ctx: AttributionContext): AISDKMiddleware {
+  return {
+    transformParams: async ({ params }) => {
+      // Build attribution headers
+      const attributionHeaders: Record<string, string> = {};
+      
+      if (ctx.agentId) {
+        attributionHeaders['X-Agent-Id'] = ctx.agentId;
+      }
+      if (ctx.runId) {
+        attributionHeaders['X-Run-Id'] = ctx.runId;
+      }
+      if (ctx.traceId) {
+        attributionHeaders['X-Trace-Id'] = ctx.traceId;
+      }
+      if (ctx.sessionId) {
+        attributionHeaders['X-Session-Id'] = ctx.sessionId;
+      }
+      if (ctx.parentSpanId) {
+        attributionHeaders['X-Parent-Span-Id'] = ctx.parentSpanId;
+      }
+      
+      // Merge with existing headers
+      const existingHeaders = (params.headers as Record<string, string>) || {};
+      const mergedHeaders = {
+        ...existingHeaders,
+        ...attributionHeaders
+      };
+      
+      // Build provider options metadata
+      const attributionMetadata: Record<string, string> = {};
+      if (ctx.agentId) attributionMetadata.agentId = ctx.agentId;
+      if (ctx.runId) attributionMetadata.runId = ctx.runId;
+      if (ctx.traceId) attributionMetadata.traceId = ctx.traceId;
+      if (ctx.sessionId) attributionMetadata.sessionId = ctx.sessionId;
+      
+      // Merge with existing provider options
+      const existingProviderOptions = (params.providerOptions as Record<string, unknown>) || {};
+      const existingMetadata = (existingProviderOptions.metadata as Record<string, unknown>) || {};
+      
+      const mergedProviderOptions = {
+        ...existingProviderOptions,
+        metadata: {
+          ...existingMetadata,
+          ...attributionMetadata
+        }
+      };
+      
+      return {
+        ...params,
+        headers: mergedHeaders,
+        providerOptions: mergedProviderOptions
+      };
+    }
+  };
+}
+
+/**
+ * Create logging middleware for debug purposes
+ * Only logs when debugLogging is enabled
+ */
+export function createLoggingMiddleware(config: AISDKBackendConfig): AISDKMiddleware {
+  if (!config.debugLogging) {
+    return {};
+  }
+  
+  return {
+    transformParams: async ({ params, type }) => {
+      const safeParams = config.redactLogs !== false 
+        ? redactSensitiveData(params) 
+        : params;
+      
+      console.log(`[AI SDK] ${type} request:`, JSON.stringify(safeParams, null, 2));
+      return params;
+    },
+    
+    wrapGenerate: async ({ doGenerate, params }) => {
+      const startTime = Date.now();
+      try {
+        const result = await doGenerate();
+        const duration = Date.now() - startTime;
+        console.log(`[AI SDK] generate completed in ${duration}ms`);
+        return result;
+      } catch (error) {
+        const duration = Date.now() - startTime;
+        console.error(`[AI SDK] generate failed after ${duration}ms:`, error);
+        throw error;
+      }
+    },
+    
+    wrapStream: async ({ doStream, params }) => {
+      const startTime = Date.now();
+      console.log(`[AI SDK] stream started`);
+      try {
+        const result = await doStream();
+        const duration = Date.now() - startTime;
+        console.log(`[AI SDK] stream setup completed in ${duration}ms`);
+        return result;
+      } catch (error) {
+        const duration = Date.now() - startTime;
+        console.error(`[AI SDK] stream failed after ${duration}ms:`, error);
+        throw error;
+      }
+    }
+  };
+}
+
+/**
+ * Create timeout middleware that wraps requests with AbortController
+ */
+export function createTimeoutMiddleware(timeoutMs: number): AISDKMiddleware {
+  return {
+    transformParams: async ({ params }) => {
+      // If there's already an abort signal, don't override it
+      if (params.abortSignal) {
+        return params;
+      }
+      
+      const controller = new AbortController();
+      const timeoutId = setTimeout(() => {
+        controller.abort(new Error(`Request timed out after ${timeoutMs}ms`));
+      }, timeoutMs);
+      
+      // Store timeout ID for cleanup (attached to signal)
+      (controller.signal as any).__timeoutId = timeoutId;
+      
+      return {
+        ...params,
+        abortSignal: controller.signal
+      };
+    }
+  };
+}
+
+/**
+ * Compose multiple middlewares into one
+ * Middlewares are applied in order (first transforms first, last wraps innermost)
+ */
+export function composeMiddleware(...middlewares: AISDKMiddleware[]): AISDKMiddleware {
+  const validMiddlewares = middlewares.filter(m => m && Object.keys(m).length > 0);
+  
+  if (validMiddlewares.length === 0) {
+    return {};
+  }
+  
+  if (validMiddlewares.length === 1) {
+    return validMiddlewares[0];
+  }
+  
+  return {
+    transformParams: async (options) => {
+      let params = options.params;
+      
+      for (const middleware of validMiddlewares) {
+        if (middleware.transformParams) {
+          params = await middleware.transformParams({
+            ...options,
+            params
+          });
+        }
+      }
+      
+      return params;
+    },
+    
+    wrapGenerate: async (options) => {
+      // Build nested wrapper from inside out
+      let doGenerate = options.doGenerate;
+      
+      for (let i = validMiddlewares.length - 1; i >= 0; i--) {
+        const middleware = validMiddlewares[i];
+        if (middleware.wrapGenerate) {
+          const currentDoGenerate = doGenerate;
+          const currentMiddleware = middleware;
+          doGenerate = () => currentMiddleware.wrapGenerate!({
+            ...options,
+            doGenerate: currentDoGenerate
+          });
+        }
+      }
+      
+      return doGenerate();
+    },
+    
+    wrapStream: async (options) => {
+      // Build nested wrapper from inside out
+      let doStream = options.doStream;
+      
+      for (let i = validMiddlewares.length - 1; i >= 0; i--) {
+        const middleware = validMiddlewares[i];
+        if (middleware.wrapStream) {
+          const currentDoStream = doStream;
+          const currentMiddleware = middleware;
+          doStream = () => currentMiddleware.wrapStream!({
+            ...options,
+            doStream: currentDoStream
+          });
+        }
+      }
+      
+      return doStream();
+    }
+  };
+}
+
+/**
+ * Redact sensitive data from objects for safe logging
+ */
+export function redactSensitiveData(obj: unknown): unknown {
+  if (obj === null || obj === undefined) {
+    return obj;
+  }
+  
+  if (typeof obj !== 'object') {
+    return obj;
+  }
+  
+  if (Array.isArray(obj)) {
+    return obj.map(redactSensitiveData);
+  }
+  
+  const result: Record<string, unknown> = {};
+  const sensitiveKeys = [
+    'apiKey', 'api_key', 'apikey',
+    'token', 'secret', 'password',
+    'authorization', 'auth',
+    'key', 'credential', 'credentials'
+  ];
+  
+  for (const [key, value] of Object.entries(obj as Record<string, unknown>)) {
+    const lowerKey = key.toLowerCase();
+    
+    if (sensitiveKeys.some(sk => lowerKey.includes(sk))) {
+      if (typeof value === 'string' && value.length > 4) {
+        result[key] = value.slice(0, 4) + '****';
+      } else {
+        result[key] = '****';
+      }
+    } else if (typeof value === 'object') {
+      result[key] = redactSensitiveData(value);
+    } else {
+      result[key] = value;
+    }
+  }
+  
+  return result;
+}
+
+/**
+ * Create all standard middlewares for the AI SDK backend
+ */
+export function createStandardMiddleware(
+  config: AISDKBackendConfig,
+  attribution?: AttributionContext
+): AISDKMiddleware {
+  const middlewares: AISDKMiddleware[] = [];
+  
+  // Attribution middleware (if context provided)
+  if (attribution && Object.keys(attribution).length > 0) {
+    middlewares.push(createAttributionMiddleware(attribution));
+  }
+  
+  // Timeout middleware
+  if (config.timeout && config.timeout > 0) {
+    middlewares.push(createTimeoutMiddleware(config.timeout));
+  }
+  
+  // Logging middleware (only if debug enabled)
+  if (config.debugLogging) {
+    middlewares.push(createLoggingMiddleware(config));
+  }
+  
+  return composeMiddleware(...middlewares);
+}

src/praisonai-ts/src/llm/providers/ai-sdk/provider-map.ts

@@ -0,0 +1,287 @@
+/**
+ * AI SDK Provider Map
+ * 
+ * Maps model strings to AI SDK providers with lazy loading.
+ * Supports formats: "provider/model" or "model" (uses default provider)
+ */
+
+import { 
+  AISDKError, 
+  AISDKProviderOptions, 
+  AISDK_PROVIDERS, 
+  PROVIDER_ALIASES 
+} from './types';
+
+/**
+ * Parsed model string result
+ */
+export interface ParsedModel {
+  providerId: string;
+  modelId: string;
+}
+
+/**
+ * Provider factory function type
+ */
+export type ProviderFactory = (options?: AISDKProviderOptions) => unknown;
+
+/**
+ * Custom provider registration
+ */
+const customProviders = new Map<string, ProviderFactory>();
+
+/**
+ * Parse a model string into provider and model ID
+ * 
+ * @example
+ * parseModelString("openai/gpt-4o") // { providerId: "openai", modelId: "gpt-4o" }
+ * parseModelString("gpt-4o-mini") // { providerId: "openai", modelId: "gpt-4o-mini" }
+ * parseModelString("claude-3-5-sonnet") // { providerId: "anthropic", modelId: "claude-3-5-sonnet" }
+ */
+export function parseModelString(model: string, defaultProvider: string = 'openai'): ParsedModel {
+  if (model.includes('/')) {
+    const [providerId, ...rest] = model.split('/');
+    const resolvedProvider = resolveProviderAlias(providerId.toLowerCase());
+    return { 
+      providerId: resolvedProvider, 
+      modelId: rest.join('/') 
+    };
+  }
+  
+  // Infer provider from model prefix
+  const inferredProvider = inferProviderFromModel(model);
+  return { 
+    providerId: inferredProvider || defaultProvider, 
+    modelId: model 
+  };
+}
+
+/**
+ * Resolve provider alias to canonical name
+ */
+export function resolveProviderAlias(providerId: string): string {
+  return PROVIDER_ALIASES[providerId] || providerId;
+}
+
+/**
+ * Infer provider from model name prefix
+ */
+function inferProviderFromModel(model: string): string | null {
+  const lowerModel = model.toLowerCase();
+  
+  // OpenAI models
+  if (lowerModel.startsWith('gpt-') || 
+      lowerModel.startsWith('o1') || 
+      lowerModel.startsWith('o3') ||
+      lowerModel.startsWith('text-') ||
+      lowerModel.startsWith('davinci') ||
+      lowerModel.startsWith('curie') ||
+      lowerModel.startsWith('babbage') ||
+      lowerModel.startsWith('ada')) {
+    return 'openai';
+  }
+  
+  // Anthropic models
+  if (lowerModel.startsWith('claude-')) {
+    return 'anthropic';
+  }
+  
+  // Google models
+  if (lowerModel.startsWith('gemini-') || 
+      lowerModel.startsWith('palm-') ||
+      lowerModel.startsWith('bison')) {
+    return 'google';
+  }
+  
+  // Mistral models
+  if (lowerModel.startsWith('mistral-') || 
+      lowerModel.startsWith('mixtral-') ||
+      lowerModel.startsWith('codestral')) {
+    return 'mistral';
+  }
+  
+  // Cohere models
+  if (lowerModel.startsWith('command-')) {
+    return 'cohere';
+  }
+  
+  // DeepSeek models
+  if (lowerModel.startsWith('deepseek-')) {
+    return 'deepseek';
+  }
+  
+  // Groq models (llama, mixtral via groq)
+  if (lowerModel.startsWith('llama-') || lowerModel.includes('groq')) {
+    return 'groq';
+  }
+  
+  return null;
+}
+
+/**
+ * Check if a provider is supported
+ */
+export function isProviderSupported(providerId: string): boolean {
+  const resolved = resolveProviderAlias(providerId);
+  return resolved in AISDK_PROVIDERS || customProviders.has(resolved);
+}
+
+/**
+ * Get the package name for a provider
+ */
+export function getProviderPackage(providerId: string): string | null {
+  const resolved = resolveProviderAlias(providerId);
+  return AISDK_PROVIDERS[resolved]?.package || null;
+}
+
+/**
+ * Get the environment variable key for a provider's API key
+ */
+export function getProviderEnvKey(providerId: string): string | null {
+  const resolved = resolveProviderAlias(providerId);
+  return AISDK_PROVIDERS[resolved]?.envKey || null;
+}
+
+/**
+ * List all supported providers
+ */
+export function listSupportedProviders(): string[] {
+  const builtIn = Object.keys(AISDK_PROVIDERS);
+  const custom = Array.from(customProviders.keys());
+  return [...new Set([...builtIn, ...custom])];
+}
+
+/**
+ * Register a custom provider factory
+ * 
+ * @example
+ * registerCustomProvider('my-provider', (options) => createMyProvider(options));
+ */
+export function registerCustomProvider(
+  providerId: string, 
+  factory: ProviderFactory
+): void {
+  customProviders.set(providerId.toLowerCase(), factory);
+}
+
+/**
+ * Unregister a custom provider
+ */
+export function unregisterCustomProvider(providerId: string): boolean {
+  return customProviders.delete(providerId.toLowerCase());
+}
+
+/**
+ * Get a custom provider factory
+ */
+export function getCustomProvider(providerId: string): ProviderFactory | undefined {
+  return customProviders.get(providerId.toLowerCase());
+}
+
+/**
+ * Dynamically import and create an AI SDK provider
+ * Uses lazy loading to avoid importing AI SDK packages until needed
+ */
+export async function createAISDKProvider(
+  providerId: string,
+  options?: AISDKProviderOptions
+): Promise<unknown> {
+  const resolved = resolveProviderAlias(providerId);
+  
+  // Check for custom provider first
+  const customFactory = customProviders.get(resolved);
+  if (customFactory) {
+    return customFactory(options);
+  }
+  
+  // Check if provider is supported
+  const providerInfo = AISDK_PROVIDERS[resolved];
+  if (!providerInfo) {
+    throw new AISDKError(
+      `Provider '${providerId}' is not supported. ` +
+      `Supported providers: ${listSupportedProviders().join(', ')}`,
+      'PROVIDER_NOT_FOUND',
+      false
+    );
+  }
+  
+  // Dynamically import the provider package
+  try {
+    const providerModule = await import(providerInfo.package);
+    
+    // Most AI SDK providers export a create<Provider> function
+    const createFnName = `create${capitalize(resolved.replace(/-/g, ''))}`;
+    const createFn = providerModule[createFnName] || providerModule.default;
+    
+    if (typeof createFn !== 'function') {
+      // Try direct provider export (some packages export the provider directly)
+      const providerName = resolved.replace(/-/g, '');
+      const directProvider = providerModule[providerName];
+      if (directProvider) {
+        return directProvider;
+      }
+      
+      throw new AISDKError(
+        `Could not find provider factory in '${providerInfo.package}'`,
+        'PROVIDER_ERROR',
+        false
+      );
+    }
+    
+    return createFn(options);
+  } catch (error: unknown) {
+    if (error instanceof AISDKError) {
+      throw error;
+    }
+    
+    const errorMessage = error instanceof Error ? error.message : String(error);
+    
+    // Check if it's a missing dependency error
+    if (errorMessage.includes('Cannot find module') || 
+        errorMessage.includes('MODULE_NOT_FOUND')) {
+      throw new AISDKError(
+        `AI SDK provider package '${providerInfo.package}' is not installed. ` +
+        `Install it with: npm install ${providerInfo.package}`,
+        'MISSING_DEPENDENCY',
+        false,
+        error
+      );
+    }
+    
+    throw new AISDKError(
+      `Failed to create AI SDK provider '${providerId}': ${errorMessage}`,
+      'PROVIDER_ERROR',
+      false,
+      error
+    );
+  }
+}
+
+/**
+ * Validate that a provider has the required API key
+ */
+export function validateProviderApiKey(providerId: string): boolean {
+  const envKey = getProviderEnvKey(providerId);
+  if (!envKey) {
+    return true; // Custom providers may not need env keys
+  }
+  return !!process.env[envKey];
+}
+
+/**
+ * Get missing API key message for a provider
+ */
+export function getMissingApiKeyMessage(providerId: string): string {
+  const envKey = getProviderEnvKey(providerId);
+  if (!envKey) {
+    return `Provider '${providerId}' may require authentication. Check provider documentation.`;
+  }
+  return `Missing API key for provider '${providerId}'. Set the ${envKey} environment variable.`;
+}
+
+/**
+ * Capitalize first letter of a string
+ */
+function capitalize(str: string): string {
+  return str.charAt(0).toUpperCase() + str.slice(1);
+}

src/praisonai-ts/src/llm/providers/ai-sdk/types.ts

@@ -0,0 +1,227 @@
+/**
+ * AI SDK Backend Types
+ * 
+ * Type definitions for the AI SDK integration with praisonai-ts.
+ * These types define the configuration, errors, and stream chunk formats.
+ */
+
+/**
+ * Attribution context for multi-agent safety
+ * Propagated to AI SDK calls via middleware
+ */
+export interface AttributionContext {
+  /** Unique identifier for the agent instance */
+  agentId?: string;
+  /** Unique identifier for this execution run */
+  runId?: string;
+  /** Trace ID for distributed tracing (OpenTelemetry compatible) */
+  traceId?: string;
+  /** Session ID for conversation continuity */
+  sessionId?: string;
+  /** Parent span ID for nested operations */
+  parentSpanId?: string;
+}
+
+/**
+ * Provider-specific configuration options
+ */
+export interface AISDKProviderOptions {
+  /** API key for the provider */
+  apiKey?: string;
+  /** Base URL override for the provider */
+  baseURL?: string;
+  /** Custom headers to include in requests */
+  headers?: Record<string, string>;
+  /** Custom fetch implementation */
+  fetch?: typeof fetch;
+}
+
+/**
+ * Telemetry settings for AI SDK calls
+ */
+export interface AISDKTelemetrySettings {
+  /** Enable or disable telemetry */
+  isEnabled?: boolean;
+  /** Enable or disable input recording */
+  recordInputs?: boolean;
+  /** Enable or disable output recording */
+  recordOutputs?: boolean;
+  /** Function identifier for grouping telemetry */
+  functionId?: string;
+  /** Additional metadata for telemetry */
+  metadata?: Record<string, unknown>;
+}
+
+/**
+ * Configuration for the AI SDK backend
+ */
+export interface AISDKBackendConfig {
+  /** Default provider if not specified in model string */
+  defaultProvider?: string;
+  /** Provider-specific configurations */
+  providers?: Record<string, AISDKProviderOptions>;
+  /** Attribution context for multi-agent safety */
+  attribution?: AttributionContext;
+  /** Telemetry settings */
+  telemetry?: AISDKTelemetrySettings;
+  /** Request timeout in milliseconds (default: 60000) */
+  timeout?: number;
+  /** Number of retries for retryable errors (default: 2) */
+  maxRetries?: number;
+  /** Maximum output tokens (default: 4096) */
+  maxOutputTokens?: number;
+  /** Enable debug logging (default: false) */
+  debugLogging?: boolean;
+  /** Redact sensitive data in logs (default: true) */
+  redactLogs?: boolean;
+}
+
+/**
+ * Error codes for AI SDK errors
+ */
+export type AISDKErrorCode =
+  | 'PROVIDER_ERROR'      // Provider-specific error
+  | 'RATE_LIMIT'          // 429 - Too many requests
+  | 'AUTHENTICATION'      // 401/403 - Auth failure
+  | 'INVALID_REQUEST'     // 400 - Bad request
+  | 'MODEL_NOT_FOUND'     // Model doesn't exist
+  | 'PROVIDER_NOT_FOUND'  // Provider not registered
+  | 'TIMEOUT'             // Request timeout
+  | 'NETWORK'             // Network failure
+  | 'CANCELLED'           // Request cancelled
+  | 'MISSING_DEPENDENCY'  // AI SDK not installed
+  | 'UNKNOWN';            // Unknown error
+
+/**
+ * Custom error class for AI SDK errors
+ */
+export class AISDKError extends Error {
+  public readonly code: AISDKErrorCode;
+  public readonly isRetryable: boolean;
+  public readonly cause?: unknown;
+  public readonly statusCode?: number;
+
+  constructor(
+    message: string,
+    code: AISDKErrorCode,
+    isRetryable: boolean,
+    cause?: unknown,
+    statusCode?: number
+  ) {
+    super(message);
+    this.name = 'AISDKError';
+    this.code = code;
+    this.isRetryable = isRetryable;
+    this.cause = cause;
+    this.statusCode = statusCode;
+    
+    // Maintain proper stack trace in V8
+    if (Error.captureStackTrace) {
+      Error.captureStackTrace(this, AISDKError);
+    }
+  }
+}
+
+/**
+ * Stream chunk types for streaming responses
+ */
+export type PraisonStreamChunk =
+  | { type: 'text'; text: string }
+  | { type: 'tool-call-start'; toolCallId: string; toolName: string }
+  | { type: 'tool-call-delta'; toolCallId: string; argsTextDelta: string }
+  | { type: 'tool-call-end'; toolCallId: string; args: unknown }
+  | { type: 'finish'; finishReason: string; usage?: TokenUsage }
+  | { type: 'error'; error: AISDKError };
+
+/**
+ * Token usage information
+ */
+export interface TokenUsage {
+  promptTokens: number;
+  completionTokens: number;
+  totalTokens: number;
+}
+
+/**
+ * Finish reasons for generation
+ */
+export type FinishReason = 
+  | 'stop'           // Natural completion
+  | 'length'         // Max tokens reached
+  | 'tool-calls'     // Tool calls requested
+  | 'content-filter' // Content filtered
+  | 'error'          // Error occurred
+  | 'cancelled'      // Request cancelled
+  | 'unknown';       // Unknown reason
+
+/**
+ * Tool definition for AI SDK
+ */
+export interface AISDKToolDefinition {
+  type: 'function';
+  name: string;
+  description?: string;
+  parameters: Record<string, unknown>;
+}
+
+/**
+ * Tool call from AI SDK response
+ */
+export interface AISDKToolCall {
+  toolCallId: string;
+  toolName: string;
+  args: unknown;
+}
+
+/**
+ * Tool result to send back to AI SDK
+ */
+export interface AISDKToolResult {
+  toolCallId: string;
+  toolName: string;
+  result: unknown;
+}
+
+/**
+ * Safe defaults for AI SDK backend
+ */
+export const SAFE_DEFAULTS = {
+  timeout: 60000,           // 60s request timeout
+  maxRetries: 2,            // Retry on transient failures
+  maxOutputTokens: 4096,    // Prevent runaway generation
+  redactLogs: true,         // Never log API keys
+  debugLogging: false,      // Opt-in verbose logging
+} as const;
+
+/**
+ * Supported AI SDK providers with their package names
+ */
+export const AISDK_PROVIDERS: Record<string, { package: string; envKey: string }> = {
+  openai: { package: '@ai-sdk/openai', envKey: 'OPENAI_API_KEY' },
+  anthropic: { package: '@ai-sdk/anthropic', envKey: 'ANTHROPIC_API_KEY' },
+  google: { package: '@ai-sdk/google', envKey: 'GOOGLE_API_KEY' },
+  azure: { package: '@ai-sdk/azure', envKey: 'AZURE_API_KEY' },
+  'amazon-bedrock': { package: '@ai-sdk/amazon-bedrock', envKey: 'AWS_ACCESS_KEY_ID' },
+  groq: { package: '@ai-sdk/groq', envKey: 'GROQ_API_KEY' },
+  mistral: { package: '@ai-sdk/mistral', envKey: 'MISTRAL_API_KEY' },
+  cohere: { package: '@ai-sdk/cohere', envKey: 'COHERE_API_KEY' },
+  deepseek: { package: '@ai-sdk/deepseek', envKey: 'DEEPSEEK_API_KEY' },
+  xai: { package: '@ai-sdk/xai', envKey: 'XAI_API_KEY' },
+  fireworks: { package: '@ai-sdk/fireworks', envKey: 'FIREWORKS_API_KEY' },
+  togetherai: { package: '@ai-sdk/togetherai', envKey: 'TOGETHER_API_KEY' },
+  perplexity: { package: '@ai-sdk/perplexity', envKey: 'PERPLEXITY_API_KEY' },
+} as const;
+
+/**
+ * Provider aliases for convenience
+ */
+export const PROVIDER_ALIASES: Record<string, string> = {
+  oai: 'openai',
+  claude: 'anthropic',
+  gemini: 'google',
+  gcp: 'google',
+  aws: 'amazon-bedrock',
+  bedrock: 'amazon-bedrock',
+  together: 'togetherai',
+  pplx: 'perplexity',
+} as const;

src/praisonai-ts/src/llm/providers/index.ts

@@ -1,5 +1,18 @@
 /**
  * LLM Providers - Factory and exports for multi-provider support
+ * 
+ * This module provides an extensible provider registry system that allows
+ * users to register custom providers (e.g., Cloudflare, Ollama) alongside
+ * the built-in providers (OpenAI, Anthropic, Google).
+ * 
+ * @example Register a custom provider
+ * ```typescript
+ * import { registerProvider, Agent } from 'praisonai';
+ * import { CloudflareProvider } from './my-cloudflare-provider';
+ * 
+ * registerProvider('cloudflare', CloudflareProvider);
+ * const agent = new Agent({ llm: 'cloudflare/workers-ai' });
+ * ```
  */
 
 export * from './types';
@@ -8,20 +21,25 @@ export { OpenAIProvider } from './openai';
 export { AnthropicProvider } from './anthropic';
 export { GoogleProvider } from './google';
 
-import type { LLMProvider, ProviderConfig } from './types';
-import { OpenAIProvider } from './openai';
-import { AnthropicProvider } from './anthropic';
-import { GoogleProvider } from './google';
+// Export registry types and functions
+export {
+  ProviderRegistry,
+  ProviderConstructor,
+  ProviderLoader,
+  RegisterOptions,
+  IProviderRegistry,
+  getDefaultRegistry,
+  createProviderRegistry,
+  registerProvider,
+  unregisterProvider,
+  hasProvider,
+  listProviders,
+  registerBuiltinProviders,
+} from './registry';
 
-/**
- * Provider registry for dynamic provider loading
- */
-const PROVIDER_MAP: Record<string, new (modelId: string, config?: ProviderConfig) => LLMProvider> = {
-  openai: OpenAIProvider,
-  anthropic: AnthropicProvider,
-  google: GoogleProvider,
-  gemini: GoogleProvider, // Alias
-};
+import type { LLMProvider, ProviderConfig } from './types';
+import { getDefaultRegistry } from './registry';
+import type { ProviderConstructor, ProviderRegistry } from './registry';
 
 /**
  * Parse model string into provider and model ID
@@ -51,25 +69,99 @@ export function parseModelString(model: string): { providerId: string; modelId:
 }
 
 /**
- * Create a provider instance from a model string
+ * Input types for createProvider
+ */
+export type ProviderInput = 
+  | string                                              // "provider/model" or "model"
+  | LLMProvider                                         // Already instantiated provider
+  | { name: string; modelId?: string; config?: ProviderConfig }; // Spec object
+
+/**
+ * Options for createProvider
+ */
+export interface CreateProviderOptions {
+  /** Override the default registry */
+  registry?: ProviderRegistry;
+  /** Provider configuration */
+  config?: ProviderConfig;
+  /** Model ID (used when input is a constructor or spec without modelId) */
+  modelId?: string;
+}
+
+/**
+ * Create a provider instance from various input types
  * 
- * @example
+ * @example String input (backward compatible)
  * ```typescript
  * const provider = createProvider('openai/gpt-4o');
  * const provider = createProvider('anthropic/claude-3-5-sonnet-latest');
  * const provider = createProvider('google/gemini-2.0-flash');
  * const provider = createProvider('gpt-4o-mini'); // Defaults to OpenAI
  * ```
+ * 
+ * @example Custom provider (after registration)
+ * ```typescript
+ * registerProvider('cloudflare', CloudflareProvider);
+ * const provider = createProvider('cloudflare/workers-ai');
+ * ```
+ * 
+ * @example Provider instance (pass-through)
+ * ```typescript
+ * const myProvider = new CustomProvider('model');
+ * const provider = createProvider(myProvider); // Returns same instance
+ * ```
+ * 
+ * @example Spec object
+ * ```typescript
+ * const provider = createProvider({ name: 'openai', modelId: 'gpt-4o', config: { timeout: 5000 } });
+ * ```
  */
-export function createProvider(model: string, config?: ProviderConfig): LLMProvider {
-  const { providerId, modelId } = parseModelString(model);
-  
-  const ProviderClass = PROVIDER_MAP[providerId];
-  if (!ProviderClass) {
-    throw new Error(`Unknown provider: ${providerId}. Available providers: ${Object.keys(PROVIDER_MAP).join(', ')}`);
+export function createProvider(
+  input: ProviderInput,
+  options?: CreateProviderOptions | ProviderConfig
+): LLMProvider {
+  // Handle legacy signature: createProvider(model, config)
+  const opts: CreateProviderOptions = options && 'registry' in options 
+    ? options 
+    : { config: options as ProviderConfig | undefined };
+
+  const registry = opts.registry || getDefaultRegistry();
+
+  // Case 1: Already a provider instance - pass through
+  if (isProviderInstance(input)) {
+    return input;
   }
-  
-  return new ProviderClass(modelId, config);
+
+  // Case 2: Spec object
+  if (typeof input === 'object' && 'name' in input) {
+    const { name, modelId, config } = input;
+    return registry.resolve(name, modelId || 'default', config || opts.config);
+  }
+
+  // Case 3: String - parse and resolve
+  if (typeof input === 'string') {
+    const { providerId, modelId } = parseModelString(input);
+    return registry.resolve(providerId, modelId, opts.config);
+  }
+
+  throw new Error(
+    `Invalid provider input. Expected string, provider instance, or spec object. ` +
+    `Got: ${typeof input}`
+  );
+}
+
+/**
+ * Type guard to check if value is a provider instance
+ */
+function isProviderInstance(value: unknown): value is LLMProvider {
+  return (
+    typeof value === 'object' &&
+    value !== null &&
+    'providerId' in value &&
+    'modelId' in value &&
+    'generateText' in value &&
+    typeof (value as any).generateText === 'function'
+  );
 }
 
 /**
@@ -83,22 +175,88 @@ export function getDefaultProvider(config?: ProviderConfig): LLMProvider {
  * Check if a provider is available (has required API key)
  */
 export function isProviderAvailable(providerId: string): boolean {
-  switch (providerId.toLowerCase()) {
+  const normalizedId = providerId.toLowerCase();
+  
+  // Check if provider is registered
+  if (!getDefaultRegistry().has(normalizedId)) {
+    return false;
+  }
+  
+  // Check for API keys based on known providers
+  switch (normalizedId) {
     case 'openai':
+    case 'oai':
       return !!process.env.OPENAI_API_KEY;
     case 'anthropic':
+    case 'claude':
       return !!process.env.ANTHROPIC_API_KEY;
     case 'google':
     case 'gemini':
       return !!process.env.GOOGLE_API_KEY;
     default:
-      return false;
+      // For custom providers, assume available if registered
+      // Users can override this behavior
+      return true;
   }
 }
 
 /**
- * Get list of available providers
+ * Get list of available providers (registered and with API keys)
  */
 export function getAvailableProviders(): string[] {
-  return Object.keys(PROVIDER_MAP).filter(isProviderAvailable);
+  return getDefaultRegistry().list().filter(isProviderAvailable);
 }
+
+// ============================================================================
+// AI SDK Integration Exports
+// ============================================================================
+
+/**
+ * AI SDK Backend - Multi-provider LLM support via Vercel's AI SDK
+ * 
+ * @example
+ * ```typescript
+ * import { createAISDKBackend } from 'praisonai';
+ * 
+ * const backend = createAISDKBackend('anthropic/claude-3-5-sonnet');
+ * const result = await backend.generateText({ messages: [...] });
+ * ```
+ */
+export {
+  // Backend
+  AISDKBackend,
+  createAISDKBackend,
+  
+  // Provider utilities
+  isProviderSupported as isAISDKProviderSupported,
+  listSupportedProviders as listAISDKProviders,
+  registerCustomProvider as registerAISDKCustomProvider,
+  validateProviderApiKey as validateAISDKProviderApiKey,
+  getMissingApiKeyMessage as getAISDKMissingApiKeyMessage,
+  isAISDKAvailable,
+  getAISDKVersion,
+  
+  // Types
+  AISDKError,
+  SAFE_DEFAULTS as AISDK_SAFE_DEFAULTS,
+  AISDK_PROVIDERS,
+  PROVIDER_ALIASES as AISDK_PROVIDER_ALIASES,
+  
+  // Middleware
+  createAttributionMiddleware,
+  createStandardMiddleware,
+  redactSensitiveData,
+} from './ai-sdk';
+
+export type {
+  AISDKBackendConfig,
+  AISDKProviderOptions,
+  AttributionContext,
+  AISDKTelemetrySettings,
+  AISDKErrorCode,
+  PraisonStreamChunk,
+  AISDKToolDefinition,
+  AISDKToolCall,
+  AISDKToolResult,
+  AISDKMiddleware,
+} from './ai-sdk';

src/praisonai-ts/src/llm/providers/registry.ts

@@ -0,0 +1,367 @@
+/**
+ * Provider Registry - Extensible provider registration system
+ * 
+ * Fixes Issue #1095: Allows users to register custom providers
+ * that can be resolved by name via createProvider().
+ */
+
+import type { LLMProvider, ProviderConfig } from './types';
+
+/**
+ * Provider constructor type
+ */
+export type ProviderConstructor = new (modelId: string, config?: ProviderConfig) => LLMProvider;
+
+/**
+ * Lazy loader function that returns a provider constructor
+ * Used for tree-shaking and lazy loading of provider implementations
+ */
+export type ProviderLoader = () => ProviderConstructor;
+
+/**
+ * Options for registering a provider
+ */
+export interface RegisterOptions {
+  /** Allow overwriting an existing registration */
+  override?: boolean;
+  /** Additional names that resolve to this provider */
+  aliases?: string[];
+}
+
+/**
+ * Internal entry in the registry
+ */
+interface RegistryEntry {
+  /** The provider constructor or loader */
+  provider: ProviderConstructor | ProviderLoader;
+  /** Whether this is a loader function (vs direct constructor) */
+  isLoader: boolean;
+  /** Cached constructor if loaded from a loader */
+  cachedConstructor?: ProviderConstructor;
+  /** The canonical name (for aliases) */
+  canonicalName: string;
+}
+
+/**
+ * Provider Registry Interface
+ */
+export interface IProviderRegistry {
+  register(name: string, provider: ProviderConstructor | ProviderLoader, options?: RegisterOptions): void;
+  unregister(name: string): boolean;
+  has(name: string): boolean;
+  list(): string[];
+  resolve(name: string, modelId: string, config?: ProviderConfig): LLMProvider;
+  get(name: string): ProviderConstructor | ProviderLoader | undefined;
+}
+
+/**
+ * Provider Registry Implementation
+ * 
+ * Manages registration and resolution of LLM providers by name.
+ * Supports lazy loading, aliases, and isolated instances.
+ */
+export class ProviderRegistry implements IProviderRegistry {
+  private entries: Map<string, RegistryEntry> = new Map();
+  private aliases: Map<string, string> = new Map(); // alias -> canonical name
+
+  /**
+   * Register a provider by name
+   * 
+   * @param name - Provider name (e.g., 'cloudflare', 'ollama')
+   * @param provider - Provider constructor or lazy loader function
+   * @param options - Registration options
+   * @throws Error if name is already registered (unless override: true)
+   */
+  register(
+    name: string,
+    provider: ProviderConstructor | ProviderLoader,
+    options: RegisterOptions = {}
+  ): void {
+    const normalizedName = name.toLowerCase();
+    
+    // Check for existing registration
+    if (this.entries.has(normalizedName) && !options.override) {
+      throw new Error(
+        `Provider '${name}' is already registered. ` +
+        `Use { override: true } to replace it.`
+      );
+    }
+
+    // Determine if this is a loader function or direct constructor
+    const isLoader = this.isLoaderFunction(provider);
+
+    const entry: RegistryEntry = {
+      provider,
+      isLoader,
+      canonicalName: normalizedName,
+    };
+
+    this.entries.set(normalizedName, entry);
+
+    // Register aliases
+    if (options.aliases) {
+      for (const alias of options.aliases) {
+        const normalizedAlias = alias.toLowerCase();
+        if (this.entries.has(normalizedAlias) && !options.override) {
+          throw new Error(
+            `Alias '${alias}' conflicts with existing provider. ` +
+            `Use { override: true } to replace it.`
+          );
+        }
+        this.aliases.set(normalizedAlias, normalizedName);
+      }
+    }
+  }
+
+  /**
+   * Unregister a provider by name
+   * 
+   * @param name - Provider name to unregister
+   * @returns true if provider was unregistered, false if not found
+   */
+  unregister(name: string): boolean {
+    const normalizedName = name.toLowerCase();
+    
+    // Check if it's an alias
+    if (this.aliases.has(normalizedName)) {
+      this.aliases.delete(normalizedName);
+      return true;
+    }
+
+    // Check if it's a canonical name
+    if (this.entries.has(normalizedName)) {
+      // Remove all aliases pointing to this provider
+      for (const [alias, canonical] of this.aliases.entries()) {
+        if (canonical === normalizedName) {
+          this.aliases.delete(alias);
+        }
+      }
+      this.entries.delete(normalizedName);
+      return true;
+    }
+
+    return false;
+  }
+
+  /**
+   * Check if a provider is registered
+   * 
+   * @param name - Provider name to check
+   * @returns true if provider is registered
+   */
+  has(name: string): boolean {
+    const normalizedName = name.toLowerCase();
+    return this.entries.has(normalizedName) || this.aliases.has(normalizedName);
+  }
+
+  /**
+   * List all registered provider names (canonical names only)
+   * 
+   * @returns Array of provider names
+   */
+  list(): string[] {
+    return Array.from(this.entries.keys());
+  }
+
+  /**
+   * List all names including aliases
+   * 
+   * @returns Array of all registered names and aliases
+   */
+  listAll(): string[] {
+    return [...this.entries.keys(), ...this.aliases.keys()];
+  }
+
+  /**
+   * Resolve a provider by name, creating an instance
+   * 
+   * @param name - Provider name
+   * @param modelId - Model ID to pass to constructor
+   * @param config - Optional provider config
+   * @returns Provider instance
+   * @throws Error if provider not found
+   */
+  resolve(name: string, modelId: string, config?: ProviderConfig): LLMProvider {
+    const normalizedName = name.toLowerCase();
+    
+    // Resolve alias to canonical name
+    const canonicalName = this.aliases.get(normalizedName) || normalizedName;
+    
+    const entry = this.entries.get(canonicalName);
+    if (!entry) {
+      const available = this.list();
+      throw new Error(
+        `Unknown provider: '${name}'. ` +
+        `Available providers: ${available.length > 0 ? available.join(', ') : 'none'}. ` +
+        `Register a custom provider with registerProvider('${name}', YourProviderClass).`
+      );
+    }
+
+    // Get constructor (resolve loader if needed)
+    const Constructor = this.getConstructor(entry);
+    
+    return new Constructor(modelId, config);
+  }
+
+  /**
+   * Get the provider constructor/loader without instantiating
+   * 
+   * @param name - Provider name
+   * @returns Provider constructor/loader or undefined
+   */
+  get(name: string): ProviderConstructor | ProviderLoader | undefined {
+    const normalizedName = name.toLowerCase();
+    const canonicalName = this.aliases.get(normalizedName) || normalizedName;
+    return this.entries.get(canonicalName)?.provider;
+  }
+
+  /**
+   * Get the resolved constructor for an entry
+   */
+  private getConstructor(entry: RegistryEntry): ProviderConstructor {
+    if (!entry.isLoader) {
+      return entry.provider as ProviderConstructor;
+    }
+
+    // Lazy load and cache
+    if (!entry.cachedConstructor) {
+      const loader = entry.provider as ProviderLoader;
+      entry.cachedConstructor = loader();
+    }
+
+    return entry.cachedConstructor;
+  }
+
+  /**
+   * Determine if a value is a loader function vs a constructor
+   * Loaders are arrow functions or regular functions that return a class
+   * Constructors have a prototype with constructor
+   */
+  private isLoaderFunction(value: ProviderConstructor | ProviderLoader): boolean {
+    // If it has a prototype with more than just constructor, it's likely a class
+    if (value.prototype && Object.getOwnPropertyNames(value.prototype).length > 1) {
+      return false;
+    }
+    
+    // Check if it looks like a class (has 'prototype' that is an object with constructor)
+    if (value.prototype && value.prototype.constructor === value) {
+      // Additional check: classes typically have a name and their toString starts with 'class'
+      const str = value.toString();
+      if (str.startsWith('class ') || str.includes('function ')) {
+        return false;
+      }
+    }
+
+    // Arrow functions and simple functions are loaders
+    return typeof value === 'function' && !value.prototype?.constructor;
+  }
+}
+
+// ============================================================================
+// Default Registry Singleton
+// ============================================================================
+
+let defaultRegistry: ProviderRegistry | null = null;
+
+/**
+ * Get the default global provider registry
+ * 
+ * This is the registry used by createProvider() when no custom registry is specified.
+ * Built-in providers (OpenAI, Anthropic, Google) are registered here.
+ */
+export function getDefaultRegistry(): ProviderRegistry {
+  if (!defaultRegistry) {
+    defaultRegistry = new ProviderRegistry();
+    registerBuiltinProviders(defaultRegistry);
+  }
+  return defaultRegistry;
+}
+
+/**
+ * Create a new isolated provider registry
+ * 
+ * Use this when you need a separate registry that doesn't share
+ * registrations with the default global registry.
+ */
+export function createProviderRegistry(): ProviderRegistry {
+  return new ProviderRegistry();
+}
+
+/**
+ * Register a provider to the default global registry
+ * 
+ * @example
+ * ```typescript
+ * import { registerProvider } from 'praisonai';
+ * import { CloudflareProvider } from './my-cloudflare-provider';
+ * 
+ * registerProvider('cloudflare', CloudflareProvider);
+ * 
+ * // Now works:
+ * const agent = new Agent({ llm: 'cloudflare/workers-ai' });
+ * ```
+ */
+export function registerProvider(
+  name: string,
+  provider: ProviderConstructor | ProviderLoader,
+  options?: RegisterOptions
+): void {
+  getDefaultRegistry().register(name, provider, options);
+}
+
+/**
+ * Unregister a provider from the default global registry
+ */
+export function unregisterProvider(name: string): boolean {
+  return getDefaultRegistry().unregister(name);
+}
+
+/**
+ * Check if a provider is registered in the default registry
+ */
+export function hasProvider(name: string): boolean {
+  return getDefaultRegistry().has(name);
+}
+
+/**
+ * List all providers in the default registry
+ */
+export function listProviders(): string[] {
+  return getDefaultRegistry().list();
+}
+
+// ============================================================================
+// Built-in Provider Registration
+// ============================================================================
+
+/**
+ * Register built-in providers to a registry
+ * Uses lazy loaders to avoid importing all providers at module load time
+ */
+export function registerBuiltinProviders(registry: ProviderRegistry): void {
+  // OpenAI - lazy loaded
+  registry.register('openai', () => {
+    const { OpenAIProvider } = require('./openai');
+    return OpenAIProvider;
+  }, { aliases: ['oai'] });
+
+  // Anthropic - lazy loaded
+  registry.register('anthropic', () => {
+    const { AnthropicProvider } = require('./anthropic');
+    return AnthropicProvider;
+  }, { aliases: ['claude'] });
+
+  // Google - lazy loaded
+  registry.register('google', () => {
+    const { GoogleProvider } = require('./google');
+    return GoogleProvider;
+  }, { aliases: ['gemini'] });
+}
+
+/**
+ * Reset the default registry (mainly for testing)
+ * @internal
+ */
+export function _resetDefaultRegistry(): void {
+  defaultRegistry = null;
+}

src/praisonai-ts/tests/unit/llm/ai-sdk/adapter.test.ts

@@ -0,0 +1,391 @@
+/**
+ * AI SDK Adapter Tests
+ */
+
+import {
+  toAISDKPrompt,
+  toAISDKTools,
+  fromAISDKToolCall,
+  fromAISDKResult,
+  fromAISDKStreamChunk,
+  mapFinishReason,
+  mapFinishReasonToProvider,
+  toAISDKToolChoice,
+  createSimplePrompt,
+} from '../../../../src/llm/providers/ai-sdk/adapter';
+
+import type { Message, ToolDefinition } from '../../../../src/llm/providers/types';
+
+describe('toAISDKPrompt', () => {
+  it('should convert system message', () => {
+    const messages: Message[] = [
+      { role: 'system', content: 'You are helpful' }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result).toHaveLength(1);
+    expect(result[0]).toEqual({
+      role: 'system',
+      content: 'You are helpful'
+    });
+  });
+
+  it('should convert user message', () => {
+    const messages: Message[] = [
+      { role: 'user', content: 'Hello!' }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result).toHaveLength(1);
+    expect(result[0]).toEqual({
+      role: 'user',
+      content: [{ type: 'text', text: 'Hello!' }]
+    });
+  });
+
+  it('should convert assistant message with text', () => {
+    const messages: Message[] = [
+      { role: 'assistant', content: 'Hi there!' }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result).toHaveLength(1);
+    expect(result[0]).toEqual({
+      role: 'assistant',
+      content: [{ type: 'text', text: 'Hi there!' }]
+    });
+  });
+
+  it('should convert assistant message with tool calls', () => {
+    const messages: Message[] = [
+      {
+        role: 'assistant',
+        content: null,
+        tool_calls: [{
+          id: 'call_123',
+          type: 'function',
+          function: {
+            name: 'get_weather',
+            arguments: '{"city": "London"}'
+          }
+        }]
+      }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result).toHaveLength(1);
+    expect(result[0].role).toBe('assistant');
+    expect((result[0] as any).content).toHaveLength(1);
+    expect((result[0] as any).content[0]).toEqual({
+      type: 'tool-call',
+      toolCallId: 'call_123',
+      toolName: 'get_weather',
+      args: { city: 'London' }
+    });
+  });
+
+  it('should convert tool message', () => {
+    const messages: Message[] = [
+      {
+        role: 'tool',
+        content: '{"temperature": 20}',
+        tool_call_id: 'call_123',
+        name: 'get_weather'
+      }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result).toHaveLength(1);
+    expect(result[0]).toEqual({
+      role: 'tool',
+      content: [{
+        type: 'tool-result',
+        toolCallId: 'call_123',
+        toolName: 'get_weather',
+        result: { temperature: 20 }
+      }]
+    });
+  });
+
+  it('should handle null content', () => {
+    const messages: Message[] = [
+      { role: 'user', content: null }
+    ];
+    
+    const result = toAISDKPrompt(messages);
+    
+    expect(result[0]).toEqual({
+      role: 'user',
+      content: [{ type: 'text', text: '' }]
+    });
+  });
+});
+
+describe('toAISDKTools', () => {
+  it('should convert tool definitions', async () => {
+    const tools: ToolDefinition[] = [
+      {
+        name: 'get_weather',
+        description: 'Get the weather for a city',
+        parameters: {
+          type: 'object',
+          properties: {
+            city: { type: 'string' }
+          },
+          required: ['city']
+        }
+      }
+    ];
+    
+    const result = await toAISDKTools(tools);
+    
+    // Check that tool was created with description
+    expect(result.get_weather).toBeDefined();
+    expect(result.get_weather.description).toBe('Get the weather for a city');
+  });
+
+  it('should handle tools without parameters', async () => {
+    const tools: ToolDefinition[] = [
+      { name: 'get_time' }
+    ];
+    
+    const result = await toAISDKTools(tools);
+    
+    expect(result.get_time).toBeDefined();
+  });
+});
+
+describe('fromAISDKToolCall', () => {
+  it('should convert AI SDK tool call to praisonai format', () => {
+    const toolCall = {
+      toolCallId: 'call_123',
+      toolName: 'get_weather',
+      args: { city: 'London' }
+    };
+    
+    const result = fromAISDKToolCall(toolCall);
+    
+    expect(result).toEqual({
+      id: 'call_123',
+      type: 'function',
+      function: {
+        name: 'get_weather',
+        arguments: '{"city":"London"}'
+      }
+    });
+  });
+
+  it('should handle string args', () => {
+    const toolCall = {
+      toolCallId: 'call_123',
+      toolName: 'test',
+      args: '{"key": "value"}'
+    };
+    
+    const result = fromAISDKToolCall(toolCall);
+    
+    expect(result.function.arguments).toBe('{"key": "value"}');
+  });
+});
+
+describe('fromAISDKResult', () => {
+  it('should convert AI SDK result to praisonai format', () => {
+    const result = fromAISDKResult({
+      text: 'Hello!',
+      usage: { promptTokens: 10, completionTokens: 5 },
+      finishReason: 'stop'
+    });
+    
+    expect(result.text).toBe('Hello!');
+    expect(result.usage).toEqual({
+      promptTokens: 10,
+      completionTokens: 5,
+      totalTokens: 15
+    });
+    expect(result.finishReason).toBe('stop');
+  });
+
+  it('should handle missing usage', () => {
+    const result = fromAISDKResult({
+      text: 'Hello!',
+      finishReason: 'stop'
+    });
+    
+    expect(result.usage).toEqual({
+      promptTokens: 0,
+      completionTokens: 0,
+      totalTokens: 0
+    });
+  });
+
+  it('should handle tool calls', () => {
+    const result = fromAISDKResult({
+      text: '',
+      toolCalls: [{
+        toolCallId: 'call_123',
+        toolName: 'test',
+        args: {}
+      }],
+      finishReason: 'tool_calls'
+    });
+    
+    expect(result.toolCalls).toHaveLength(1);
+    expect(result.toolCalls![0].id).toBe('call_123');
+    expect(result.finishReason).toBe('tool_calls');
+  });
+});
+
+describe('mapFinishReason', () => {
+  it('should map stop reasons', () => {
+    expect(mapFinishReason('stop')).toBe('stop');
+    expect(mapFinishReason('end_turn')).toBe('stop');
+    expect(mapFinishReason('end')).toBe('stop');
+  });
+
+  it('should map length reasons', () => {
+    expect(mapFinishReason('length')).toBe('length');
+    expect(mapFinishReason('max_tokens')).toBe('length');
+  });
+
+  it('should map tool call reasons', () => {
+    expect(mapFinishReason('tool_calls')).toBe('tool-calls');
+    expect(mapFinishReason('tool-calls')).toBe('tool-calls');
+    expect(mapFinishReason('function_call')).toBe('tool-calls');
+  });
+
+  it('should map content filter', () => {
+    expect(mapFinishReason('content_filter')).toBe('content-filter');
+    expect(mapFinishReason('content-filter')).toBe('content-filter');
+  });
+
+  it('should return unknown for undefined', () => {
+    expect(mapFinishReason(undefined)).toBe('unknown');
+    expect(mapFinishReason('something_else')).toBe('unknown');
+  });
+});
+
+describe('mapFinishReasonToProvider', () => {
+  it('should map to provider format with underscores', () => {
+    expect(mapFinishReasonToProvider('tool_calls')).toBe('tool_calls');
+    expect(mapFinishReasonToProvider('tool-calls')).toBe('tool_calls');
+    expect(mapFinishReasonToProvider('content_filter')).toBe('content_filter');
+    expect(mapFinishReasonToProvider('content-filter')).toBe('content_filter');
+  });
+
+  it('should default to stop for undefined', () => {
+    expect(mapFinishReasonToProvider(undefined)).toBe('stop');
+  });
+});
+
+describe('fromAISDKStreamChunk', () => {
+  it('should convert text delta', () => {
+    const chunk = fromAISDKStreamChunk({
+      type: 'text-delta',
+      textDelta: 'Hello'
+    });
+    
+    expect(chunk).toEqual({ type: 'text', text: 'Hello' });
+  });
+
+  it('should convert tool call start', () => {
+    const chunk = fromAISDKStreamChunk({
+      type: 'tool-call-streaming-start',
+      toolCallId: 'call_123',
+      toolName: 'test'
+    });
+    
+    expect(chunk).toEqual({
+      type: 'tool-call-start',
+      toolCallId: 'call_123',
+      toolName: 'test'
+    });
+  });
+
+  it('should convert tool call delta', () => {
+    const chunk = fromAISDKStreamChunk({
+      type: 'tool-call-delta',
+      toolCallId: 'call_123',
+      argsTextDelta: '{"key":'
+    });
+    
+    expect(chunk).toEqual({
+      type: 'tool-call-delta',
+      toolCallId: 'call_123',
+      argsTextDelta: '{"key":'
+    });
+  });
+
+  it('should convert finish', () => {
+    const chunk = fromAISDKStreamChunk({
+      type: 'finish',
+      finishReason: 'stop',
+      usage: { promptTokens: 10, completionTokens: 5 }
+    });
+    
+    expect(chunk).toEqual({
+      type: 'finish',
+      finishReason: 'stop',
+      usage: {
+        promptTokens: 10,
+        completionTokens: 5,
+        totalTokens: 15
+      }
+    });
+  });
+
+  it('should return null for unknown chunk types', () => {
+    const chunk = fromAISDKStreamChunk({
+      type: 'unknown-type'
+    });
+    
+    expect(chunk).toBeNull();
+  });
+});
+
+describe('toAISDKToolChoice', () => {
+  it('should pass through string values', () => {
+    expect(toAISDKToolChoice('auto')).toBe('auto');
+    expect(toAISDKToolChoice('none')).toBe('none');
+    expect(toAISDKToolChoice('required')).toBe('required');
+  });
+
+  it('should pass through tool object', () => {
+    const choice = { type: 'tool' as const, toolName: 'test' };
+    expect(toAISDKToolChoice(choice)).toEqual(choice);
+  });
+
+  it('should return undefined for undefined', () => {
+    expect(toAISDKToolChoice(undefined)).toBeUndefined();
+  });
+});
+
+describe('createSimplePrompt', () => {
+  it('should create prompt with user message', () => {
+    const result = createSimplePrompt('Hello!');
+    
+    expect(result).toHaveLength(1);
+    expect(result[0]).toEqual({
+      role: 'user',
+      content: [{ type: 'text', text: 'Hello!' }]
+    });
+  });
+
+  it('should include system prompt if provided', () => {
+    const result = createSimplePrompt('Hello!', 'You are helpful');
+    
+    expect(result).toHaveLength(2);
+    expect(result[0]).toEqual({
+      role: 'system',
+      content: 'You are helpful'
+    });
+    expect(result[1]).toEqual({
+      role: 'user',
+      content: [{ type: 'text', text: 'Hello!' }]
+    });
+  });
+});

src/praisonai-ts/tests/unit/llm/ai-sdk/lazy-import.test.ts

@@ -0,0 +1,110 @@
+/**
+ * AI SDK Lazy Import Tests
+ * 
+ * Verifies that AI SDK modules are not loaded until actually used.
+ */
+
+describe('Lazy Import', () => {
+  beforeEach(() => {
+    // Clear module cache to test fresh imports
+    jest.resetModules();
+  });
+
+  it('should not import AI SDK when importing types', () => {
+    // Types should be importable without triggering AI SDK load
+    const types = require('../../../../src/llm/providers/ai-sdk/types');
+    
+    expect(types.AISDKError).toBeDefined();
+    expect(types.SAFE_DEFAULTS).toBeDefined();
+    expect(types.AISDK_PROVIDERS).toBeDefined();
+    
+    // AI SDK should not be in require.cache
+    const aiSdkCached = Object.keys(require.cache).some(k => 
+      k.includes('node_modules/ai/') || k.includes('node_modules/@ai-sdk/')
+    );
+    expect(aiSdkCached).toBe(false);
+  });
+
+  it('should not import AI SDK when importing provider-map', () => {
+    const providerMap = require('../../../../src/llm/providers/ai-sdk/provider-map');
+    
+    expect(providerMap.parseModelString).toBeDefined();
+    expect(providerMap.isProviderSupported).toBeDefined();
+    
+    // AI SDK should not be in require.cache
+    const aiSdkCached = Object.keys(require.cache).some(k => 
+      k.includes('node_modules/ai/') || k.includes('node_modules/@ai-sdk/')
+    );
+    expect(aiSdkCached).toBe(false);
+  });
+
+  it('should not import AI SDK when importing adapter', () => {
+    const adapter = require('../../../../src/llm/providers/ai-sdk/adapter');
+    
+    expect(adapter.toAISDKPrompt).toBeDefined();
+    expect(adapter.fromAISDKResult).toBeDefined();
+    
+    // AI SDK should not be in require.cache
+    const aiSdkCached = Object.keys(require.cache).some(k => 
+      k.includes('node_modules/ai/') || k.includes('node_modules/@ai-sdk/')
+    );
+    expect(aiSdkCached).toBe(false);
+  });
+
+  it('should not import AI SDK when importing middleware', () => {
+    const middleware = require('../../../../src/llm/providers/ai-sdk/middleware');
+    
+    expect(middleware.createAttributionMiddleware).toBeDefined();
+    expect(middleware.redactSensitiveData).toBeDefined();
+    
+    // AI SDK should not be in require.cache
+    const aiSdkCached = Object.keys(require.cache).some(k => 
+      k.includes('node_modules/ai/') || k.includes('node_modules/@ai-sdk/')
+    );
+    expect(aiSdkCached).toBe(false);
+  });
+
+  it('should not import AI SDK when importing index (before backend use)', () => {
+    const aiSdk = require('../../../../src/llm/providers/ai-sdk');
+    
+    // These should be available without AI SDK
+    expect(aiSdk.AISDKError).toBeDefined();
+    expect(aiSdk.parseModelString).toBeDefined();
+    expect(aiSdk.toAISDKPrompt).toBeDefined();
+    expect(aiSdk.createAttributionMiddleware).toBeDefined();
+    
+    // AI SDK should not be in require.cache yet
+    const aiSdkCached = Object.keys(require.cache).some(k => 
+      k.includes('node_modules/ai/') || k.includes('node_modules/@ai-sdk/')
+    );
+    expect(aiSdkCached).toBe(false);
+  });
+
+  it('should export createAISDKBackend function', () => {
+    const aiSdk = require('../../../../src/llm/providers/ai-sdk');
+    
+    expect(typeof aiSdk.createAISDKBackend).toBe('function');
+  });
+
+  it('should export isAISDKAvailable function', () => {
+    const aiSdk = require('../../../../src/llm/providers/ai-sdk');
+    
+    expect(typeof aiSdk.isAISDKAvailable).toBe('function');
+  });
+});
+
+describe('Backend Instantiation', () => {
+  it('should create backend instance without immediate AI SDK import', () => {
+    jest.resetModules();
+    
+    const { createAISDKBackend } = require('../../../../src/llm/providers/ai-sdk');
+    
+    // Creating the backend should not immediately import AI SDK
+    // The import happens on first method call
+    const backend = createAISDKBackend('openai/gpt-4o-mini');
+    
+    expect(backend).toBeDefined();
+    expect(backend.providerId).toBe('openai');
+    expect(backend.modelId).toBe('gpt-4o-mini');
+  });
+});

src/praisonai-ts/tests/unit/llm/ai-sdk/middleware.test.ts

@@ -0,0 +1,296 @@
+/**
+ * AI SDK Middleware Tests
+ */
+
+import {
+  createAttributionMiddleware,
+  createLoggingMiddleware,
+  createTimeoutMiddleware,
+  composeMiddleware,
+  createStandardMiddleware,
+  redactSensitiveData,
+} from '../../../../src/llm/providers/ai-sdk/middleware';
+
+import type { AttributionContext, AISDKBackendConfig } from '../../../../src/llm/providers/ai-sdk/types';
+
+describe('createAttributionMiddleware', () => {
+  it('should inject attribution headers', async () => {
+    const ctx: AttributionContext = {
+      agentId: 'agent-123',
+      runId: 'run-456',
+      traceId: 'trace-789',
+      sessionId: 'session-abc'
+    };
+    
+    const middleware = createAttributionMiddleware(ctx);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.headers).toEqual({
+      'X-Agent-Id': 'agent-123',
+      'X-Run-Id': 'run-456',
+      'X-Trace-Id': 'trace-789',
+      'X-Session-Id': 'session-abc'
+    });
+  });
+
+  it('should inject provider options metadata', async () => {
+    const ctx: AttributionContext = {
+      agentId: 'agent-123',
+      runId: 'run-456'
+    };
+    
+    const middleware = createAttributionMiddleware(ctx);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect((result.providerOptions as any).metadata).toEqual({
+      agentId: 'agent-123',
+      runId: 'run-456'
+    });
+  });
+
+  it('should merge with existing headers', async () => {
+    const ctx: AttributionContext = {
+      agentId: 'agent-123'
+    };
+    
+    const middleware = createAttributionMiddleware(ctx);
+    
+    const result = await middleware.transformParams!({
+      params: {
+        headers: { 'X-Custom': 'value' }
+      },
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.headers).toEqual({
+      'X-Custom': 'value',
+      'X-Agent-Id': 'agent-123'
+    });
+  });
+
+  it('should include parentSpanId if provided', async () => {
+    const ctx: AttributionContext = {
+      agentId: 'agent-123',
+      parentSpanId: 'span-xyz'
+    };
+    
+    const middleware = createAttributionMiddleware(ctx);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.headers).toEqual({
+      'X-Agent-Id': 'agent-123',
+      'X-Parent-Span-Id': 'span-xyz'
+    });
+  });
+});
+
+describe('createLoggingMiddleware', () => {
+  it('should return empty middleware when debugLogging is false', () => {
+    const config: AISDKBackendConfig = {
+      debugLogging: false
+    };
+    
+    const middleware = createLoggingMiddleware(config);
+    
+    expect(middleware.transformParams).toBeUndefined();
+    expect(middleware.wrapGenerate).toBeUndefined();
+    expect(middleware.wrapStream).toBeUndefined();
+  });
+
+  it('should return middleware when debugLogging is true', () => {
+    const config: AISDKBackendConfig = {
+      debugLogging: true
+    };
+    
+    const middleware = createLoggingMiddleware(config);
+    
+    expect(middleware.transformParams).toBeDefined();
+    expect(middleware.wrapGenerate).toBeDefined();
+    expect(middleware.wrapStream).toBeDefined();
+  });
+});
+
+describe('createTimeoutMiddleware', () => {
+  it('should add abort signal to params', async () => {
+    const middleware = createTimeoutMiddleware(5000);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.abortSignal).toBeDefined();
+    expect(result.abortSignal).toBeInstanceOf(AbortSignal);
+  });
+
+  it('should not override existing abort signal', async () => {
+    const middleware = createTimeoutMiddleware(5000);
+    const existingSignal = new AbortController().signal;
+    
+    const result = await middleware.transformParams!({
+      params: { abortSignal: existingSignal },
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.abortSignal).toBe(existingSignal);
+  });
+});
+
+describe('composeMiddleware', () => {
+  it('should return empty middleware for empty array', () => {
+    const composed = composeMiddleware();
+    expect(Object.keys(composed)).toHaveLength(0);
+  });
+
+  it('should return single middleware unchanged', () => {
+    const middleware = {
+      transformParams: async ({ params }: any) => ({ ...params, test: true })
+    };
+    
+    const composed = composeMiddleware(middleware);
+    expect(composed).toBe(middleware);
+  });
+
+  it('should compose multiple transformParams', async () => {
+    const m1 = {
+      transformParams: async ({ params }: any) => ({ ...params, m1: true })
+    };
+    const m2 = {
+      transformParams: async ({ params }: any) => ({ ...params, m2: true })
+    };
+    
+    const composed = composeMiddleware(m1, m2);
+    
+    const result = await composed.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result).toEqual({ m1: true, m2: true });
+  });
+
+  it('should filter out empty middlewares', () => {
+    const m1 = {
+      transformParams: async ({ params }: any) => ({ ...params, m1: true })
+    };
+    
+    const composed = composeMiddleware({}, m1, {});
+    
+    expect(composed.transformParams).toBeDefined();
+  });
+});
+
+describe('createStandardMiddleware', () => {
+  it('should include attribution middleware when context provided', async () => {
+    const config: AISDKBackendConfig = {};
+    const attribution: AttributionContext = { agentId: 'test' };
+    
+    const middleware = createStandardMiddleware(config, attribution);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.headers).toEqual({ 'X-Agent-Id': 'test' });
+  });
+
+  it('should include timeout middleware when timeout configured', async () => {
+    const config: AISDKBackendConfig = { timeout: 5000 };
+    
+    const middleware = createStandardMiddleware(config);
+    
+    const result = await middleware.transformParams!({
+      params: {},
+      type: 'generate',
+      model: {}
+    });
+    
+    expect(result.abortSignal).toBeDefined();
+  });
+
+  it('should return empty middleware when no config', () => {
+    const config: AISDKBackendConfig = {};
+    
+    const middleware = createStandardMiddleware(config);
+    
+    // Should have no transformParams if no attribution or timeout
+    expect(Object.keys(middleware).length).toBe(0);
+  });
+});
+
+describe('redactSensitiveData', () => {
+  it('should redact API keys', () => {
+    const data = {
+      apiKey: 'sk-1234567890abcdef',
+      message: 'hello'
+    };
+    
+    const result = redactSensitiveData(data) as any;
+    
+    expect(result.apiKey).toBe('sk-1****');
+    expect(result.message).toBe('hello');
+  });
+
+  it('should redact nested sensitive data', () => {
+    const data = {
+      config: {
+        api_key: 'secret-key-12345',
+        url: 'https://api.example.com'
+      }
+    };
+    
+    const result = redactSensitiveData(data) as any;
+    
+    expect(result.config.api_key).toBe('secr****');
+    expect(result.config.url).toBe('https://api.example.com');
+  });
+
+  it('should redact arrays', () => {
+    const data = [
+      { token: 'abc123', value: 'test' }
+    ];
+    
+    const result = redactSensitiveData(data) as any;
+    
+    expect(result[0].token).toBe('abc1****');
+    expect(result[0].value).toBe('test');
+  });
+
+  it('should handle null and undefined', () => {
+    expect(redactSensitiveData(null)).toBeNull();
+    expect(redactSensitiveData(undefined)).toBeUndefined();
+  });
+
+  it('should handle primitives', () => {
+    expect(redactSensitiveData('string')).toBe('string');
+    expect(redactSensitiveData(123)).toBe(123);
+    expect(redactSensitiveData(true)).toBe(true);
+  });
+
+  it('should redact short sensitive values', () => {
+    const data = { key: 'abc' };
+    const result = redactSensitiveData(data) as any;
+    expect(result.key).toBe('****');
+  });
+});

src/praisonai-ts/tests/unit/llm/ai-sdk/provider-map.test.ts

@@ -0,0 +1,210 @@
+/**
+ * AI SDK Provider Map Tests
+ */
+
+import {
+  parseModelString,
+  resolveProviderAlias,
+  isProviderSupported,
+  getProviderPackage,
+  getProviderEnvKey,
+  listSupportedProviders,
+  registerCustomProvider,
+  unregisterCustomProvider,
+  getCustomProvider,
+  validateProviderApiKey,
+  getMissingApiKeyMessage,
+} from '../../../../src/llm/providers/ai-sdk/provider-map';
+
+describe('parseModelString', () => {
+  it('should parse provider/model format', () => {
+    const result = parseModelString('openai/gpt-4o');
+    expect(result.providerId).toBe('openai');
+    expect(result.modelId).toBe('gpt-4o');
+  });
+
+  it('should parse provider/model with slashes in model name', () => {
+    const result = parseModelString('azure/deployments/gpt-4/chat');
+    expect(result.providerId).toBe('azure');
+    expect(result.modelId).toBe('deployments/gpt-4/chat');
+  });
+
+  it('should infer openai from gpt- prefix', () => {
+    const result = parseModelString('gpt-4o-mini');
+    expect(result.providerId).toBe('openai');
+    expect(result.modelId).toBe('gpt-4o-mini');
+  });
+
+  it('should infer anthropic from claude- prefix', () => {
+    const result = parseModelString('claude-3-5-sonnet');
+    expect(result.providerId).toBe('anthropic');
+    expect(result.modelId).toBe('claude-3-5-sonnet');
+  });
+
+  it('should infer google from gemini- prefix', () => {
+    const result = parseModelString('gemini-2.0-flash');
+    expect(result.providerId).toBe('google');
+    expect(result.modelId).toBe('gemini-2.0-flash');
+  });
+
+  it('should infer mistral from mistral- prefix', () => {
+    const result = parseModelString('mistral-large');
+    expect(result.providerId).toBe('mistral');
+    expect(result.modelId).toBe('mistral-large');
+  });
+
+  it('should use default provider for unknown models', () => {
+    const result = parseModelString('unknown-model', 'openai');
+    expect(result.providerId).toBe('openai');
+    expect(result.modelId).toBe('unknown-model');
+  });
+
+  it('should lowercase provider id', () => {
+    const result = parseModelString('OpenAI/gpt-4o');
+    expect(result.providerId).toBe('openai');
+  });
+});
+
+describe('resolveProviderAlias', () => {
+  it('should resolve oai to openai', () => {
+    expect(resolveProviderAlias('oai')).toBe('openai');
+  });
+
+  it('should resolve claude to anthropic', () => {
+    expect(resolveProviderAlias('claude')).toBe('anthropic');
+  });
+
+  it('should resolve gemini to google', () => {
+    expect(resolveProviderAlias('gemini')).toBe('google');
+  });
+
+  it('should return original if no alias', () => {
+    expect(resolveProviderAlias('openai')).toBe('openai');
+    expect(resolveProviderAlias('custom-provider')).toBe('custom-provider');
+  });
+});
+
+describe('isProviderSupported', () => {
+  it('should return true for built-in providers', () => {
+    expect(isProviderSupported('openai')).toBe(true);
+    expect(isProviderSupported('anthropic')).toBe(true);
+    expect(isProviderSupported('google')).toBe(true);
+  });
+
+  it('should return true for aliases', () => {
+    expect(isProviderSupported('oai')).toBe(true);
+    expect(isProviderSupported('claude')).toBe(true);
+    expect(isProviderSupported('gemini')).toBe(true);
+  });
+
+  it('should return false for unknown providers', () => {
+    expect(isProviderSupported('unknown-provider')).toBe(false);
+  });
+});
+
+describe('getProviderPackage', () => {
+  it('should return package name for known providers', () => {
+    expect(getProviderPackage('openai')).toBe('@ai-sdk/openai');
+    expect(getProviderPackage('anthropic')).toBe('@ai-sdk/anthropic');
+    expect(getProviderPackage('google')).toBe('@ai-sdk/google');
+  });
+
+  it('should return null for unknown providers', () => {
+    expect(getProviderPackage('unknown')).toBeNull();
+  });
+
+  it('should resolve aliases', () => {
+    expect(getProviderPackage('oai')).toBe('@ai-sdk/openai');
+    expect(getProviderPackage('claude')).toBe('@ai-sdk/anthropic');
+  });
+});
+
+describe('getProviderEnvKey', () => {
+  it('should return env key for known providers', () => {
+    expect(getProviderEnvKey('openai')).toBe('OPENAI_API_KEY');
+    expect(getProviderEnvKey('anthropic')).toBe('ANTHROPIC_API_KEY');
+    expect(getProviderEnvKey('google')).toBe('GOOGLE_API_KEY');
+  });
+
+  it('should return null for unknown providers', () => {
+    expect(getProviderEnvKey('unknown')).toBeNull();
+  });
+});
+
+describe('listSupportedProviders', () => {
+  it('should return array of provider ids', () => {
+    const providers = listSupportedProviders();
+    expect(Array.isArray(providers)).toBe(true);
+    expect(providers.length).toBeGreaterThan(0);
+    expect(providers).toContain('openai');
+    expect(providers).toContain('anthropic');
+    expect(providers).toContain('google');
+  });
+});
+
+describe('custom providers', () => {
+  const customFactory = jest.fn().mockReturnValue({ test: true });
+
+  afterEach(() => {
+    unregisterCustomProvider('test-custom');
+  });
+
+  it('should register custom provider', () => {
+    registerCustomProvider('test-custom', customFactory);
+    expect(getCustomProvider('test-custom')).toBe(customFactory);
+    expect(isProviderSupported('test-custom')).toBe(true);
+  });
+
+  it('should unregister custom provider', () => {
+    registerCustomProvider('test-custom', customFactory);
+    expect(unregisterCustomProvider('test-custom')).toBe(true);
+    expect(getCustomProvider('test-custom')).toBeUndefined();
+    expect(isProviderSupported('test-custom')).toBe(false);
+  });
+
+  it('should include custom providers in list', () => {
+    registerCustomProvider('test-custom', customFactory);
+    const providers = listSupportedProviders();
+    expect(providers).toContain('test-custom');
+  });
+});
+
+describe('validateProviderApiKey', () => {
+  const originalEnv = process.env;
+
+  beforeEach(() => {
+    process.env = { ...originalEnv };
+  });
+
+  afterAll(() => {
+    process.env = originalEnv;
+  });
+
+  it('should return true when API key is set', () => {
+    process.env.OPENAI_API_KEY = 'test-key';
+    expect(validateProviderApiKey('openai')).toBe(true);
+  });
+
+  it('should return false when API key is not set', () => {
+    delete process.env.OPENAI_API_KEY;
+    expect(validateProviderApiKey('openai')).toBe(false);
+  });
+
+  it('should return true for custom providers without env key', () => {
+    registerCustomProvider('no-env-provider', () => ({}));
+    expect(validateProviderApiKey('no-env-provider')).toBe(true);
+    unregisterCustomProvider('no-env-provider');
+  });
+});
+
+describe('getMissingApiKeyMessage', () => {
+  it('should return message with env key for known providers', () => {
+    const msg = getMissingApiKeyMessage('openai');
+    expect(msg).toContain('OPENAI_API_KEY');
+  });
+
+  it('should return generic message for unknown providers', () => {
+    const msg = getMissingApiKeyMessage('unknown');
+    expect(msg).toContain('unknown');
+  });
+});

src/praisonai-ts/tests/unit/llm/ai-sdk/types.test.ts

@@ -0,0 +1,105 @@
+/**
+ * AI SDK Types Tests
+ */
+
+import {
+  AISDKError,
+  SAFE_DEFAULTS,
+  AISDK_PROVIDERS,
+  PROVIDER_ALIASES,
+} from '../../../../src/llm/providers/ai-sdk/types';
+
+describe('AISDKError', () => {
+  it('should create error with all properties', () => {
+    const error = new AISDKError(
+      'Test error message',
+      'RATE_LIMIT',
+      true,
+      new Error('cause'),
+      429
+    );
+
+    expect(error.message).toBe('Test error message');
+    expect(error.code).toBe('RATE_LIMIT');
+    expect(error.isRetryable).toBe(true);
+    expect(error.cause).toBeInstanceOf(Error);
+    expect(error.statusCode).toBe(429);
+    expect(error.name).toBe('AISDKError');
+  });
+
+  it('should create error without optional properties', () => {
+    const error = new AISDKError('Simple error', 'UNKNOWN', false);
+
+    expect(error.message).toBe('Simple error');
+    expect(error.code).toBe('UNKNOWN');
+    expect(error.isRetryable).toBe(false);
+    expect(error.cause).toBeUndefined();
+    expect(error.statusCode).toBeUndefined();
+  });
+
+  it('should be instanceof Error', () => {
+    const error = new AISDKError('Test', 'UNKNOWN', false);
+    expect(error).toBeInstanceOf(Error);
+    expect(error).toBeInstanceOf(AISDKError);
+  });
+});
+
+describe('SAFE_DEFAULTS', () => {
+  it('should have correct default values', () => {
+    expect(SAFE_DEFAULTS.timeout).toBe(60000);
+    expect(SAFE_DEFAULTS.maxRetries).toBe(2);
+    expect(SAFE_DEFAULTS.maxOutputTokens).toBe(4096);
+    expect(SAFE_DEFAULTS.redactLogs).toBe(true);
+    expect(SAFE_DEFAULTS.debugLogging).toBe(false);
+  });
+});
+
+describe('AISDK_PROVIDERS', () => {
+  it('should have openai provider', () => {
+    expect(AISDK_PROVIDERS.openai).toBeDefined();
+    expect(AISDK_PROVIDERS.openai.package).toBe('@ai-sdk/openai');
+    expect(AISDK_PROVIDERS.openai.envKey).toBe('OPENAI_API_KEY');
+  });
+
+  it('should have anthropic provider', () => {
+    expect(AISDK_PROVIDERS.anthropic).toBeDefined();
+    expect(AISDK_PROVIDERS.anthropic.package).toBe('@ai-sdk/anthropic');
+    expect(AISDK_PROVIDERS.anthropic.envKey).toBe('ANTHROPIC_API_KEY');
+  });
+
+  it('should have google provider', () => {
+    expect(AISDK_PROVIDERS.google).toBeDefined();
+    expect(AISDK_PROVIDERS.google.package).toBe('@ai-sdk/google');
+    expect(AISDK_PROVIDERS.google.envKey).toBe('GOOGLE_API_KEY');
+  });
+
+  it('should have all expected providers', () => {
+    const expectedProviders = [
+      'openai', 'anthropic', 'google', 'azure', 'amazon-bedrock',
+      'groq', 'mistral', 'cohere', 'deepseek', 'xai',
+      'fireworks', 'togetherai', 'perplexity'
+    ];
+
+    for (const provider of expectedProviders) {
+      expect(AISDK_PROVIDERS[provider as keyof typeof AISDK_PROVIDERS]).toBeDefined();
+    }
+  });
+});
+
+describe('PROVIDER_ALIASES', () => {
+  it('should map oai to openai', () => {
+    expect(PROVIDER_ALIASES.oai).toBe('openai');
+  });
+
+  it('should map claude to anthropic', () => {
+    expect(PROVIDER_ALIASES.claude).toBe('anthropic');
+  });
+
+  it('should map gemini to google', () => {
+    expect(PROVIDER_ALIASES.gemini).toBe('google');
+  });
+
+  it('should map bedrock to amazon-bedrock', () => {
+    expect(PROVIDER_ALIASES.bedrock).toBe('amazon-bedrock');
+  });
+});

src/praisonai-ts/tests/unit/llm/provider-registry.test.ts

@@ -0,0 +1,401 @@
+/**
+ * Provider Registry Unit Tests (TDD)
+ * 
+ * Tests for the extensible provider registry that fixes Issue #1095
+ * These tests define the expected behavior before implementation.
+ */
+
+import { describe, it, expect, beforeEach, afterEach, jest } from '@jest/globals';
+import type { LLMProvider, ProviderConfig, GenerateTextOptions, GenerateTextResult, StreamTextOptions, StreamChunk, GenerateObjectOptions, GenerateObjectResult } from '../../../src/llm/providers/types';
+
+// Mock provider for testing
+class MockProvider implements LLMProvider {
+  readonly providerId: string;
+  readonly modelId: string;
+
+  constructor(modelId: string, config?: ProviderConfig) {
+    this.providerId = 'mock';
+    this.modelId = modelId;
+  }
+
+  async generateText(options: GenerateTextOptions): Promise<GenerateTextResult> {
+    return {
+      text: 'mock response',
+      usage: { promptTokens: 10, completionTokens: 20, totalTokens: 30 },
+      finishReason: 'stop'
+    };
+  }
+
+  async streamText(options: StreamTextOptions): Promise<AsyncIterable<StreamChunk>> {
+    return {
+      async *[Symbol.asyncIterator]() {
+        yield { text: 'mock' };
+      }
+    };
+  }
+
+  async generateObject<T>(options: GenerateObjectOptions<T>): Promise<GenerateObjectResult<T>> {
+    return {
+      object: {} as T,
+      usage: { promptTokens: 10, completionTokens: 20, totalTokens: 30 }
+    };
+  }
+}
+
+// Custom provider for testing registration
+class CustomCloudflareProvider implements LLMProvider {
+  readonly providerId = 'cloudflare';
+  readonly modelId: string;
+
+  constructor(modelId: string, config?: ProviderConfig) {
+    this.modelId = modelId;
+  }
+
+  async generateText(options: GenerateTextOptions): Promise<GenerateTextResult> {
+    return {
+      text: 'cloudflare response',
+      usage: { promptTokens: 5, completionTokens: 15, totalTokens: 20 },
+      finishReason: 'stop'
+    };
+  }
+
+  async streamText(options: StreamTextOptions): Promise<AsyncIterable<StreamChunk>> {
+    return {
+      async *[Symbol.asyncIterator]() {
+        yield { text: 'cloudflare' };
+      }
+    };
+  }
+
+  async generateObject<T>(options: GenerateObjectOptions<T>): Promise<GenerateObjectResult<T>> {
+    return {
+      object: {} as T,
+      usage: { promptTokens: 5, completionTokens: 15, totalTokens: 20 }
+    };
+  }
+}
+
+describe('ProviderRegistry', () => {
+  // Import will be from the implementation once created
+  let ProviderRegistry: any;
+  let createProviderRegistry: any;
+  let getDefaultRegistry: any;
+  let registerProvider: any;
+  let unregisterProvider: any;
+
+  beforeEach(async () => {
+    // Dynamic import to get the registry module
+    const registryModule = await import('../../../src/llm/providers/registry');
+    ProviderRegistry = registryModule.ProviderRegistry;
+    createProviderRegistry = registryModule.createProviderRegistry;
+    getDefaultRegistry = registryModule.getDefaultRegistry;
+    registerProvider = registryModule.registerProvider;
+    unregisterProvider = registryModule.unregisterProvider;
+  });
+
+  describe('Registry Creation', () => {
+    it('should create an empty registry', () => {
+      const registry = createProviderRegistry();
+      expect(registry).toBeDefined();
+      expect(registry.list()).toEqual([]);
+    });
+
+    it('should get the default registry singleton', () => {
+      const registry1 = getDefaultRegistry();
+      const registry2 = getDefaultRegistry();
+      expect(registry1).toBe(registry2);
+    });
+  });
+
+  describe('Provider Registration', () => {
+    it('should register a provider class', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      expect(registry.has('mock')).toBe(true);
+      expect(registry.list()).toContain('mock');
+    });
+
+    it('should register a provider with lazy loader function', () => {
+      const registry = createProviderRegistry();
+      const loader = () => MockProvider;
+      registry.register('mock', loader);
+      expect(registry.has('mock')).toBe(true);
+    });
+
+    it('should register provider with aliases', () => {
+      const registry = createProviderRegistry();
+      registry.register('cloudflare', CustomCloudflareProvider, { aliases: ['cf', 'workers-ai'] });
+      
+      expect(registry.has('cloudflare')).toBe(true);
+      expect(registry.has('cf')).toBe(true);
+      expect(registry.has('workers-ai')).toBe(true);
+    });
+
+    it('should throw on duplicate registration by default', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      
+      expect(() => {
+        registry.register('mock', CustomCloudflareProvider);
+      }).toThrow(/already registered/i);
+    });
+
+    it('should allow override with explicit flag', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      registry.register('mock', CustomCloudflareProvider, { override: true });
+      
+      const provider = registry.resolve('mock', 'test-model');
+      expect(provider.providerId).toBe('cloudflare');
+    });
+
+    it('should unregister a provider', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      expect(registry.has('mock')).toBe(true);
+      
+      const result = registry.unregister('mock');
+      expect(result).toBe(true);
+      expect(registry.has('mock')).toBe(false);
+    });
+
+    it('should return false when unregistering non-existent provider', () => {
+      const registry = createProviderRegistry();
+      const result = registry.unregister('nonexistent');
+      expect(result).toBe(false);
+    });
+  });
+
+  describe('Provider Resolution', () => {
+    it('should resolve a registered provider by name', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      
+      const provider = registry.resolve('mock', 'test-model');
+      expect(provider).toBeInstanceOf(MockProvider);
+      expect(provider.modelId).toBe('test-model');
+    });
+
+    it('should resolve provider with config', () => {
+      const registry = createProviderRegistry();
+      registry.register('mock', MockProvider);
+      
+      const config: ProviderConfig = { apiKey: 'test-key', timeout: 5000 };
+      const provider = registry.resolve('mock', 'test-model', config);
+      expect(provider).toBeInstanceOf(MockProvider);
+    });
+
+    it('should resolve provider from lazy loader', () => {
+      const registry = createProviderRegistry();
+      const loaderFn = jest.fn(() => MockProvider);
+      registry.register('mock', loaderFn);
+      
+      // First resolution should call loader
+      const provider1 = registry.resolve('mock', 'model-1');
+      expect(loaderFn).toHaveBeenCalledTimes(1);
+      
+      // Second resolution should reuse cached constructor
+      const provider2 = registry.resolve('mock', 'model-2');
+      expect(loaderFn).toHaveBeenCalledTimes(1); // Still 1, not called again
+    });
+
+    it('should throw clear error for unknown provider', () => {
+      const registry = createProviderRegistry();
+      registry.register('openai', MockProvider);
+      registry.register('anthropic', MockProvider);
+      
+      expect(() => {
+        registry.resolve('cloudflare', 'model');
+      }).toThrow(/unknown provider.*cloudflare/i);
+      
+      // Error should include available providers
+      try {
+        registry.resolve('cloudflare', 'model');
+      } catch (e: any) {
+        expect(e.message).toMatch(/openai/i);
+        expect(e.message).toMatch(/anthropic/i);
+      }
+    });
+
+    it('should resolve via alias', () => {
+      const registry = createProviderRegistry();
+      registry.register('cloudflare', CustomCloudflareProvider, { aliases: ['cf'] });
+      
+      const provider = registry.resolve('cf', 'workers-ai-model');
+      expect(provider.providerId).toBe('cloudflare');
+    });
+  });
+
+  describe('Global Registration Functions', () => {
+    it('should register provider to default registry', () => {
+      // Reset default registry state
+      const registry = getDefaultRegistry();
+      
+      registerProvider('custom-test', MockProvider);
+      expect(registry.has('custom-test')).toBe(true);
+      
+      // Cleanup
+      unregisterProvider('custom-test');
+    });
+
+    it('should unregister provider from default registry', () => {
+      registerProvider('custom-test-2', MockProvider);
+      expect(getDefaultRegistry().has('custom-test-2')).toBe(true);
+      
+      unregisterProvider('custom-test-2');
+      expect(getDefaultRegistry().has('custom-test-2')).toBe(false);
+    });
+  });
+
+  describe('Multi-agent Safety', () => {
+    it('should support isolated registries per context', () => {
+      const registry1 = createProviderRegistry();
+      const registry2 = createProviderRegistry();
+      
+      registry1.register('provider-a', MockProvider);
+      registry2.register('provider-b', CustomCloudflareProvider);
+      
+      expect(registry1.has('provider-a')).toBe(true);
+      expect(registry1.has('provider-b')).toBe(false);
+      
+      expect(registry2.has('provider-a')).toBe(false);
+      expect(registry2.has('provider-b')).toBe(true);
+    });
+
+    it('should not leak registrations between isolated registries', () => {
+      const registry1 = createProviderRegistry();
+      const registry2 = createProviderRegistry();
+      
+      registry1.register('shared-name', MockProvider);
+      registry2.register('shared-name', CustomCloudflareProvider);
+      
+      const provider1 = registry1.resolve('shared-name', 'model');
+      const provider2 = registry2.resolve('shared-name', 'model');
+      
+      expect(provider1.providerId).toBe('mock');
+      expect(provider2.providerId).toBe('cloudflare');
+    });
+  });
+});
+
+describe('createProvider with Registry', () => {
+  let createProvider: any;
+  let registerProvider: any;
+  let unregisterProvider: any;
+  let getDefaultRegistry: any;
+
+  beforeEach(async () => {
+    const providersModule = await import('../../../src/llm/providers');
+    createProvider = providersModule.createProvider;
+    registerProvider = providersModule.registerProvider;
+    unregisterProvider = providersModule.unregisterProvider;
+    getDefaultRegistry = providersModule.getDefaultRegistry;
+  });
+
+  describe('Backward Compatibility', () => {
+    it('should resolve built-in openai provider', () => {
+      if (!process.env.OPENAI_API_KEY) {
+        console.log('Skipping: OPENAI_API_KEY not set');
+        return;
+      }
+      const provider = createProvider('openai/gpt-4o-mini');
+      expect(provider.providerId).toBe('openai');
+      expect(provider.modelId).toBe('gpt-4o-mini');
+    });
+
+    it('should resolve built-in anthropic provider', () => {
+      if (!process.env.ANTHROPIC_API_KEY) {
+        console.log('Skipping: ANTHROPIC_API_KEY not set');
+        return;
+      }
+      const provider = createProvider('anthropic/claude-3-5-sonnet-latest');
+      expect(provider.providerId).toBe('anthropic');
+    });
+
+    it('should resolve built-in google provider', () => {
+      if (!process.env.GOOGLE_API_KEY) {
+        console.log('Skipping: GOOGLE_API_KEY not set');
+        return;
+      }
+      const provider = createProvider('google/gemini-2.0-flash');
+      expect(provider.providerId).toBe('google');
+    });
+
+    it('should default to openai for gpt- models', () => {
+      if (!process.env.OPENAI_API_KEY) {
+        console.log('Skipping: OPENAI_API_KEY not set');
+        return;
+      }
+      const provider = createProvider('gpt-4o-mini');
+      expect(provider.providerId).toBe('openai');
+    });
+  });
+
+  describe('Custom Provider Support', () => {
+    afterEach(() => {
+      // Cleanup custom registrations
+      try {
+        unregisterProvider('custom-test');
+      } catch {}
+    });
+
+    it('should resolve custom registered provider', () => {
+      registerProvider('custom-test', MockProvider);
+      
+      const provider = createProvider('custom-test/my-model');
+      expect(provider.providerId).toBe('mock');
+      expect(provider.modelId).toBe('my-model');
+    });
+
+    it('should accept provider instance directly', () => {
+      const instance = new MockProvider('direct-model');
+      const provider = createProvider(instance);
+      
+      expect(provider).toBe(instance);
+      expect(provider.modelId).toBe('direct-model');
+    });
+
+    it('should accept provider constructor', () => {
+      const provider = createProvider(MockProvider, { modelId: 'constructor-model' });
+      expect(provider).toBeInstanceOf(MockProvider);
+    });
+
+    it('should accept provider spec object', () => {
+      registerProvider('custom-test', MockProvider);
+      
+      const provider = createProvider({ 
+        name: 'custom-test', 
+        modelId: 'spec-model',
+        config: { timeout: 5000 } 
+      });
+      expect(provider.providerId).toBe('mock');
+      expect(provider.modelId).toBe('spec-model');
+    });
+
+    it('should use custom registry when provided', () => {
+      const { createProviderRegistry } = require('../../../src/llm/providers/registry');
+      const customRegistry = createProviderRegistry();
+      customRegistry.register('isolated', CustomCloudflareProvider);
+      
+      const provider = createProvider('isolated/model', { registry: customRegistry });
+      expect(provider.providerId).toBe('cloudflare');
+      
+      // Should not be in default registry
+      expect(() => createProvider('isolated/model')).toThrow(/unknown provider/i);
+    });
+  });
+
+  describe('Error Messages', () => {
+    it('should provide helpful error for unknown provider', () => {
+      expect(() => createProvider('nonexistent/model')).toThrow();
+      
+      try {
+        createProvider('nonexistent/model');
+      } catch (e: any) {
+        expect(e.message).toMatch(/unknown provider/i);
+        expect(e.message).toMatch(/nonexistent/i);
+        expect(e.message).toMatch(/available/i);
+      }
+    });
+  });
+});

src/praisonai/praisonai.rb

@@ -3,8 +3,8 @@ class Praisonai < Formula
   
     desc "AI tools for various AI applications"
     homepage "https://github.com/MervinPraison/PraisonAI"
-    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.7.8.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.7.8.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.8.0.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.8.0.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/deploy.py

@@ -57,7 +57,7 @@ class CloudDeployer:
             file.write("FROM python:3.11-slim\n")
             file.write("WORKDIR /app\n")
             file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==2.7.8 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.8.0 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
             

src/praisonai/praisonai/llm/__init__.py

@@ -0,0 +1,66 @@
+"""
+LLM Module for PraisonAI CLI Wrapper.
+
+This module provides LLM provider registry and utilities for the CLI wrapper.
+The core LLM functionality is in praisonaiagents.llm.
+"""
+
+# Lazy loading for performance
+_lazy_cache = {}
+
+
+def __getattr__(name):
+    """Lazy load LLM registry classes."""
+    if name in _lazy_cache:
+        return _lazy_cache[name]
+    
+    if name == "LLMProviderRegistry":
+        from .registry import LLMProviderRegistry
+        _lazy_cache[name] = LLMProviderRegistry
+        return LLMProviderRegistry
+    elif name == "get_default_llm_registry":
+        from .registry import get_default_llm_registry
+        _lazy_cache[name] = get_default_llm_registry
+        return get_default_llm_registry
+    elif name == "register_llm_provider":
+        from .registry import register_llm_provider
+        _lazy_cache[name] = register_llm_provider
+        return register_llm_provider
+    elif name == "unregister_llm_provider":
+        from .registry import unregister_llm_provider
+        _lazy_cache[name] = unregister_llm_provider
+        return unregister_llm_provider
+    elif name == "has_llm_provider":
+        from .registry import has_llm_provider
+        _lazy_cache[name] = has_llm_provider
+        return has_llm_provider
+    elif name == "list_llm_providers":
+        from .registry import list_llm_providers
+        _lazy_cache[name] = list_llm_providers
+        return list_llm_providers
+    elif name == "create_llm_provider":
+        from .registry import create_llm_provider
+        _lazy_cache[name] = create_llm_provider
+        return create_llm_provider
+    elif name == "parse_model_string":
+        from .registry import parse_model_string
+        _lazy_cache[name] = parse_model_string
+        return parse_model_string
+    elif name == "_reset_default_registry":
+        from .registry import _reset_default_registry
+        _lazy_cache[name] = _reset_default_registry
+        return _reset_default_registry
+    
+    raise AttributeError(f"module {__name__!r} has no attribute {name!r}")
+
+
+__all__ = [
+    "LLMProviderRegistry",
+    "get_default_llm_registry",
+    "register_llm_provider",
+    "unregister_llm_provider",
+    "has_llm_provider",
+    "list_llm_providers",
+    "create_llm_provider",
+    "parse_model_string",
+]

src/praisonai/praisonai/llm/registry.py

@@ -0,0 +1,382 @@
+"""
+LLM Provider Registry - Extensible provider registration system for Python.
+
+This module provides parity with the TypeScript ProviderRegistry,
+allowing users to register custom LLM providers that can be resolved by name.
+
+Example:
+    from praisonai.llm import register_llm_provider, create_llm_provider
+    
+    class CloudflareProvider:
+        provider_id = "cloudflare"
+        def __init__(self, model_id, config=None):
+            self.model_id = model_id
+            self.config = config or {}
+        def generate(self, prompt):
+            # Implementation
+            pass
+    
+    register_llm_provider("cloudflare", CloudflareProvider)
+    provider = create_llm_provider("cloudflare/workers-ai")
+"""
+
+from typing import Any, Callable, Dict, List, Optional, Type, Union
+
+
+# Type aliases
+ProviderClass = Type[Any]  # Class with __init__(model_id, config)
+ProviderFactory = Callable[[str, Optional[Dict[str, Any]]], Any]
+ProviderType = Union[ProviderClass, ProviderFactory]
+
+
+class LLMProviderRegistry:
+    """
+    Registry for LLM providers.
+    
+    Manages registration and resolution of LLM providers by name.
+    Supports lazy loading, aliases, and isolated instances.
+    """
+    
+    def __init__(self):
+        """Initialize an empty registry."""
+        self._providers: Dict[str, ProviderType] = {}
+        self._aliases: Dict[str, str] = {}  # alias -> canonical name
+    
+    def register(
+        self,
+        name: str,
+        provider: ProviderType,
+        *,
+        override: bool = False,
+        aliases: Optional[List[str]] = None
+    ) -> None:
+        """
+        Register a provider by name.
+        
+        Args:
+            name: Provider name (e.g., 'cloudflare', 'ollama')
+            provider: Provider class or factory function
+            override: Allow overwriting existing registration
+            aliases: Additional names that resolve to this provider
+            
+        Raises:
+            ValueError: If name is already registered (unless override=True)
+        """
+        normalized_name = name.lower()
+        
+        # Check for existing registration
+        if normalized_name in self._providers and not override:
+            raise ValueError(
+                f"Provider '{name}' is already registered. "
+                f"Use override=True to replace it."
+            )
+        
+        self._providers[normalized_name] = provider
+        
+        # Register aliases
+        if aliases:
+            for alias in aliases:
+                normalized_alias = alias.lower()
+                # Check collision with existing provider name
+                if normalized_alias in self._providers and not override:
+                    raise ValueError(
+                        f"Alias '{alias}' conflicts with existing provider name. "
+                        f"Use override=True to replace it."
+                    )
+                # Check collision with existing alias
+                if normalized_alias in self._aliases and not override:
+                    existing_target = self._aliases[normalized_alias]
+                    raise ValueError(
+                        f"Alias '{alias}' is already registered (points to '{existing_target}'). "
+                        f"Use override=True to replace it."
+                    )
+                self._aliases[normalized_alias] = normalized_name
+    
+    def unregister(self, name: str) -> bool:
+        """
+        Unregister a provider by name.
+        
+        Args:
+            name: Provider name to unregister
+            
+        Returns:
+            True if provider was unregistered, False if not found
+        """
+        normalized_name = name.lower()
+        
+        # Check if it's an alias
+        if normalized_name in self._aliases:
+            del self._aliases[normalized_name]
+            return True
+        
+        # Check if it's a canonical name
+        if normalized_name in self._providers:
+            # Remove all aliases pointing to this provider
+            aliases_to_remove = [
+                alias for alias, canonical in self._aliases.items()
+                if canonical == normalized_name
+            ]
+            for alias in aliases_to_remove:
+                del self._aliases[alias]
+            
+            del self._providers[normalized_name]
+            return True
+        
+        return False
+    
+    def has(self, name: str) -> bool:
+        """
+        Check if a provider is registered.
+        
+        Args:
+            name: Provider name to check
+            
+        Returns:
+            True if provider is registered
+        """
+        normalized_name = name.lower()
+        return normalized_name in self._providers or normalized_name in self._aliases
+    
+    def list(self) -> List[str]:
+        """
+        List all registered provider names (canonical names only).
+        
+        Returns:
+            List of provider names
+        """
+        return list(self._providers.keys())
+    
+    def list_all(self) -> List[str]:
+        """
+        List all names including aliases.
+        
+        Returns:
+            List of all registered names and aliases
+        """
+        return list(self._providers.keys()) + list(self._aliases.keys())
+    
+    def resolve(
+        self,
+        name: str,
+        model_id: str,
+        config: Optional[Dict[str, Any]] = None
+    ) -> Any:
+        """
+        Resolve a provider by name, creating an instance.
+        
+        Args:
+            name: Provider name
+            model_id: Model ID to pass to constructor
+            config: Optional provider config
+            
+        Returns:
+            Provider instance
+            
+        Raises:
+            ValueError: If provider not found
+        """
+        normalized_name = name.lower()
+        
+        # Resolve alias to canonical name
+        canonical_name = self._aliases.get(normalized_name, normalized_name)
+        
+        provider = self._providers.get(canonical_name)
+        if provider is None:
+            available = self.list()
+            raise ValueError(
+                f"Unknown provider: '{name}'. "
+                f"Available providers: {', '.join(available) if available else 'none'}. "
+                f"Register a custom provider with register_llm_provider('{name}', YourProviderClass)."
+            )
+        
+        # Create instance
+        return provider(model_id, config)
+    
+    def get(self, name: str) -> Optional[ProviderType]:
+        """
+        Get the provider class/factory without instantiating.
+        
+        Args:
+            name: Provider name
+            
+        Returns:
+            Provider class/factory or None
+        """
+        normalized_name = name.lower()
+        canonical_name = self._aliases.get(normalized_name, normalized_name)
+        return self._providers.get(canonical_name)
+
+
+# ============================================================================
+# Default Registry Singleton
+# ============================================================================
+
+_default_registry: Optional[LLMProviderRegistry] = None
+
+
+def get_default_llm_registry() -> LLMProviderRegistry:
+    """
+    Get the default global LLM provider registry.
+    
+    This is the registry used by create_llm_provider() when no custom registry
+    is specified.
+    """
+    global _default_registry
+    if _default_registry is None:
+        _default_registry = LLMProviderRegistry()
+        _register_builtin_providers(_default_registry)
+    return _default_registry
+
+
+def _register_builtin_providers(registry: LLMProviderRegistry) -> None:
+    """
+    Register built-in providers to a registry.
+    
+    Uses lazy loading to avoid importing heavy dependencies at module load time.
+    """
+    # Note: In Python, the actual LLM providers are in praisonaiagents.llm
+    # which uses LiteLLM. This registry is for custom provider extensions.
+    # Built-in providers are handled by LiteLLM automatically.
+    pass
+
+
+def register_llm_provider(
+    name: str,
+    provider: ProviderType,
+    *,
+    override: bool = False,
+    aliases: Optional[List[str]] = None
+) -> None:
+    """
+    Register a provider to the default global registry.
+    
+    Example:
+        from praisonai.llm import register_llm_provider
+        
+        class CloudflareProvider:
+            provider_id = "cloudflare"
+            def __init__(self, model_id, config=None):
+                self.model_id = model_id
+                self.config = config or {}
+        
+        register_llm_provider("cloudflare", CloudflareProvider)
+    """
+    get_default_llm_registry().register(name, provider, override=override, aliases=aliases)
+
+
+def unregister_llm_provider(name: str) -> bool:
+    """Unregister a provider from the default global registry."""
+    return get_default_llm_registry().unregister(name)
+
+
+def has_llm_provider(name: str) -> bool:
+    """Check if a provider is registered in the default registry."""
+    return get_default_llm_registry().has(name)
+
+
+def list_llm_providers() -> List[str]:
+    """List all providers in the default registry."""
+    return get_default_llm_registry().list()
+
+
+# ============================================================================
+# Provider Creation
+# ============================================================================
+
+def parse_model_string(model: str) -> Dict[str, str]:
+    """
+    Parse model string into provider and model ID.
+    
+    Supports formats:
+    - "provider/model" (e.g., "openai/gpt-4o")
+    - "model" (defaults based on prefix)
+    
+    Args:
+        model: Model string
+        
+    Returns:
+        Dict with 'provider_id' and 'model_id' keys
+    """
+    if "/" in model:
+        parts = model.split("/", 1)
+        return {"provider_id": parts[0].lower(), "model_id": parts[1]}
+    
+    # Default based on model prefix
+    model_lower = model.lower()
+    if model_lower.startswith("gpt-") or model_lower.startswith("o1") or model_lower.startswith("o3"):
+        return {"provider_id": "openai", "model_id": model}
+    if model_lower.startswith("claude-"):
+        return {"provider_id": "anthropic", "model_id": model}
+    if model_lower.startswith("gemini-"):
+        return {"provider_id": "google", "model_id": model}
+    
+    # Default to openai
+    return {"provider_id": "openai", "model_id": model}
+
+
+def create_llm_provider(
+    input_value: Union[str, Dict[str, Any], Any],
+    *,
+    registry: Optional[LLMProviderRegistry] = None,
+    config: Optional[Dict[str, Any]] = None
+) -> Any:
+    """
+    Create a provider instance from various input types.
+    
+    Args:
+        input_value: One of:
+            - String: "provider/model" or "model"
+            - Dict: {"name": "provider", "model_id": "model", "config": {...}}
+            - Provider instance: passed through
+        registry: Optional custom registry (defaults to global)
+        config: Optional provider config
+        
+    Returns:
+        Provider instance
+        
+    Example:
+        # String input
+        provider = create_llm_provider("openai/gpt-4o")
+        
+        # Custom provider (after registration)
+        register_llm_provider("cloudflare", CloudflareProvider)
+        provider = create_llm_provider("cloudflare/workers-ai")
+        
+        # Provider instance (pass-through)
+        provider = create_llm_provider(existing_provider)
+        
+        # Spec dict
+        provider = create_llm_provider({
+            "name": "openai",
+            "model_id": "gpt-4o",
+            "config": {"timeout": 5000}
+        })
+    """
+    reg = registry or get_default_llm_registry()
+    
+    # Case 1: Already a provider instance (has provider_id and model_id)
+    if hasattr(input_value, "provider_id") and hasattr(input_value, "model_id"):
+        return input_value
+    
+    # Case 2: Spec dict
+    if isinstance(input_value, dict) and "name" in input_value:
+        name = input_value["name"]
+        model_id = input_value.get("model_id", "default")
+        provider_config = input_value.get("config") or config
+        return reg.resolve(name, model_id, provider_config)
+    
+    # Case 3: String - parse and resolve
+    if isinstance(input_value, str):
+        parsed = parse_model_string(input_value)
+        return reg.resolve(parsed["provider_id"], parsed["model_id"], config)
+    
+    raise ValueError(
+        f"Invalid provider input. Expected string, provider instance, or spec dict. "
+        f"Got: {type(input_value).__name__}"
+    )
+
+
+def _reset_default_registry() -> None:
+    """Reset the default registry (mainly for testing)."""
+    global _default_registry
+    _default_registry = None

src/praisonai/praisonai/version.py

@@ -1 +1 @@
-__version__ = "2.7.8"
+__version__ = "2.8.0"

src/praisonai/tests/unit/llm/test_provider_registry.py

@@ -0,0 +1,484 @@
+"""
+LLM Provider Registry Unit Tests (TDD)
+
+Tests for the extensible LLM provider registry that provides parity
+with the TypeScript implementation for Issue #1095.
+"""
+
+import pytest
+from typing import Any, Dict, Optional
+
+
+class MockLLMProvider:
+    """Mock LLM provider for testing."""
+    
+    provider_id = "mock"
+    
+    def __init__(self, model_id: str, config: Optional[Dict[str, Any]] = None):
+        self.model_id = model_id
+        self.config = config or {}
+    
+    def generate(self, prompt: str) -> str:
+        return f"Mock response for: {prompt}"
+
+
+class CustomCloudflareProvider:
+    """Custom provider for testing registration."""
+    
+    provider_id = "cloudflare"
+    
+    def __init__(self, model_id: str, config: Optional[Dict[str, Any]] = None):
+        self.model_id = model_id
+        self.config = config or {}
+    
+    def generate(self, prompt: str) -> str:
+        return f"Cloudflare response for: {prompt}"
+
+
+class TestLLMProviderRegistry:
+    """Tests for LLMProviderRegistry class."""
+    
+    def test_create_empty_registry(self):
+        """Should create an empty registry."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        assert registry is not None
+        assert registry.list() == []
+    
+    def test_register_provider_class(self):
+        """Should register a provider class."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        
+        assert registry.has("mock")
+        assert "mock" in registry.list()
+    
+    def test_register_provider_with_factory(self):
+        """Should register a provider with a factory function."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        def factory(model_id, config=None):
+            return MockLLMProvider(model_id, config)
+        registry.register("mock", factory)
+        
+        assert registry.has("mock")
+    
+    def test_register_provider_with_aliases(self):
+        """Should register provider with aliases."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("cloudflare", CustomCloudflareProvider, aliases=["cf", "workers-ai"])
+        
+        assert registry.has("cloudflare")
+        assert registry.has("cf")
+        assert registry.has("workers-ai")
+    
+    def test_duplicate_registration_raises_error(self):
+        """Should raise error on duplicate registration by default."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        
+        with pytest.raises(ValueError, match="already registered"):
+            registry.register("mock", CustomCloudflareProvider)
+    
+    def test_override_registration(self):
+        """Should allow override with explicit flag."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        registry.register("mock", CustomCloudflareProvider, override=True)
+        
+        provider = registry.resolve("mock", "test-model")
+        assert provider.provider_id == "cloudflare"
+    
+    def test_unregister_provider(self):
+        """Should unregister a provider."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        assert registry.has("mock")
+        
+        result = registry.unregister("mock")
+        assert result is True
+        assert not registry.has("mock")
+    
+    def test_unregister_nonexistent_returns_false(self):
+        """Should return False when unregistering non-existent provider."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        result = registry.unregister("nonexistent")
+        assert result is False
+    
+    def test_resolve_provider(self):
+        """Should resolve a registered provider by name."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        
+        provider = registry.resolve("mock", "test-model")
+        assert isinstance(provider, MockLLMProvider)
+        assert provider.model_id == "test-model"
+    
+    def test_resolve_provider_with_config(self):
+        """Should resolve provider with config."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("mock", MockLLMProvider)
+        
+        config = {"api_key": "test-key", "timeout": 5000}
+        provider = registry.resolve("mock", "test-model", config)
+        assert provider.config == config
+    
+    def test_resolve_via_alias(self):
+        """Should resolve provider via alias."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("cloudflare", CustomCloudflareProvider, aliases=["cf"])
+        
+        provider = registry.resolve("cf", "workers-ai-model")
+        assert provider.provider_id == "cloudflare"
+    
+    def test_resolve_unknown_provider_raises_error(self):
+        """Should raise clear error for unknown provider."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("openai", MockLLMProvider)
+        registry.register("anthropic", MockLLMProvider)
+        
+        with pytest.raises(ValueError) as exc_info:
+            registry.resolve("cloudflare", "model")
+        
+        error_msg = str(exc_info.value).lower()
+        assert "unknown provider" in error_msg
+        assert "cloudflare" in error_msg
+        assert "openai" in error_msg or "anthropic" in error_msg
+
+
+class TestDefaultRegistry:
+    """Tests for default global registry."""
+    
+    def test_get_default_registry_singleton(self):
+        """Should return the same registry instance."""
+        from praisonai.llm.registry import get_default_llm_registry
+        
+        registry1 = get_default_llm_registry()
+        registry2 = get_default_llm_registry()
+        assert registry1 is registry2
+    
+    def test_register_provider_global(self):
+        """Should register provider to default registry."""
+        from praisonai.llm.registry import (
+            register_llm_provider,
+            unregister_llm_provider,
+            get_default_llm_registry
+        )
+        
+        register_llm_provider("custom-test", MockLLMProvider)
+        assert get_default_llm_registry().has("custom-test")
+        
+        # Cleanup
+        unregister_llm_provider("custom-test")
+    
+    def test_unregister_provider_global(self):
+        """Should unregister provider from default registry."""
+        from praisonai.llm.registry import (
+            register_llm_provider,
+            unregister_llm_provider,
+            get_default_llm_registry
+        )
+        
+        register_llm_provider("custom-test-2", MockLLMProvider)
+        assert get_default_llm_registry().has("custom-test-2")
+        
+        unregister_llm_provider("custom-test-2")
+        assert not get_default_llm_registry().has("custom-test-2")
+
+
+class TestMultiAgentSafety:
+    """Tests for multi-agent safety with isolated registries."""
+    
+    def test_isolated_registries(self):
+        """Should support isolated registries per context."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry1 = LLMProviderRegistry()
+        registry2 = LLMProviderRegistry()
+        
+        registry1.register("provider-a", MockLLMProvider)
+        registry2.register("provider-b", CustomCloudflareProvider)
+        
+        assert registry1.has("provider-a")
+        assert not registry1.has("provider-b")
+        
+        assert not registry2.has("provider-a")
+        assert registry2.has("provider-b")
+    
+    def test_no_leak_between_registries(self):
+        """Should not leak registrations between isolated registries."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry1 = LLMProviderRegistry()
+        registry2 = LLMProviderRegistry()
+        
+        registry1.register("shared-name", MockLLMProvider)
+        registry2.register("shared-name", CustomCloudflareProvider)
+        
+        provider1 = registry1.resolve("shared-name", "model")
+        provider2 = registry2.resolve("shared-name", "model")
+        
+        assert provider1.provider_id == "mock"
+        assert provider2.provider_id == "cloudflare"
+
+
+class TestCreateLLMProvider:
+    """Tests for create_llm_provider function."""
+    
+    def test_create_from_string(self):
+        """Should create provider from string."""
+        from praisonai.llm.registry import (
+            create_llm_provider,
+            register_llm_provider,
+            unregister_llm_provider
+        )
+        
+        register_llm_provider("mock", MockLLMProvider)
+        
+        try:
+            provider = create_llm_provider("mock/test-model")
+            assert provider.provider_id == "mock"
+            assert provider.model_id == "test-model"
+        finally:
+            unregister_llm_provider("mock")
+    
+    def test_create_from_instance(self):
+        """Should pass through provider instance."""
+        from praisonai.llm.registry import create_llm_provider
+        
+        instance = MockLLMProvider("direct-model")
+        provider = create_llm_provider(instance)
+        
+        assert provider is instance
+        assert provider.model_id == "direct-model"
+    
+    def test_create_from_spec_dict(self):
+        """Should create provider from spec dict."""
+        from praisonai.llm.registry import (
+            create_llm_provider,
+            register_llm_provider,
+            unregister_llm_provider
+        )
+        
+        register_llm_provider("mock", MockLLMProvider)
+        
+        try:
+            provider = create_llm_provider({
+                "name": "mock",
+                "model_id": "spec-model",
+                "config": {"timeout": 5000}
+            })
+            assert provider.provider_id == "mock"
+            assert provider.model_id == "spec-model"
+        finally:
+            unregister_llm_provider("mock")
+    
+    def test_create_with_custom_registry(self):
+        """Should use custom registry when provided."""
+        from praisonai.llm.registry import create_llm_provider, LLMProviderRegistry
+        
+        custom_registry = LLMProviderRegistry()
+        custom_registry.register("isolated", CustomCloudflareProvider)
+        
+        provider = create_llm_provider("isolated/model", registry=custom_registry)
+        assert provider.provider_id == "cloudflare"
+        
+        # Should not be in default registry
+        with pytest.raises(ValueError):
+            create_llm_provider("isolated/model")
+
+
+class TestCollisionDetection:
+    """Tests for collision detection and error messages."""
+    
+    def test_alias_collision_with_existing_alias(self):
+        """Should raise error when alias collides with existing alias."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("provider-a", MockLLMProvider, aliases=["shared-alias"])
+        
+        with pytest.raises(ValueError) as exc_info:
+            registry.register("provider-b", CustomCloudflareProvider, aliases=["shared-alias"])
+        
+        error_msg = str(exc_info.value)
+        assert "shared-alias" in error_msg
+        assert "already registered" in error_msg
+        assert "provider-a" in error_msg  # Should mention the existing target
+    
+    def test_alias_collision_with_provider_name(self):
+        """Should raise error when alias collides with provider name."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("existing-provider", MockLLMProvider)
+        
+        with pytest.raises(ValueError) as exc_info:
+            registry.register("new-provider", CustomCloudflareProvider, aliases=["existing-provider"])
+        
+        error_msg = str(exc_info.value)
+        assert "existing-provider" in error_msg
+        assert "conflicts" in error_msg
+    
+    def test_alias_override_with_flag(self):
+        """Should allow alias override with override=True."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("provider-a", MockLLMProvider, aliases=["shared-alias"])
+        registry.register("provider-b", CustomCloudflareProvider, aliases=["shared-alias"], override=True)
+        
+        # Alias should now point to provider-b
+        provider = registry.resolve("shared-alias", "model")
+        assert provider.provider_id == "cloudflare"
+    
+    def test_case_insensitive_collision(self):
+        """Should detect collision regardless of case."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("MyProvider", MockLLMProvider)
+        
+        with pytest.raises(ValueError, match="already registered"):
+            registry.register("myprovider", CustomCloudflareProvider)
+    
+    def test_error_message_includes_available_providers(self):
+        """Error message should list available providers."""
+        from praisonai.llm.registry import LLMProviderRegistry
+        
+        registry = LLMProviderRegistry()
+        registry.register("openai", MockLLMProvider)
+        registry.register("anthropic", MockLLMProvider)
+        
+        with pytest.raises(ValueError) as exc_info:
+            registry.resolve("unknown", "model")
+        
+        error_msg = str(exc_info.value).lower()
+        assert "unknown provider" in error_msg
+        assert "openai" in error_msg
+        assert "anthropic" in error_msg
+        assert "register" in error_msg  # Should suggest how to register
+
+
+class TestParseModelString:
+    """Tests for model string parsing."""
+    
+    def test_parse_provider_model_format(self):
+        """Should parse provider/model format."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("openai/gpt-4o")
+        assert result["provider_id"] == "openai"
+        assert result["model_id"] == "gpt-4o"
+    
+    def test_parse_gpt_model_defaults_to_openai(self):
+        """Should default gpt-* models to openai."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("gpt-4o-mini")
+        assert result["provider_id"] == "openai"
+        assert result["model_id"] == "gpt-4o-mini"
+    
+    def test_parse_claude_model_defaults_to_anthropic(self):
+        """Should default claude-* models to anthropic."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("claude-3-5-sonnet")
+        assert result["provider_id"] == "anthropic"
+        assert result["model_id"] == "claude-3-5-sonnet"
+    
+    def test_parse_gemini_model_defaults_to_google(self):
+        """Should default gemini-* models to google."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("gemini-2.0-flash")
+        assert result["provider_id"] == "google"
+        assert result["model_id"] == "gemini-2.0-flash"
+    
+    def test_parse_o1_model_defaults_to_openai(self):
+        """Should default o1* models to openai."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("o1-preview")
+        assert result["provider_id"] == "openai"
+        assert result["model_id"] == "o1-preview"
+    
+    def test_parse_unknown_model_defaults_to_openai(self):
+        """Should default unknown models to openai."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("llama-3.1-8b")
+        assert result["provider_id"] == "openai"
+        assert result["model_id"] == "llama-3.1-8b"
+    
+    def test_parse_custom_provider_model(self):
+        """Should parse custom provider/model format."""
+        from praisonai.llm.registry import parse_model_string
+        
+        result = parse_model_string("cloudflare/workers-ai-model")
+        assert result["provider_id"] == "cloudflare"
+        assert result["model_id"] == "workers-ai-model"
+
+
+class TestLiteLLMIsolation:
+    """Tests to verify LiteLLM paths are not affected."""
+    
+    def test_registry_does_not_import_litellm(self):
+        """Registry module should not import litellm."""
+        import sys
+        
+        # Clear any cached imports
+        modules_before = set(sys.modules.keys())
+        
+        # Import registry
+        from praisonai.llm import registry
+        
+        # Check litellm was not imported
+        modules_after = set(sys.modules.keys())
+        new_modules = modules_after - modules_before
+        
+        litellm_modules = [m for m in new_modules if 'litellm' in m.lower()]
+        assert len(litellm_modules) == 0, f"Registry imported litellm modules: {litellm_modules}"
+    
+    def test_registry_only_imports_typing(self):
+        """Registry should only import from typing module."""
+        import ast
+        import inspect
+        from praisonai.llm import registry
+        
+        source = inspect.getsource(registry)
+        tree = ast.parse(source)
+        
+        imports = []
+        for node in ast.walk(tree):
+            if isinstance(node, ast.Import):
+                for alias in node.names:
+                    imports.append(alias.name)
+            elif isinstance(node, ast.ImportFrom):
+                if node.module:
+                    imports.append(node.module)
+        
+        # Only typing should be imported
+        assert imports == ['typing'], f"Unexpected imports: {imports}"