chore: bump praisonai and praisonaiagents package versions

fix: Add base_url and api_key parameters to Agent class for Ollama support

docker/Dockerfile

@@ -16,7 +16,7 @@ RUN mkdir -p /root/.praison
 # Install Python packages (using latest versions)
 RUN pip install --no-cache-dir \
     flask \
-    "praisonai>=2.2.35" \
+    "praisonai>=2.2.36" \
     "praisonai[api]" \
     gunicorn \
     markdown

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>=2.2.35" \
+    "praisonai>=2.2.36" \
     "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>=2.2.35" \
+    "praisonai>=2.2.36" \
     "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>=2.2.35" \
+    "praisonai>=2.2.36" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

docker/README.md

@@ -121,7 +121,7 @@ healthcheck:
 ## 📦 Package Versions
 
 All Docker images use consistent, up-to-date versions:
-- PraisonAI: `>=2.2.35`
+- PraisonAI: `>=2.2.36`
 - PraisonAI Agents: `>=0.0.92`
 - Python: `3.11-slim`
 
@@ -218,7 +218,7 @@ docker-compose up -d
 ### Version Pinning
 To use specific versions, update the Dockerfile:
 ```dockerfile
-RUN pip install "praisonai==2.2.35" "praisonaiagents==0.0.92"
+RUN pip install "praisonai==2.2.36" "praisonaiagents==0.0.92"
 ```
 
 ## 🌐 Production Deployment

examples/python/providers/ollama/ollama-base-url-example.py

@@ -0,0 +1,34 @@
+# Example: Using Ollama with a remote host via base_url parameter
+# pip install praisonaiagents
+
+from praisonaiagents import Agent
+
+# Method 1: Using base_url parameter directly (NEW)
+agent = Agent(
+    instructions="You are a helpful assistant",
+    llm="ollama/llama3.2",
+    base_url="http://remote-host:11434"
+)
+
+response = agent.start("Why is the sky blue?")
+print(response)
+
+# Method 2: Using dict configuration
+agent2 = Agent(
+    instructions="You are a helpful assistant",
+    llm={
+        "model": "ollama/llama3.2",
+        "base_url": "http://remote-host:11434"
+    }
+)
+
+response2 = agent2.start("What is the capital of France?")
+print(response2)
+
+# Method 3: Using environment variable (existing method)
+# export OPENAI_BASE_URL=http://remote-host:11434
+# Then just:
+# agent3 = Agent(
+#     instructions="You are a helpful assistant",
+#     llm="ollama/llama3.2"
+# )

src/praisonai-agents/praisonaiagents/agent/agent.py

@@ -373,7 +373,9 @@ class Agent:
         user_id: Optional[str] = None,
         reasoning_steps: bool = False,
         guardrail: Optional[Union[Callable[['TaskOutput'], Tuple[bool, Any]], str]] = None,
-        max_guardrail_retries: int = 3
+        max_guardrail_retries: int = 3,
+        base_url: Optional[str] = None,
+        api_key: Optional[str] = None
     ):
         """Initialize an Agent instance.
 
@@ -457,6 +459,10 @@ class Agent:
                 description string for LLM-based validation. Defaults to None.
             max_guardrail_retries (int, optional): Maximum number of retry attempts when guardrail
                 validation fails before giving up. Defaults to 3.
+            base_url (Optional[str], optional): Base URL for custom LLM endpoints (e.g., Ollama).
+                If provided, automatically creates a custom LLM instance. Defaults to None.
+            api_key (Optional[str], optional): API key for LLM provider. If not provided,
+                falls back to environment variables. Defaults to None.
 
         Raises:
             ValueError: If all of name, role, goal, backstory, and instructions are None.
@@ -503,10 +509,40 @@ class Agent:
         # Check for model name in environment variable if not provided
         self._using_custom_llm = False
 
-        # If the user passes a dictionary (for advanced configuration)
-        if isinstance(llm, dict) and "model" in llm:
+        # If base_url is provided, always create a custom LLM instance
+        if base_url:
             try:
                 from ..llm.llm import LLM
+                # Handle different llm parameter types with base_url
+                if isinstance(llm, dict):
+                    # Merge base_url and api_key into the dict
+                    llm_config = llm.copy()
+                    llm_config['base_url'] = base_url
+                    if api_key:
+                        llm_config['api_key'] = api_key
+                    self.llm_instance = LLM(**llm_config)
+                else:
+                    # Create LLM with model string and base_url
+                    model_name = llm or os.getenv('OPENAI_MODEL_NAME', 'gpt-4o')
+                    self.llm_instance = LLM(
+                        model=model_name,
+                        base_url=base_url,
+                        api_key=api_key
+                    )
+                self._using_custom_llm = True
+            except ImportError as e:
+                raise ImportError(
+                    "LLM features requested but dependencies not installed. "
+                    "Please install with: pip install \"praisonaiagents[llm]\""
+                ) from e
+        # If the user passes a dictionary (for advanced configuration)
+        elif isinstance(llm, dict) and "model" in llm:
+            try:
+                from ..llm.llm import LLM
+                # Add api_key if provided and not in dict
+                if api_key and 'api_key' not in llm:
+                    llm = llm.copy()
+                    llm['api_key'] = api_key
                 self.llm_instance = LLM(**llm)  # Pass all dict items as kwargs
                 self._using_custom_llm = True
             except ImportError as e:
@@ -519,7 +555,10 @@ class Agent:
             try:
                 from ..llm.llm import LLM
                 # Pass the entire string so LiteLLM can parse provider/model
-                self.llm_instance = LLM(model=llm)
+                llm_params = {'model': llm}
+                if api_key:
+                    llm_params['api_key'] = api_key
+                self.llm_instance = LLM(**llm_params)
                 self._using_custom_llm = True
                 
                 # Ensure tools are properly accessible when using custom LLM

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.0.108"
+version = "0.0.109"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [

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/v2.2.35.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.35.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.36.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.36.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/cli.py

@@ -170,6 +170,25 @@ class PraisonAI:
             pass
         return None
 
+    def read_file_if_provided(self, file_path):
+        """
+        Read content from a file if the file path is provided.
+        Returns the file content or None if file cannot be read.
+        """
+        if not file_path:
+            return None
+        
+        try:
+            with open(file_path, 'r', encoding='utf-8') as f:
+                file_content = f.read().strip()
+                return file_content if file_content else None
+        except FileNotFoundError:
+            print(f"[red]ERROR: File not found: {file_path}[/red]")
+            sys.exit(1)
+        except Exception as e:
+            print(f"[red]ERROR: Failed to read file: {e}[/red]")
+            sys.exit(1)
+
     def main(self):
         """
         The main function of the PraisonAI object. It parses the command-line arguments,
@@ -189,15 +208,24 @@ class PraisonAI:
 
         # Check for piped input from stdin
         stdin_input = self.read_stdin_if_available()
+        
+        # Check for file input if --file is provided
+        file_input = self.read_file_if_provided(getattr(args, 'file', None))
 
         if args.command:
             if args.command.startswith("tests.test") or args.command.startswith("tests/test"):  # Argument used for testing purposes
                 print("test")
                 return "test"
             else:
-                # If stdin input is available, append it to the command
+                # Combine command with any available inputs (stdin and/or file)
+                combined_inputs = []
                 if stdin_input:
-                    combined_prompt = f"{args.command} {stdin_input}"
+                    combined_inputs.append(stdin_input)
+                if file_input:
+                    combined_inputs.append(file_input)
+                
+                if combined_inputs:
+                    combined_prompt = f"{args.command} {' '.join(combined_inputs)}"
                     result = self.handle_direct_prompt(combined_prompt)
                     print(result)
                     return result
@@ -206,20 +234,30 @@ class PraisonAI:
         elif hasattr(args, 'direct_prompt') and args.direct_prompt:
             # Only handle direct prompt if agent_file wasn't explicitly set in constructor
             if original_agent_file == "agents.yaml":  # Default value, so safe to use direct prompt
-                # If stdin input is available, append it to the direct prompt
-                prompt = args.direct_prompt
+                # Combine direct prompt with any available inputs (stdin and/or file)
+                prompt_parts = [args.direct_prompt]
                 if stdin_input:
-                    prompt = f"{args.direct_prompt} {stdin_input}"
+                    prompt_parts.append(stdin_input)
+                if file_input:
+                    prompt_parts.append(file_input)
+                prompt = ' '.join(prompt_parts)
                 result = self.handle_direct_prompt(prompt)
                 print(result)
                 return result
             else:
                 # Agent file was explicitly set, ignore direct prompt and use the file
                 pass
-        elif stdin_input:
-            # If only stdin input is provided (no command), use it as direct prompt
-            if original_agent_file == "agents.yaml":  # Default value, so safe to use stdin as prompt
-                result = self.handle_direct_prompt(stdin_input)
+        elif stdin_input or file_input:
+            # If only stdin/file input is provided (no command), use it as direct prompt
+            if original_agent_file == "agents.yaml":  # Default value, so safe to use input as prompt
+                # Combine any available inputs
+                inputs = []
+                if stdin_input:
+                    inputs.append(stdin_input)
+                if file_input:
+                    inputs.append(file_input)
+                combined_input = ' '.join(inputs)
+                result = self.handle_direct_prompt(combined_input)
                 print(result)
                 return result
         # If no command or direct_prompt, preserve agent_file from constructor (don't overwrite)
@@ -530,6 +568,7 @@ class PraisonAI:
         parser.add_argument("--public", action="store_true", help="Use ngrok to expose the server publicly (only with --call)")
         parser.add_argument("--merge", action="store_true", help="Merge existing agents.yaml with auto-generated agents instead of overwriting")
         parser.add_argument("--claudecode", action="store_true", help="Enable Claude Code integration for file modifications and coding tasks")
+        parser.add_argument("--file", "-f", type=str, help="Read input from a file and append it to the prompt")
         
         # If we're in a test environment, parse with empty args to avoid pytest interference
         if in_test_env:

src/praisonai/praisonai/deploy.py

@@ -56,7 +56,7 @@ 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==2.2.35 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.2.36 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
             

src/praisonai/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "PraisonAI"
-version = "2.2.35"
+version = "2.2.36"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 readme = "README.md"
 license = ""
@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.0.108",
+    "praisonaiagents>=0.0.109",
     "python-dotenv>=0.19.0",
     "instructor>=1.3.3",
     "PyYAML>=6.0",
@@ -95,7 +95,7 @@ autogen = ["pyautogen>=0.2.19", "praisonai-tools>=0.0.15", "crewai"]
 
 [tool.poetry]
 name = "PraisonAI"
-version = "2.2.35"
+version = "2.2.36"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 authors = ["Mervin Praison"]
 license = ""
@@ -113,7 +113,7 @@ python = ">=3.10,<3.13"
 rich = ">=13.7"
 markdown = ">=3.5"
 pyparsing = ">=3.0.0"
-praisonaiagents = ">=0.0.108"
+praisonaiagents = ">=0.0.109"
 python-dotenv = ">=0.19.0"
 instructor = ">=1.3.3"
 PyYAML = ">=6.0"

src/praisonai/uv.lock

@@ -3932,7 +3932,7 @@ wheels = [
 
 [[package]]
 name = "praisonai"
-version = "2.2.35"
+version = "2.2.36"
 source = { editable = "." }
 dependencies = [
     { name = "instructor" },
@@ -4074,7 +4074,7 @@ requires-dist = [
     { name = "plotly", marker = "extra == 'realtime'", specifier = ">=5.24.0" },
     { name = "praisonai-tools", marker = "extra == 'autogen'", specifier = ">=0.0.15" },
     { name = "praisonai-tools", marker = "extra == 'crewai'", specifier = ">=0.0.15" },
-    { name = "praisonaiagents", specifier = ">=0.0.108" },
+    { name = "praisonaiagents", specifier = ">=0.0.109" },
     { name = "pyautogen", marker = "extra == 'autogen'", specifier = ">=0.2.19" },
     { name = "pydantic", marker = "extra == 'chat'", specifier = "<=2.10.1" },
     { name = "pydantic", marker = "extra == 'code'", specifier = "<=2.10.1" },
@@ -4132,7 +4132,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.0.108"
+version = "0.0.109"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "mcp" },
@@ -4141,9 +4141,9 @@ dependencies = [
     { name = "pydantic" },
     { name = "rich" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/f3/48/577f09adfacbfe45367c038483350f125268e8adb8ed48ebc5e0d2ef93f3/praisonaiagents-0.0.108.tar.gz", hash = "sha256:c8e29f7ed5228ba2b6334c9dc5eff9c72abf5fcba10489888f7ac6f2a73764f9", size = 157136, upload-time = "2025-06-27T12:24:00.945Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/c4/1e/e99db01581df3eb819d5f140433eea4cf99b7b152c288b9e60e121c4f676/praisonaiagents-0.0.109.tar.gz", hash = "sha256:133b9c0070a858cf5af46683e04fc8245543e02d411956e4c2a8cc894a55a7b1", size = 157598, upload-time = "2025-06-28T08:43:43.388Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0b/55/fb139f711ce2653bc0a67d9891ad83558427cc9e3c1becbf766aac6bfd25/praisonaiagents-0.0.108-py3-none-any.whl", hash = "sha256:ea0fe4bf9d8fa5ed293997bb035476369d70b46878ba4976a35087adfe0e8575", size = 177749, upload-time = "2025-06-27T12:23:59.646Z" },
+    { url = "https://files.pythonhosted.org/packages/7c/dc/5a88261b4879c9b8961b066909ab4f128cfcf81cc951d09c10ae9a1ad44b/praisonaiagents-0.0.109-py3-none-any.whl", hash = "sha256:d94cdea8d868dbe1baadb422c225a7e71efd2706c08c1a88d556c398ae57d042", size = 178224, upload-time = "2025-06-28T08:43:41.627Z" },
 ]
 
 [[package]]