Release v2.3.25

README.md

@@ -40,7 +40,17 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
 | 🔄 Self Reflection AI Agents | [Example](examples/python/concepts/self-reflection-details.py) | [📖](https://docs.praison.ai/features/selfreflection) |
 | 🧠 Reasoning AI Agents | [Example](examples/python/concepts/reasoning-extraction.py) | [📖](https://docs.praison.ai/features/reasoning) |
 | 👁️ Multi Modal AI Agents | [Example](examples/python/general/multimodal.py) | [📖](https://docs.praison.ai/features/multimodal) |
-| 🎭 AI Agent Workflow (Context Passing, Per-Step Agents) | [Example](examples/python/stateful/workflow-state-example.py) | [📖](https://docs.praison.ai/features/workflows) |
+| **🔄 Workflows** | | |
+| ↳ Simple Workflow | [Example](examples/python/workflows/simple_workflow.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow with Agents | [Example](examples/python/workflows/workflow_with_agents.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Agentic Routing (`route()`) | [Example](examples/python/workflows/workflow_routing.py) | [📖](https://docs.praison.ai/features/routing) |
+| ↳ Parallel Execution (`parallel()`) | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/parallelisation) |
+| ↳ Loop over List/CSV (`loop()`) | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/repetitive) |
+| ↳ Evaluator-Optimizer (`repeat()`) | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/evaluator-optimiser) |
+| ↳ Conditional Steps | [Example](examples/python/workflows/workflow_conditional.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Branching | [Example](examples/python/workflows/workflow_branching.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Early Stop | [Example](examples/python/workflows/workflow_early_stop.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Checkpoints | [Example](examples/python/workflows/workflow_checkpoints.py) | [📖](https://docs.praison.ai/features/workflows) |
 | 📚 Add Custom Knowledge | [Example](examples/python/concepts/knowledge-agents.py) | [📖](https://docs.praison.ai/features/knowledge) |
 | 🧠 Memory (Short & Long Term) | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
 | 📄 Chat with PDF Agents | [Example](examples/python/concepts/chat-with-pdf.py) | [📖](https://docs.praison.ai/features/chat-with-pdf) |
@@ -103,19 +113,6 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
 | @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/cli/mentions) |
 | 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
 | 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
-| ⏸️ Workflow Checkpoints | [Example](examples/python/workflows/workflow_checkpoints.py) | [📖](https://docs.praison.ai/cli/session) |
-| 🔀 Workflow Branching | [Example](examples/python/workflows/workflow_branching.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔁 Workflow Loops | [Example](examples/python/workflows/workflow_loops.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 📞 Task Callbacks | [Example](examples/python/workflows/task_callbacks.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🛑 Workflow Early Stop | [Example](examples/python/workflows/workflow_early_stop.py) | [📖](https://docs.praison.ai/features/workflows) |
-| ⚡ Simple Workflow | [Example](examples/python/workflows/simple_workflow.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🤖 Workflow with Agents | [Example](examples/python/workflows/workflow_with_agents.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔄 Conditional Steps | [Example](examples/python/workflows/workflow_conditional.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🎭 Mixed Steps | [Example](examples/python/workflows/workflow_mixed_steps.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔀 Agentic Routing | [Example](examples/python/workflows/workflow_routing.py) | [📖](https://docs.praison.ai/features/workflows) |
-| ⚡ Parallel Execution | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 📄 CSV Loop Processing | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔄 Evaluator-Optimizer | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/workflows) |
 
 ## Supported Providers
 
@@ -466,8 +463,8 @@ result = asyncio.run(manager.aexecute("deploy", default_llm="gpt-4o-mini"))
 |----------|-------------|
 | Simple function pipelines | `Workflow` class ⭐ |
 | Agent-only pipelines | `Workflow` class |
-| CSV batch processing | `process="workflow"` |
-| Complex task routing | `process="workflow"` |
+| CSV batch processing | `Workflow` + `loop()` |
+| Complex task routing | `Workflow` + `route()` |
 | Markdown templates | `WorkflowManager` |
 | Early stop / conditional | `Workflow` class |
 
@@ -525,7 +522,9 @@ loop_step = WorkflowStep(
 
 ```python
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import route, parallel, loop, repeat
+# Or use Pipeline (alias for Workflow)
+from praisonaiagents import Pipeline
+from praisonaiagents.workflows import route, parallel, loop, repeat
 
 # 1. ROUTING - Decision-based branching
 workflow = Workflow(steps=[
@@ -559,35 +558,178 @@ workflow = Workflow(steps=[
         max_iterations=5
     )
 ])
+
+# 5. CALLBACKS - Monitor workflow execution
+workflow = Workflow(
+    steps=[step1, step2],
+    on_workflow_start=lambda w, i: print(f"Starting: {i}"),
+    on_step_complete=lambda name, r: print(f"{name}: {r.output[:50]}"),
+    on_workflow_complete=lambda w, r: print(f"Done: {r['status']}")
+)
+
+# 6. GUARDRAILS - Validate and retry
+def validate(result):
+    return ("error" not in result.output, "Fix the error")
+
+workflow = Workflow(steps=[
+    WorkflowStep(name="gen", handler=generator, guardrail=validate, max_retries=3)
+])
 ```
 
-### Task Callbacks & Variables (process="workflow")
+### Workflow with Agents
+
+Use Agent objects directly as workflow steps:
 
 ```python
-from praisonaiagents import Agent, Task, PraisonAIAgents
+from praisonaiagents import Agent, Workflow
+from praisonaiagents.workflows import route, parallel
 
-# Per-task agent config (no need to create agent separately)
-task = Task(
-    description="Research {{topic}}",
-    agent_config={"name": "Researcher", "role": "Expert", "llm": "gpt-4o-mini"},
-    variables={"topic": "AI trends"}
+# 1. SEQUENTIAL AGENTS
+researcher = Agent(name="Researcher", role="Research expert", tools=[tavily_search])
+writer = Agent(name="Writer", role="Content writer")
+editor = Agent(name="Editor", role="Editor")
+
+workflow = Workflow(steps=[researcher, writer, editor])
+result = workflow.start("Research and write about AI")
+
+# 2. PARALLEL AGENTS
+workflow = Workflow(steps=[
+    parallel([researcher1, researcher2, researcher3]),
+    aggregator_agent
+])
+
+# 3. ROUTE TO AGENTS
+workflow = Workflow(steps=[
+    classifier_function,
+    route({
+        "technical": [tech_agent],
+        "creative": [creative_agent],
+        "default": [general_agent]
+    })
+])
+
+# 4. WITH PLANNING & REASONING
+workflow = Workflow(
+    steps=[researcher, writer, editor],
+    planning=True,           # Create execution plan
+    planning_llm="gpt-4o",   # LLM for planning
+    reasoning=True,          # Chain-of-thought reasoning
+    verbose=True
 )
 
-# Callbacks for workflow execution
-def on_start(task, task_id):
-    print(f"Starting: {task.name}")
+# 5. TOOLS PER STEP
+workflow = Workflow(steps=[
+    WorkflowStep(
+        name="research",
+        action="Research {{topic}}",
+        tools=[tavily_search, web_scraper],
+        agent_config={"name": "Researcher", "role": "Expert"}
+    )
+])
 
-def on_complete(task, output):
-    print(f"Completed: {task.name}")
+# 6. OUTPUT TO FILE / IMAGES / PYDANTIC
+from pydantic import BaseModel
 
-agents = PraisonAIAgents(
-    agents=[agent],
-    tasks=[task],
-    process="workflow",
-    on_task_start=on_start,
-    on_task_complete=on_complete,
-    variables={"global_var": "shared_value"}  # Global variables for all tasks
+class Report(BaseModel):
+    title: str
+    content: str
+
+workflow = Workflow(steps=[
+    WorkflowStep(name="analyze", action="Analyze image", images=["image.jpg"]),
+    WorkflowStep(name="report", action="Generate report", output_pydantic=Report),
+    WorkflowStep(name="save", action="Save results", output_file="output/report.txt")
+])
+
+# 7. ASYNC EXECUTION
+import asyncio
+
+async def main():
+    result = await workflow.astart("input")
+    print(result)
+
+asyncio.run(main())
+
+# 8. STATUS TRACKING
+workflow.status  # "not_started" | "running" | "completed"
+workflow.step_statuses  # {"step1": "completed", "step2": "skipped"}
+
+# 9. MEMORY CONFIG
+workflow = Workflow(
+    steps=[researcher, writer],
+    memory_config={"provider": "chroma", "persist": True, "collection": "my_workflow"}
 )
+result1 = workflow.start("Research AI")
+result2 = workflow.start("Continue the research")  # Remembers first run
+```
+
+### YAML Workflow Template
+
+```yaml
+# .praison/workflows/research.yaml
+name: Research Workflow
+description: Research and write content with all patterns
+
+agents:
+  researcher:
+    role: Research Expert
+    goal: Find accurate information
+    tools: [tavily_search, web_scraper]
+  writer:
+    role: Content Writer
+    goal: Write engaging content
+  editor:
+    role: Editor
+    goal: Polish content
+
+steps:
+  # Sequential
+  - agent: researcher
+    action: Research {{topic}}
+    output_variable: research_data
+
+  # Routing
+  - name: classifier
+    action: Classify content type
+    route:
+      technical: [tech_handler]
+      creative: [creative_handler]
+      default: [general_handler]
+
+  # Parallel
+  - name: parallel_research
+    parallel:
+      - agent: researcher
+        action: Research market
+      - agent: researcher
+        action: Research competitors
+
+  # Loop
+  - agent: writer
+    action: Write about {{item}}
+    loop_over: topics
+    loop_var: item
+
+  # Repeat (evaluator-optimizer)
+  - agent: editor
+    action: Review and improve
+    repeat:
+      until: "quality > 8"
+      max_iterations: 3
+
+  # Output to file
+  - agent: writer
+    action: Write final report
+    output_file: output/{{topic}}_report.md
+
+variables:
+  topic: AI trends
+  topics: [ML, NLP, Vision]
+
+planning: true
+planning_llm: gpt-4o
+memory_config:
+  provider: chroma
+  persist: true
 ```
 
 ### 9. Hooks
@@ -733,6 +875,12 @@ praisonai workflow run deploy --workflow-var environment=staging --workflow-var
 # Execute with planning mode (AI creates sub-steps for each workflow step)
 praisonai workflow run "Research Blog" --planning --verbose
 
+# Execute with reasoning mode (chain-of-thought)
+praisonai workflow run "Analysis" --reasoning --verbose
+
+# Execute with memory enabled
+praisonai workflow run "Research" --memory
+
 # Show workflow details
 praisonai workflow show deploy
 
@@ -744,8 +892,23 @@ praisonai "What is AI?" --workflow "Research,Summarize" --save
 
 # Inline workflow with step actions
 praisonai "GPT-5" --workflow "Research:Search for info,Write:Write blog" --tools tavily
+
+# Workflow CLI help
+praisonai workflow help
 ```
 
+**Workflow CLI Options:**
+| Flag | Description |
+|------|-------------|
+| `--workflow-var key=value` | Set workflow variable (can be repeated) |
+| `--llm <model>` | LLM model (e.g., openai/gpt-4o-mini) |
+| `--tools <tools>` | Tools (comma-separated, e.g., tavily) |
+| `--planning` | Enable planning mode |
+| `--reasoning` | Enable reasoning mode |
+| `--memory` | Enable memory |
+| `--verbose` | Enable verbose output |
+| `--save` | Save output to file |
+
 ### Hooks CLI:
 ```bash
 # List configured hooks

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>=2.3.20" \
+    "praisonai>=2.3.25" \
     "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>=2.3.20" \
+    "praisonai>=2.3.25" \
     "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>=2.3.20" \
+    "praisonai>=2.3.25" \
     "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>=2.3.20" \
+    "praisonai>=2.3.25" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/python/workflows/simple_workflow.py

@@ -1,36 +1,38 @@
 """
-Simple Workflow Example
+Simple Agentic Workflow Example
 
-The easiest way to create and run workflows in PraisonAI.
-Just pass functions or agents as steps - no complex configuration needed!
+Demonstrates using Agent instances directly as workflow steps.
+Each agent processes the input and passes output to the next agent.
 """
 
-from praisonaiagents import Workflow, WorkflowContext, StepResult
+from praisonaiagents import Agent, Workflow
 
-# Define simple handler functions
-def validate(ctx: WorkflowContext) -> StepResult:
-    """Validate the input data."""
-    if not ctx.input:
-        return StepResult(output="No input provided", stop_workflow=True)
-    return StepResult(output=f"Validated: {ctx.input}")
+# Create agents with specific roles
+researcher = Agent(
+    name="Researcher",
+    role="Research Analyst",
+    goal="Research and provide information about topics",
+    instructions="You are a research analyst. Provide concise, factual information."
+)
 
-def process(ctx: WorkflowContext) -> StepResult:
-    """Process the validated data."""
-    return StepResult(output=f"Processed: {ctx.previous_result}")
+writer = Agent(
+    name="Writer", 
+    role="Content Writer",
+    goal="Write engaging content based on research",
+    instructions="You are a content writer. Write clear, engaging content based on the research provided."
+)
 
-def format_output(ctx: WorkflowContext) -> StepResult:
-    """Format the final output."""
-    return StepResult(output=f"✅ Final: {ctx.previous_result}")
-
-# Create workflow - just list your functions!
+# Create workflow with agents as steps
 workflow = Workflow(
-    name="Simple Pipeline",
-    steps=[validate, process, format_output]
+    name="Simple Agentic Pipeline",
+    steps=[researcher, writer]
 )
 
 if __name__ == "__main__":
-    # Run the workflow - PraisonAI style uses .start()
-    result = workflow.start("Hello, World!", verbose=True)
+    # Run workflow - agents process sequentially
+    result = workflow.start(
+        "What are the key benefits of AI agents?",
+        verbose=True
+    )
     
-    print(f"\nFinal output: {result['output']}")
-    print(f"Steps completed: {len(result['steps'])}")
+    print(f"\nFinal output:\n{result['output']}")

examples/python/workflows/simple_workflow_non_agentic.py

@@ -0,0 +1,36 @@
+"""
+Simple Workflow Example
+
+The easiest way to create and run workflows in PraisonAI.
+Just pass functions or agents as steps - no complex configuration needed!
+"""
+
+from praisonaiagents import Workflow, WorkflowContext, StepResult
+
+# Define simple handler functions
+def validate(ctx: WorkflowContext) -> StepResult:
+    """Validate the input data."""
+    if not ctx.input:
+        return StepResult(output="No input provided", stop_workflow=True)
+    return StepResult(output=f"Validated: {ctx.input}")
+
+def process(ctx: WorkflowContext) -> StepResult:
+    """Process the validated data."""
+    return StepResult(output=f"Processed: {ctx.previous_result}")
+
+def format_output(ctx: WorkflowContext) -> StepResult:
+    """Format the final output."""
+    return StepResult(output=f"✅ Final: {ctx.previous_result}")
+
+# Create workflow - just list your functions!
+workflow = Workflow(
+    name="Simple Pipeline",
+    steps=[validate, process, format_output]
+)
+
+if __name__ == "__main__":
+    # Run the workflow - PraisonAI style uses .start()
+    result = workflow.start("Hello, World!", verbose=True)
+    
+    print(f"\nFinal output: {result['output']}")
+    print(f"Steps completed: {len(result['steps'])}")

examples/python/workflows/workflow_loop_csv_non_agentic.py

@@ -5,7 +5,7 @@ Demonstrates iterating over a CSV file, processing each row.
 """
 
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import loop
+from praisonaiagents.workflows import loop
 import tempfile
 import os
 

examples/python/workflows/workflow_loop_list.py

@@ -0,0 +1,52 @@
+"""
+Workflow Loop with List Example
+
+Demonstrates iterating over a list of items, processing each one.
+"""
+
+from praisonaiagents import Workflow, WorkflowContext, StepResult
+from praisonaiagents.workflows import loop
+
+# Sample data
+fruits = ["apple", "banana", "cherry", "date", "elderberry"]
+
+# Processor for each item
+def process_fruit(ctx: WorkflowContext) -> StepResult:
+    """Process a single fruit from the list."""
+    fruit = ctx.variables.get("item", "unknown")
+    index = ctx.variables.get("loop_index", 0)
+    
+    # Simulate processing
+    result = f"🍎 [{index + 1}] {fruit.upper()} - processed successfully"
+    
+    return StepResult(
+        output=result,
+        variables={"last_fruit": fruit}
+    )
+
+# Aggregator to summarize results
+def summarize(ctx: WorkflowContext) -> StepResult:
+    """Summarize all processed fruits."""
+    outputs = ctx.variables.get("loop_outputs", [])
+    summary = f"📊 Processed {len(outputs)} fruits:\n"
+    summary += "\n".join(f"  {o}" for o in outputs)
+    return StepResult(output=summary)
+
+# Create workflow
+workflow = Workflow(
+    name="Fruit Processor",
+    steps=[
+        loop(process_fruit, over="fruits"),
+        summarize
+    ],
+    variables={"fruits": fruits}
+)
+
+if __name__ == "__main__":
+    print("=== Testing Loop with List ===\n")
+    
+    result = workflow.start("Process all fruits", verbose=True)
+    
+    print(f"\nFinal Output:\n{result['output']}")
+    print(f"\nLoop outputs count: {len(result['variables']['loop_outputs'])}")
+    print(f"Last processed: {result['variables'].get('last_fruit')}")

examples/python/workflows/workflow_parallel_non_agentic.py

@@ -6,7 +6,7 @@ combining their results.
 """
 
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import parallel
+from praisonaiagents.workflows import parallel
 import time
 
 # Parallel workers - each does independent work

examples/python/workflows/workflow_repeat_non_agentic.py

@@ -6,7 +6,7 @@ This is useful for iterative improvement patterns.
 """
 
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import repeat
+from praisonaiagents.workflows import repeat
 
 # Simulated content generator that improves each iteration
 class ContentGenerator:

examples/python/workflows/workflow_routing_non_agentic.py

@@ -6,7 +6,7 @@ takes different paths based on the output of a decision step.
 """
 
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import route
+from praisonaiagents.workflows import route
 
 # Decision maker - determines which route to take
 def classify_request(ctx: WorkflowContext) -> StepResult:

src/praisonai-agents/praisonaiagents/__init__.py

@@ -54,10 +54,12 @@ except ImportError:
     MCP = None
 from .session import Session
 from .memory.memory import Memory
-from .memory.workflows import (
+# Workflows - import from dedicated workflows module
+from .workflows import (
     Workflow, WorkflowStep, WorkflowContext, StepResult,
     Route, Parallel, Loop, Repeat,
-    route, parallel, loop, repeat
+    route, parallel, loop, repeat,
+    Pipeline  # Alias for Workflow
 )
 from .guardrails import GuardrailResult, LLMGuardrail
 

src/praisonai-agents/praisonaiagents/memory/__init__.py

@@ -48,30 +48,58 @@ def __getattr__(name):
     if name == "create_auto_memory":
         from .auto_memory import create_auto_memory
         return create_auto_memory
+    # Workflows - now in dedicated module, re-export for backward compatibility
     if name == "WorkflowManager":
-        from .workflows import WorkflowManager
+        from ..workflows import WorkflowManager
         return WorkflowManager
     if name == "Workflow":
-        from .workflows import Workflow
+        from ..workflows import Workflow
         return Workflow
     if name == "WorkflowStep":
-        from .workflows import WorkflowStep
+        from ..workflows import WorkflowStep
         return WorkflowStep
     if name == "WorkflowContext":
-        from .workflows import WorkflowContext
+        from ..workflows import WorkflowContext
         return WorkflowContext
     if name == "StepResult":
-        from .workflows import StepResult
+        from ..workflows import StepResult
         return StepResult
+    if name == "Pipeline":
+        from ..workflows import Pipeline
+        return Pipeline
+    if name == "Route":
+        from ..workflows import Route
+        return Route
+    if name == "Parallel":
+        from ..workflows import Parallel
+        return Parallel
+    if name == "Loop":
+        from ..workflows import Loop
+        return Loop
+    if name == "Repeat":
+        from ..workflows import Repeat
+        return Repeat
+    if name == "route":
+        from ..workflows import route
+        return route
+    if name == "parallel":
+        from ..workflows import parallel
+        return parallel
+    if name == "loop":
+        from ..workflows import loop
+        return loop
+    if name == "repeat":
+        from ..workflows import repeat
+        return repeat
     # Backward compatibility aliases
     if name == "StepInput":
-        from .workflows import WorkflowContext
+        from ..workflows import WorkflowContext
         return WorkflowContext
     if name == "StepOutput":
-        from .workflows import StepResult
+        from ..workflows import StepResult
         return StepResult
     if name == "create_workflow_manager":
-        from .workflows import create_workflow_manager
+        from ..workflows.workflows import create_workflow_manager
         return create_workflow_manager
     if name == "HooksManager":
         from .hooks import HooksManager
@@ -98,13 +126,23 @@ __all__ = [
     "AutoMemory",
     "AutoMemoryExtractor",
     "create_auto_memory",
-    # Workflows
+    # Workflows (re-exported from praisonaiagents.workflows for backward compatibility)
     "WorkflowManager",
     "Workflow",
+    "Pipeline",
     "WorkflowStep",
     "WorkflowContext",
     "StepResult",
     "create_workflow_manager",
+    # Workflow patterns
+    "Route",
+    "Parallel",
+    "Loop",
+    "Repeat",
+    "route",
+    "parallel",
+    "loop",
+    "repeat",
     # Hooks
     "HooksManager",
     "HookResult",

src/praisonai-agents/praisonaiagents/memory/workflows.py

@@ -779,6 +779,10 @@ class Workflow:
         return self.run(input, **kwargs)
 
 
+# Alias: Pipeline = Workflow (they are the same concept)
+Pipeline = Workflow
+
+
 class WorkflowManager:
     """
     Manages workflow discovery, loading, and execution.

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

@@ -826,7 +826,34 @@ Provide a JSON with the structure:
         logging.info("Hierarchical task execution finished")
 
     def workflow(self):
-        """Synchronous version of workflow method"""
+        """Synchronous version of workflow method.
+        
+        DEPRECATED: This method is deprecated. Use the Workflow class instead:
+        
+        ```python
+        from praisonaiagents import Workflow, StepResult
+        from praisonaiagents.workflows import route, parallel, loop, repeat
+        
+        workflow = Workflow(steps=[step1, step2])
+        result = workflow.start("input")
+        ```
+        
+        The Workflow class provides a simpler API with more features:
+        - route() for decision-based branching
+        - parallel() for concurrent execution
+        - loop() for iteration over lists/CSV
+        - repeat() for evaluator-optimizer patterns
+        - Callbacks (on_step_start, on_step_complete, etc.)
+        - Guardrails with validation feedback
+        - Status tracking
+        """
+        import warnings
+        warnings.warn(
+            "process='workflow' is deprecated. Use the Workflow class instead: "
+            "from praisonaiagents import Workflow; workflow = Workflow(steps=[...]); workflow.start()",
+            DeprecationWarning,
+            stacklevel=2
+        )
         current_iter = 0  # Track how many times we've looped
         # Build workflow relationships first
         for task in self.tasks.values():

src/praisonai-agents/praisonaiagents/workflows/__init__.py

@@ -0,0 +1,55 @@
+"""
+Workflows module for PraisonAI Agents.
+
+Provides workflow/pipeline patterns for orchestrating agents and functions.
+"""
+
+from .workflows import (
+    # Core classes
+    Workflow,
+    Pipeline,  # Alias for Workflow
+    WorkflowStep,
+    WorkflowContext,
+    StepResult,
+    WorkflowManager,
+    
+    # Pattern helpers
+    Route,
+    Parallel,
+    Loop,
+    Repeat,
+    
+    # Convenience functions
+    route,
+    parallel,
+    loop,
+    repeat,
+    
+    # Backward compatibility aliases
+    StepInput,
+    StepOutput,
+)
+
+__all__ = [
+    # Core
+    "Workflow",
+    "Pipeline",
+    "WorkflowStep",
+    "WorkflowContext",
+    "StepResult",
+    "WorkflowManager",
+    
+    # Patterns
+    "Route",
+    "Parallel",
+    "Loop",
+    "Repeat",
+    "route",
+    "parallel",
+    "loop",
+    "repeat",
+    
+    # Aliases
+    "StepInput",
+    "StepOutput",
+]

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.0.198"
+version = "0.1.3"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [

src/praisonai-agents/uv.lock

@@ -2422,7 +2422,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.0.198"
+version = "0.1.3"
 source = { editable = "." }
 dependencies = [
     { name = "aiohttp" },

src/praisonai/README.md

@@ -40,7 +40,17 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
 | 🔄 Self Reflection AI Agents | [Example](examples/python/concepts/self-reflection-details.py) | [📖](https://docs.praison.ai/features/selfreflection) |
 | 🧠 Reasoning AI Agents | [Example](examples/python/concepts/reasoning-extraction.py) | [📖](https://docs.praison.ai/features/reasoning) |
 | 👁️ Multi Modal AI Agents | [Example](examples/python/general/multimodal.py) | [📖](https://docs.praison.ai/features/multimodal) |
-| 🎭 AI Agent Workflow (Context Passing, Per-Step Agents) | [Example](examples/python/stateful/workflow-state-example.py) | [📖](https://docs.praison.ai/features/workflows) |
+| **🔄 Workflows** | | |
+| ↳ Simple Workflow | [Example](examples/python/workflows/simple_workflow.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow with Agents | [Example](examples/python/workflows/workflow_with_agents.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Agentic Routing (`route()`) | [Example](examples/python/workflows/workflow_routing.py) | [📖](https://docs.praison.ai/features/routing) |
+| ↳ Parallel Execution (`parallel()`) | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/parallelisation) |
+| ↳ Loop over List/CSV (`loop()`) | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/repetitive) |
+| ↳ Evaluator-Optimizer (`repeat()`) | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/evaluator-optimiser) |
+| ↳ Conditional Steps | [Example](examples/python/workflows/workflow_conditional.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Branching | [Example](examples/python/workflows/workflow_branching.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Early Stop | [Example](examples/python/workflows/workflow_early_stop.py) | [📖](https://docs.praison.ai/features/workflows) |
+| ↳ Workflow Checkpoints | [Example](examples/python/workflows/workflow_checkpoints.py) | [📖](https://docs.praison.ai/features/workflows) |
 | 📚 Add Custom Knowledge | [Example](examples/python/concepts/knowledge-agents.py) | [📖](https://docs.praison.ai/features/knowledge) |
 | 🧠 Memory (Short & Long Term) | [Example](examples/python/general/memory_example.py) | [📖](https://docs.praison.ai/concepts/memory) |
 | 📄 Chat with PDF Agents | [Example](examples/python/concepts/chat-with-pdf.py) | [📖](https://docs.praison.ai/features/chat-with-pdf) |
@@ -103,19 +113,6 @@ PraisonAI is a production-ready Multi-AI Agents framework with self-reflection,
 | @ @Mentions in Prompts | [Example](#mentions-in-prompts) | [📖](https://docs.praison.ai/cli/mentions) |
 | 💾 Auto-Save Sessions | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
 | 📜 History in Context | [Example](#session-management-python) | [📖](https://docs.praison.ai/cli/session) |
-| ⏸️ Workflow Checkpoints | [Example](examples/python/workflows/workflow_checkpoints.py) | [📖](https://docs.praison.ai/cli/session) |
-| 🔀 Workflow Branching | [Example](examples/python/workflows/workflow_branching.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔁 Workflow Loops | [Example](examples/python/workflows/workflow_loops.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 📞 Task Callbacks | [Example](examples/python/workflows/task_callbacks.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🛑 Workflow Early Stop | [Example](examples/python/workflows/workflow_early_stop.py) | [📖](https://docs.praison.ai/features/workflows) |
-| ⚡ Simple Workflow | [Example](examples/python/workflows/simple_workflow.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🤖 Workflow with Agents | [Example](examples/python/workflows/workflow_with_agents.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔄 Conditional Steps | [Example](examples/python/workflows/workflow_conditional.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🎭 Mixed Steps | [Example](examples/python/workflows/workflow_mixed_steps.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔀 Agentic Routing | [Example](examples/python/workflows/workflow_routing.py) | [📖](https://docs.praison.ai/features/workflows) |
-| ⚡ Parallel Execution | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 📄 CSV Loop Processing | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/workflows) |
-| 🔄 Evaluator-Optimizer | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/workflows) |
 
 ## Supported Providers
 
@@ -466,8 +463,8 @@ result = asyncio.run(manager.aexecute("deploy", default_llm="gpt-4o-mini"))
 |----------|-------------|
 | Simple function pipelines | `Workflow` class ⭐ |
 | Agent-only pipelines | `Workflow` class |
-| CSV batch processing | `process="workflow"` |
-| Complex task routing | `process="workflow"` |
+| CSV batch processing | `Workflow` + `loop()` |
+| Complex task routing | `Workflow` + `route()` |
 | Markdown templates | `WorkflowManager` |
 | Early stop / conditional | `Workflow` class |
 
@@ -525,7 +522,9 @@ loop_step = WorkflowStep(
 
 ```python
 from praisonaiagents import Workflow, WorkflowContext, StepResult
-from praisonaiagents.memory.workflows import route, parallel, loop, repeat
+# Or use Pipeline (alias for Workflow)
+from praisonaiagents import Pipeline
+from praisonaiagents.workflows import route, parallel, loop, repeat
 
 # 1. ROUTING - Decision-based branching
 workflow = Workflow(steps=[
@@ -559,35 +558,178 @@ workflow = Workflow(steps=[
         max_iterations=5
     )
 ])
+
+# 5. CALLBACKS - Monitor workflow execution
+workflow = Workflow(
+    steps=[step1, step2],
+    on_workflow_start=lambda w, i: print(f"Starting: {i}"),
+    on_step_complete=lambda name, r: print(f"{name}: {r.output[:50]}"),
+    on_workflow_complete=lambda w, r: print(f"Done: {r['status']}")
+)
+
+# 6. GUARDRAILS - Validate and retry
+def validate(result):
+    return ("error" not in result.output, "Fix the error")
+
+workflow = Workflow(steps=[
+    WorkflowStep(name="gen", handler=generator, guardrail=validate, max_retries=3)
+])
 ```
 
-### Task Callbacks & Variables (process="workflow")
+### Workflow with Agents
+
+Use Agent objects directly as workflow steps:
 
 ```python
-from praisonaiagents import Agent, Task, PraisonAIAgents
+from praisonaiagents import Agent, Workflow
+from praisonaiagents.workflows import route, parallel
 
-# Per-task agent config (no need to create agent separately)
-task = Task(
-    description="Research {{topic}}",
-    agent_config={"name": "Researcher", "role": "Expert", "llm": "gpt-4o-mini"},
-    variables={"topic": "AI trends"}
+# 1. SEQUENTIAL AGENTS
+researcher = Agent(name="Researcher", role="Research expert", tools=[tavily_search])
+writer = Agent(name="Writer", role="Content writer")
+editor = Agent(name="Editor", role="Editor")
+
+workflow = Workflow(steps=[researcher, writer, editor])
+result = workflow.start("Research and write about AI")
+
+# 2. PARALLEL AGENTS
+workflow = Workflow(steps=[
+    parallel([researcher1, researcher2, researcher3]),
+    aggregator_agent
+])
+
+# 3. ROUTE TO AGENTS
+workflow = Workflow(steps=[
+    classifier_function,
+    route({
+        "technical": [tech_agent],
+        "creative": [creative_agent],
+        "default": [general_agent]
+    })
+])
+
+# 4. WITH PLANNING & REASONING
+workflow = Workflow(
+    steps=[researcher, writer, editor],
+    planning=True,           # Create execution plan
+    planning_llm="gpt-4o",   # LLM for planning
+    reasoning=True,          # Chain-of-thought reasoning
+    verbose=True
 )
 
-# Callbacks for workflow execution
-def on_start(task, task_id):
-    print(f"Starting: {task.name}")
+# 5. TOOLS PER STEP
+workflow = Workflow(steps=[
+    WorkflowStep(
+        name="research",
+        action="Research {{topic}}",
+        tools=[tavily_search, web_scraper],
+        agent_config={"name": "Researcher", "role": "Expert"}
+    )
+])
 
-def on_complete(task, output):
-    print(f"Completed: {task.name}")
+# 6. OUTPUT TO FILE / IMAGES / PYDANTIC
+from pydantic import BaseModel
 
-agents = PraisonAIAgents(
-    agents=[agent],
-    tasks=[task],
-    process="workflow",
-    on_task_start=on_start,
-    on_task_complete=on_complete,
-    variables={"global_var": "shared_value"}  # Global variables for all tasks
+class Report(BaseModel):
+    title: str
+    content: str
+
+workflow = Workflow(steps=[
+    WorkflowStep(name="analyze", action="Analyze image", images=["image.jpg"]),
+    WorkflowStep(name="report", action="Generate report", output_pydantic=Report),
+    WorkflowStep(name="save", action="Save results", output_file="output/report.txt")
+])
+
+# 7. ASYNC EXECUTION
+import asyncio
+
+async def main():
+    result = await workflow.astart("input")
+    print(result)
+
+asyncio.run(main())
+
+# 8. STATUS TRACKING
+workflow.status  # "not_started" | "running" | "completed"
+workflow.step_statuses  # {"step1": "completed", "step2": "skipped"}
+
+# 9. MEMORY CONFIG
+workflow = Workflow(
+    steps=[researcher, writer],
+    memory_config={"provider": "chroma", "persist": True, "collection": "my_workflow"}
 )
+result1 = workflow.start("Research AI")
+result2 = workflow.start("Continue the research")  # Remembers first run
+```
+
+### YAML Workflow Template
+
+```yaml
+# .praison/workflows/research.yaml
+name: Research Workflow
+description: Research and write content with all patterns
+
+agents:
+  researcher:
+    role: Research Expert
+    goal: Find accurate information
+    tools: [tavily_search, web_scraper]
+  writer:
+    role: Content Writer
+    goal: Write engaging content
+  editor:
+    role: Editor
+    goal: Polish content
+
+steps:
+  # Sequential
+  - agent: researcher
+    action: Research {{topic}}
+    output_variable: research_data
+
+  # Routing
+  - name: classifier
+    action: Classify content type
+    route:
+      technical: [tech_handler]
+      creative: [creative_handler]
+      default: [general_handler]
+
+  # Parallel
+  - name: parallel_research
+    parallel:
+      - agent: researcher
+        action: Research market
+      - agent: researcher
+        action: Research competitors
+
+  # Loop
+  - agent: writer
+    action: Write about {{item}}
+    loop_over: topics
+    loop_var: item
+
+  # Repeat (evaluator-optimizer)
+  - agent: editor
+    action: Review and improve
+    repeat:
+      until: "quality > 8"
+      max_iterations: 3
+
+  # Output to file
+  - agent: writer
+    action: Write final report
+    output_file: output/{{topic}}_report.md
+
+variables:
+  topic: AI trends
+  topics: [ML, NLP, Vision]
+
+planning: true
+planning_llm: gpt-4o
+memory_config:
+  provider: chroma
+  persist: true
 ```
 
 ### 9. Hooks
@@ -733,6 +875,12 @@ praisonai workflow run deploy --workflow-var environment=staging --workflow-var
 # Execute with planning mode (AI creates sub-steps for each workflow step)
 praisonai workflow run "Research Blog" --planning --verbose
 
+# Execute with reasoning mode (chain-of-thought)
+praisonai workflow run "Analysis" --reasoning --verbose
+
+# Execute with memory enabled
+praisonai workflow run "Research" --memory
+
 # Show workflow details
 praisonai workflow show deploy
 
@@ -744,8 +892,23 @@ praisonai "What is AI?" --workflow "Research,Summarize" --save
 
 # Inline workflow with step actions
 praisonai "GPT-5" --workflow "Research:Search for info,Write:Write blog" --tools tavily
+
+# Workflow CLI help
+praisonai workflow help
 ```
 
+**Workflow CLI Options:**
+| Flag | Description |
+|------|-------------|
+| `--workflow-var key=value` | Set workflow variable (can be repeated) |
+| `--llm <model>` | LLM model (e.g., openai/gpt-4o-mini) |
+| `--tools <tools>` | Tools (comma-separated, e.g., tavily) |
+| `--planning` | Enable planning mode |
+| `--reasoning` | Enable reasoning mode |
+| `--memory` | Enable memory |
+| `--verbose` | Enable verbose output |
+| `--save` | Save output to file |
+
 ### Hooks CLI:
 ```bash
 # List configured hooks

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/v2.3.20.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.20.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.25.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.25.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==2.3.20 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.3.25 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
             

src/praisonai/praisonai/version.py

@@ -1 +1 @@
-__version__ = "2.3.20"
+__version__ = "2.3.25"

src/praisonai/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.0.198",
+    "praisonaiagents>=0.1.3",
     "python-dotenv>=0.19.0",
     "instructor>=1.3.3",
     "PyYAML>=6.0",

src/praisonai/uv.lock

@@ -4197,7 +4197,7 @@ requires-dist = [
     { name = "praisonai-tools", marker = "extra == 'autogen'", specifier = ">=0.0.22" },
     { name = "praisonai-tools", marker = "extra == 'autogen-v4'", specifier = ">=0.0.22" },
     { name = "praisonai-tools", marker = "extra == 'crewai'", specifier = ">=0.0.22" },
-    { name = "praisonaiagents", specifier = ">=0.0.198" },
+    { name = "praisonaiagents", specifier = ">=0.1.3" },
     { name = "pyautogen", marker = "extra == 'autogen'", specifier = "==0.2.29" },
     { name = "pydantic", marker = "extra == 'chat'", specifier = "<=2.10.1" },
     { name = "pydantic", marker = "extra == 'code'", specifier = "<=2.10.1" },
@@ -4252,7 +4252,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.0.198"
+version = "0.1.3"
 source = { registry = "https://pypi.org/simple" }
 dependencies = [
     { name = "aiohttp" },
@@ -4261,9 +4261,9 @@ dependencies = [
     { name = "pydantic" },
     { name = "rich" },
 ]
-sdist = { url = "https://files.pythonhosted.org/packages/68/bb/a3daf58206327a4cc92abed7295b41c03f9c4a8f3411d9435c633eb45b7f/praisonaiagents-0.0.198.tar.gz", hash = "sha256:d02180d476dd3ea260ade633764f6f8831dddc550b17ffb21eed79809166d315", size = 523691, upload-time = "2025-12-16T23:46:10.247Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/6d/6d/4c350703c10a53c8efee4a3ba989916f9e802dcc142b1a7fef8b874a7a00/praisonaiagents-0.1.3.tar.gz", hash = "sha256:064abf379e5ed4535db7c32fbe4344cb7274ef23f91842de1b336b12143c418d", size = 551139, upload-time = "2025-12-17T08:14:38.557Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/0f/cf/704504b3f5f3c9fc5674a0514ebea294fd4ffe7d040aae86d8af91dc0446/praisonaiagents-0.0.198-py3-none-any.whl", hash = "sha256:9011703eca1474fbef0a7208e0f875f1b62ff19bfaf7806fa25ccf7afb5c65a0", size = 499909, upload-time = "2025-12-16T23:46:08.677Z" },
+    { url = "https://files.pythonhosted.org/packages/15/ba/fd74ac9f0fef8e05c9665faf541898cc8d015e857fd8524501409453d592/praisonaiagents-0.1.3-py3-none-any.whl", hash = "sha256:37e7320cbd304bc901cd32abb7184ffecc9ddf5526c25204c47097f391954334", size = 518808, upload-time = "2025-12-17T08:14:36.864Z" },
 ]
 
 [[package]]