Release v2.3.24

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) |
@@ -103,20 +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/workflow-routing) |
-| ⚡ Parallel Execution | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/workflow-parallel) |
-| 🔁 Loop over List | [Example](examples/python/workflows/workflow_loop_list.py) | [📖](https://docs.praison.ai/features/workflow-loop) |
-| 📄 Loop over CSV | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/workflow-loop) |
-| 🔄 Evaluator-Optimizer | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/workflow-repeat) |
 
 ## Supported Providers
 
@@ -467,8 +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 |
 
@@ -580,6 +576,162 @@ workflow = Workflow(steps=[
 ])
 ```
 
+### Workflow with Agents
+
+Use Agent objects directly as workflow steps:
+
+```python
+from praisonaiagents import Agent, Workflow
+from praisonaiagents.workflows import route, parallel
+
+# 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
+)
+
+# 5. TOOLS PER STEP
+workflow = Workflow(steps=[
+    WorkflowStep(
+        name="research",
+        action="Research {{topic}}",
+        tools=[tavily_search, web_scraper],
+        agent_config={"name": "Researcher", "role": "Expert"}
+    )
+])
+
+# 6. OUTPUT TO FILE / IMAGES / PYDANTIC
+from pydantic import BaseModel
+
+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
 
 Configure in `.praison/hooks.json`:
@@ -723,6 +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
 
@@ -734,8 +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>=2.3.22" \
+    "praisonai>=2.3.24" \
     "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>=2.3.22" \
+    "praisonai>=2.3.24" \
     "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>=2.3.22" \
+    "praisonai>=2.3.24" \
     "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>=2.3.22" \
+    "praisonai>=2.3.24" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

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

@@ -213,6 +213,19 @@ class WorkflowStep:
     # Guardrail (like process="workflow")
     guardrail: Optional[Callable[['StepResult'], Tuple[bool, Any]]] = None  # Returns (is_valid, feedback)
     
+    # Output configuration (migrated from Task)
+    output_file: Optional[str] = None  # Save output to file
+    output_json: Optional[Any] = None  # Pydantic model for JSON output
+    output_pydantic: Optional[Any] = None  # Pydantic model for structured output
+    
+    # Image handling (migrated from Task)
+    images: Optional[List[str]] = None  # Image paths/URLs for vision tasks
+    
+    # Execution control (migrated from Task)
+    async_execution: bool = False  # Run step asynchronously
+    quality_check: bool = True  # Enable quality validation
+    rerun: bool = True  # Allow step to be rerun
+    
     # Status tracking
     status: str = "pending"  # pending, running, completed, failed, skipped
     retry_count: int = 0
@@ -245,7 +258,14 @@ class WorkflowStep:
             "next_steps": self.next_steps,
             "branch_condition": self.branch_condition,
             "loop_over": self.loop_over,
-            "loop_var": self.loop_var
+            "loop_var": self.loop_var,
+            "output_file": self.output_file,
+            "output_json": self.output_json is not None,
+            "output_pydantic": self.output_pydantic is not None,
+            "images": self.images,
+            "async_execution": self.async_execution,
+            "quality_check": self.quality_check,
+            "rerun": self.rerun
         }
 
 
@@ -264,6 +284,8 @@ class Workflow:
     memory_config: Optional[Dict[str, Any]] = None  # Memory configuration
     planning: bool = False  # Enable planning mode
     planning_llm: Optional[str] = None  # LLM for planning
+    reasoning: bool = False  # Enable chain-of-thought reasoning
+    verbose: bool = False  # Enable verbose output
     
     # Callbacks (like process="workflow")
     on_workflow_start: Optional[Callable[['Workflow', str], None]] = None  # (workflow, input)
@@ -325,6 +347,9 @@ class Workflow:
         # Use default LLM if not specified
         model = llm or self.default_llm or "gpt-4o-mini"
         
+        # Use workflow verbose setting if not overridden
+        verbose = verbose or self.verbose
+        
         # Add input to variables
         all_variables = {**self.variables, "input": input}
         
@@ -341,6 +366,13 @@ class Workflow:
             except Exception as e:
                 logger.error(f"on_workflow_start callback failed: {e}")
         
+        # Planning mode - create execution plan before running
+        if self.planning:
+            plan = self._create_plan(input, model, verbose)
+            if plan and verbose:
+                print(f"📋 Execution Plan: {plan}")
+            all_variables["execution_plan"] = plan
+        
         # Process steps (may include Route, Parallel, Loop, Repeat)
         i = 0
         while i < len(self.steps):
@@ -456,19 +488,57 @@ class Workflow:
                             output = str(result)
                             
                     elif step.agent:
-                        # Direct agent
-                        output = step.agent.chat(step.action or input)
+                        # Direct agent with tools
+                        # Substitute variables in action
+                        action = step.action or input
+                        for key, value in all_variables.items():
+                            action = action.replace(f"{{{{{key}}}}}", str(value))
+                        if previous_output:
+                            action = action.replace("{{previous_output}}", str(previous_output))
+                        action = action.replace("{{input}}", input)
+                        
+                        # Add reasoning prompt if enabled
+                        if self.reasoning:
+                            action = f"Think step by step and reason through this task:\n\n{action}"
+                        
+                        # Add validation feedback if retrying
+                        if validation_feedback:
+                            action = f"{action}\n\nPrevious attempt feedback: {validation_feedback}"
+                        
+                        # Handle images if present
+                        step_images = getattr(step, 'images', None)
+                        if step_images:
+                            output = step.agent.chat(action, images=step_images)
+                        else:
+                            output = step.agent.chat(action)
+                        
+                        # Handle output_pydantic if present
+                        output_pydantic = getattr(step, 'output_pydantic', None)
+                        if output_pydantic and output:
+                            try:
+                                # Try to parse output as Pydantic model
+                                if hasattr(output_pydantic, 'model_validate_json'):
+                                    parsed = output_pydantic.model_validate_json(output)
+                                    output = parsed.model_dump_json()
+                            except Exception as e:
+                                logger.debug(f"Pydantic parsing failed: {e}")
                             
                     elif step.action:
                         # Action with agent_config - create temporary agent
                         from ..agent.agent import Agent
                         config = step.agent_config or self.default_agent_config or {}
+                        
+                        # Get tools from step or config
+                        step_tools = step.tools or config.get("tools", [])
+                        
                         temp_agent = Agent(
                             name=config.get("name", step.name),
                             role=config.get("role", "Assistant"),
                             goal=config.get("goal", "Complete the task"),
                             llm=config.get("llm", model),
-                            verbose=verbose
+                            tools=step_tools if step_tools else None,
+                            verbose=verbose,
+                            reasoning=self.reasoning
                         )
                         # Substitute variables in action
                         action = step.action
@@ -476,6 +546,12 @@ class Workflow:
                             action = action.replace(f"{{{{{key}}}}}", str(value))
                         if previous_output:
                             action = action.replace("{{previous_output}}", str(previous_output))
+                        action = action.replace("{{input}}", input)
+                        
+                        # Add reasoning prompt if enabled
+                        if self.reasoning:
+                            action = f"Think step by step and reason through this task:\n\n{action}"
+                        
                         if validation_feedback:
                             action = f"{action}\n\nPrevious attempt feedback: {validation_feedback}"
                         output = temp_agent.chat(action)
@@ -526,6 +602,23 @@ class Workflow:
                 except Exception as e:
                     logger.error(f"on_step_complete callback failed: {e}")
             
+            # Handle output_file - save output to file
+            if hasattr(step, 'output_file') and step.output_file and output:
+                try:
+                    import os
+                    output_path = step.output_file
+                    # Substitute variables in path
+                    for key, value in all_variables.items():
+                        output_path = output_path.replace(f"{{{{{key}}}}}", str(value))
+                    # Create directory if needed
+                    os.makedirs(os.path.dirname(output_path) if os.path.dirname(output_path) else ".", exist_ok=True)
+                    with open(output_path, "w") as f:
+                        f.write(str(output))
+                    if verbose:
+                        print(f"📁 Saved output to: {output_path}")
+                except Exception as e:
+                    logger.error(f"Failed to save output to file: {e}")
+            
             # Store result
             results.append({
                 "step": step.name,
@@ -569,6 +662,41 @@ class Workflow:
         
         return final_result
     
+    async def astart(
+        self,
+        input: str = "",
+        llm: Optional[str] = None,
+        verbose: bool = False
+    ) -> Dict[str, Any]:
+        """Async version of start() for async workflow execution.
+        
+        Args:
+            input: The input text/prompt for the workflow
+            llm: LLM model to use (default: gpt-4o-mini)
+            verbose: Print step outputs
+            
+        Returns:
+            Dict with 'output' (final result) and 'steps' (all step results)
+        """
+        import asyncio
+        
+        # Run the synchronous version in a thread pool
+        loop = asyncio.get_event_loop()
+        result = await loop.run_in_executor(
+            None,
+            lambda: self.run(input, llm, verbose)
+        )
+        return result
+    
+    async def arun(
+        self,
+        input: str = "",
+        llm: Optional[str] = None,
+        verbose: bool = False
+    ) -> Dict[str, Any]:
+        """Alias for astart() for backward compatibility."""
+        return await self.astart(input, llm, verbose)
+    
     def _normalize_steps(self) -> List['WorkflowStep']:
         """Convert mixed steps (Agent, function, WorkflowStep) to WorkflowStep list."""
         normalized = []
@@ -598,21 +726,89 @@ class Workflow:
         
         return normalized
     
+    def _create_plan(self, input: str, model: str, verbose: bool) -> Optional[str]:
+        """Create an execution plan for the workflow using LLM.
+        
+        Args:
+            input: The workflow input
+            model: LLM model to use
+            verbose: Print verbose output
+            
+        Returns:
+            Execution plan as string, or None if planning fails
+        """
+        try:
+            from ..agent.agent import Agent
+            
+            # Describe the steps
+            step_descriptions = []
+            for i, step in enumerate(self.steps):
+                if isinstance(step, WorkflowStep):
+                    step_descriptions.append(f"{i+1}. {step.name}: {step.description or step.action or 'Execute step'}")
+                elif hasattr(step, 'name'):
+                    role = getattr(step, 'role', 'Agent')
+                    step_descriptions.append(f"{i+1}. {step.name} ({role})")
+                elif callable(step):
+                    step_descriptions.append(f"{i+1}. {getattr(step, '__name__', 'function')}")
+                elif isinstance(step, (Route, Parallel, Loop, Repeat)):
+                    step_descriptions.append(f"{i+1}. {type(step).__name__} pattern")
+                else:
+                    step_descriptions.append(f"{i+1}. Step {i+1}")
+            
+            steps_text = "\n".join(step_descriptions)
+            
+            planning_prompt = f"""You are a workflow planner. Given the following workflow steps and input, create a brief execution plan.
+
+Workflow: {self.name}
+Description: {self.description}
+
+Steps:
+{steps_text}
+
+Input: {input}
+
+Create a brief execution plan (2-3 sentences) describing how to best accomplish this task using the available steps. Focus on the key objectives and any important considerations."""
+
+            planner = Agent(
+                name="Planner",
+                role="Workflow Planner",
+                goal="Create efficient execution plans",
+                llm=self.planning_llm or model,
+                verbose=False
+            )
+            
+            plan = planner.chat(planning_prompt)
+            return plan
+            
+        except Exception as e:
+            logger.error(f"Planning failed: {e}")
+            return None
+    
     def _normalize_single_step(self, step: Any, index: int) -> 'WorkflowStep':
-        """Normalize a single step to WorkflowStep."""
+        """Normalize a single step to WorkflowStep.
+        
+        Supports:
+        - WorkflowStep objects (passed through)
+        - Agent objects (wrapped with agent reference and tools)
+        - Callable functions (wrapped as handler)
+        - Strings (used as action)
+        """
         if isinstance(step, WorkflowStep):
             return step
+        elif hasattr(step, 'chat'):
+            # It's an Agent - wrap with agent reference and preserve tools
+            agent_tools = getattr(step, 'tools', None)
+            return WorkflowStep(
+                name=getattr(step, 'name', f'agent_{index+1}'),
+                agent=step,
+                tools=agent_tools,
+                action="{{previous_output}}" if index > 0 else "{{input}}"
+            )
         elif callable(step):
             return WorkflowStep(
                 name=getattr(step, '__name__', f'step_{index+1}'),
                 handler=step
             )
-        elif hasattr(step, 'chat'):
-            return WorkflowStep(
-                name=getattr(step, 'name', f'agent_{index+1}'),
-                agent=step,
-                action="{{input}}"
-            )
         else:
             return WorkflowStep(
                 name=f'step_{index+1}',
@@ -1031,6 +1227,13 @@ class WorkflowManager:
         loop_var_pattern = re.compile(r'loop_var:\s*(\w+)', re.IGNORECASE)
         branch_pattern = re.compile(r'```branch\s*\n(.*?)\n```', re.DOTALL)
         
+        # New patterns for route, parallel, images, output_file
+        route_pattern = re.compile(r'```route\s*\n(.*?)\n```', re.DOTALL)
+        parallel_pattern = re.compile(r'```parallel\s*\n(.*?)\n```', re.DOTALL)
+        images_pattern = re.compile(r'```images\s*\n(.*?)\n```', re.DOTALL)
+        output_file_pattern = re.compile(r'output_file:\s*(.+)', re.IGNORECASE)
+        repeat_pattern = re.compile(r'```repeat\s*\n(.*?)\n```', re.DOTALL)
+        
         # Find all step headers
         matches = list(step_pattern.finditer(body))
         
@@ -1106,6 +1309,41 @@ class WorkflowManager:
             if loop_var_match:
                 loop_var = loop_var_match.group(1)
             
+            # Extract route pattern (same as branch_condition)
+            route_match = route_pattern.search(step_content)
+            if route_match and not branch_condition:
+                branch_condition = self._parse_branch_condition(route_match.group(1).strip())
+            
+            # Extract parallel pattern
+            parallel_steps = None
+            parallel_match = parallel_pattern.search(step_content)
+            if parallel_match:
+                parallel_str = parallel_match.group(1).strip()
+                # Parse as list of step names
+                parallel_steps = [s.strip().lstrip('- ').strip('"\'') for s in parallel_str.split('\n') if s.strip()]
+                # Set next_steps to parallel steps if not already set
+                if not next_steps:
+                    next_steps = parallel_steps
+            
+            # Extract images
+            images = None
+            images_match = images_pattern.search(step_content)
+            if images_match:
+                images_str = images_match.group(1).strip()
+                images = [s.strip() for s in images_str.split('\n') if s.strip()]
+            
+            # Extract output_file
+            output_file = None
+            output_file_match = output_file_pattern.search(step_content)
+            if output_file_match:
+                output_file = output_file_match.group(1).strip()
+            
+            # Extract repeat config
+            repeat_config = None
+            repeat_match = repeat_pattern.search(step_content)
+            if repeat_match:
+                repeat_config = self._parse_agent_config(repeat_match.group(1).strip())
+            
             # Get description (text before action block)
             description = step_content
             if action_match:
@@ -1119,8 +1357,14 @@ class WorkflowManager:
             description = re.sub(r'next_steps:.*', '', description)
             description = re.sub(r'loop_over:.*', '', description)
             description = re.sub(r'loop_var:.*', '', description)
+            description = re.sub(r'output_file:.*', '', description)
             description = description.strip()
             
+            # Set max_retries from repeat config
+            max_retries = 3
+            if repeat_config and 'max_iterations' in repeat_config:
+                max_retries = int(repeat_config['max_iterations'])
+            
             steps.append(WorkflowStep(
                 name=step_name,
                 description=description,
@@ -1134,7 +1378,10 @@ class WorkflowManager:
                 next_steps=next_steps,
                 branch_condition=branch_condition,
                 loop_over=loop_over,
-                loop_var=loop_var
+                loop_var=loop_var,
+                output_file=output_file,
+                images=images,
+                max_retries=max_retries
             ))
         
         return steps

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.1.0"
+version = "0.1.2"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [

src/praisonai-agents/tests/test_workflow_patterns.py

@@ -1017,6 +1017,767 @@ class TestDocumentationExamples:
         assert attempts[0] == 2  # First attempt + 1 retry
 
 
+# =============================================================================
+# Test: Agent Integration in Workflows
+# =============================================================================
+
+class TestAgentWorkflows:
+    """Test Agent objects as workflow steps."""
+    
+    def test_agent_normalization(self):
+        """Test that Agent objects are properly normalized to WorkflowStep."""
+        # Create a mock agent
+        class MockAgent:
+            def __init__(self, name, tools=None):
+                self.name = name
+                self.tools = tools or []
+            
+            def chat(self, message):
+                return f"Response from {self.name}: {message}"
+        
+        agent = MockAgent("TestAgent", tools=["tool1", "tool2"])
+        
+        workflow = Workflow(steps=[agent])
+        
+        # Normalize and check
+        normalized = workflow._normalize_single_step(agent, 0)
+        assert normalized.name == "TestAgent"
+        assert normalized.agent == agent
+        assert normalized.tools == ["tool1", "tool2"]
+    
+    def test_workflow_with_mock_agent(self):
+        """Test workflow execution with mock agent."""
+        class MockAgent:
+            def __init__(self, name):
+                self.name = name
+            
+            def chat(self, message):
+                return f"Processed: {message}"
+        
+        agent = MockAgent("Processor")
+        
+        workflow = Workflow(steps=[agent])
+        result = workflow.start("Hello World")
+        
+        assert "Processed:" in result["output"]
+        assert "Hello World" in result["output"]
+    
+    def test_sequential_mock_agents(self):
+        """Test sequential execution of multiple mock agents."""
+        class MockAgent:
+            def __init__(self, name, prefix):
+                self.name = name
+                self.prefix = prefix
+            
+            def chat(self, message):
+                return f"{self.prefix}: {message}"
+        
+        agent1 = MockAgent("Agent1", "First")
+        agent2 = MockAgent("Agent2", "Second")
+        agent3 = MockAgent("Agent3", "Third")
+        
+        workflow = Workflow(steps=[agent1, agent2, agent3])
+        result = workflow.start("Input")
+        
+        # Final output should be from agent3
+        assert "Third:" in result["output"]
+        assert len(result["steps"]) == 3
+    
+    def test_parallel_mock_agents(self):
+        """Test parallel execution of mock agents."""
+        class MockAgent:
+            def __init__(self, name, output):
+                self.name = name
+                self.output = output
+            
+            def chat(self, message):
+                return self.output
+        
+        agent1 = MockAgent("Agent1", "Result A")
+        agent2 = MockAgent("Agent2", "Result B")
+        agent3 = MockAgent("Agent3", "Result C")
+        
+        def aggregator(ctx: WorkflowContext) -> StepResult:
+            outputs = ctx.variables.get("parallel_outputs", [])
+            return StepResult(output=f"Combined: {len(outputs)} results")
+        
+        workflow = Workflow(steps=[
+            parallel([agent1, agent2, agent3]),
+            aggregator
+        ])
+        
+        result = workflow.start("Test")
+        assert "Combined: 3 results" in result["output"]
+    
+    def test_route_to_mock_agents(self):
+        """Test routing to different mock agents."""
+        class MockAgent:
+            def __init__(self, name, output):
+                self.name = name
+                self.output = output
+            
+            def chat(self, message):
+                return self.output
+        
+        tech_agent = MockAgent("TechAgent", "Technical response")
+        creative_agent = MockAgent("CreativeAgent", "Creative response")
+        
+        def classifier(ctx: WorkflowContext) -> StepResult:
+            if "tech" in ctx.input.lower():
+                return StepResult(output="category: technical")
+            return StepResult(output="category: creative")
+        
+        workflow = Workflow(steps=[
+            classifier,
+            route({
+                "technical": [tech_agent],
+                "creative": [creative_agent]
+            })
+        ])
+        
+        # Test technical route
+        result = workflow.start("tech question")
+        assert "Technical response" in result["output"]
+        
+        # Test creative route
+        result = workflow.start("creative request")
+        assert "Creative response" in result["output"]
+    
+    def test_loop_with_mock_agent(self):
+        """Test loop pattern with mock agent."""
+        class MockAgent:
+            def __init__(self, name):
+                self.name = name
+            
+            def chat(self, message):
+                return f"Processed: {message}"
+        
+        processor = MockAgent("Processor")
+        
+        workflow = Workflow(
+            steps=[loop(processor, over="items")],
+            variables={"items": ["A", "B", "C"]}
+        )
+        
+        result = workflow.start("Process items")
+        outputs = result["variables"].get("loop_outputs", [])
+        assert len(outputs) == 3
+
+
+# =============================================================================
+# Test: Workflow Configuration
+# =============================================================================
+
+class TestWorkflowConfiguration:
+    """Test workflow configuration options."""
+    
+    def test_workflow_verbose_setting(self):
+        """Test that workflow verbose setting is used."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1], verbose=True)
+        assert workflow.verbose == True
+    
+    def test_workflow_reasoning_setting(self):
+        """Test that workflow reasoning setting is stored."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1], reasoning=True)
+        assert workflow.reasoning == True
+    
+    def test_workflow_planning_setting(self):
+        """Test that workflow planning setting is stored."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1], planning=True, planning_llm="gpt-4o")
+        assert workflow.planning == True
+        assert workflow.planning_llm == "gpt-4o"
+    
+    def test_workflow_default_llm(self):
+        """Test default LLM setting."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1], default_llm="gpt-4o-mini")
+        assert workflow.default_llm == "gpt-4o-mini"
+    
+    def test_workflow_default_agent_config(self):
+        """Test default agent config."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(
+            steps=[step1],
+            default_agent_config={
+                "name": "DefaultAgent",
+                "role": "Assistant",
+                "tools": ["tool1"]
+            }
+        )
+        assert workflow.default_agent_config["name"] == "DefaultAgent"
+        assert workflow.default_agent_config["tools"] == ["tool1"]
+
+
+# =============================================================================
+# Test: WorkflowStep with Tools
+# =============================================================================
+
+class TestWorkflowStepTools:
+    """Test WorkflowStep with tools configuration."""
+    
+    def test_step_with_tools(self):
+        """Test WorkflowStep with tools parameter."""
+        def my_tool(): return "tool result"
+        
+        step = WorkflowStep(
+            name="step_with_tools",
+            action="Do something",
+            tools=[my_tool]
+        )
+        
+        assert step.tools == [my_tool]
+    
+    def test_step_with_agent_config_tools(self):
+        """Test WorkflowStep with tools in agent_config."""
+        def my_tool(): return "tool result"
+        
+        step = WorkflowStep(
+            name="step_with_config",
+            action="Do something",
+            agent_config={
+                "name": "Agent",
+                "role": "Helper",
+                "tools": [my_tool]
+            }
+        )
+        
+        assert step.agent_config["tools"] == [my_tool]
+
+
+# =============================================================================
+# Test: Migrated Features (output_file, images, async, etc.)
+# =============================================================================
+
+class TestMigratedFeatures:
+    """Test features migrated from process='workflow'."""
+    
+    def test_step_output_file(self):
+        """Test WorkflowStep with output_file parameter."""
+        import tempfile
+        import os
+        
+        with tempfile.TemporaryDirectory() as tmpdir:
+            output_path = os.path.join(tmpdir, "output.txt")
+            
+            def generate_content(ctx: WorkflowContext) -> StepResult:
+                return StepResult(output="Generated content for file")
+            
+            workflow = Workflow(steps=[
+                WorkflowStep(
+                    name="generator",
+                    handler=generate_content,
+                    output_file=output_path
+                )
+            ])
+            
+            result = workflow.start("Generate content")
+            
+            # Check file was created
+            assert os.path.exists(output_path)
+            with open(output_path) as f:
+                content = f.read()
+            assert "Generated content" in content
+    
+    def test_step_images_parameter(self):
+        """Test WorkflowStep with images parameter."""
+        step = WorkflowStep(
+            name="vision_step",
+            action="Analyze this image",
+            images=["image1.jpg", "image2.png"]
+        )
+        
+        assert step.images == ["image1.jpg", "image2.png"]
+    
+    def test_step_output_pydantic_parameter(self):
+        """Test WorkflowStep with output_pydantic parameter."""
+        from pydantic import BaseModel
+        
+        class OutputModel(BaseModel):
+            title: str
+            content: str
+        
+        step = WorkflowStep(
+            name="structured_step",
+            action="Generate structured output",
+            output_pydantic=OutputModel
+        )
+        
+        assert step.output_pydantic == OutputModel
+    
+    def test_step_async_execution_parameter(self):
+        """Test WorkflowStep with async_execution parameter."""
+        step = WorkflowStep(
+            name="async_step",
+            action="Run async",
+            async_execution=True
+        )
+        
+        assert step.async_execution == True
+    
+    def test_step_quality_check_parameter(self):
+        """Test WorkflowStep with quality_check parameter."""
+        step = WorkflowStep(
+            name="quality_step",
+            action="Check quality",
+            quality_check=False
+        )
+        
+        assert step.quality_check == False
+    
+    def test_step_rerun_parameter(self):
+        """Test WorkflowStep with rerun parameter."""
+        step = WorkflowStep(
+            name="rerun_step",
+            action="Can rerun",
+            rerun=False
+        )
+        
+        assert step.rerun == False
+    
+    def test_workflow_astart_method_exists(self):
+        """Test that Workflow has astart method."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1])
+        
+        assert hasattr(workflow, 'astart')
+        assert callable(workflow.astart)
+    
+    def test_workflow_arun_method_exists(self):
+        """Test that Workflow has arun method."""
+        def step1(ctx): return StepResult(output="Done")
+        
+        workflow = Workflow(steps=[step1])
+        
+        assert hasattr(workflow, 'arun')
+        assert callable(workflow.arun)
+    
+    def test_step_to_dict_includes_new_fields(self):
+        """Test that to_dict includes all new fields."""
+        step = WorkflowStep(
+            name="test_step",
+            action="Test action",
+            output_file="output.txt",
+            images=["img.jpg"],
+            async_execution=True,
+            quality_check=False,
+            rerun=False
+        )
+        
+        d = step.to_dict()
+        
+        assert d["output_file"] == "output.txt"
+        assert d["images"] == ["img.jpg"]
+        assert d["async_execution"] == True
+        assert d["quality_check"] == False
+        assert d["rerun"] == False
+
+
+# =============================================================================
+# Test: Planning and Reasoning Modes
+# =============================================================================
+
+class TestPlanningAndReasoning:
+    """Test planning and reasoning modes in workflows."""
+    
+    def test_workflow_planning_parameter_exists(self):
+        """Test that Workflow accepts planning parameter."""
+        workflow = Workflow(
+            steps=[lambda ctx: StepResult(output="test")],
+            planning=True,
+            planning_llm="gpt-4o"
+        )
+        assert workflow.planning == True
+        assert workflow.planning_llm == "gpt-4o"
+    
+    def test_workflow_reasoning_parameter_exists(self):
+        """Test that Workflow accepts reasoning parameter."""
+        workflow = Workflow(
+            steps=[lambda ctx: StepResult(output="test")],
+            reasoning=True
+        )
+        assert workflow.reasoning == True
+    
+    def test_workflow_memory_config_parameter_exists(self):
+        """Test that Workflow accepts memory_config parameter."""
+        workflow = Workflow(
+            steps=[lambda ctx: StepResult(output="test")],
+            memory_config={"provider": "rag", "persist": True}
+        )
+        assert workflow.memory_config == {"provider": "rag", "persist": True}
+    
+    def test_workflow_verbose_parameter_exists(self):
+        """Test that Workflow accepts verbose parameter."""
+        workflow = Workflow(
+            steps=[lambda ctx: StepResult(output="test")],
+            verbose=True
+        )
+        assert workflow.verbose == True
+
+
+class TestToolsPerStep:
+    """Test tools per step functionality."""
+    
+    def test_step_with_tools_list(self):
+        """Test WorkflowStep with tools list."""
+        def my_tool():
+            return "tool result"
+        
+        step = WorkflowStep(
+            name="test",
+            action="Do something",
+            tools=[my_tool]
+        )
+        
+        assert step.tools == [my_tool]
+    
+    def test_step_with_agent_config_tools(self):
+        """Test WorkflowStep with tools in agent_config."""
+        def my_tool():
+            return "tool result"
+        
+        step = WorkflowStep(
+            name="test",
+            action="Do something",
+            agent_config={
+                "name": "TestAgent",
+                "role": "Tester",
+                "tools": [my_tool]
+            }
+        )
+        
+        assert step.agent_config["tools"] == [my_tool]
+    
+    def test_agent_with_tools_in_workflow(self):
+        """Test Agent with tools is properly handled in workflow."""
+        class MockAgent:
+            def __init__(self, name, tools=None):
+                self.name = name
+                self.tools = tools or []
+            
+            def chat(self, message):
+                return f"Response with {len(self.tools)} tools"
+        
+        def mock_tool():
+            return "tool result"
+        
+        agent = MockAgent("TestAgent", tools=[mock_tool])
+        workflow = Workflow(steps=[agent])
+        
+        # Normalize and verify tools are preserved
+        normalized = workflow._normalize_single_step(agent, 0)
+        assert normalized.tools == [mock_tool]
+        
+        # Execute and verify
+        result = workflow.start("test")
+        assert "1 tools" in result["output"]
+
+
+# =============================================================================
+# Test: WorkflowManager with Patterns in MD Files
+# =============================================================================
+
+class TestWorkflowManagerPatterns:
+    """Test WorkflowManager parsing of pattern syntax in markdown files."""
+    
+    def test_parse_route_pattern_in_md(self):
+        """Test parsing route pattern from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Route Test
+description: Test routing pattern
+---
+
+## Step 1: Classifier
+Classify the input.
+
+```action
+Classify this input as technical or creative
+```
+
+```route
+technical: [Tech Handler]
+creative: [Creative Handler]
+default: [General Handler]
+```
+
+## Step 2: Tech Handler
+Handle technical requests.
+
+```action
+Process technical request
+```
+
+## Step 3: Creative Handler
+Handle creative requests.
+
+```action
+Process creative request
+```
+
+## Step 4: General Handler
+Handle general requests.
+
+```action
+Process general request
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "route_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            assert workflow.name == "Route Test"
+            
+            # Check that route pattern is parsed
+            step1 = workflow.steps[0]
+            assert step1.name == "Classifier"
+            assert step1.branch_condition is not None
+            assert "technical" in step1.branch_condition
+    
+    def test_parse_parallel_pattern_in_md(self):
+        """Test parsing parallel pattern from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Parallel Test
+description: Test parallel pattern
+---
+
+## Step 1: Research
+Research in parallel.
+
+```parallel
+- Market Research
+- Competitor Analysis
+- Customer Survey
+```
+
+```action
+Research the topic
+```
+
+## Step 2: Market Research
+Research the market.
+
+```action
+Analyze market trends
+```
+
+## Step 3: Competitor Analysis
+Analyze competitors.
+
+```action
+Analyze competitors
+```
+
+## Step 4: Customer Survey
+Survey customers.
+
+```action
+Survey customers
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "parallel_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            assert workflow.name == "Parallel Test"
+            
+            # Check that parallel steps are parsed
+            step1 = workflow.steps[0]
+            assert step1.name == "Research"
+            assert hasattr(step1, 'parallel_steps') or step1.next_steps is not None
+    
+    def test_parse_loop_pattern_in_md(self):
+        """Test parsing loop pattern from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Loop Test
+description: Test loop pattern
+variables:
+  items: ["item1", "item2", "item3"]
+---
+
+## Step 1: Process Items
+Process each item in the list.
+
+loop_over: items
+loop_var: current_item
+
+```action
+Process {{current_item}}
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "loop_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            
+            step1 = workflow.steps[0]
+            assert step1.name == "Process Items"
+            assert step1.loop_over == "items"
+            assert step1.loop_var == "current_item"
+    
+    def test_parse_repeat_pattern_in_md(self):
+        """Test parsing repeat pattern from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Repeat Test
+description: Test repeat pattern
+---
+
+## Step 1: Generate
+Generate content repeatedly.
+
+```repeat
+max_iterations: 5
+until: count >= 10
+```
+
+```action
+Generate more content
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "repeat_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            
+            step1 = workflow.steps[0]
+            assert step1.name == "Generate"
+            # Check repeat config is parsed
+            assert hasattr(step1, 'max_retries') or hasattr(step1, 'repeat_config')
+    
+    def test_parse_output_file_in_md(self):
+        """Test parsing output_file from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Output Test
+description: Test output file
+---
+
+## Step 1: Generate Report
+Generate a report and save to file.
+
+output_file: output/report.txt
+
+```action
+Generate the report
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "output_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            
+            step1 = workflow.steps[0]
+            assert step1.name == "Generate Report"
+            assert step1.output_file == "output/report.txt"
+    
+    def test_parse_images_in_md(self):
+        """Test parsing images from markdown."""
+        import tempfile
+        import os
+        from praisonaiagents.workflows import WorkflowManager
+        
+        md_content = """---
+name: Vision Test
+description: Test image handling
+---
+
+## Step 1: Analyze Image
+Analyze the provided image.
+
+```images
+image1.jpg
+image2.png
+```
+
+```action
+Analyze these images
+```
+"""
+        with tempfile.TemporaryDirectory() as tmpdir:
+            workflows_dir = os.path.join(tmpdir, ".praison", "workflows")
+            os.makedirs(workflows_dir)
+            
+            with open(os.path.join(workflows_dir, "vision_test.md"), "w") as f:
+                f.write(md_content)
+            
+            manager = WorkflowManager(workspace_path=tmpdir)
+            workflows = manager.list_workflows()
+            
+            assert len(workflows) == 1
+            workflow = workflows[0]
+            
+            step1 = workflow.steps[0]
+            assert step1.name == "Analyze Image"
+            assert step1.images is not None
+            assert "image1.jpg" in step1.images
+
+
 # =============================================================================
 # Run Tests
 # =============================================================================

src/praisonai-agents/uv.lock

@@ -2422,7 +2422,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.1.0"
+version = "0.1.2"
 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) |
@@ -103,20 +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/workflow-routing) |
-| ⚡ Parallel Execution | [Example](examples/python/workflows/workflow_parallel.py) | [📖](https://docs.praison.ai/features/workflow-parallel) |
-| 🔁 Loop over List | [Example](examples/python/workflows/workflow_loop_list.py) | [📖](https://docs.praison.ai/features/workflow-loop) |
-| 📄 Loop over CSV | [Example](examples/python/workflows/workflow_loop_csv.py) | [📖](https://docs.praison.ai/features/workflow-loop) |
-| 🔄 Evaluator-Optimizer | [Example](examples/python/workflows/workflow_repeat.py) | [📖](https://docs.praison.ai/features/workflow-repeat) |
 
 ## Supported Providers
 
@@ -467,8 +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 |
 
@@ -580,6 +576,162 @@ workflow = Workflow(steps=[
 ])
 ```
 
+### Workflow with Agents
+
+Use Agent objects directly as workflow steps:
+
+```python
+from praisonaiagents import Agent, Workflow
+from praisonaiagents.workflows import route, parallel
+
+# 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
+)
+
+# 5. TOOLS PER STEP
+workflow = Workflow(steps=[
+    WorkflowStep(
+        name="research",
+        action="Research {{topic}}",
+        tools=[tavily_search, web_scraper],
+        agent_config={"name": "Researcher", "role": "Expert"}
+    )
+])
+
+# 6. OUTPUT TO FILE / IMAGES / PYDANTIC
+from pydantic import BaseModel
+
+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
 
 Configure in `.praison/hooks.json`:
@@ -723,6 +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
 
@@ -734,8 +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/v2.3.22.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.22.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.24.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.24.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==2.3.22 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.3.24 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__ = "2.3.22"
+__version__ = "2.3.24"

src/praisonai/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.1.0",
+    "praisonaiagents>=0.1.2",
     "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 = ">=0.1.0" },
+    { name = "praisonaiagents", specifier = ">=0.1.2" },
     { 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 = "0.1.0"
+version = "0.1.2"
 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/1a/69/062b8e0867ec673483d83a7529b15d17c15196460060cd7e1542f96c8036/praisonaiagents-0.1.0.tar.gz", hash = "sha256:9c87d8ef965997ab6df2f76badda7911889c6409333b8d2afa20a4f60c80fef9", size = 545876, upload-time = "2025-12-17T00:24:37.466Z" }
+sdist = { url = "https://files.pythonhosted.org/packages/e3/cd/e00b4dfc4127e2f51acc8c414a392ec45b5e80c45386f082efc31fe7af1b/praisonaiagents-0.1.2.tar.gz", hash = "sha256:e8f94748af81897cd73cee1e74d031296c2103c2c7b8911ee0618c5cfb2a8492", size = 551139, upload-time = "2025-12-17T07:43:27.008Z" }
 wheels = [
-    { url = "https://files.pythonhosted.org/packages/42/11/9f9a8802208e50a44d2e105c6b9743fa08f02378829fb5fad1b3ee9c8b8d/praisonaiagents-0.1.0-py3-none-any.whl", hash = "sha256:bb39f79e92b8a3abe215fcb8f49be896dee539a5e8998f55b14fb8bbbeb86905", size = 516692, upload-time = "2025-12-17T00:24:35.719Z" },
+    { url = "https://files.pythonhosted.org/packages/8c/1f/8a4e5097bee7e8031c2428cf8c1e47b06c85c5f4ce552231de3224d0c301/praisonaiagents-0.1.2-py3-none-any.whl", hash = "sha256:c5a1241da8feb32957b0820ffaa37b03e4ff45462d322fde4ff84f224f10eb91", size = 518797, upload-time = "2025-12-17T07:43:25.172Z" },
 ]
 
 [[package]]