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) |
@@ -103,20 +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`:

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>=2.3.23" \
+    "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>=2.3.23" \
+    "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>=2.3.23" \
+    "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>=2.3.23" \
+    "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'])}")

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

@@ -852,7 +852,14 @@ Create a brief execution plan (2-3 sentences) describing how to best accomplish
                 output = f"Error: {e}"
         elif normalized.agent:
             try:
-                output = normalized.agent.chat(normalized.action or input)
+                action = normalized.action or input
+                # Substitute variables
+                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)
+                output = normalized.agent.chat(action)
             except Exception as e:
                 output = f"Error: {e}"
         elif normalized.action:

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.1.1"
+version = "0.1.3"
 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

@@ -1381,6 +1381,106 @@ class TestMigratedFeatures:
         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
 # =============================================================================

src/praisonai-agents/uv.lock

@@ -2422,7 +2422,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.1.1"
+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) |
@@ -103,20 +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`:

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/v2.3.23.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.3.23.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==2.3.23 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__ = "2.3.23"
+__version__ = "2.3.25"

src/praisonai/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.1.1",
+    "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 = ">=0.1.1" },
+    { 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 = "0.1.1"
+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/b0/41/14a8e49c644c26ee565511776c67cc978427f36aec68a1442ac666c35401/praisonaiagents-0.1.1.tar.gz", hash = "sha256:76f69188e4893b0e868f33ea02d26cccfa90b99d679c2db4185d8cf624fa740e", size = 550745, upload-time = "2025-12-17T00:37:35.974Z" }
+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/f7/93/2cef070fae77bbef32a986ad7e1787f799442047f5dac831b9c137839353/praisonaiagents-0.1.1-py3-none-any.whl", hash = "sha256:c116551a35df0f8766496ba5102c54633f071735eae2a71b33eb4df5e2728e86", size = 518796, upload-time = "2025-12-17T00:37:33.824Z" },
+    { 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]]