Release v4.6.56

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>=4.6.55" \
+    "praisonai>=4.6.56" \
     "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>=4.6.55" \
+    "praisonai>=4.6.56" \
     "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>=4.6.55" \
+    "praisonai>=4.6.56" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

examples/consolidated_params/advanced_workflow_full_features.py

@@ -32,7 +32,7 @@ workflow = AgentFlow(
         ),
     ],
     # Workflow-level consolidated params
-    output=WorkflowOutputConfig(output="verbose", stream=True),
+    output=WorkflowOutputConfig(verbose=True, stream=True),
     planning=WorkflowPlanningConfig(enabled=True, reasoning=True),
     memory=WorkflowMemoryConfig(backend="file"),
     # Agent-like params

examples/consolidated_params/basic_web.py

@@ -5,12 +5,12 @@ Demonstrates web search with consolidated params.
 Presets: duckduckgo, tavily, google, bing, serper, search_only, fetch_only
 """
 
-from praisonaiagents import Agent
+from praisonaiagents import Agent, WebConfig
 
-# Basic: Enable web search with preset
+# Basic: Enable web search with preset (search only — fetch needs Claude)
 agent = Agent(
     instructions="You are a research assistant with web access.",
-    web="duckduckgo",  # Presets: duckduckgo, tavily, google, bing, serper
+    web=WebConfig(search=True, fetch=False, search_provider="duckduckgo"),
 )
 
 if __name__ == "__main__":

examples/python/agents/code-agent.py

@@ -6,10 +6,18 @@ It includes self-reflection for improving code quality and multiple specialized
 """
 
 from praisonaiagents import Agent, Task, AgentTeam
-from praisonaiagents.tools import CodeInterpreter
 
-# Initialize code execution tool
-code_interpreter = CodeInterpreter()
+def run_python_code(code: str) -> str:
+    """Execute Python code safely and return stdout or errors."""
+    import io
+    import contextlib
+    try:
+        buf = io.StringIO()
+        with contextlib.redirect_stdout(buf):
+            exec(code, {"__builtins__": __builtins__})
+        return buf.getvalue() or "Executed successfully (no output)"
+    except Exception as e:
+        return f"Execution error: {e}"
 
 # Custom code analysis tool
 def analyze_code_complexity(code: str) -> str:
@@ -32,9 +40,7 @@ code_writer = Agent(
     goal="Write clean, efficient, and well-documented Python code",
     backstory="You are a senior Python developer with 10+ years of experience in writing production-quality code.",
     instructions="Write Python code that follows PEP 8 standards, includes proper error handling, and has clear documentation.",
-    reflection=True,
-    
-    
+    output="silent",
 )
 
 code_reviewer = Agent(
@@ -52,7 +58,7 @@ code_executor = Agent(
     goal="Safely execute and test Python code",
     backstory="You are responsible for running code and reporting results or errors.",
     instructions="Execute the provided code safely and report the output or any errors encountered.",
-    tools=[code_interpreter]
+    tools=[run_python_code]
 )
 
 # Example tasks
@@ -87,7 +93,7 @@ def demonstrate_code_agent():
     workflow = AgentTeam(
         agents=[code_writer, code_reviewer, code_executor],
         tasks=[write_task, review_task, execute_task],
-        process="sequential", output="verbose"
+        process="sequential", output="silent"
     )
     
     # Run the workflow
@@ -106,10 +112,8 @@ general_code_agent = Agent(
 3. Explain code concepts
 4. Refactor code for better performance
 5. Add tests and documentation""",
-    tools=[code_interpreter, analyze_code_complexity],
-    reflection=True,
-    
-    
+    tools=[run_python_code, analyze_code_complexity],
+    output="silent",
 )
 
 if __name__ == "__main__":

examples/python/agents/math-agent.py

@@ -41,21 +41,25 @@ def calculate_statistics(numbers: list) -> str:
     """Calculate basic statistics for a list of numbers."""
     if not numbers:
         return "No numbers provided"
-    
-    n = len(numbers)
-    mean = sum(numbers) / n
-    sorted_nums = sorted(numbers)
+    try:
+        nums = [float(x) for x in numbers]
+    except (TypeError, ValueError):
+        return "Error: all values must be numbers"
+
+    n = len(nums)
+    mean = sum(nums) / n
+    sorted_nums = sorted(nums)
     median = sorted_nums[n//2] if n % 2 else (sorted_nums[n//2-1] + sorted_nums[n//2]) / 2
-    variance = sum((x - mean)**2 for x in numbers) / n
+    variance = sum((x - mean)**2 for x in nums) / n
     std_dev = math.sqrt(variance)
-    
+
     return f"""Statistics:
 - Count: {n}
 - Mean: {mean:.4f}
 - Median: {median:.4f}
 - Standard Deviation: {std_dev:.4f}
-- Min: {min(numbers)}
-- Max: {max(numbers)}"""
+- Min: {min(nums)}
+- Max: {max(nums)}"""
 
 # Create specialized math agents
 calculation_agent = Agent(
@@ -66,8 +70,7 @@ calculation_agent = Agent(
     instructions="Perform the requested calculations step by step, showing your work clearly.",
     tools=[basic_calculator, solve_quadratic, calculate_statistics],
     reflection=True,
-    
-    
+    output="silent",
 )
 
 problem_solver_agent = Agent(
@@ -82,8 +85,7 @@ problem_solver_agent = Agent(
 4. Show each step of the solution
 5. Verify the answer makes sense""",
     reflection=True,
-    
-    
+    output="silent",
 )
 
 math_tutor_agent = Agent(
@@ -91,7 +93,8 @@ math_tutor_agent = Agent(
     role="Mathematics tutor and explainer",
     goal="Explain mathematical concepts clearly and help users understand math",
     backstory="You are a patient math tutor who can explain concepts at any level from elementary to advanced.",
-    instructions="Explain mathematical concepts using simple language, provide examples, and check for understanding."
+    instructions="Explain mathematical concepts using simple language, provide examples, and check for understanding.",
+    output="silent",
 )
 
 # Example workflow for solving complex problems
@@ -126,7 +129,8 @@ def solve_math_problem_workflow():
     workflow = AgentTeam(
         agents=[problem_solver_agent, calculation_agent, math_tutor_agent],
         tasks=[understand_task, solve_task, verify_task],
-        process="sequential", output="verbose"
+        process="sequential",
+        output="silent",
     )
     
     return workflow.start()
@@ -148,8 +152,7 @@ math_assistant = Agent(
 Always show your work step by step.""",
     tools=[basic_calculator, solve_quadratic, calculate_statistics],
     reflection=True,
-    
-    
+    output="silent",
 )
 
 if __name__ == "__main__":

examples/python/workflows/workflow_branching.py

@@ -6,7 +6,6 @@ to different next steps based on output content.
 """
 
 from praisonaiagents import AgentFlow, Task
-from praisonaiagents import AgentFlowManager
 
 # Create a workflow with branching
 workflow = AgentFlow(
@@ -36,16 +35,9 @@ workflow = AgentFlow(
 )
 
 if __name__ == "__main__":
-    # Create manager and register workflow
-    manager = WorkflowManager()
-    manager.workflows["Decision Workflow"] = workflow
-    
-    # Execute - will branch to success_handler since 42 is positive
-    result = manager.execute(
-        "Decision Workflow",
-        default_llm="gpt-4o-mini"
-    )
-    
+    result = workflow.run("", llm="gpt-4o-mini", verbose=True)
     print("Workflow completed!")
-    for step_result in result["results"]:
-        print(f"  {step_result['step']}: {step_result['status']}")
+    for step in result.get("steps", []):
+        name = step.get("step", step.get("name", "unknown"))
+        status = step.get("status", "completed")
+        print(f"  {name}: {status}")

examples/python/workflows/workflow_early_stop.py

@@ -6,9 +6,8 @@ functions that return StepResult with stop_workflow=True.
 """
 
 from praisonaiagents import (
-    Workflow, Task, WorkflowContext, StepResult
+    AgentFlow, Task, WorkflowContext, StepResult
 )
-from praisonaiagents import AgentFlowManager
 
 # Custom validator that can stop the workflow
 def validate_data(context: WorkflowContext) -> StepResult:
@@ -50,20 +49,13 @@ workflow = AgentFlow(
 )
 
 if __name__ == "__main__":
-    manager = WorkflowManager()
-    manager.workflows["Data Processing"] = workflow
-    
-    # Test with invalid data (will stop early)
     print("=== Testing with invalid data ===")
-    result = manager.execute("Data Processing", default_llm="gpt-4o-mini")
-    
-    for step_result in result["results"]:
-        print(f"  {step_result['step']}: {step_result['output']}")
-    
-    # Test with valid data (will complete)
+    result = workflow.run("", llm="gpt-4o-mini", verbose=True)
+    for step in result.get("steps", []):
+        print(f"  {step.get('step', 'step')}: {step.get('output', step.get('status'))}")
+
     print("\n=== Testing with valid data ===")
     workflow.variables["data"] = {"value": 42}
-    result = manager.execute("Data Processing", default_llm="gpt-4o-mini")
-    
-    for step_result in result["results"]:
-        print(f"  {step_result['step']}: {step_result['status']}")
+    result = workflow.run("", llm="gpt-4o-mini", verbose=True)
+    for step in result.get("steps", []):
+        print(f"  {step.get('step', 'step')}: {step.get('status', 'completed')}")

examples/python/workflows/workflow_loops.py

@@ -6,7 +6,6 @@ Each item is processed individually with the loop variable.
 """
 
 from praisonaiagents import AgentFlow, Task
-from praisonaiagents import AgentFlowManager
 
 # Create a workflow with loop
 workflow = AgentFlow(
@@ -30,18 +29,12 @@ workflow = AgentFlow(
 )
 
 if __name__ == "__main__":
-    # Create manager and register workflow
-    manager = WorkflowManager()
-    manager.workflows["Process Items"] = workflow
-    
-    # Execute - will process each fruit in the list
-    result = manager.execute(
-        "Process Items",
-        default_llm="gpt-4o-mini"
-    )
-    
+    result = workflow.run("", llm="gpt-4o-mini", verbose=True)
     print("Workflow completed!")
-    for step_result in result["results"]:
-        print(f"  {step_result['step']}: {step_result['status']}")
-        if isinstance(step_result.get("output"), list):
-            print(f"    Loop processed {len(step_result['output'])} items")
+    for step in result.get("steps", []):
+        name = step.get("step", step.get("name", "unknown"))
+        status = step.get("status", "completed")
+        print(f"  {name}: {status}")
+        out = step.get("output")
+        if isinstance(out, list):
+            print(f"    Loop processed {len(out)} items")

examples/python/workflows/workflow_mixed_steps.py

@@ -53,7 +53,7 @@ workflow = AgentFlow(
         # Step 4: Function - formats output
         format_output
     ],
-    default_llm="gpt-4o-mini"  # Used for action-based steps
+    llm="gpt-4o-mini"  # Used for action-based steps
 )
 
 if __name__ == "__main__":

examples/python/workflows/workflow_parallel.py

@@ -5,7 +5,7 @@ Demonstrates running multiple agents concurrently and
 combining their results with an aggregator agent.
 """
 
-from praisonaiagents import Agent, Workflow
+from praisonaiagents import Agent, AgentFlow
 from praisonaiagents.workflows import parallel
 
 # Create parallel research agents

examples/python/workflows/workflow_routing.py

@@ -5,7 +5,7 @@ Demonstrates decision-based routing where an agent classifier
 routes to specialized handler agents based on the request type.
 """
 
-from praisonaiagents import Agent, Workflow
+from praisonaiagents import Agent, AgentFlow
 from praisonaiagents.workflows import route
 
 # Create classifier agent

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "1.6.55"
+version = "1.6.56"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 readme = "README.md"
 requires-python = ">=3.10"

src/praisonai-agents/uv.lock

@@ -3125,7 +3125,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "1.6.55"
+version = "1.6.56"
 source = { editable = "." }
 dependencies = [
     { name = "aiohttp" },

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/v4.6.55.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.55.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.56.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v4.6.56.tar.gz | shasum -a 256`.split.first
     license "MIT"
   
     depends_on "[email protected]"

src/praisonai/praisonai/version.py

@@ -1 +1 @@
-__version__ = "4.6.55"
+__version__ = "4.6.56"

src/praisonai/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=1.6.55",
+    "praisonaiagents>=1.6.56",
     "python-dotenv>=0.19.0",
     "litellm>=1.83.14,<2",
     "PyYAML>=6.0",

src/praisonai/uv.lock

@@ -5491,7 +5491,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "1.6.55"
+version = "1.6.56"
 source = { directory = "../praisonai-agents" }
 dependencies = [
     { name = "aiohttp" },