Release v2.3.25

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>=2.3.24" \
+    "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>=2.3.24" \
+    "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>=2.3.24" \
+    "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>=2.3.24" \
+    "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 = "0.1.2"
+version = "0.1.3"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [

src/praisonai-agents/uv.lock

@@ -2422,7 +2422,7 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.1.2"
+version = "0.1.3"
 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/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
+    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==2.3.24 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__ = "2.3.24"
+__version__ = "2.3.25"

src/praisonai/pyproject.toml

@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.1.2",
+    "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 = ">=0.1.2" },
+    { 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 = "0.1.2"
+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/e3/cd/e00b4dfc4127e2f51acc8c414a392ec45b5e80c45386f082efc31fe7af1b/praisonaiagents-0.1.2.tar.gz", hash = "sha256:e8f94748af81897cd73cee1e74d031296c2103c2c7b8911ee0618c5cfb2a8492", size = 551139, upload-time = "2025-12-17T07:43:27.008Z" }
+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/8c/1f/8a4e5097bee7e8031c2428cf8c1e47b06c85c5f4ce552231de3224d0c301/praisonaiagents-0.1.2-py3-none-any.whl", hash = "sha256:c5a1241da8feb32957b0820ffaa37b03e4ff45462d322fde4ff84f224f10eb91", size = 518797, upload-time = "2025-12-17T07:43:25.172Z" },
+    { 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]]