Develop

.gitignore

@@ -74,4 +74,5 @@ agents/praisonaiagents/praisonaiagents.egg-info
 .praison
 # Local Netlify folder
 .netlify
-.qodo
+.qodo
+CopilotKit*

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>=2.2.28" \
+    "praisonai>=2.2.29" \
     "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>=2.2.28" \
+    "praisonai>=2.2.29" \
     "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>=2.2.28" \
+    "praisonai>=2.2.29" \
     "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>=2.2.28" \
+    "praisonai>=2.2.29" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

docker/README.md

@@ -121,7 +121,7 @@ healthcheck:
 ## 📦 Package Versions
 
 All Docker images use consistent, up-to-date versions:
-- PraisonAI: `>=2.2.28`
+- PraisonAI: `>=2.2.29`
 - PraisonAI Agents: `>=0.0.92`
 - Python: `3.11-slim`
 
@@ -218,7 +218,7 @@ docker-compose up -d
 ### Version Pinning
 To use specific versions, update the Dockerfile:
 ```dockerfile
-RUN pip install "praisonai==2.2.28" "praisonaiagents==0.0.92"
+RUN pip install "praisonai==2.2.29" "praisonaiagents==0.0.92"
 ```
 
 ## 🌐 Production Deployment

src/praisonai-agents/guardrail_agent_example.py

@@ -0,0 +1,14 @@
+from praisonaiagents import Agent
+
+def validate_content(data):
+    if len(str(data)) < 50:
+        return False, "Content too short"
+    return True, data
+
+agent = Agent(
+    instructions="You are a writer",
+    guardrail=validate_content,
+    max_guardrail_retries=1
+)
+
+agent.start("Write a welcome message with 5 words")

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

@@ -619,12 +619,9 @@ def _apply_guardrail_with_retry(self, response_text, prompt, temperature=0.2, to
         while retry_count <= self.max_guardrail_retries:
             # Create TaskOutput object
             task_output = TaskOutput(
+                description="Agent response output",
                 raw=current_response,
-                output=current_response,
-                pydantic=None,
-                json_dict=None,
-                name=f"{self.name}_output",
-                description="Agent response output"
+                agent=self.name
             )
 
             # Process guardrail

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

@@ -910,11 +910,14 @@ def calculate_quality_metrics(
         """
 
         try:
-            # Use OpenAI client from main.py
-            from ..main import client
+            # Use LiteLLM for consistency with the rest of the codebase
+            import litellm
 
-            response = client.chat.completions.create(
-                model=llm or "gpt-4o",
+            # Convert model name if it's in litellm format
+            model_name = llm or "gpt-4o-mini"
+
+            response = litellm.completion(
+                model=model_name,
                 messages=[{
                     "role": "user", 
                     "content": custom_prompt or default_prompt

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

@@ -308,7 +308,11 @@ async def execute_callback(self, task_output: TaskOutput) -> None:
                 if self.agent:
                     if getattr(self.agent, '_using_custom_llm', False) and hasattr(self.agent, 'llm_instance'):
                         # For custom LLM instances (like Ollama)
-                        llm_model = self.agent.llm_instance
+                        # Extract the model name from the LLM instance
+                        if hasattr(self.agent.llm_instance, 'model'):
+                            llm_model = self.agent.llm_instance.model
+                        else:
+                            llm_model = "gpt-4o-mini"  # Default fallback
                     elif hasattr(self.agent, 'llm') and self.agent.llm:
                         # For standard model strings
                         llm_model = self.agent.llm

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.0.99"
+version = "0.0.101"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [
@@ -25,7 +25,8 @@ mcp = [
 ]
 
 memory = [
-    "chromadb>=1.0.0"
+    "chromadb>=1.0.0",
+    "litellm>=1.50.0",
 ]
 
 knowledge = [
@@ -63,5 +64,6 @@ all = [
     "praisonaiagents[api]"
 ]
 
-[tool.setuptools]
-packages = ["praisonaiagents"]
+[tool.setuptools.packages.find]
+where = ["."]
+include = ["praisonaiagents*"]

src/praisonai-agents/test.py

@@ -0,0 +1,33 @@
+from praisonaiagents import Agent, Task, PraisonAIAgents
+import os
+from dotenv import load_dotenv
+
+load_dotenv()
+
+llm_config = {
+    "model": "openai/gpt-4o-mini",
+    "api_key": os.getenv('OPENAI_API_KEY'),
+    "temperature": 0.7,
+    "max_tokens": 2000
+}
+
+blog_agent = Agent(
+    role="Blog Writer",
+    goal="Write a blog post about AI",
+    backstory="Expert at writing blog posts",
+    llm="gpt-4o-mini",
+)
+
+blog_task = Task(
+    description="Write a blog post about AI trends in 1 paragraph",
+    expected_output="Well-written blog post about AI trends",
+    agent=blog_agent
+)
+
+agents = PraisonAIAgents(
+    agents=[blog_agent],
+    tasks=[blog_task],
+    memory=True
+)
+
+result = agents.start()

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/v2.2.28.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.28.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.29.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.29.tar.gz | shasum -a 256`.split.first
     license "MIT"
 
     depends_on "python@3.11"

src/praisonai/praisonai/deploy.py

@@ -56,7 +56,7 @@ def create_dockerfile(self):
             file.write("FROM python:3.11-slim\n")
             file.write("WORKDIR /app\n")
             file.write("COPY . .\n")
-            file.write("RUN pip install flask praisonai==2.2.28 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.2.29 gunicorn markdown\n")
             file.write("EXPOSE 8080\n")
             file.write('CMD ["gunicorn", "-b", "0.0.0.0:8080", "api:app"]\n')
 

src/praisonai/pyproject.toml

@@ -1,6 +1,6 @@
 [project]
 name = "PraisonAI"
-version = "2.2.28"
+version = "2.2.29"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 readme = "README.md"
 license = ""
@@ -12,7 +12,7 @@ dependencies = [
     "rich>=13.7",
     "markdown>=3.5",
     "pyparsing>=3.0.0",
-    "praisonaiagents>=0.0.99",
+    "praisonaiagents>=0.0.101",
     "python-dotenv>=0.19.0",
     "instructor>=1.3.3",
     "PyYAML>=6.0",
@@ -95,7 +95,7 @@ autogen = ["pyautogen>=0.2.19", "praisonai-tools>=0.0.15", "crewai"]
 
 [tool.poetry]
 name = "PraisonAI"
-version = "2.2.28"
+version = "2.2.29"
 description = "PraisonAI is an AI Agents Framework with Self Reflection. PraisonAI application combines PraisonAI Agents, AutoGen, and CrewAI into a low-code solution for building and managing multi-agent LLM systems, focusing on simplicity, customisation, and efficient human-agent collaboration."
 authors = ["Mervin Praison"]
 license = ""
@@ -113,7 +113,7 @@ python = ">=3.10,<3.13"
 rich = ">=13.7"
 markdown = ">=3.5"
 pyparsing = ">=3.0.0"
-praisonaiagents = ">=0.0.99"
+praisonaiagents = ">=0.0.101"
 python-dotenv = ">=0.19.0"
 instructor = ">=1.3.3"
 PyYAML = ">=6.0"