chore: bump praisonai to v2.2.62 and praisonaiagents to v0.0.135 across all files

refactor: inline Gemini internal tools detection logic

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>=2.2.60" \
+    "praisonai>=2.2.62" \
     "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>=2.2.60" \
+    "praisonai>=2.2.62" \
     "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>=2.2.60" \
+    "praisonai>=2.2.62" \
     "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>=2.2.60" \
+    "praisonai>=2.2.62" \
     "praisonai[ui]" \
     "praisonai[crewai]"
 

docker/README.md

@@ -121,7 +121,7 @@ healthcheck:
 ## 📦 Package Versions
 
 All Docker images use consistent, up-to-date versions:
-- PraisonAI: `>=2.2.60`
+- PraisonAI: `>=2.2.62`
 - 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==2.2.60" "praisonaiagents==0.0.92"
+RUN pip install "praisonai==2.2.62" "praisonaiagents==0.0.92"
 ```
 
 ## 🌐 Production Deployment

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

@@ -2,6 +2,7 @@ import logging
 import os
 import warnings
 import re
+import inspect
 from typing import Any, Dict, List, Optional, Union, Literal, Callable
 from pydantic import BaseModel
 import time
@@ -16,7 +17,6 @@ from ..main import (
     ReflectionOutput,
     execute_sync_callback,
 )
-from .model_capabilities import is_gemini_internal_tool
 from rich.console import Console
 from rich.live import Live
 
@@ -380,6 +380,65 @@ class LLM:
             
         return function_name, arguments, tool_call_id
 
+    def _validate_and_filter_ollama_arguments(self, function_name: str, arguments: Dict[str, Any], available_tools: List) -> Dict[str, Any]:
+        """
+        Validate and filter tool call arguments for Ollama provider.
+        
+        Ollama sometimes generates tool calls with mixed parameters where arguments
+        from different functions are combined. This method validates arguments against
+        the actual function signature and removes invalid parameters.
+        
+        Args:
+            function_name: Name of the function to call
+            arguments: Arguments provided in the tool call
+            available_tools: List of available tool functions
+            
+        Returns:
+            Filtered arguments dictionary with only valid parameters
+        """
+        if not available_tools:
+            logging.debug(f"[OLLAMA_FIX] No available tools provided for validation")
+            return arguments
+            
+        # Find the target function
+        target_function = None
+        for tool in available_tools:
+            tool_name = getattr(tool, '__name__', str(tool))
+            if tool_name == function_name:
+                target_function = tool
+                break
+                
+        if not target_function:
+            logging.debug(f"[OLLAMA_FIX] Function {function_name} not found in available tools")
+            return arguments
+            
+        try:
+            # Get function signature
+            sig = inspect.signature(target_function)
+            valid_params = set(sig.parameters.keys())
+            
+            # Filter arguments to only include valid parameters
+            filtered_args = {}
+            invalid_params = []
+            
+            for param_name, param_value in arguments.items():
+                if param_name in valid_params:
+                    filtered_args[param_name] = param_value
+                else:
+                    invalid_params.append(param_name)
+                    
+            if invalid_params:
+                logging.debug(f"[OLLAMA_FIX] Function {function_name} received invalid parameters: {invalid_params}")
+                logging.debug(f"[OLLAMA_FIX] Valid parameters for {function_name}: {list(valid_params)}")
+                logging.debug(f"[OLLAMA_FIX] Original arguments: {arguments}")
+                logging.debug(f"[OLLAMA_FIX] Filtered arguments: {filtered_args}")
+                
+            return filtered_args
+            
+        except Exception as e:
+            logging.debug(f"[OLLAMA_FIX] Error validating arguments for {function_name}: {e}")
+            return arguments
+
     def _needs_system_message_skip(self) -> bool:
         """Check if this model requires skipping system messages"""
         if not self.model:
@@ -591,10 +650,14 @@ class LLM:
                 if tool_def:
                     formatted_tools.append(tool_def)
             # Handle Gemini internal tools (e.g., {"googleSearch": {}}, {"urlContext": {}}, {"codeExecution": {}})
-            elif is_gemini_internal_tool(tool):
+            elif isinstance(tool, dict) and len(tool) == 1:
                 tool_name = next(iter(tool.keys()))
-                logging.debug(f"Using Gemini internal tool: {tool_name}")
-                formatted_tools.append(tool)
+                gemini_internal_tools = {'googleSearch', 'urlContext', 'codeExecution'}
+                if tool_name in gemini_internal_tools:
+                    logging.debug(f"Using Gemini internal tool: {tool_name}")
+                    formatted_tools.append(tool)
+                else:
+                    logging.debug(f"Skipping unknown tool: {tool_name}")
             else:
                 logging.debug(f"Skipping tool of unsupported type: {type(tool)}")
                 
@@ -959,6 +1022,10 @@ class LLM:
                             is_ollama = self._is_ollama_provider()
                             function_name, arguments, tool_call_id = self._extract_tool_call_info(tool_call, is_ollama)
 
+                            # Validate and filter arguments for Ollama provider
+                            if is_ollama and tools:
+                                arguments = self._validate_and_filter_ollama_arguments(function_name, arguments, tools)
+
                             logging.debug(f"[TOOL_EXEC_DEBUG] About to execute tool {function_name} with args: {arguments}")
                             tool_result = execute_tool_fn(function_name, arguments)
                             logging.debug(f"[TOOL_EXEC_DEBUG] Tool execution result: {tool_result}")
@@ -1610,6 +1677,10 @@ Output MUST be JSON with 'reflection' and 'satisfactory'.
                         is_ollama = self._is_ollama_provider()
                         function_name, arguments, tool_call_id = self._extract_tool_call_info(tool_call, is_ollama)
 
+                        # Validate and filter arguments for Ollama provider
+                        if is_ollama and tools:
+                            arguments = self._validate_and_filter_ollama_arguments(function_name, arguments, tools)
+
                         tool_result = await execute_tool_fn(function_name, arguments)
                         tool_results.append(tool_result)  # Store the result
 

src/praisonai-agents/praisonaiagents/llm/openai_client.py

@@ -18,7 +18,6 @@ from dataclasses import dataclass
 from rich.console import Console
 from rich.live import Live
 import inspect
-from .model_capabilities import is_gemini_internal_tool
 
 # Constants
 LOCAL_SERVER_API_KEY_PLACEHOLDER = "not-needed"
@@ -407,10 +406,14 @@ class OpenAIClient:
                 if tool_def:
                     formatted_tools.append(tool_def)
             # Handle Gemini internal tools (e.g., {"googleSearch": {}}, {"urlContext": {}}, {"codeExecution": {}})
-            elif is_gemini_internal_tool(tool):
+            elif isinstance(tool, dict) and len(tool) == 1:
                 tool_name = next(iter(tool.keys()))
-                logging.debug(f"Using Gemini internal tool: {tool_name}")
-                formatted_tools.append(tool)
+                gemini_internal_tools = {'googleSearch', 'urlContext', 'codeExecution'}
+                if tool_name in gemini_internal_tools:
+                    logging.debug(f"Using Gemini internal tool: {tool_name}")
+                    formatted_tools.append(tool)
+                else:
+                    logging.debug(f"Skipping unknown tool: {tool_name}")
             else:
                 logging.debug(f"Skipping tool of unsupported type: {type(tool)}")
                 

src/praisonai-agents/pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "praisonaiagents"
-version = "0.0.134"
+version = "0.0.135"
 description = "Praison AI agents for completing complex tasks with Self Reflection Agents"
 requires-python = ">=3.10"
 authors = [
@@ -14,7 +14,6 @@ dependencies = [
     "pydantic",
     "rich",
     "openai",
-    "mcp>=1.6.0",
     "posthog>=3.0.0",
     "aiohttp>=3.8.0"
 ]

src/praisonai-agents/tests/test_ollama_sequential_fix.py

@@ -0,0 +1,129 @@
+#!/usr/bin/env python3
+"""
+Test script to verify Ollama sequential tool calling argument mixing fix.
+
+This test validates that the parameter validation and filtering fix correctly handles
+the case where Ollama generates tool calls with mixed parameters from different functions.
+"""
+
+import logging
+from praisonaiagents.llm.llm import LLM
+
+# Enable debug logging
+logging.basicConfig(level=logging.DEBUG)
+
+# Test functions matching the issue description
+def get_stock_price(company_name: str) -> str:
+    """
+    Get the stock price of a company
+    
+    Args:
+        company_name (str): The name of the company
+        
+    Returns:
+        str: The stock price of the company
+    """
+    return f"The stock price of {company_name} is 100"
+
+def multiply(a: int, b: int) -> int:
+    """
+    Multiply two numbers
+    """
+    return a * b
+
+def test_ollama_argument_validation():
+    """
+    Test the Ollama argument validation and filtering functionality.
+    """
+    print("Testing Ollama argument validation and filtering...")
+    
+    llm = LLM(model="ollama/llama3.2")
+    tools = [get_stock_price, multiply]
+    
+    # Test case 1: Valid arguments (should pass through unchanged)
+    print("\n1. Testing valid arguments:")
+    valid_args = {"a": 100, "b": 2}
+    filtered_args = llm._validate_and_filter_ollama_arguments("multiply", valid_args, tools)
+    print(f"Original: {valid_args}")
+    print(f"Filtered: {filtered_args}")
+    assert filtered_args == valid_args, "Valid arguments should pass through unchanged"
+    print("✅ Valid arguments test passed")
+    
+    # Test case 2: Mixed arguments (the actual issue from #918)
+    print("\n2. Testing mixed arguments (the main issue):")
+    mixed_args = {"a": "get_stock_price", "company_name": "Google", "b": "2"}
+    filtered_args = llm._validate_and_filter_ollama_arguments("multiply", mixed_args, tools)
+    expected_filtered = {"a": "get_stock_price", "b": "2"}  # Should remove 'company_name'
+    print(f"Original: {mixed_args}")
+    print(f"Filtered: {filtered_args}")
+    print(f"Expected: {expected_filtered}")
+    assert filtered_args == expected_filtered, f"Expected {expected_filtered}, got {filtered_args}"
+    print("✅ Mixed arguments filtering test passed")
+    
+    # Test case 3: All invalid arguments
+    print("\n3. Testing all invalid arguments:")
+    invalid_args = {"invalid_param1": "value1", "invalid_param2": "value2"}
+    filtered_args = llm._validate_and_filter_ollama_arguments("multiply", invalid_args, tools)
+    expected_empty = {}
+    print(f"Original: {invalid_args}")
+    print(f"Filtered: {filtered_args}")
+    assert filtered_args == expected_empty, "All invalid arguments should be filtered out"
+    print("✅ Invalid arguments filtering test passed")
+    
+    # Test case 4: Function not found in tools
+    print("\n4. Testing function not found:")
+    some_args = {"param": "value"}
+    filtered_args = llm._validate_and_filter_ollama_arguments("nonexistent_function", some_args, tools)
+    print(f"Original: {some_args}")
+    print(f"Filtered: {filtered_args}")
+    assert filtered_args == some_args, "Arguments should pass through if function not found"
+    print("✅ Function not found test passed")
+    
+    # Test case 5: Empty tools list
+    print("\n5. Testing empty tools list:")
+    some_args = {"param": "value"}
+    filtered_args = llm._validate_and_filter_ollama_arguments("multiply", some_args, [])
+    print(f"Original: {some_args}")
+    print(f"Filtered: {filtered_args}")
+    assert filtered_args == some_args, "Arguments should pass through if no tools provided"
+    print("✅ Empty tools test passed")
+    
+    print("\n🎉 All Ollama argument validation tests passed!")
+    return True
+
+def test_provider_detection():
+    """
+    Test the Ollama provider detection functionality.
+    """
+    print("\nTesting Ollama provider detection...")
+    
+    # Test Ollama provider detection
+    ollama_llm = LLM(model="ollama/llama3.2")
+    assert ollama_llm._is_ollama_provider(), "Should detect ollama/ prefix"
+    print("✅ Ollama prefix detection works")
+    
+    # Test non-Ollama provider
+    openai_llm = LLM(model="gpt-4o-mini")
+    assert not openai_llm._is_ollama_provider(), "Should not detect OpenAI as Ollama"
+    print("✅ Non-Ollama provider detection works")
+    
+    print("✅ Provider detection tests passed!")
+    return True
+
+if __name__ == "__main__":
+    print("Running Ollama sequential tool calling fix tests...")
+    print("=" * 60)
+    
+    # Run tests
+    try:
+        test_provider_detection()
+        test_ollama_argument_validation()
+        
+        print("\n" + "=" * 60)
+        print("🎉 ALL TESTS PASSED!")
+        print("The Ollama sequential tool calling argument mixing issue has been fixed!")
+        
+    except Exception as e:
+        print(f"\n❌ TEST FAILED: {e}")
+        import traceback
+        traceback.print_exc()

src/praisonai-agents/uv.lock

@@ -2375,11 +2375,10 @@ wheels = [
 
 [[package]]
 name = "praisonaiagents"
-version = "0.0.134"
+version = "0.0.135"
 source = { editable = "." }
 dependencies = [
     { name = "aiohttp" },
-    { name = "mcp" },
     { name = "openai" },
     { name = "posthog" },
     { name = "pydantic" },
@@ -2442,7 +2441,6 @@ requires-dist = [
     { name = "litellm", marker = "extra == 'llm'", specifier = ">=1.72.0" },
     { name = "litellm", marker = "extra == 'memory'", specifier = ">=1.72.0" },
     { name = "markitdown", extras = ["all"], marker = "extra == 'knowledge'", specifier = ">=0.1.0" },
-    { name = "mcp", specifier = ">=1.6.0" },
     { name = "mcp", marker = "extra == 'mcp'", specifier = ">=1.6.0" },
     { name = "mem0ai", marker = "extra == 'knowledge'", specifier = ">=0.1.0" },
     { name = "mem0ai", extras = ["graph"], marker = "extra == 'graph'", specifier = ">=0.1.0" },

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/v2.2.60.tar.gz"
-    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.60.tar.gz | shasum -a 256`.split.first
+    url "https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.62.tar.gz"
+    sha256 `curl -sL https://github.com/MervinPraison/PraisonAI/archive/refs/tags/v2.2.62.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==2.2.60 gunicorn markdown\n")
+            file.write("RUN pip install flask praisonai==2.2.62 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 = "2.2.60"
+version = "2.2.62"
 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>=0.0.134",
+    "praisonaiagents>=0.0.135",
     "python-dotenv>=0.19.0",
     "instructor>=1.3.3",
     "PyYAML>=6.0",
@@ -90,12 +90,12 @@ call = [
     "openai>=1.54.0",
 ]
 train = []
-crewai = ["crewai>=0.32.0", "praisonai-tools>=0.0.15"]
-autogen = ["pyautogen>=0.2.19", "praisonai-tools>=0.0.15", "crewai"]
+crewai = ["crewai>=0.32.0", "praisonai-tools>=0.0.22"]
+autogen = ["pyautogen>=0.10.0", "praisonai-tools>=0.0.22", "crewai"]
 
 [tool.poetry]
 name = "PraisonAI"
-version = "2.2.60"
+version = "2.2.62"
 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 = ""
@@ -113,14 +113,14 @@ python = ">=3.10,<3.13"
 rich = ">=13.7"
 markdown = ">=3.5"
 pyparsing = ">=3.0.0"
-praisonaiagents = ">=0.0.134"
+praisonaiagents = ">=0.0.135"
 python-dotenv = ">=0.19.0"
 instructor = ">=1.3.3"
 PyYAML = ">=6.0"
 mcp = ">=1.6.0"
 pyautogen = {version = ">=0.2.19", optional = true}
 crewai = {version = ">=0.32.0", optional = true}
-praisonai-tools = {version = ">=0.0.15", optional = true}
+praisonai-tools = {version = ">=0.0.22", optional = true}
 chainlit = {version = "==2.5.5", optional = true}
 gradio = {version = ">=4.26.0", optional = true}
 flask = {version = ">=3.0.0", optional = true}

test_gemini_tools.py

@@ -0,0 +1,40 @@
+#!/usr/bin/env python3
+"""Test script to verify the refactored Gemini tools logic."""
+
+import logging
+import sys
+import os
+
+# Setup logging to see debug messages
+logging.basicConfig(level=logging.DEBUG, format='%(levelname)s: %(message)s')
+
+# Add the src directory to the Python path
+sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'src', 'praisonai-agents'))
+
+try:
+    from praisonaiagents.llm.llm import LLM
+    from praisonaiagents.llm.openai_client import OpenAIClient
+    
+    print("Testing LLM tool formatting...")
+    llm = LLM(model="gpt-4o-mini")
+    tools = [
+        {'googleSearch': {}},  # Valid Gemini tool
+        {'urlContext': {}},    # Valid Gemini tool  
+        {'codeExecution': {}}, # Valid Gemini tool
+        {'unknown': {}}        # Invalid tool - should be skipped
+    ]
+    
+    formatted = llm._format_tools_for_litellm(tools)
+    print(f"LLM formatted tools ({len(formatted)} tools):", formatted)
+    
+    print("\nTesting OpenAI client tool formatting...")
+    client = OpenAIClient(api_key="not-needed")
+    formatted = client.format_tools(tools)
+    print(f"OpenAI client formatted tools ({len(formatted)} tools):", formatted)
+    
+    print("\nTest completed successfully!")
+    
+except Exception as e:
+    import traceback
+    print(f"Error: {e}")
+    traceback.print_exc()