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| # ===================================================================== | |
| # Local AI Agent using smolagents with LiteLLM and Ollama | |
| # ===================================================================== | |
| # This application creates a local AI agent that can: | |
| # - Search the web using DuckDuckGo | |
| # - Generate images using Hugging Face's text-to-image model | |
| # - Get current time in different timezones | |
| # - Check if a number is prime | |
| # - And more! | |
| # | |
| # IMPORTANT: This agent requires local execution with Ollama running on port 11434 | |
| # Remote models from Hugging Face (like Qwen2.5-Coder or Mistral-7B) are often overloaded | |
| # and may return 'Payment Required' errors or be paused by their providers. | |
| # | |
| # Setup requirements: | |
| # 1. Install Ollama (https://ollama.ai/) | |
| # 2. Pull the llama3.2 model: `ollama pull llama3.2` | |
| # 3. Ensure Ollama is running before starting this application | |
| # 4. Install Python dependencies from requirements.txt | |
| # ===================================================================== | |
| from smolagents import CodeAgent, DuckDuckGoSearchTool, load_tool, tool | |
| from smolagents.models import LiteLLMModel | |
| import os | |
| import datetime | |
| import requests | |
| import pytz | |
| import yaml | |
| from tools.final_answer import FinalAnswerTool | |
| from Gradio_UI import GradioUI | |
| # ===================================================================== | |
| # Tool Definitions | |
| # ===================================================================== | |
| # Each tool is defined with the @tool decorator and includes docstrings | |
| # that help the agent understand when and how to use each tool. | |
| # ===================================================================== | |
| # Simple example tool that can be customized | |
| def my_custom_tool(arg1:str, arg2:int)-> str: #it's import to specify the return type | |
| #Keep this format for the description / args / args description but feel free to modify the tool | |
| """A tool that does nothing yet | |
| Args: | |
| arg1: the first argument | |
| arg2: the second argument | |
| """ | |
| return "What magic will you build ?" | |
| def get_current_time_in_timezone(timezone: str) -> str: | |
| """A tool that fetches the current local time in a specified timezone. | |
| Args: | |
| timezone: A string representing a valid timezone (e.g., 'America/New_York'). | |
| """ | |
| try: | |
| # Create timezone object | |
| tz = pytz.timezone(timezone) | |
| # Get current time in that timezone | |
| local_time = datetime.datetime.now(tz).strftime("%Y-%m-%d %H:%M:%S") | |
| return f"The current local time in {timezone} is: {local_time}" | |
| except Exception as e: | |
| return f"Error fetching time for timezone '{timezone}': {str(e)}" | |
| # Import image generation tool from Hugging Face Hub | |
| # This allows the agent to create images based on text prompts | |
| image_generation_tool = load_tool("agents-course/text-to-image", trust_remote_code=True) | |
| def generate_image(prompt:str) -> str: | |
| """Generate image(s) from a text prompt via HF text-to-image. | |
| Args: | |
| prompt: description of the image | |
| """ | |
| return image_generation_tool(prompt) | |
| def duckduckgo_search(query: str, max_results: int = 5) -> str: | |
| """Search DuckDuckGo for a query and return the top N results. | |
| Args: | |
| query: The search query string to look up on DuckDuckGo | |
| max_results: Maximum number of search results to return (default is 5) | |
| Returns: | |
| A string containing the search results | |
| """ | |
| searcher = DuckDuckGoSearchTool(max_results=max_results) | |
| return searcher(query) | |
| def is_prime(number: int) -> bool: | |
| """ | |
| Check if a number is prime using an optimized 6k±1 algorithm. | |
| Args: | |
| number: The integer to check for primality. | |
| Returns: | |
| True if `number` is prime, False otherwise. | |
| """ | |
| # Numbers less than 2 are not prime | |
| if number <= 1: | |
| return False | |
| # 2 and 3 are prime | |
| if number <= 3: | |
| return True | |
| # Eliminate multiples of 2 and 3 | |
| if number % 2 == 0 or number % 3 == 0: | |
| return False | |
| # Test 6k ± 1 factors up to sqrt(number) | |
| i = 5 | |
| while i * i <= number: | |
| if number % i == 0 or number % (i + 2) == 0: | |
| return False | |
| i += 6 | |
| return True | |
| # ===================================================================== | |
| # Agent Configuration | |
| # ===================================================================== | |
| # The FinalAnswerTool is used to provide final responses to the user | |
| final_answer = FinalAnswerTool() | |
| # IMPORTANT: Remote models are often overloaded or require payment | |
| # Previous attempts to use these models resulted in errors: | |
| # - Qwen/Qwen2.5-Coder-32B-Instruct: "Payment Required" error | |
| # - mistralai/Mistral-7B-Instruct-v0.2: Model was paused | |
| # | |
| # Alternative HF endpoint (if needed): | |
| # model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud' | |
| # | |
| # Instead, we use a local Ollama model which is more reliable: | |
| # Configure LiteLLM to use local Ollama instance | |
| os.environ["LITELLM_OLLAMA_API_BASE"] = "http://localhost:11434" | |
| # Initialize the model with appropriate parameters | |
| model = LiteLLMModel( | |
| model_name="ollama/llama3.2", # Using the locally available Llama3.2 model | |
| max_tokens=1024, # Maximum tokens in the response | |
| temperature=0.7, # Controls randomness (higher = more creative) | |
| model_id="ollama/llama3.2" # Explicitly set model_id to avoid default to Claude | |
| ) | |
| # ===================================================================== | |
| # Agent Initialization | |
| # ===================================================================== | |
| # Initialize the agent with the configured model and tools | |
| agent = CodeAgent( | |
| model=model, | |
| # List of tools available to the agent - add new tools here | |
| tools=[ | |
| final_answer, # Required for providing final answers | |
| duckduckgo_search, # Web search capability | |
| get_current_time_in_timezone, # Time-related functions | |
| my_custom_tool, # Example custom tool | |
| generate_image, # Image generation | |
| is_prime # Prime number checker | |
| ], | |
| max_steps=6, # Maximum reasoning steps per query | |
| verbosity_level=1, # Controls logging detail | |
| grammar=None, # Optional grammar constraints | |
| planning_interval=None, # How often to plan next steps | |
| name=None, | |
| description=None | |
| # Not specifying prompt_templates will use the default ones from smolagents | |
| ) | |
| # ===================================================================== | |
| # Launch the Gradio Web Interface | |
| # ===================================================================== | |
| # This creates a user-friendly web interface for interacting with the agent | |
| # Accessible at http://127.0.0.1:7860 by default | |
| GradioUI(agent).launch() |