iflow-mcp-bessouat40-coding-assistant

# Coding Assistant Your Local AI Pair Programmer: Point this AI assistant to your project folder and start asking questions! It reads your code locally to provide truly context-aware help, explanations, and suggestions directly related to your files. Code smarter, locally.  ## Prerequisites 📝 - **Python:** Version 3.11 or higher recommended. - **`tree` command:** The `get_tree_folders` tool relies on this. - **Linux (Debian/Ubuntu):** `sudo apt update && sudo apt install tree` - **macOS (using Homebrew):** `brew install tree` ## Installation ⚙️ 1. **Clone the repository:** ```bash git clone https://github.com/Bessouat40/coding-assistant cd coding-assistant ``` 2. **Install Python dependencies:** ```bash pip install -r requirements.txt ``` ## Configuration 🔑 1. **API Keys & Settings:** Sensitive information like LLM API keys should be stored in a `.env` file in the project's root directory. - Copy the example file or create a new file named `.env`: ```bash cp .env.example .env ``` - Edit the `.env` file and add your keys: ```dotenv # .env MISTRAL_API_KEY=your_mistral_api_key_here # GOOGLE_API_KEY=your_google_api_key_here # Add other variables if needed, e.g., MAX_CONTEXT_TOKENS=7000 ``` 2. **LLM Provider:** Change LLM provider if you want : - Go to `api/utils.py` and modify `loadl_llm` function. Uncomment the line with the provider you need. By default, it's set to `Google` : ```python def load_llm(logger): try: model = ChatOllama(model="llama3.1:8b") # model = ChatMistralAI(model="codestral-latest") # model = ChatGoogleGenerativeAI(model="gemini-2.0-flash-001") logger.info(f"ChatGoogleGenerativeAI model '{model.model}' initialized successfully.") return model except Exception as e: logger.error(f"Failed to initialize the LLM model: {e}") raise RuntimeError(f"Could not initialize LLM: {e}") from e ``` ## Running th…