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Instead of searching the web for everything about a competitor, this system uses specialized AI agents to analyze a competitor specifically in relation to *your* company's value proposition, your customers' specific pain points, and your strategic sales goals.\n\nIt uses **CrewAI** to orchestrate three specialized agents that research, compare, and synthesize actionable sales intelligence: a Market Scout, a Product Strategist, and a Battlecard Author.\n\nThis tool is designed for:\n- **Sales Teams:** Who need immediate, punchy arguments to win against specific competitors.\n- **Product Managers:** Who need to understand technical feature gaps vs. rivals.\n- **Founders:** Who need to quickly validate their positioning in a crowded market.\n\n## Features\n\n- **Context-Aware Research:** Agents don't just search; they filter data based on your specific business pain points.\n- **Real-time Reasoning Logs:** Transparency in the UI shows the agent’s internal \"thought process\" and research steps.\n- **No-Jargon Battlecards:** Specialized synthesis agent trained to write punchy, founder-to-founder sales arguments rather than robotic reports.\n- **Structured UI:** Form-based Gradio interface for clean, professional input and side-by-side analysis.\n\n## Tech Stack\n\n**Frameworks & Libraries:**\n- **CrewAI:** Multi-agent orchestration.\n- **Gemma 4-26B (via Gemini API/LiteLLM):** Advanced reasoning LLM.\n- **Gradio:** Interactive web-based user interface.\n- **LiteLLM:** Fallback adapter for broad model support.\n\n**Additional Tools:**\n- **Tavily Search API:** Real-time, AI-optimized web research.\n- **dotenv:** Environment variable management.\n- **uv:** Modern, high-speed Python dependency management.\n\n## Prerequisites\n\nBefore you begin, ensure you have:\n\n- Python 3.12 or higher\n- [uv](https://github.com/astral-sh/uv) (Recommended for dependency management)\n- API keys for:\n  - [Google AI Studio](https://aistudio.google.com) for Gemini/Gemma \n  - [Tavily Search API](https://tavily.com) \n\n## Installation\n\n### 1. Clone the Repository\n\n```bash\ngit clone https://github.com/vishakha-codes/competitive_intelligence_agent.git\ncd competitive_intelligence_agent\n```\n\n### 2. Set Up Environment Variables\n\nWe use an `.env.example` file to manage configuration. Copy it to create your local `.env` file:\n\n```bash\ncp .env.example .env\n```\n\nOpen the newly created `.env` file and insert your API keys:\n\n```bash\nGEMINI_API_KEY=your_gemini_api_key_here\nTAVILY_API_KEY=tvly-your_tavily_key_here\n```\n\n### 3. Sync Environment\n\nSince the project uses `uv` for dependency management, synchronize your local environment to match the project requirements:\n\n```bash\n# This will automatically create the virtual environment \n# and install all dependencies defined in pyproject.toml\nuv sync\n```\n\n## Usage\n\n### Running the Application\n\n```bash\nuv run main.py\n```\n*Navigate to the local URL (typically http://127.0.0.1:7860) to access the Gradio interface.*\n\n## Project Structure\n\n```text\ncompetitive_intelligence_agent/\n├── main.py                # Gradio UI and event loop\n├── agents_logic.py        # CrewAI agent/task definitions\n├── .env.example           # Template for API keys\n├── pyproject.toml         # uv project configuration\n├── uv.lock                # Locked dependencies for consistency\n├── assets/\n│   └── demo.png           # Demo screenshot\n└── .venv/                 # Virtual environment (auto-generated)\n```\n\n## How It Works\n\n**Technical Details:**\n- **Sequential Orchestration:** The system uses a strictly defined pipeline: Market Scout $\\rightarrow$ Product Strategist $\\rightarrow$ Battlecard Author. 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