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Retrieval-Augmented Generation (RAG)** application powered by **CrewAI**, **LangChain**, **ChromaDB**, and **Streamlit**.\n\nThis application orchestrates multiple specialized AI agents to handle complex queries combining internal PDF documents, real-time web search, and weather forecasts.\n\n---\n\n## 🌟 Key Features\n\n- **📄 Document RAG Agent**: Indexes uploaded PDF files into ChromaDB vector store using chunking & OpenAI embeddings to provide accurate, factual document Q&A.\n- **🌐 Web Search Agent**: Searches the public internet using DuckDuckGo to answer queries on breaking news, live data, and online facts.\n- **🌤️ Weather Agent**: Integrates with Open-Meteo API to fetch real-time atmospheric conditions and temperature forecasts by city.\n- **🧠 Orchestrator / Manager Agent**: Supports both **Sequential** and **Hierarchical** multi-agent processes to route and synthesize sub-task results into a single answer.\n- **🎨 Interactive Streamlit UI**: Sleek, modern web user interface 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Specialist\n│   ├── weather_agent.py             # Meteorological Specialist\n│   └── web_agent.py                 # Live Web Search Specialist\n│\n├── tools/                           # Custom CrewAI Tool wrappers\n│   ├── pdf_tool.py                  # Chroma Vector DB Retriever Tool\n│   ├── weather_tool.py              # Open-Meteo Weather API Tool\n│   └── web_search_tool.py           # DuckDuckGo Web Search Tool\n│\n├── rag/                             # Vector RAG Pipeline\n│   ├── ingest.py                    # PDF loading & chunk indexing\n│   ├── vectorstore.py               # Chroma DB initialization & persistence\n│   └── retriever.py                 # Similarity search retrieval engine\n│\n├── crew/                            # CrewAI Workflow Orchestration\n│   ├── crew.py                      # Crew assembly & kickoff\n│   └── tasks.py                     # Agent task definitions\n│\n├── utils/                           # Configuration & Prompts\n│   ├── config.py                    # Environment variable loader\n│   └── prompts.py                   # System prompts & backstory definitions\n│\n├── data/                            # PDF document storage\n├── vector_db/                       # Chroma DB persistent storage\n├── screenshots/                     # UI Screenshots\n├── Dockerfile                       # Multi-stage Docker container build\n│\n└── .github/\n    └── workflows/\n        └── ci.yml                   # GitHub Actions CI workflow\n```\n\n---\n\n## 🚀 Quickstart Guide\n\n### 1. Prerequisites\n- Python 3.10+\n- OpenAI API Key\n\n### 2. Installation\nClone the repository and install dependencies:\n```bash\ncd crewai-agentic-rag\npython -m venv venv\nsource venv/bin/activate  # On Windows: venv\\Scripts\\activate\npip install -r requirements.txt\n```\n\n### 3. Environment Setup\nCreate a `.env` file based on `.env.example`:\n```bash\ncp .env.example .env\n```\nEdit `.env` and set your `OPENAI_API_KEY`:\n```env\nOPENAI_API_KEY=sk-your-openai-api-key\nOPENAI_MODEL_NAME=gpt-4o-mini\n```\n\n---\n\n## 💻 Running the Application\n\n### Option A: Streamlit Web UI\nLaunch the interactive web application:\n```bash\nstreamlit run app.py\n```\nOpen your browser at `http://localhost:8501`.\n\n### Option B: Command Line Test\nTest the Crew execution directly in CLI:\n```bash\npython crew/crew.py\n```\n\n### Option C: Jupyter Notebook\nRun the interactive notebook:\n```bash\njupyter notebook notebook/CrewAI_Agentic_RAG.ipynb\n```\n\n---\n\n## 🐳 Docker Deployment\n\nBuild and run using Docker:\n```bash\n# Build the docker image\ndocker build -t crewai-agentic-rag .\n\n# Run the container\ndocker run -p 8501:8501 -e OPENAI_API_KEY=\"your-api-key\" crewai-agentic-rag\n```\n\n---\n\n## 🛠️ Tech Stack\n\n- **Framework**: [CrewAI](https://github.com/joaomdmoura/crewAI)\n- **RAG & Embeddings**: [LangChain](https://github.com/langchain-ai/langchain) & [ChromaDB](https://www.trychroma.com/)\n- **Frontend**: [Streamlit](https://streamlit.io/)\n- **Search & Tools**: DuckDuckGo Search API, Open-Meteo Weather API\n- **Containerization**: Docker & GitHub Actions CI\n\n---\n\n## 📜 License\n\nMIT License. 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