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Update README.md to enhance project overview, key features, and integration recommendations
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| title: Medivocate | |
| emoji: 🐢 | |
| colorFrom: purple | |
| colorTo: red | |
| sdk: gradio | |
| sdk_version: 5.9.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| short_description: Medivocate is an AI-driven platform leveraging Retrieval-Aug | |
| # Medivocate | |
| An AI-driven platform empowering users with trustworthy, personalized history guidance to combat misinformation and promote equitable history. | |
| ## Follows us [here](https://github.com/KameniAlexNea/medivocate) | |
| * [**Alex Kameni**](https://www.linkedin.com/in/elie-alex-kameni-ngangue/) | |
| * [**Esdras Fandio**](https://www.linkedin.com/in/esdras-fandio/) | |
| * [**Patric Zeufack**](https://www.linkedin.com/in/zeufack-patric-hermann-7a9256143/) | |
| ## Project Overview | |
| **Medivocate** is structured for modular development and ease of scalability, as seen in its directory layout: | |
| ``` | |
| 📦 ./ | |
| ├── 📁 docs/ | |
| ├── 📁 src/ | |
| │ ├── 📁 ocr/ | |
| │ ├── 📁 preprocessing/ | |
| │ ├── 📁 chunking/ | |
| │ ├── 📁 vector_store/ | |
| │ ├── 📁 rag_pipeline/ | |
| │ ├── 📁 llm_integration/ | |
| │ └── 📁 prompt_engineering/ | |
| ├── 📁 tests/ | |
| │ ├── 📁 unit/ | |
| │ └── 📁 integration/ | |
| ├── 📁 examples/ | |
| ├── 📁 notebooks/ | |
| ├── 📁 config/ | |
| ├── 📄 README.md | |
| ├── 📄 CONTRIBUTING.md | |
| ├── 📄 requirements.txt | |
| ├── 📄 .gitignore | |
| └── 📄 LICENSE | |
| ``` | |
| ### Key Features | |
| 1. **Trustworthy Information Access** : Using RAG (Retrieval-Augmented Generation) pipelines to deliver fact-based responses. | |
| 2. **Advanced Document Handling** : Leveraging OCR, preprocessing, and chunking for scalable document ingestion. | |
| 3. **Integrated Tools** : Supports integration with vector databases (e.g., Chroma), LLMs, and advanced prompt engineering techniques. | |
| ### Recommendations for Integration | |
| * **Groq** : Utilize Groq APIs for free-tier LLM support, perfect for prototyping RAG applications. | |
| * **LangChain + LangSmith** : Build and monitor intelligent agents with LangChain and enhance debugging and evaluation using LangSmith. | |
| * **Hugging Face Datasets** : For one-liner dataset loading and preprocessing, supporting efficient ML training pipelines. | |
| * **Search Index** : Include Chroma for robust semantic search capabilities in RAG. | |
| This modular design and extensive integration make Medivocate a powerful tool for historical education and research. | |