🧠 Trauma-Informed RAG Chatbot

This project is a Retrieval-Augmented Generation (RAG) chatbot that answers trauma-related questions grounded in texts from Gabor Maté, Thomas Hübl, and other somatic/psychological wisdom sources. It uses LangChain to retrieve relevant passages and generate insightful, emotionally aware responses using a local or cloud-based LLM.

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🔍 What It Does

• Loads and chunks trauma-related text files
• Embeds them using OpenAIEmbeddings (or local alternatives)
• Stores embeddings in ChromaDB (or FAISS)
• Retrieves the most relevant chunks for each user query
• Uses an LLM (e.g., GPT-3.5 / Claude / Mistral / Ollama) to answer questions with reference to the source material

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🧰 Tech Stack

• 🧠 LangChain – Orchestration of retrieval + generation
• 🗂️ ChromaDB – Local vector database for embedding search
• 🔠 OpenAI / Ollama – LLM for generating responses
• 📚 Markdown/Text/PDF loaders – for your personal trauma text sources
• 🧪 Streamlit (optional) – UI for easy interaction

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🚀 How to Run

1. Clone the repo

git clone https://github.com/yourusername/trauma-rag-chatbot.git
cd trauma-rag-chatbot

2. Install dependencies

pip install -r requirements.txt

3. Set your .env file

OPENAI_API_KEY=your-key

4. Run the app

python app.py

Or if using Streamlit:

streamlit run app.py

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💬 Example Q&A

Q: Why do I feel disconnected from my body after trauma?
A: Based on Thomas Hübl's work, trauma often interrupts the nervous system’s ability to stay present. Disconnection from the body is a protective adaptation to unbearable sensations.

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🧠 Skills Demonstrated

• LangChain chains and retrieval techniques
• Embedding + chunking strategies
• Building a local RAG pipeline (MVP)
• Clean, modular code for real-world use
• Deployable RAG chatbot structure

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📂 Project Structure

trauma-rag-chatbot/
├── data/                 # Source texts (e.g., Gabor Maté excerpts)
├── app.py                # Main chatbot logic
├── requirements.txt
├── .env                  # API keys
└── README.md             # This file

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📌 Future Enhancements

• Switch to local LLM via Ollama or Hugging Face
• Add feedback logging and analytics
• Integrate summarization and content clustering
• Add frontend to embed on personal site

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👤 Author

Didi Berman – AI & Automation Engineer | Trauma-Informed Tech Creator
Helping people build humane tools with AI & nervous system awareness
🌐 didiberman.com · 💻 GitHub

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🔖 Keywords

rag langchain trauma gabor mate ai chatbot embeddings mental health chroma fastapi streamlit mlops openai ollama