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| title: Personal ChatBot | |
| emoji: 💬 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.0.1 | |
| app_file: app.py | |
| pinned: false | |
| license: apache-2.0 | |
| short_description: Krishna's Persona Chat Bot using Multi RAG network | |
| # 🧠 Krishna's Personal AI Chatbot | |
| A memory-grounded, retrieval-augmented AI assistant built with LangChain, FAISS, BM25, and Llama3 — personalized to Krishna Vamsi Dhulipalla’s career, projects, and technical profile. | |
| > ⚡️ Ask me anything about Krishna — skills, experience, goals, or even what tools he used at Virginia Tech. | |
| --- | |
| ## 📌 Features | |
| - ✅ **Hybrid Retrieval**: Combines dense vector search (FAISS) + keyword search (BM25) for precise, high-recall chunk selection | |
| - 🤖 **LLM-Powered Pipelines**: Uses OpenAI GPT-4o and NVIDIA NIMs (e.g. LLaMA-3, Mixtral) for rewriting, validation, and final answer generation | |
| - 🧠 **Memory Module**: Stores user preferences, recent topics, and inferred tone using a structured `KnowledgeBase` schema | |
| - 🛠️ **Custom Architecture**: | |
| - Query → Rewriting → Hybrid Retriever → Scope Validator → LLM Answer | |
| - Fallback humor model (Mixtral) for out-of-scope queries | |
| - 🧩 **Document Grounding**: Powered by Krishna’s actual markdown files like `profile.md`, `goals.md`, and `chatbot_architecture.md` | |
| - 📊 **Enriched Vector Store**: Chunks include LLM-generated summaries and synthetic queries for better search performance | |
| - 🎛️ **Gradio Frontend**: Responsive, markdown-formatted interface for natural, real-time interaction | |
| --- | |
| ## 🏗️ Architecture | |
| ```text | |
| User Query | |
| ↓ | |
| [LLM1] → Rephrase into 3 diverse subqueries | |
| ↓ | |
| Hybrid Retrieval (BM25 + FAISS) | |
| ↓ | |
| [LLM2] → Classify: In-scope or Out-of-scope | |
| ↓ | |
| ├─ In-scope → Top-k Chunks → GPT-4o | |
| └─ Out-of-scope → Mixtral (funny fallback) | |
| ↓ | |
| Final Answer + Async Memory Update | |
| ``` | |
| --- | |
| ## 📂 Project Structure | |
| ``` | |
| . | |
| ├── app.py # Main Gradio app and pipeline logic | |
| ├── Vector_storing.py # Chunking, LLM-based enrichment, and FAISS store creation | |
| ├── requirements.txt # Python package dependencies | |
| ├── faiss_store/ # Saved FAISS vector index | |
| ├── all_chunks.json # JSON of enriched document chunks | |
| ├── personal_data/ # Source markdown files (right now excluded) | |
| ├── README.md | |
| ``` | |
| --- | |
| ## 🧠 Knowledge Sources | |
| All answers are grounded in curated markdown files: | |
| | File Name | Description | | |
| | ------------------------- | ---------------------------------------------- | | |
| | `profile.md` | Krishna’s full technical profile and education | | |
| | `goals.md` | Short- and long-term personal goals | | |
| | `chatbot_architecture.md` | System-level breakdown of this AI assistant | | |
| | `personal_interests.md` | Hobbies, cultural identity, food preferences | | |
| | `conversations.md` | Sample queries and expected response tone | | |
| --- | |
| ## 🧪 How It Works | |
| 1. **User input** is rewritten into subqueries (LLM1) | |
| 2. **Retriever** fetches relevant chunks using BM25 and FAISS | |
| 3. **Classifier LLM** decides if results are relevant to Krishna | |
| 4. **GPT-4o** generates final answer using top-k chunks | |
| 5. **Memory is updated** asynchronously with every turn | |
| --- | |
| ## 💬 Example Queries | |
| - What programming languages does Krishna know? | |
| - Tell me about Krishna’s chatbot architecture | |
| - Can this chatbot explain Krishna's work at Virginia Tech? | |
| - What tools has Krishna used for data engineering? | |
| --- | |
| ## 🚀 Setup & Usage | |
| ```bash | |
| # 1. Clone the repo | |
| git clone https://github.com/krishna-creator/krishna-personal-chatbot.git | |
| cd krishna-personal-chatbot | |
| # 2. Install dependencies | |
| pip install -r requirements.txt | |
| # 3. Set your API keys (OpenAI, NVIDIA) | |
| export OPENAI_API_KEY=... | |
| export NVIDIA_API_KEY=... | |
| # 4. Launch the chatbot | |
| python app.py | |
| ``` | |
| --- | |
| ## 🔮 Model Stack | |
| | Purpose | Model Name | Provider | | |
| | ------------------ | ------------------------ | -------- | | |
| | Query Rewriting | `phi-3-mini-4k-instruct` | NVIDIA | | |
| | Scope Classifier | `llama-3-70b-instruct` | NVIDIA | | |
| | Answer Generator | `gpt-4o` | OpenAI | | |
| | Fallback Humor LLM | `mixtral-8x22b-instruct` | NVIDIA | | |
| --- | |
| ## 📌 Acknowledgments | |
| - Built as part of Krishna's exploration into **LLM orchestration and agentic RAG** | |
| - Inspired by LangChain, SentenceTransformers, and NVIDIA RAG Agents Course | |
| --- | |
| ## 📜 License | |
| MIT License © Krishna Vamsi Dhulipalla | |