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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
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