https://github.com/mohammad-nour-alawad/chatbot-rag-langchain-pinecone
A chatbot built with RAG, LangChain, and Pinecone as vector database, it utilized the mistral8x7b API from HuggingFace.
https://github.com/mohammad-nour-alawad/chatbot-rag-langchain-pinecone
chatbot huggingface langchain llm mistral nlp pinecone rag streamlit
Last synced: about 1 month ago
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A chatbot built with RAG, LangChain, and Pinecone as vector database, it utilized the mistral8x7b API from HuggingFace.
- Host: GitHub
- URL: https://github.com/mohammad-nour-alawad/chatbot-rag-langchain-pinecone
- Owner: mohammad-nour-alawad
- Created: 2024-08-03T02:11:48.000Z (9 months ago)
- Default Branch: main
- Last Pushed: 2024-08-03T02:26:34.000Z (9 months ago)
- Last Synced: 2025-02-01T17:12:59.276Z (3 months ago)
- Topics: chatbot, huggingface, langchain, llm, mistral, nlp, pinecone, rag, streamlit
- Language: Python
- Homepage:
- Size: 9.77 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
# Chatbot-RAG-LangChain-Pinecone
## Key Ideas and Techniques
- **Natural Language Processing**: Utilizes HuggingFace's language models to generate human-like responses.
- **Knowledge Base Search**: Implements a search mechanism using Pinecone to retrieve relevant context from a horoscope text file.
- **Web Interface**: Uses Streamlit to create an interactive web interface for users to chat with the bot.
## Installation
To set up the project locally, follow these steps:
1. **Clone the repository**:
```
git clone https://github.com/your-username/random-fortune-telling-bot.git
cd random-fortune-telling-bot
```
2. **Create and activate a virtual environment:**
```
python3 -m venv venv
source venv/bin/activate # On Windows, use `venv\Scripts\activate`
```
3. **Install dependencies:**
```
pip install -r requirements.txt
```
4. **Usage:** Please run it on **Linux**
```
export PINECONE_API_KEY=your_pinecone_api_key
export HUGGINGFACE_API_KEY=your_huggingface_api_key
```
then:
```
streamlit run app.py
```