https://github.com/davidskumar/langchain-chatbot-api
https://github.com/davidskumar/langchain-chatbot-api
Last synced: about 1 year ago
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- Host: GitHub
- URL: https://github.com/davidskumar/langchain-chatbot-api
- Owner: Davidskumar
- License: mit
- Created: 2025-02-08T18:42:27.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-08T20:19:07.000Z (over 1 year ago)
- Last Synced: 2025-02-08T20:23:26.286Z (over 1 year ago)
- Language: Python
- Size: 4.88 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# LangChain Chatbot API
This is a **Conversational AI Chatbot** built using **LangChain, Flask, and Hugging Face models**.
It retrieves technical courses from [Brainlox](https://brainlox.com/courses/category/technical) and allows users to ask questions via an API.
## 🚀 Features
- **Extracts Data** from a website using LangChain URL loaders
- **Stores Embeddings** in a vector database (ChromaDB)
- **Conversational AI** using `Mistral 7B` or other LLMs
- **Flask API** for user interactions
- **Deployed with Ngrok** for public access
- **Tested API** using Postman
## **Google Colab Notebook**
👉 [Run the chatbot in Google Colab](https://colab.research.google.com/drive/1z9EyV4KQq37De3YZFhRYpLFDOY60fcDQ?usp=sharing)
## 📌 Installation & Usage
1. Health Check
Method: GET
URL: https://your-ngrok-url.ngrok.io/health
Response:
{
"status": "ready"
}
2. Chat with the AI
Method: POST
URL: https://your-ngrok-url.ngrok.io/chat
or /test_qa_chain or /test_model
Headers:
{
"Content-Type": "application/json"
}
Request Body:
{
"message": "Tell me about technical courses."
}
Response:
{
"response": "Here’s a list of technical courses: Data Science, AI, Web Development..."
}
## Sample Output Screenshot
Here’s an example of the chatbot's response:
