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A newer version of the Streamlit SDK is available: 1.40.1

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metadata
title: BlogpostQA Retrieval Bot
emoji: ⚡
colorFrom: purple
colorTo: pink
sdk: streamlit
sdk_version: 1.38.0
app_file: app.py
pinned: false

Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

🤖 Chatbot with URL-based Document Retrieval

This Streamlit app is designed to provide a chatbot interface for querying content from a blog post URL. It utilizes various NLP models to retrieve and summarize relevant content based on user queries.

Features

  • URL Input: Allows users to input the URL of a blog post.
  • API Key Input: Users can either use pre-provided API keys or enter their own.
  • Chat Interface: Users can ask questions related to the content of the blog post.
  • Dynamic Styling: Includes colorful, animated backgrounds and a stylish sidebar.
  • Response Generation: Uses models to retrieve and summarize content related to the query.

Installation

To run this app, ensure you have Python installed, then install the necessary packages using the provided requirements.txt file.

  1. Clone the repository:

    git clone https://github.com/mldatascientist23/Generative_AI_Projects.git

  2. Navigate to the project directory:

    cd your-repository

  3. Create and activate a virtual environment (optional but recommended):

    python -m venv env
source env/bin/activate  # On Windows use: .\env\Scripts\activate

  4. Install the required packages:

    pip install -r requirements.txt

Usage

  1. Run the Streamlit app:

    streamlit run app.py

  2. Access the app: Open a web browser and navigate to https://huggingface.co/spaces/datascientist22/blogpostQA-retrieval-bot to interact with the chatbot.

Sidebar Configuration

  • Enter Blog Post URL: Input the URL of the blog post you want to retrieve data from.
  • Use pre-provided API keys: Check this box if you want to use pre-provided API keys. If unchecked, enter your own API keys.
  • API Key Fields: Enter your LangChain and Groq API keys if not using pre-provided keys.

Main Interface

  • Ask a question based on the blog post: Type your question in the input field and click "Submit Query" to get a response based on the content of the blog post.

Error Handling

  • URL Validation: Ensure that the URL is valid before submitting.
  • API Key Submission: Both API keys must be provided unless using pre-provided keys.

Notes

  • Ensure that the requirements.txt file includes the necessary libraries, such as streamlit, langchain, langchain_chroma, langchain_community, langchain_core, langchain_text_splitters, sentence_transformers, torch, and transformers.
  • The app uses the facebook/bart-large-cnn model for summarization, and SentenceTransformer for embedding.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Author

Feel free to open an issue or submit a pull request if you have any questions or suggestions!