https://github.com/fosetorico/article_research_bot

End-to-End Research Bot for Summarizing and Extracting Insights from Multiple URLs using advanced text processing, FAISS vector storage, and OpenAI services for accurate and concise responses.
https://github.com/fosetorico/article_research_bot

faiss-vector-database genai-chatbot generative-ai gpt langchain large-language-model llm openai-api python research-bot streamlit vector-database-embedding

Last synced: 11 months ago
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End-to-End Research Bot for Summarizing and Extracting Insights from Multiple URLs using advanced text processing, FAISS vector storage, and OpenAI services for accurate and concise responses.

• Host: GitHub
• URL: https://github.com/fosetorico/article_research_bot
• Owner: fosetorico
• License: mit
• Created: 2024-07-01T17:35:46.000Z (over 1 year ago)
• Default Branch: main
• Last Pushed: 2025-02-04T14:27:57.000Z (about 1 year ago)
• Last Synced: 2025-02-04T15:29:49.949Z (about 1 year ago)
• Topics: faiss-vector-database, genai-chatbot, generative-ai, gpt, langchain, large-language-model, llm, openai-api, python, research-bot, streamlit, vector-database-embedding
• Language: Jupyter Notebook
• Homepage: https://huggingface.co/spaces/valleeneutral/article_research_bot
• Size: 638 KB
• Stars: 0
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# Research Bot for URL-Based Data Summarization and Insight Extraction

#### Link: https://huggingface.co/spaces/valleeneutral/article_research_bot

This project provides a robust research bot designed to assist users in summarizing and extracting meaningful insights from multiple URLs. By leveraging the capabilities of advanced text processing and vector storage, the bot ensures efficient data handling and insightful responses. The workflow involves loading data from URLs, splitting the data into manageable chunks, storing the data in a FAISS vector database, and responding to user prompts with accurate and concise summaries.

## Architechtural Overview

![arch_pix](https://github.com/fosetorico/tomato_disease_detection/assets/14139087/d06136c5-ae64-4c2f-9fe2-3eda2b80a352)

## Steps to run this Project?

#### 1. Clone the repository

```

git clone https://github.com/fosetorico/article_research_bot.git

```

#### 2. Create a conda environment after opening the repository

```

conda create -n your-chosen-name python=3.10 -y

```

```

conda activate your-chosen-name

```

#### 3. Rename the '.env.example' file to '.env' and insert your OpenAI key

#### 4. Install the requirements

```

pip install -r requirements.txt

```

#### 5. Finally run the following command

```

streamlit run app.py

```