https://github.com/digitalspy12/socialmedia_analyst_levelsupermind-hackathon_2024

This is Simple Social Media analyst which is langflow Ai system which uses RAG ( Retrieval-Augmented generation ) to analysis and retrieval information from document. Dataset is stored as astra DB. after data is upload in flow its split in chuck. default Open ai modal is used But you can use free ai model like ollama or Hugging face.
https://github.com/digitalspy12/socialmedia_analyst_levelsupermind-hackathon_2024

langflow rag social-media streamlit

Last synced: 4 months ago
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This is Simple Social Media analyst which is langflow Ai system which uses RAG ( Retrieval-Augmented generation ) to analysis and retrieval information from document. Dataset is stored as astra DB. after data is upload in flow its split in chuck. default Open ai modal is used But you can use free ai model like ollama or Hugging face.

• Host: GitHub
• URL: https://github.com/digitalspy12/socialmedia_analyst_levelsupermind-hackathon_2024
• Owner: Digitalspy12
• Created: 2025-01-03T05:46:10.000Z (6 months ago)
• Default Branch: main
• Last Pushed: 2025-01-03T10:16:06.000Z (6 months ago)
• Last Synced: 2025-02-16T17:50:19.158Z (4 months ago)
• Topics: langflow, rag, social-media, streamlit
• Language: Python
• Homepage:
• Size: 234 KB
• Stars: 1
• Watchers: 1
• Forks: 0
• Open Issues: 0
• Metadata Files:
  • Readme: README.md

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README

        

# Social Media Analysis Chatbot 

This Streamlit application provides a chatbot for analyzing social media content. It leverages the Langflow API to process user input and generate insights.

## Langflow 

![Screenshot from 2025-01-03 14-24-28](https://github.com/user-attachments/assets/5a378722-53e7-4fc8-81a6-0c041b719389)

## How Data is upload in database and Processing 

![Screenshot from 2025-01-03 14-24-44](https://github.com/user-attachments/assets/4a434c99-a49f-4f9c-b49e-988dfed8c882)

## Roadmap

```bash

1.Import json file in langflow

2. Edit open api Keys and create database and collection

3. Add the Dataset in file

4. Test in Playground

5. Generate Authication Token from langflow

6. Add main.py in code Editor and paste Token in

 .env

```

## Deployment

To run the code in terminal

```bash

  streamlit run ./main.py

```

## Demo 

[Screencast from 2025-01-01 19-03-30.webm](https://github.com/user-attachments/assets/667334fe-eb37-4276-a92e-2ab269fed790)

[Screencast from 2025-01-02 19-20-59.webm](https://github.com/user-attachments/assets/9c10f3cc-4cc0-4375-bbba-ee08d4b7a075)