https://github.com/aimaster-dev/langchain-agent
These #LangChain-powered apps include a Research Assistant that generates reports using web scraping and GPT-4o-mini, and Chat With Video, a #Streamlit app that #transcribes videos and enables content-based Q&A via #embeddings.
https://github.com/aimaster-dev/langchain-agent
ai-assistant chatbots content-analysis embeddings gpt-4o langchain-python nlp openai pinecone-db python research-assistant semantic-search streamlit summarization transcription vector-database video-qa web-scraping whisper-ai
Last synced: 3 months ago
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These #LangChain-powered apps include a Research Assistant that generates reports using web scraping and GPT-4o-mini, and Chat With Video, a #Streamlit app that #transcribes videos and enables content-based Q&A via #embeddings.
- Host: GitHub
- URL: https://github.com/aimaster-dev/langchain-agent
- Owner: aimaster-dev
- Created: 2025-05-27T06:57:51.000Z (4 months ago)
- Default Branch: main
- Last Pushed: 2025-05-27T07:10:45.000Z (4 months ago)
- Last Synced: 2025-06-03T14:50:51.546Z (4 months ago)
- Topics: ai-assistant, chatbots, content-analysis, embeddings, gpt-4o, langchain-python, nlp, openai, pinecone-db, python, research-assistant, semantic-search, streamlit, summarization, transcription, vector-database, video-qa, web-scraping, whisper-ai
- Language: Python
- Homepage:
- Size: 3.12 MB
- Stars: 6
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: Readme.md
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README
# Langchain Applications
## Research Assistant
This project aims to create a research assistant using LangChain and OpenAI's GPT-4o-mini model. The assistant can generate comprehensive research reports based on user-provided topics. The system utilizes web scraping, text summarization, and search query generation to gather and analyze information from various online sources.
- [Readme](./research-assistant/Readme.md)
## Chat With Video
This project is a Streamlit based application allows users to upload videos, transcribe their audio using OpenAI's Whisper, and create embeddings with LangChain-OpenAI and store the embeddings in Pinecone Vector DB for further querying. Users can then chat with the video content by selecting transcribed videos and asking questions.
- [Readme](./chat-with-video/Readme.md)