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Tanishka158/FINSIGHT-LLM-Powered-News-Research-Assistant-for-Equity-Analysts

FinSight is an AI-powered financial news research platform that uses LLMs, NLP, semantic search, and RAG to analyze, summarize, and retrieve insights from financial news articles. Built with Python, Streamlit, LangChain, OpenAI APIs, and FAISS for intelligent document retrieval and analysis.

Python GitHub ↗
★ 0
stars
65
AI relevance
50
solo dev
0
tool sigs

SUMMARY AI summary by gpt-5-mini

FinSight is an open-source research assistant for equity analysts that ingests financial news, builds semantic indexes, and answers analyst queries using LLMs and retrieval-augmented generation (RAG). It’s implemented in Python with Streamlit for UI, LangChain for data flows, OpenAI embeddings/LLMs for semantic understanding, and FAISS for fast similarity search. Who uses it: equity analysts, financial researchers, or developers who need searchable summaries and source-linked answers from news articles. Key features: - Load single URLs or batch-upload text files of URLs - Fetch article content via LangChain’s UnstructuredURL loader - Create OpenAI embeddings and store them in a FAISS index - Perform semantic retrieval and RAG to answer queries - Return LLM responses with source URLs Basic install: clone repo, pip install -r requirements.txt, set OPENAI_API_KEY in a .env. Main files: main.py, requirements.txt, faiss_store_openai.pkl, .env.

DETECTED Detected AI stack

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🧠 LLM providers (1)
OpenAI
🧩 AI frameworks (1)
LangChain
🌐 Web frameworks (1)
Streamlit

Language breakdown (by bytes)

Python
100%

Owner

Account
Tanishka158
Type
User
Followers
0

Dates

Created on GitHub 2026-05-10
Last push 2026-05-10
First seen here 2026-05-10
Last fetched 2026-05-10 16:11

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