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.
SUMMARY AI要約 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.
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| GitHub作成日 | 2026-05-10 |
| 最終Push | 2026-05-10 |
| 当サイト初検出 | 2026-05-10 |
| 最終取得 | 2026-05-10 16:11 |
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