alejandrorodriguezdelarosa-ux/asistia-rag-agente-conversacional
Agente RAG conversacional sobre IA Generativa con Google Gemini, ChromaDB y LangGraph. Memoria por thread, interfaz Streamlit y base de conocimiento propia. Práctica final del Máster en Data Science e IA.
SUMMARY AI summary by gpt-5-mini
AsistIA is a conversational RAG agent for Generative AI: a demo/advisor built with Google Gemini, ChromaDB, LangGraph/LangChain and persistent memory. Intended for students and developers (final project for a Master module), it answers Spanish queries grounded on a local vector knowledge base (three PDF docs) and keeps per-conversation memory. Key features: chunking via RecursiveCharacterTextSplitter, embeddings with Gemini, ChromaDB persistent collection (./chroma_db, top-3 cosine retrieval), MemorySaver-based thread memory, system prompt enforcing use of retrieved context and Spanish output, explicit fallback when context is missing, low temperature (0.3) for consistent technical answers. Repo includes a Jupyter notebook, optional Streamlit app, requirements and .env template.
DETECTED Detected AI stack
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The AI relevance score checks four places for AI keywords and adds the weight of each one that matches. Full methodology
Total AI relevance score: 90 / 100
Position among AI repos in the same language
We track 966 Jupyter Notebook repos, of which 715 score 40 or above on AI relevance. 22 have more stars than this one (top 2.4%), and 27 score higher (top 2.9%).
Owner
Profesional del marketing, el Data Science y la inteligencia artficial.
Dates
| Created on GitHub | 2026-05-11 |
| Last push | 2026-05-11 |
| First seen here | 2026-05-11 |
| Last fetched | 2026-08-18 16:23 |
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