A RAG-based conversational AI for knowledge seekers and autodidactic learners.
ACTA · API MCP com ferramentas de integração entre IA, PostgreSQL, MongoDB e Qdrant · Inteligência Artificial
Premium full-stack monorepo RAG Q&A system for industrial documents. Built with React (Vite), FastAPI, Qdrant Cloud, Hugging Face Serverless, and Groq (Llama 3.1). Deployed on Vercel.
MCP server for Qdrant: manage Qdrant Cloud (clusters, backups, keys) and your data (collections, hybrid search, text memory) from Claude Code, Codex, Cursor or any MCP client.
Qdrant Essentials final project: hybrid retrieval, Qdrant Cloud, Context Engineering, and validated RAG over Qdrant documentation.
Semantic cache benchmark for Olostep web search using Qdrant Cloud Inference.
RAG chatbot demo (FastAPI + Qdrant + Ollama), cited-answer retrieval over PDF/DOCX/TXT, containerized with docker CI/CD
Chatbot administrable avec RAG (Qdrant) et tool-calling LLM réel - backend Symfony/API Platform, frontend Nuxt/Vue, modèles Ollama en local / Cloud
Real-time external memory and cognitive continuity layer for LLMs, autonomous agents, and model pretraining workflows. Built with zero PyTorch overhead using FastEmbed.
ReAct Framework agent in Python. 14 tools with AST-sandboxed code execution and SSRF-guarded fetching, multi-provider LLM failover, pluggable vector DBs (Pinecone/Weaviate/Qdrant), Redis caching, and independent validation of every answer. Graceful fallbacks throughout.
Multi-agent RAG copilot for enterprise documentation using Gradio, FastAPI, LangGraph, Qdrant Cloud, Anthropic Claude, and Langfuse.
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