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qna-system

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Md-Emon-Hasan / AutoDocThinker

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Agentic AI system that allows users to upload documents (PDFs, DOCX, etc.) and natural language questions. It uses LLM-based RAG to extract relevant information. The architecture includes multi-agent components such as document retrievers, summarizers, web searchers, and tool routers — enabling dynamic reasoning and accurate responses.

semantic-search document-retrieval ai-agents rag vector-search ai-assistant document-intelligence conversation-memory document-qa llm-apps llm-reasoning langgraph agentic-ai ai-document-search auto-document-analysis tool-usage-llm smart-document-search duckduckgo-tool qna-system planner-executor-agent
  • Updated Oct 3, 2025
  • Jupyter Notebook

sanikasalunke / AI-Customer-Support-Agent-with-RAG---Voice--Local-LLM---Local-TTS---Local-STT-

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AI Customer Support Agent with RAG + Voice A fully local, privacy-focused AI customer support system powered by open-source models. It supports multi-turn conversations, PDF/manual search (RAG), product recommendations, FAQ reasoning, and voice input/output using local STT + TTS. Built with Mistral 7B GGUF, FAISS, Whisper Tiny, Coqui TTS, FastAPI.

nlp text-to-speech customer-support speech-to-text whisper ai-agents conversational-ai faiss rag fastapi vector-search streamlit voice-ai coqui-tts llms local-llm mistral-7b voice-ai-agents qna-system
  • Updated Nov 18, 2025
  • Python

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