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| title: MultiAgent Research Assistant | |
| emoji: 💬 | |
| colorFrom: yellow | |
| colorTo: purple | |
| sdk: gradio | |
| sdk_version: 5.0.1 | |
| app_file: app.py | |
| pinned: true | |
| license: apache-2.0 | |
| short_description: A MultiAgent research assistant and critique | |
| tags: | |
| - agent-demo-track | |
| Multi-Agent Research Assistant | |
| A powerful research assistant built using LangChain agents, LangGraph, and Hugging Face Transformers, designed to automate the research process across academic topics. This app retrieves papers, summarizes them, critiques findings, and generates a final synthesized report—all via coordinated AI agents. | |
| 🚀 Demo (Hugging Face Space) | |
| Enter your research topic and let the assistant do the heavy lifting. | |
| 🧩 Agents Overview | |
| Agent Description | |
| Retriever Queries ArXiv, Semantic Scholar, OpenAlex for relevant academic papers. | |
| Summarizer Extracts core ideas and results from each paper using Mistral-small. | |
| Critique Compares papers, detects contradictions, and flags hype/missing data. | |
| Synthesizer Generates a final report with structured summary and analysis. | |
| 🛠️ Tech Stack | |
| LangChain for agent orchestration | |
| Mistral models (Tiny, Small, Medium, Large) via Hugging Face Inference APIs | |
| FAISS for optional RAG (Retrieval-Augmented Generation) | |
| PDFPlumber for extracting full-text content | |
| Research APIs: ArXiv, Semantic Scholar, OpenAlex, PapersWithCode | |
| Gradio UI for simple user interaction | |
| An example chatbot using [Gradio](https://gradio.app), [`huggingface_hub`](https://huggingface.co/docs/huggingface_hub/v0.22.2/en/index), and the [Hugging Face Inference API](https://huggingface.co/docs/api-inference/index). |