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README.md

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----
-license: mit
----
+---
+license: mit
+---
+<p align="center">
+  <img src="public/paper-circle-logo.svg" alt="PaperCircle" width="140"/>
+</p>
+
+<h1 align="center">PaperCircle</h1>
+
+<p align="center">
+  <b>An Open-source Multi-agent Research Discovery and Analysis Framework</b>
+</p>
+
+<p align="center">
+  <a href="https://papercircle.vercel.app"><img src="https://img.shields.io/badge/Live_Demo-papercircle.vercel.app-blue?logo=vercel" alt="Live Demo"/></a>
+  <a href="https://arxiv.org/abs/2604.06170"><img src="https://img.shields.io/badge/arXiv-Paper-b31b1b?logo=arxiv" alt="arXiv"/></a>
+  <a href="https://huggingface.co/spaces/ItsMaxNorm/pc-bench"><img src="https://img.shields.io/badge/%F0%9F%A4%97-Benchmark-orange" alt="Benchmark"/></a>
+  <img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="MIT"/>
+</p>
+
+---
+
+> **Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework**
+>
+> Komal Kumar<sup>1</sup>, Aman Chadha<sup>2</sup>, Salman Khan<sup>1</sup>, Fahad Shahbaz Khan<sup>1</sup>, Hisham Cholakkal<sup>1</sup>
+>
+> <sup>1</sup> Mohamed bin Zayed University of Artificial Intelligence &nbsp; <sup>2</sup> AWS Generative AI Innovation Center, Amazon Web Services
+>
+> [[arXiv]](https://arxiv.org/abs/2604.06170) &nbsp; [[Live Demo]](https://papercircle.vercel.app) &nbsp; [[Benchmark]](https://huggingface.co/spaces/ItsMaxNorm/pc-bench)
+
+---
+
+## Architecture
+
+<p align="center">
+  <img src="assets/paperdig/main_arc.png" alt="PaperCircle Architecture" width="100%"/>
+</p>
+
+---
+
+## Results
+
+<p align="center">
+  <img src="assets/paperdig/output_results_qualitative.png" alt="PaperCircle Qualitative Results" width="100%"/>
+</p>
+
+Qualitative output of the Paper Mind Graph module: **(A)** Interactive mind map flowchart extracted from a paper, **(B)** Extracted concepts with descriptions and page references, **(C)** Natural language Q&A over paper content with figure references, **(D)** Detailed method and component descriptions, **(E)** Tab navigation across Flowchart, Concepts, Methods, Experiments, and Interactive Graph views.
+
+---
+
+## Features
+
+- **Paper Discovery** — Multi-agent AI search across arXiv, Scopus, and IEEE with hybrid BM25 + TF-IDF ranking and three discovery modes (Stable, Discovery, Balanced)
+- **Paper Mind Graph** — LLM-powered extraction of concepts, methods, and experiments into structured knowledge graphs with interactive Q&A
+- **Paper Review Generation** — Conference-format reviews (ICLR/NeurIPS/ICML style) via multi-agent analysis with lineage extraction
+- **Paper Lineage** — Relationship mapping (extends/applies/evaluates/contradicts/survey/prerequisite) with interactive graph visualization
+- **Reading Circles** — Community-based reading groups with role-based access, session scheduling, RSVP, and discussion threads
+
+---
+
+## Hugging Face Resources
+
+| Resource | Type | Link |
+|----------|------|------|
+| **Papers Database** | Dataset | [ItsMaxNorm/pc-database](https://huggingface.co/datasets/ItsMaxNorm/pc-database) |
+| **Papers API** | Space | [ItsMaxNorm/papercircle-papers-api](https://huggingface.co/spaces/ItsMaxNorm/papercircle-papers-api) |
+| **Benchmark Leaderboard** | Space | [ItsMaxNorm/pc-bench](https://huggingface.co/spaces/ItsMaxNorm/pc-bench) |
+| **Benchmark Results** | Dataset | [ItsMaxNorm/pc-benchmark](https://huggingface.co/datasets/ItsMaxNorm/pc-benchmark) |
+| **Research Sessions** | Dataset | [ItsMaxNorm/pc-research](https://huggingface.co/datasets/ItsMaxNorm/pc-research) |
+
+---
+
+## Getting Started
+
+### Prerequisites
+
+- **Node.js** >= 18 and **Python** >= 3.10
+- A [Supabase](https://supabase.com) project
+- An LLM provider: [Ollama](https://ollama.com) (local), OpenAI, or Anthropic
+
+### Install and Run
+
+```bash
+git clone https://github.com/MAXNORM8650/papercircle.git
+cd papercircle
+
+# Install
+npm install
+pip install -r backend/requirements-prod.txt
+
+# Configure
+cp .env.example .env   # Edit with your Supabase & LLM credentials
+
+# Run
+npm run dev                                  # Frontend (localhost:5173)
+python backend/apis/fast_discovery_api.py    # Discovery API (localhost:8000)
+python backend/apis/paper_review_server.py   # Review API (localhost:8005)
+python backend/apis/paper_analysis_api.py    # Analysis API (localhost:8006)
+```
+
+See [docs/QUICK_START.md](docs/QUICK_START.md) for detailed setup and [docs/DEPLOYMENT_GUIDE.md](docs/DEPLOYMENT_GUIDE.md) for production deployment.
+
+---
+
+## Project Structure
+
+```
+papercircle/
+├── src/                                  # Frontend (React 18 + TypeScript)
+│   ├── components/
+│   │   ├── Papers/                       #   Paper discovery, detail, analysis views
+│   │   ├── Lineage/                      #   Paper relationship graph & analysis hub
+│   │   ├── Sessions/                     #   Session scheduling, RSVP, attendance
+│   │   ├── Communities/                  #   Reading circle management
+│   │   ├── Dashboard/                    #   User dashboard
+│   │   ├── Auth/                         #   Authentication modals
+│   │   ├── Layout/                       #   Header, navigation
+│   │   ├── Admin/                        #   Admin panel
+│   │   └── Settings/                     #   LLM & user settings
+│   ├── contexts/                         #   AuthContext, CommunityContext, LineageAnalysisContext
+│   ├── lib/                              #   Supabase client, API helpers, arXiv client
+│   └── hooks/                            #   Custom React hooks
+│
+├── backend/
+│   ├── agents/
+│   │   ├── paper_review_agents/          #   Multi-agent review generation & benchmarking
+│   │   │   ├── orchestrator.py           #     Agent orchestration pipeline
+│   │   │   ├── specialized_agents.py     #     Critic, Literature, Reproducibility agents
+│   │   │   ├── benchmark_framework.py    #     Review benchmark framework
+│   │   │   ├── benchmark_paper_review.py #     Benchmark CLI
+│   │   │   ├── evaluation_metrics.py     #     MSE, MAE, correlation, accuracy metrics
+│   │   │   └── benchmark_results/        #     Cached benchmark outputs
+│   │   ├── paper_mind_graph/             #   Knowledge graph extraction from PDFs
+│   │   │   ├── graph_builder.py          #     LLM-based concept/method extraction
+│   │   │   ├── qa_system.py              #     Interactive Q&A over papers
+│   │   │   ├── ingestion.py              #     PDF parsing & chunking
+│   │   │   └── export.py                 #     JSON/Markdown/Mermaid/HTML export
+│   │   ├── discovery/                    #   Paper discovery agents & ranking
+│   │   └── agents/                       #   Core query & research agents
+│   ├── apis/
+│   │   ├── fast_discovery_api.py         #   Discovery API (port 8000)
+│   │   ├── paper_review_server.py        #   Review API (port 8005)
+│   │   ├── paper_analysis_api.py         #   Analysis API (port 8006)
+│   │   ├── community_papers_api.py       #   Community papers API
+│   │   ├── research_pipeline_api.py      #   Research pipeline API
+│   │   └── unified/                      #   Unified Docker API (app.py + routers/)
+│   ├── core/                             #   paperfinder.py, discovery_papers.py
+│   ├── services/                         #   HuggingFace papers client
+│   └── utils/                            #   Storage utilities
+│
+├── supabase/
+│   ├── migrations/                       #   55 SQL migrations (schema, RLS, seeds)
+│   └── functions/                        #   Edge functions (arxiv-search)
+│
+├── api/                                  # Vercel serverless functions
+│   ├── arxiv.js                          #   arXiv CORS proxy
+│   ├── community-papers.js              #   Community papers endpoint
+│   └── sync-status.js                   #   Sync status endpoint
+│
+├── scripts/                              # Utility scripts
+│   ├── javascript/                       #   arxiv-proxy, search engine, test scripts
+│   ├── shell/                            #   Start scripts for each API service
+│   └── *.py                              #   Dataset builder, sync, DB fixes
+│
+├── docs/                                 # Documentation
+│   ├── BENCHMARKS.md                     #   Benchmark guide (review + retrieval)
+│   ├── QUICK_START.md                    #   Quick start guide
+│   ├── DEPLOYMENT_GUIDE.md              #   Production deployment
+│   ├── SECURITY.md                       #   Security guidelines
+│   ├── MIGRATION_COMPLETE.md            #   Serverless migration summary
+│   └── PAPER_REVIEW_AGENTS_IMPLEMENTATION.md  # Review system implementation
+│
+├── examples/
+│   ├── pc-data/                          #   Benchmark datasets
+│   └── docs/                             #   Architecture & integration guides
+│       ├── ARCHITECTURE_DIAGRAMS.md      #     System diagrams
+│       ├── MULTI_AGENT_PIPELINE_ARCHITECTURE.md
+│       ├── ORCHESTRATOR_ARCHITECTURE.md
+│       ├── PAPER_MIND_GRAPH_ARCHITECTURE.md
+│       ├── AGENT_OPTIMIZATION_GUIDE.md
+│       ├── RERANKER_INTEGRATION_SUMMARY.md
+│       └── setup/                        #     Module setup & integration guides
+│
+├── hf_spaces/                            # HuggingFace Spaces (Papers API app)
+├── assets/                               # Architecture & results figures
+└── public/                               # Logo and static assets
+```
+
+---
+
+## Benchmarks
+
+Two evaluation suites: **Review Quality** (AI reviews vs human reviewers) and **Retrieval Quality** (paper search accuracy).
+
+| Benchmark | Metrics | Conferences | Details |
+|-----------|---------|-------------|---------|
+| **Paper Review** | MSE, MAE, Pearson r, Spearman ρ, Accuracy ±0.5/1.0/1.5 | ICLR, NeurIPS, ICML | [docs/BENCHMARKS.md](docs/BENCHMARKS.md) |
+| **Retrieval** | Recall@k, MRR, Success Rate | 30+ conferences | [docs/BENCHMARKS.md](docs/BENCHMARKS.md) |
+
+```bash
+# Review benchmark
+python backend/agents/paper_review_agents/benchmark_paper_review.py \
+  --data iclr2024.json --conference iclr --limit 100
+
+# Retrieval benchmark
+python benchmark_multiagent.py --queries queries.json --baseline bm25+reranker
+```
+
+Model results: [ItsMaxNorm/pc-benchmark](https://huggingface.co/datasets/ItsMaxNorm/pc-benchmark) &nbsp; Interactive leaderboard: [ItsMaxNorm/pc-bench](https://huggingface.co/spaces/ItsMaxNorm/pc-bench)
+
+---
+
+## Citation
+
+If you find PaperCircle useful in your research, please cite our paper:
+
+```bibtex
+misc{kumar2026papercircleopensourcemultiagent,
+      title={Paper Circle: An Open-source Multi-agent Research Discovery and Analysis Framework}, 
+      author={Komal Kumar and Aman Chadha and Salman Khan and Fahad Shahbaz Khan and Hisham Cholakkal},
+      year={2026},
+      eprint={2604.06170},
+      archivePrefix={arXiv},
+      primaryClass={cs.CL},
+      url={https://arxiv.org/abs/2604.06170}, 
+}
+```
+
+---
+
+## License
+
+MIT License — see [LICENSE](LICENSE)
+
+## Acknowledgments
+
+[arXiv](https://arxiv.org) &bull; [Supabase](https://supabase.com) &bull; [smolagents](https://github.com/huggingface/smolagents) &bull; [LiteLLM](https://github.com/BerriAI/litellm) &bull; [Ollama](https://ollama.com) &bull; [Hugging Face](https://huggingface.co)