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https://app.stepsecurity.io/secureworkflow/LearningCircuit/local-deep-research/osv-scanner.yml/main?enable=pin","Warn: third-party GitHubAction not pinned by hash: .github/workflows/release.yml:157: update your workflow using https://app.stepsecurity.io/secureworkflow/LearningCircuit/local-deep-research/release.yml/main?enable=pin","Warn: containerImage not pinned by hash: Dockerfile:4: pin your Docker image by updating python:3.13.9-slim to python:3.13.9-slim@sha256:326df678c20c78d465db501563f3492d17c42a4afe33a1f2bf5406a1d56b0e86","Warn: containerImage not pinned by hash: Dockerfile:39","Warn: containerImage not pinned by hash: Dockerfile:53","Warn: containerImage not pinned by hash: Dockerfile:149: pin your Docker image by updating python:3.13.9-slim to python:3.13.9-slim@sha256:326df678c20c78d465db501563f3492d17c42a4afe33a1f2bf5406a1d56b0e86","Warn: downloadThenRun not pinned by hash: Dockerfile:7-18","Warn: pipCommand not pinned by hash: Dockerfile:21","Warn: pipCommand not pinned by hash: Dockerfile:21","Warn: npmCommand not pinned by hash: Dockerfile:42","Warn: downloadThenRun not pinned by hash: Dockerfile:56-85","Warn: npmCommand not pinned by hash: Dockerfile:107","Warn: npmCommand not pinned by hash: Dockerfile:109","Warn: downloadThenRun not pinned by hash: examples/elasticsearch/test_elasticsearch.sh:60","Warn: npmCommand not pinned by hash: tests/run_followup_tests.sh:70","Warn: npmCommand not pinned by hash: tests/ui_tests/run_api_key_test.sh:27","Warn: pipCommand not pinned by hash: .github/workflows/check-env-vars.yml:33","Warn: pipCommand not pinned by hash: .github/workflows/checkov.yml:38","Warn: npmCommand not pinned by hash: .github/workflows/critical-ui-tests.yml:124","Warn: npmCommand not pinned by hash: .github/workflows/extended-ui-tests.yml:47","Warn: npmCommand not pinned by hash: .github/workflows/followup-research-tests.yml:50","Warn: pipCommand not pinned by hash: .github/workflows/fuzz.yml:40","Warn: pipCommand not pinned by hash: .github/workflows/fuzz.yml:41","Warn: npmCommand not pinned by hash: .github/workflows/infrastructure-tests.yml:38","Warn: npmCommand not pinned by hash: .github/workflows/metrics-analytics-tests.yml:52","Warn: pipCommand not pinned by hash: .github/workflows/mypy-type-check.yml:32","Warn: pipCommand not pinned by hash: .github/workflows/mypy-type-check.yml:40","Warn: pipCommand not pinned by hash: .github/workflows/mypy-type-check.yml:41","Warn: npmCommand not pinned by hash: .github/workflows/news-tests.yml:48","Warn: npmCommand not pinned by hash: .github/workflows/npm-audit.yml:48","Warn: npmCommand not pinned by hash: .github/workflows/npm-audit.yml:64","Warn: npmCommand not pinned by hash: .github/workflows/performance-tests.yml:188","Warn: npmCommand not pinned by hash: .github/workflows/publish.yml:51","Warn: pipCommand not pinned by hash: .github/workflows/publish.yml:121","Warn: pipCommand not pinned by hash: .github/workflows/publish.yml:310","Warn: pipCommand not pinned by hash: .github/workflows/semgrep.yml:34","Warn: npmCommand not pinned by hash: .github/workflows/tests.yml:199","Warn: npmCommand not pinned by hash: .github/workflows/tests.yml:33","Warn: npmCommand not pinned by hash: .github/workflows/tests.yml:78","Warn: npmCommand not pinned by hash: .github/workflows/ui-tests.yml:56","Warn: npmCommand not pinned by hash: .github/workflows/update-npm-dependencies.yml:61","Warn: pipCommand not pinned by hash: .github/workflows/update-precommit-hooks.yml:31","Warn: pipCommand not pinned by hash: .github/workflows/update-precommit-hooks.yml:32","Warn: pipCommand not pinned by hash: .github/workflows/zizmor-security.yml:47","Info: 145 out of 145 GitHub-owned GitHubAction dependencies pinned","Info:  50 out of  53 third-party GitHubAction dependencies pinned","Info:   0 out of   4 containerImage dependencies pinned","Info:   0 out of   3 downloadThenRun dependencies pinned","Info:   0 out of  15 pipCommand dependencies pinned","Info:   0 out of  20 npmCommand dependencies pinned"],"documentation":{"short":"Determines if the project has declared and pinned the dependencies of its build process.","url":"https://github.com/ossf/scorecard/blob/c22063e786c11f9dd714d777a687ff7c4599b600/docs/checks.md#pinned-dependencies"}},{"name":"Vulnerabilities","score":9,"reason":"1 existing vulnerabilities detected","details":["Warn: Project is vulnerable to: GHSA-f83h-ghpp-7wcc"],"documentation":{"short":"Determines if the project has open, known unfixed vulnerabilities.","url":"https://github.com/ossf/scorecard/blob/c22063e786c11f9dd714d777a687ff7c4599b600/docs/checks.md#vulnerabilities"}},{"name":"SAST","score":10,"reason":"SAST tool detected","details":["Info: SAST configuration detected: CodeQL","Info: SAST configuration detected: Hadolint","Info: SAST configuration detected: Hadolint","Warn: 29 commits out of 30 are checked with a SAST tool"],"documentation":{"short":"Determines if the project uses static code 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.github/workflows/container-security.yml:16"],"documentation":{"short":"Determines if the project is published as a package that others can easily download, install, easily update, and uninstall.","url":"https://github.com/ossf/scorecard/blob/c22063e786c11f9dd714d777a687ff7c4599b600/docs/checks.md#packaging"}},{"name":"Branch-Protection","score":5,"reason":"branch protection is not maximal on development and all release branches","details":["Info: 'allow deletion' disabled on branch 'main'","Info: 'force pushes' disabled on branch 'main'","Info: 'branch protection settings apply to administrators' is required to merge on branch 'main'","Info: 'stale review dismissal' is required to merge on branch 'main'","Warn: required approving review count is 1 on branch 'main'","Info: codeowner review is required on branch 'main'","Info: 'last push approval' is required to merge on branch 'main'","Warn: 'up-to-date branches' is disabled on branch 'main'","Info: status check found to merge onto on branch 'main'","Info: PRs are required in order to make changes on branch 'main'"],"documentation":{"short":"Determines if the default and release branches are protected with GitHub's branch protection settings.","url":"https://github.com/ossf/scorecard/blob/c22063e786c11f9dd714d777a687ff7c4599b600/docs/checks.md#branch-protection"}},{"name":"Signed-Releases","score":3,"reason":"2 out of the last 5 releases have a total of 2 signed artifacts.","details":["Info: signed release artifact: sbom-cyclonedx.json.sig: https://github.com/LearningCircuit/local-deep-research/releases/tag/v1.2.26","Warn: release artifact v1.2.25 not signed: https://api.github.com/repos/LearningCircuit/local-deep-research/releases/265846454","Warn: release artifact v1.2.24 not signed: https://api.github.com/repos/LearningCircuit/local-deep-research/releases/265596356","Warn: release artifact v1.2.23 not signed: https://api.github.com/repos/LearningCircuit/local-deep-research/releases/265588698","Info: provenance 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Local Deep Research\n\n\u003cdiv align=\"center\"\u003e\n\n[![GitHub stars](https://img.shields.io/github/stars/LearningCircuit/local-deep-research?style=for-the-badge)](https://github.com/LearningCircuit/local-deep-research/stargazers)\n[![Docker Pulls](https://img.shields.io/docker/pulls/localdeepresearch/local-deep-research?style=for-the-badge)](https://hub.docker.com/r/localdeepresearch/local-deep-research)\n[![PyPI Downloads](https://img.shields.io/pypi/dm/local-deep-research?style=for-the-badge)](https://pypi.org/project/local-deep-research/)\n\n[![Trendshift](https://trendshift.io/api/badge/repositories/14116)](https://trendshift.io/repositories/14116)\n\n[![Commits](https://img.shields.io/github/commit-activity/m/LearningCircuit/local-deep-research?style=for-the-badge)](https://github.com/LearningCircuit/local-deep-research/commits/main)\n[![Last Commit](https://img.shields.io/github/last-commit/LearningCircuit/local-deep-research?style=for-the-badge)](https://github.com/LearningCircuit/local-deep-research/commits/main)\n\n[![SimpleQA Accuracy](https://img.shields.io/badge/SimpleQA-~95%25_Accuracy-gold?style=for-the-badge)](https://github.com/LearningCircuit/ldr-benchmarks)\n[![SQLCipher](https://img.shields.io/badge/Database-SQLCipher_Encrypted-red?style=for-the-badge\u0026logo=sqlite\u0026logoColor=white)](docs/SQLCIPHER_INSTALL.md)\n\n\u003c!-- Well-known security scanners that visitors will recognize --\u003e\n[![OpenSSF Scorecard](https://api.securityscorecards.dev/projects/github.com/LearningCircuit/local-deep-research/badge)](https://securityscorecards.dev/viewer/?uri=github.com/LearningCircuit/local-deep-research)\n[![CodeQL](https://github.com/LearningCircuit/local-deep-research/actions/workflows/codeql.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/security/code-scanning)\n[![Semgrep](https://github.com/LearningCircuit/local-deep-research/actions/workflows/semgrep.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/semgrep.yml)\n\n[![🔧 Pre-commit](https://github.com/LearningCircuit/local-deep-research/actions/workflows/pre-commit.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/pre-commit.yml)\n\n[![🐳 Docker Publish](https://github.com/LearningCircuit/local-deep-research/actions/workflows/docker-publish.yml/badge.svg)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/docker-publish.yml)\n[![📦 PyPI Publish](https://github.com/LearningCircuit/local-deep-research/actions/workflows/publish.yml/badge.svg)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/publish.yml)\n\n[![Discord](https://img.shields.io/discord/1352043059562680370?style=for-the-badge\u0026logo=discord)](https://discord.gg/ttcqQeFcJ3)\n[![Reddit](https://img.shields.io/badge/Reddit-r/LocalDeepResearch-FF4500?style=for-the-badge\u0026logo=reddit)](https://www.reddit.com/r/LocalDeepResearch/)\n[![YouTube](https://img.shields.io/badge/YouTube-Channel-red?style=for-the-badge\u0026logo=youtube)](https://www.youtube.com/@local-deep-research)\n\n\n**AI-powered research assistant for deep, agentic research**\n\n*Performs deep, agentic research using multiple LLMs and search engines with proper citations*\n\n\u003ca href=\"https://www.youtube.com/watch?v=pfxgLX-MxMY\u0026t=1999\"\u003e\n  ▶️ Watch Review by The Art Of The Terminal\n\u003c/a\u003e\n\n\u003c/div\u003e\n\n## 🚀 What is Local Deep Research?\n\nAI research assistant you control. Run locally for privacy, use any LLM and build your own searchable knowledge base. You own your data and see exactly how it works.\n\n## ⚡ Quick Start\n\n\n\n**Option 1: Docker Run (Linux)**\n```bash\n# Step 1: Pull and run Ollama\ndocker run -d -p 11434:11434 --name ollama ollama/ollama\ndocker exec ollama ollama pull gpt-oss:20b\n\n# Step 2: Pull and run SearXNG for optimal search results\ndocker run -d -p 8080:8080 --name searxng searxng/searxng\n\n# Step 3: Pull and run Local Deep Research\ndocker run -d -p 5000:5000 --network host \\\n  --name local-deep-research \\\n  --volume \"deep-research:/data\" \\\n  -e LDR_DATA_DIR=/data \\\n  localdeepresearch/local-deep-research\n```\n\n**Option 2: Docker Compose**\n\nCPU-only (all platforms):\n```bash\ncurl -O https://raw.githubusercontent.com/LearningCircuit/local-deep-research/main/docker-compose.yml \u0026\u0026 docker compose up -d\n```\n\nWith NVIDIA GPU (Linux):\n```bash\ncurl -O https://raw.githubusercontent.com/LearningCircuit/local-deep-research/main/docker-compose.yml \u0026\u0026 \\\ncurl -O https://raw.githubusercontent.com/LearningCircuit/local-deep-research/main/docker-compose.gpu.override.yml \u0026\u0026 \\\ndocker compose -f docker-compose.yml -f docker-compose.gpu.override.yml up -d\n```\n\nOpen http://localhost:5000 after ~30 seconds. For GPU setup, environment variables, and more, see the [Docker Compose Guide](docs/docker-compose-guide.md).\n\n**Option 3: pip install**\n```bash\npip install local-deep-research\n```\n\u003e Works on Windows, macOS, and Linux. SQLCipher encryption is included via pre-built wheels — no compilation needed.\n\u003e PDF export on Windows requires Pango ([setup guide](https://doc.courtbouillon.org/weasyprint/stable/first_steps.html)).\n\u003e If you encounter issues with encryption, set `export LDR_BOOTSTRAP_ALLOW_UNENCRYPTED=true` to use standard SQLite instead.\n\n[More install options →](#-installation-options)\n\n## 🏗️ How It Works\n\n### Research\n\nYou ask a complex question. LDR:\n- Does the research for you automatically\n- Searches across web, academic papers, and your own documents\n- Synthesizes everything into a report with proper citations\n\nChoose from 20+ research strategies for quick facts, deep analysis, or academic research.\n\n**New: LangGraph Agent Strategy** — An autonomous agentic research mode where the LLM decides what to search, which specialized engines to use (arXiv, PubMed, Semantic Scholar, etc.), and when to synthesize. Early results are promising — it adaptively switches between search engines based on what it finds and collects significantly more sources than pipeline-based strategies. Select `langgraph-agent` in Settings to try it.\n\n### Build Your Knowledge Base\n\n```mermaid\nflowchart LR\n    R[Research] --\u003e D[Download Sources]\n    D --\u003e L[(Library)]\n    L --\u003e I[Index \u0026 Embed]\n    I --\u003e S[Search Your Docs]\n    S -.-\u003e R\n```\n\nEvery research session finds valuable sources. Download them directly into your encrypted library—academic papers from ArXiv, PubMed articles, web pages. LDR extracts text, indexes everything, and makes it searchable. Next time you research, ask questions across your own documents and the live web together. Your knowledge compounds over time.\n\n## 🛡️ Security\n\n\u003cdiv align=\"center\"\u003e\n\n\u003c!-- Static Analysis (additional scanners beyond CodeQL/Semgrep) --\u003e\n[![DevSkim](https://github.com/LearningCircuit/local-deep-research/actions/workflows/devskim.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/devskim.yml)\n[![Bearer](https://github.com/LearningCircuit/local-deep-research/actions/workflows/bearer.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/bearer.yml)\n\n\u003c!-- Dependency \u0026 Secrets Scanning --\u003e\n[![Gitleaks](https://github.com/LearningCircuit/local-deep-research/actions/workflows/gitleaks-main.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/gitleaks-main.yml)\n[![OSV-Scanner](https://github.com/LearningCircuit/local-deep-research/actions/workflows/osv-scanner.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/osv-scanner.yml)\n[![npm-audit](https://github.com/LearningCircuit/local-deep-research/actions/workflows/npm-audit.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/npm-audit.yml)\n[![Retire.js](https://github.com/LearningCircuit/local-deep-research/actions/workflows/retirejs.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/retirejs.yml)\n\n\u003c!-- Container Security --\u003e\n[![Container Security](https://github.com/LearningCircuit/local-deep-research/actions/workflows/container-security.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/container-security.yml)\n[![Dockle](https://github.com/LearningCircuit/local-deep-research/actions/workflows/dockle.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/dockle.yml)\n[![Hadolint](https://github.com/LearningCircuit/local-deep-research/actions/workflows/hadolint.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/hadolint.yml)\n[![Checkov](https://github.com/LearningCircuit/local-deep-research/actions/workflows/checkov.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/checkov.yml)\n\n\u003c!-- Workflow \u0026 Runtime Security --\u003e\n[![Zizmor](https://github.com/LearningCircuit/local-deep-research/actions/workflows/zizmor-security.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/zizmor-security.yml)\n[![OWASP ZAP](https://github.com/LearningCircuit/local-deep-research/actions/workflows/owasp-zap-scan.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/owasp-zap-scan.yml)\n[![Security Tests](https://github.com/LearningCircuit/local-deep-research/actions/workflows/security-tests.yml/badge.svg?branch=main)](https://github.com/LearningCircuit/local-deep-research/actions/workflows/security-tests.yml)\n\n\u003c/div\u003e\n\n```mermaid\nflowchart LR\n    U1[User A] --\u003e D1[(Encrypted DB)]\n    U2[User B] --\u003e D2[(Encrypted DB)]\n```\n\nYour data stays yours. Each user gets their own isolated SQLCipher database encrypted with AES-256 (Signal-level security). No password recovery means true zero-knowledge—even server admins can't read your data. Run fully local with Ollama + SearXNG and nothing ever leaves your machine.\n\n**In-memory credentials**: Like all applications that use secrets at runtime — including [password managers](https://www.ise.io/casestudies/password-manager-hacking/), browsers, and API clients — credentials are held in plain text in process memory during active sessions. This is an [industry-wide accepted reality](https://cheatsheetseries.owasp.org/cheatsheets/Secrets_Management_Cheat_Sheet.html), not specific to LDR: if an attacker can read process memory, they can also read any in-process decryption key. We mitigate this with session-scoped credential lifetimes and core dump exclusion. Ideas for further improvements are always welcome via [GitHub Issues](https://github.com/LearningCircuit/local-deep-research/issues). See our [Security Policy](SECURITY.md) for details.\n\n**Supply Chain Security**: Docker images are signed with [Cosign](https://github.com/sigstore/cosign), include SLSA provenance attestations, and attach SBOMs. Verify with:\n```bash\ncosign verify localdeepresearch/local-deep-research:latest\n```\n\n**Security Transparency**: Scanner suppressions are documented with justifications in [Security Alerts Assessment](.github/SECURITY_ALERTS.md), [Scorecard Compliance](.github/SECURITY_SCORECARD.md), [Container CVE Suppressions](.trivyignore), and [SAST Rule Rationale](bearer.yml). Some alerts (Dependabot, code scanning) can only be dismissed or are very difficult to suppress outside the [GitHub Security tab](https://docs.github.com/en/code-security/dependabot/dependabot-alerts/viewing-and-updating-dependabot-alerts), so the files above do not cover every dismissed finding.\n\n[Detailed Architecture →](docs/architecture.md) | [Security Policy →](SECURITY.md) | [Security Review Process →](docs/SECURITY_REVIEW_PROCESS.md)\n\n### 🔒 Privacy \u0026 Data\n\nLocal Deep Research contains **no telemetry, no analytics, and no tracking**. We do not collect, transmit, or store any data about you or your usage. No analytics SDKs, no phone-home calls, no crash reporting, no external scripts. Usage metrics stay in your local encrypted database.\n\nThe only network calls LDR makes are ones **you** initiate: search queries (to engines you configure), LLM API calls (to your chosen provider), and notifications (only if you set up Apprise).\n\nSince we don't collect any usage data, we rely on you to tell us what works, what's broken, and what you'd like to see next — [bug reports](https://github.com/LearningCircuit/local-deep-research/issues), feature ideas, and even which features you love or never use all help us improve LDR.\n\n## 📊 Performance\n\n**~95% accuracy on SimpleQA benchmark** (preliminary results)\n- Tested with GPT-4.1-mini + SearXNG + focused-iteration strategy\n- Comparable to state-of-the-art AI research systems\n- Local models can achieve similar performance with proper configuration\n- [Community benchmarks \u0026 leaderboard →](https://github.com/LearningCircuit/ldr-benchmarks) | [Browse on Hugging Face →](https://huggingface.co/datasets/local-deep-research/ldr-benchmarks)\n\n## ✨ Key Features\n\n### 🔍 Research Modes\n- **Quick Summary** - Get answers in 30 seconds to 3 minutes with citations\n- **Detailed Research** - Comprehensive analysis with structured findings\n- **Report Generation** - Professional reports with sections and table of contents\n- **Document Analysis** - Search your private documents with AI\n\n### 🛠️ Advanced Capabilities\n- **[LangChain Integration](docs/LANGCHAIN_RETRIEVER_INTEGRATION.md)** - Use any vector store as a search engine\n- **[REST API](docs/api-quickstart.md)** - Authenticated HTTP access with per-user databases\n- **[Benchmarking](docs/BENCHMARKING.md)** - Test and optimize your configuration\n- **[Analytics Dashboard](docs/analytics-dashboard.md)** - Track costs, performance, and usage metrics\n- **[Journal Quality System](docs/journal-quality.md)** - Automatic journal reputation scoring with 212K+ indexed sources, predatory detection, and quality dashboard. Powered by [OpenAlex](https://openalex.org) (CC0), [DOAJ](https://doaj.org) (CC0), and [Stop Predatory Journals](https://predatoryjournals.org) (MIT).\n- **Real-time Updates** - WebSocket support for live research progress\n- **Export Options** - Download results as PDF or Markdown\n- **Research History** - Save, search, and revisit past research\n- **Adaptive Rate Limiting** - Intelligent retry system that learns optimal wait times\n- **Keyboard Shortcuts** - Navigate efficiently (ESC, Ctrl+Shift+1-5)\n- **Per-User Encrypted Databases** - Secure, isolated data storage for each user\n\n### 📰 News \u0026 Research Subscriptions\n- **Automated Research Digests** - Subscribe to topics and receive AI-powered research summaries\n- **Customizable Frequency** - Daily, weekly, or custom schedules for research updates\n- **Smart Filtering** - AI filters and summarizes only the most relevant developments\n- **Multi-format Delivery** - Get updates as markdown reports or structured summaries\n- **Topic \u0026 Query Support** - Track specific searches or broad research areas\n\n### 🌐 Search Sources\n\n#### Free Search Engines\n- **Academic**: arXiv, PubMed, Semantic Scholar\n- **General**: Wikipedia, SearXNG\n- **Technical**: GitHub, Elasticsearch\n- **Historical**: Wayback Machine\n- **News**: The Guardian, Wikinews\n\n#### Premium Search Engines\n- **Tavily** - AI-powered search\n- **Google** - Via SerpAPI or Programmable Search Engine\n- **Brave Search** - Privacy-focused web search\n\n#### Custom Sources\n- **Local Documents** - Search your files with AI\n- **LangChain Retrievers** - Any vector store or database\n- **Meta Search** - Combine multiple engines intelligently\n\nLDR respects `robots.txt` and identifies itself honestly when fetching web pages — no stealth or anti-detection techniques. In rare cases this means a page that blocks automated access won't be fetched, which we consider the right trade-off.\n\n[Full Search Engines Guide →](docs/search-engines.md)\n\n## 📦 Installation Options\n\nFor most users, the [Quick Start](#-quick-start) above is all you need.\n\n| Method | Best for | Guide |\n|--------|----------|-------|\n| Docker Compose | Most users (recommended) | [Docker Compose Guide](docs/docker-compose-guide.md) |\n| Docker | Minimal setup | [Installation Guide](docs/installation.md#docker) |\n| pip | Developers, Python integration | [pip Guide](docs/install-pip.md) |\n| Unraid | Unraid servers | [Unraid Guide](docs/deployment/unraid.md) |\n\n[All installation options →](docs/installation.md)\n\n## 💻 Usage Examples\n\n### Python API\n```python\nfrom local_deep_research.api import LDRClient, quick_query\n\n# Option 1: Simplest - one line research\nsummary = quick_query(\"username\", \"password\", \"What is quantum computing?\")\nprint(summary)\n\n# Option 2: Client for multiple operations\nclient = LDRClient()\nclient.login(\"username\", \"password\")\nresult = client.quick_research(\"What are the latest advances in quantum computing?\")\nprint(result[\"summary\"])\n```\n\n### HTTP API\n\n*The code example below shows the basic API structure - for working examples, see the link below*\n\n```python\nimport requests\nfrom bs4 import BeautifulSoup\n\n# Create session and authenticate\nsession = requests.Session()\nlogin_page = session.get(\"http://localhost:5000/auth/login\")\nsoup = BeautifulSoup(login_page.text, \"html.parser\")\nlogin_csrf = soup.find(\"input\", {\"name\": \"csrf_token\"}).get(\"value\")\n\n# Login and get API CSRF token\nsession.post(\"http://localhost:5000/auth/login\",\n            data={\"username\": \"user\", \"password\": \"pass\", \"csrf_token\": login_csrf})\ncsrf = session.get(\"http://localhost:5000/auth/csrf-token\").json()[\"csrf_token\"]\n\n# Make API request\nresponse = session.post(\"http://localhost:5000/api/start_research\",\n                       json={\"query\": \"Your research question\"},\n                       headers={\"X-CSRF-Token\": csrf})\n```\n\n🚀 **[Ready-to-use HTTP API Examples → examples/api_usage/http/](examples/api_usage/http/)**\n- ✅ **Automatic user creation** - works out of the box\n- ✅ **Complete authentication** with CSRF handling\n- ✅ **Result retry logic** - waits until research completes\n- ✅ **Progress monitoring** and error handling\n\n### Command Line Tools\n\n```bash\n# Run benchmarks from CLI\npython -m local_deep_research.benchmarks --dataset simpleqa --examples 50\n\n# Manage rate limiting\npython -m local_deep_research.web_search_engines.rate_limiting status\npython -m local_deep_research.web_search_engines.rate_limiting reset\n```\n\n## 🔗 Enterprise Integration\n\nConnect LDR to your existing knowledge base:\n\n```python\nfrom local_deep_research.api import quick_summary\n\n# Use your existing LangChain retriever\nresult = quick_summary(\n    query=\"What are our deployment procedures?\",\n    retrievers={\"company_kb\": your_retriever},\n    search_tool=\"company_kb\"\n)\n```\n\nWorks with: FAISS, Chroma, Pinecone, Weaviate, Elasticsearch, and any LangChain-compatible retriever.\n\n[Integration Guide →](docs/LANGCHAIN_RETRIEVER_INTEGRATION.md)\n\n## 🔌 MCP Server (Claude Integration)\n\nLDR provides an MCP (Model Context Protocol) server that allows AI assistants like Claude Desktop and Claude Code to perform deep research.\n\n\u003e ⚠️ **Security Note**: This MCP server is designed for **local use only** via STDIO transport (e.g., Claude Desktop). It has no built-in authentication or rate limiting. Do not expose over a network without implementing proper security controls. See the [MCP Security Guide](https://modelcontextprotocol.io/docs/concepts/security) for network deployment requirements.\n\n### Installation\n\n```bash\n# Install with MCP extras\npip install \"local-deep-research[mcp]\"\n```\n\n### Claude Desktop Configuration\n\nAdd to your `claude_desktop_config.json`:\n\n```json\n{\n  \"mcpServers\": {\n    \"local-deep-research\": {\n      \"command\": \"ldr-mcp\",\n      \"env\": {\n        \"LDR_LLM_PROVIDER\": \"openai\",\n        \"LDR_LLM_OPENAI_API_KEY\": \"sk-...\"\n      }\n    }\n  }\n}\n```\n\n### Claude Code Configuration\n\nAdd to your `.mcp.json` (project-level) or `~/.claude/mcp.json` (global):\n\n```json\n{\n  \"mcpServers\": {\n    \"local-deep-research\": {\n      \"command\": \"ldr-mcp\",\n      \"env\": {\n        \"LDR_LLM_PROVIDER\": \"ollama\",\n        \"LDR_LLM_OLLAMA_URL\": \"http://localhost:11434\"\n      }\n    }\n  }\n}\n```\n\n### Available Tools\n\n| Tool | Description | Duration | LLM Cost |\n|------|-------------|----------|----------|\n| `search` | Raw results from a specific engine (arxiv, pubmed, wikipedia, ...) | 5-30s | None |\n| `quick_research` | Fast research summary | 1-5 min | Yes |\n| `detailed_research` | Comprehensive analysis | 5-15 min | Yes |\n| `generate_report` | Full markdown report | 10-30 min | Yes |\n| `analyze_documents` | Search local collections | 30s-2 min | Yes |\n| `list_search_engines` | List available search engines | instant | None |\n| `list_strategies` | List research strategies | instant | None |\n| `get_configuration` | Get current config | instant | None |\n\n### Individual Search Engines\n\nThe `search` tool lets you query specific search engines directly and get raw results (title, link, snippet) — no LLM processing, no cost, fast. This is especially useful for **monitoring and subscriptions** where you want to check for new content regularly without burning LLM tokens.\n\n```\n# Search arXiv for recent papers\nsearch(query=\"transformer architecture improvements\", engine=\"arxiv\")\n\n# Search PubMed for medical literature\nsearch(query=\"CRISPR clinical trials 2024\", engine=\"pubmed\")\n\n# Search Wikipedia for quick facts\nsearch(query=\"quantum error correction\", engine=\"wikipedia\")\n\n# Search OpenClaw for legal case law\nsearch(query=\"copyright fair use precedents\", engine=\"openclaw\")\n\n# Use list_search_engines() to see all available engines\n```\n\n### Example Usage\n\n```\n\"Use quick_research to find information about quantum computing applications\"\n\"Search arxiv for recent papers on diffusion models\"\n\"Generate a detailed research report on renewable energy trends\"\n```\n\n## 📊 Performance \u0026 Analytics\n\n### Benchmark Results\nEarly experiments on small SimpleQA dataset samples:\n\n| Configuration | Accuracy | Notes |\n|--------------|----------|--------|\n| gpt-4.1-mini + SearXNG + focused_iteration | 90-95% | Limited sample size |\n| gpt-4.1-mini + Tavily + focused_iteration | 90-95% | Limited sample size |\n| gemini-2.0-flash-001 + SearXNG | 82% | Single test run |\n\nNote: These are preliminary results from initial testing. Performance varies significantly based on query types, model versions, and configurations. [Run your own benchmarks →](docs/BENCHMARKING.md)\n\n**Full community leaderboard:** The community maintains a growing collection of benchmark results across models, strategies, and search engines in a dedicated repo with CI-validated submissions and auto-generated leaderboards:\n\n- **[GitHub: LearningCircuit/ldr-benchmarks](https://github.com/LearningCircuit/ldr-benchmarks)** — submit your results here\n- **[Hugging Face: local-deep-research/ldr-benchmarks](https://huggingface.co/datasets/local-deep-research/ldr-benchmarks)** — browse leaderboards and download CSVs\n\n### Benchmark Contributors\n\nThanks to the community members who have contributed benchmark runs:\n\n\u003c!-- BENCHMARK_CONTRIBUTORS:START --\u003e\n\u003c!-- BENCHMARK_CONTRIBUTORS:END --\u003e\n\n[See all contributors →](https://github.com/LearningCircuit/ldr-benchmarks/blob/main/CONTRIBUTORS.md)\n\n### Built-in Analytics Dashboard\nTrack costs, performance, and usage with detailed metrics. [Learn more →](docs/analytics-dashboard.md)\n\n## 🤖 Supported LLMs\n\n### Local Models (via Ollama)\n- Llama 3, Mistral, Gemma, DeepSeek\n- LLM processing stays local (search queries still go to web)\n- No API costs\n\n### Cloud Models\n- OpenAI (GPT-4, GPT-3.5)\n- Anthropic (Claude 3)\n- Google (Gemini)\n- 100+ models via OpenRouter\n\n[Model Setup →](docs/env_configuration.md)\n\n## 📚 Documentation\n\n### Getting Started\n- [Installation Guide](docs/installation.md)\n- [Frequently Asked Questions](docs/faq.md)\n- [API Quickstart](docs/api-quickstart.md)\n- [Configuration Guide](docs/env_configuration.md)\n- [Full Configuration Reference](docs/CONFIGURATION.md)\n\n### Core Features\n- [All Features Guide](docs/features.md)\n- [Search Engines Guide](docs/search-engines.md)\n- [Analytics Dashboard](docs/analytics-dashboard.md)\n\n### Advanced Features\n- [LangChain Integration](docs/LANGCHAIN_RETRIEVER_INTEGRATION.md)\n- [Benchmarking System](docs/BENCHMARKING.md)\n- [Elasticsearch Setup](docs/elasticsearch_search_engine.md)\n- [SearXNG Setup](docs/SearXNG-Setup.md)\n\n### Development\n- [Docker Compose Guide](docs/docker-compose-guide.md)\n- [Development Guide](docs/developing.md)\n- [Security Guide](docs/security/CODEQL_GUIDE.md)\n- [Release Guide](docs/RELEASE_GUIDE.md)\n\n### Examples \u0026 Tutorials\n- [API Examples](examples/api_usage/)\n- [Benchmark Examples](examples/benchmarks/)\n- [Optimization Examples](examples/optimization/)\n\n## 📰 Featured In\n\n\u003e \"Local Deep Research **deserves special mention** for those who prioritize privacy... **tuned to use open-source LLMs** that can run on consumer GPUs or even CPUs. Journalists, researchers, or companies with sensitive topics can investigate information **without queries ever hitting an external server**.\"\n\u003e\n\u003e — [Medium: Open-Source Deep Research AI Assistants](https://medium.com/@leucopsis/open-source-deep-research-ai-assistants-157462a59c14)\n\n### News \u0026 Articles\n- [Korben.info](https://korben.info/local-deep-research-alternative-gratuite-recherche-ia-sourcee.html) - French tech blog (\"Sherlock Holmes numérique\")\n- [Roboto.fr](https://www.roboto.fr/blog/local-deep-research-l-alternative-open-source-gratuite-deep-research-d-openai) - \"L'alternative open-source gratuite à Deep Research d'OpenAI\"\n- [KDJingPai AI Tools](https://www.kdjingpai.com/en/local-deep-research/) - AI productivity tools coverage\n- [AI Sharing Circle](https://aisharenet.com/en/local-deep-research/) - AI resources coverage\n\n### Community Discussions\n- [Hacker News](https://news.ycombinator.com/item?id=43330164) - 190+ points, community discussion\n- [LangChain Twitter/X](https://x.com/LangChainAI/status/1901347759757902038) - Official LangChain promotion\n- [LangChain LinkedIn](https://www.linkedin.com/posts/langchain_local-deep-research-an-ai-research-activity-7307113456095137792-cXRH) - 400+ likes\n\n### International Coverage\n\n#### 🇨🇳 Chinese\n- [Juejin (掘金)](https://juejin.cn/post/7481604667589885991) - Developer community\n- [Cnblogs (博客园)](https://www.cnblogs.com/qife122/p/18955032) - Developer blogs\n- [GitHubDaily (Twitter/X)](https://x.com/GitHub_Daily/status/1900169979313741846) - Influential tech account\n- [Zhihu (知乎)](https://zhuanlan.zhihu.com/p/30886269290) - Tech community\n- [A姐分享](https://www.ahhhhfs.com/68713/) - AI resources\n- [CSDN](https://blog.csdn.net/gitblog_01198/article/details/147061415) - Installation guide\n- [NetEase (网易)](https://www.163.com/dy/article/JQKAS50205567BLV.html) - Tech news portal\n\n#### 🇯🇵 Japanese\n- [note.com: 調査革命：Local Deep Research徹底活用法](https://note.com/r7038xx/n/nb3b74debbb30) - Comprehensive tutorial\n- [Qiita: Local Deep Researchを試す](https://qiita.com/orca13/items/635f943287c45388d48f) - Docker setup guide\n- [LangChainJP (Twitter/X)](https://x.com/LangChainJP/status/1902918110073807073) - Japanese LangChain community\n\n#### 🇰🇷 Korean\n- [PyTorch Korea Forum](https://discuss.pytorch.kr/t/local-deep-research/6476) - Korean ML community\n- [GeekNews (Hada.io)](https://news.hada.io/topic?id=19707) - Korean tech news\n\n### Reviews \u0026 Analysis\n- [BSAIL Lab: How useful is Deep Research in Academia?](https://uflbsail.net/uncategorized/how-useful-is-deep-research-in-academia/) - Academic review by contributor [@djpetti](https://github.com/djpetti)\n- [The Art Of The Terminal: Use Local LLMs Already!](https://youtu.be/pfxgLX-MxMY?t=1999) - Comprehensive review of local AI tools, featuring LDR's research capabilities (embeddings now work!)\n\n### Related Projects\n- [SearXNG LDR-Academic](https://github.com/porespellar/searxng-LDR-academic) - Academic-focused SearXNG fork with 12 research engines (arXiv, Google Scholar, PubMed, etc.) designed for LDR\n- [DeepWiki Documentation](https://deepwiki.com/LearningCircuit/local-deep-research) - Third-party documentation and guides\n\n\u003e **Note:** Third-party projects and articles are independently maintained. We link to them as useful resources but cannot guarantee their code quality or security.\n\n## 🤝 Community \u0026 Support\n\n- [Discord](https://discord.gg/ttcqQeFcJ3) - Get help and share research techniques\n- [Reddit](https://www.reddit.com/r/LocalDeepResearch/) - Updates and showcases\n- [GitHub Issues](https://github.com/LearningCircuit/local-deep-research/issues) - Bug reports\n\n## 🚀 Contributing\n\nWe welcome contributions of all sizes — from typo fixes to new features. The key rule: **keep PRs small and atomic** (one change per PR). For larger changes, please open an issue or start a discussion first — we want to protect your time and make sure your effort leads to a successful merge rather than a misaligned PR. See our [Contributing Guide](CONTRIBUTING.md) to get started.\n\n## Acknowledgements\n\nLocal Deep Research is built on the work of many open-access initiatives, academic databases, and open-source projects. We are grateful to:\n\n### Academic \u0026 Research Data\n\n| Source | What It Provides | License |\n|--------|-----------------|---------|\n| [OpenAlex](https://openalex.org) | Academic metadata for ~280K sources and ~120K institutions, including DOAJ status | CC0 |\n| [DOAJ](https://doaj.org) | Directory of Open Access Journals — open-access verification (via OpenAlex) | CC0 |\n| [arXiv](https://arxiv.org) | Preprints in physics, mathematics, CS, and more | Various (see arXiv license) |\n| [PubMed / NCBI](https://pubmed.ncbi.nlm.nih.gov) | Biomedical and life sciences literature | Public domain (US Gov) |\n| [Semantic Scholar](https://www.semanticscholar.org) | Cross-discipline academic search with citation data | [Terms](https://www.semanticscholar.org/product/api/license) |\n| [NASA ADS](https://ui.adsabs.harvard.edu) | Astrophysics, physics, and astronomy papers | [Terms](https://ui.adsabs.harvard.edu/help/terms/) |\n| [Zenodo](https://zenodo.org) | Open research data, datasets, and software | Various per record |\n| [PubChem](https://pubchem.ncbi.nlm.nih.gov) | Chemistry and biochemistry database | Public domain (US Gov) |\n| [Stop Predatory Journals](https://predatoryjournals.org) | Predatory journal/publisher blacklist | MIT |\n| [JabRef](https://github.com/JabRef/abbrv.jabref.org) | Journal abbreviation database | CC0 |\n\n### Knowledge \u0026 Content Sources\n\n[Wikipedia](https://www.wikipedia.org) \u0026bull; [OpenLibrary](https://openlibrary.org) \u0026bull; [Project Gutenberg](https://www.gutenberg.org) \u0026bull; [GitHub](https://github.com) \u0026bull; [Stack Exchange](https://stackexchange.com) \u0026bull; [The Guardian](https://www.theguardian.com) \u0026bull; [Wayback Machine](https://web.archive.org)\n\n### Infrastructure \u0026 Frameworks\n\n[LangChain](https://github.com/hwchase17/langchain) \u0026bull; [Ollama](https://ollama.ai) \u0026bull; [SearXNG](https://searxng.org/) \u0026bull; [FAISS](https://github.com/facebookresearch/faiss)\n\n### Support Open Access\n\nThese projects run on donations and grants, not paywalls. If Local Deep Research is useful to you, consider giving back to the open-access ecosystem that makes it possible:\n\n- [arXiv](https://arxiv.org/about/give) — free preprints for physics, math, CS, and more\n- [PubMed / NLM](https://www.nlm.nih.gov/pubs/donations/donations.html) — open biomedical literature\n- [Wikipedia / Wikimedia](https://donate.wikimedia.org) — the free encyclopedia\n- [Internet Archive](https://archive.org/donate) — the Wayback Machine and open digital library\n- [DOAJ](https://doaj.org/support) — curating and verifying open-access journals worldwide\n- [OpenAlex](https://openalex.org) — open scholarly metadata (sponsored by [OurResearch](https://ourresearch.org))\n- [Project Gutenberg](https://www.gutenberg.org/donate/) — free ebooks since 1971\n\n## 📄 License\n\nMIT License - see [LICENSE](LICENSE) file.\n\n**Dependencies:** All third-party packages use permissive licenses (MIT, Apache-2.0, BSD, etc.) - see [allowlist](.github/workflows/dependency-review.yml#L50-L68)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flearningcircuit%2Flocal-deep-research","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Flearningcircuit%2Flocal-deep-research","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Flearningcircuit%2Flocal-deep-research/lists"}