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docs: Add README with examples for CocoIndex projects (#1273)
This README provides an overview of example projects for CocoIndex, including various indexing solutions and their features.
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examples/README.md

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# Examples
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This folder contains example CocoIndex projects, designed to help you learn CocoIndex features and inspire you to build powerful indexing solutions.
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Check out our [examples documentation](https://cocoindex.io/docs/examples) for more details.
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## Vector Search & Embedding
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- 📄 [**text_embedding**](./text_embedding) - Build text embedding index from local markdown files and perform semantic search
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- 📄 [**text_embedding_lancedb**](./text_embedding_lancedb) - Build text embedding index with LanceDB as vector database
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- 📄 [**text_embedding_qdrant**](./text_embedding_qdrant) - Build text embedding index with Qdrant as vector database
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- 📄 [**pdf_embedding**](./pdf_embedding) - Build embedding index from PDF files and query with natural language
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- 🖼️ [**image_search**](./image_search) - Build live image search using multimodal embedding models
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- 🖼️ [**pdf_elements_embedding**](./pdf_elements_embedding) - Extract text and images from PDFs and build multimodal search
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- 🖼️ [**multi_format_indexing**](./multi_format_indexing) - Build visual document index from PDFs and images with ColPali
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- 👤 [**face_recognition**](./face_recognition) - Recognize faces in images and build embedding index
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## Cloud Storage Sources
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- ☁️ [**amazon_s3_embedding**](./amazon_s3_embedding) - Build embedding index from Amazon S3 bucket with continuous sync
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- ☁️ [**azure_blob_embedding**](./azure_blob_embedding) - Build embedding index from Azure Blob Storage with continuous sync
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- ☁️ [**gdrive_text_embedding**](./gdrive_text_embedding) - Build embedding index from Google Drive files with real-time sync
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## Code & Documentation
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- 💻 [**code_embedding**](./code_embedding) - Build real-time index for codebase using Tree-sitter for syntax-aware chunking
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- 📚 [**docs_to_knowledge_graph**](./docs_to_knowledge_graph) - Build real-time knowledge graph from documents using LLM to extract relationships
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## Structured Data Extraction
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- 🏥 [**patient_intake_extraction**](./patient_intake_extraction) - Extract structured data from patient intake forms (PDF, Docx) using LLM
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- 🏥 [**patient_intake_extraction_baml**](./patient_intake_extraction_baml) - Extract structured data from patient intake PDFs using BAML
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- 📖 [**manuals_llm_extraction**](./manuals_llm_extraction) - Extract structured information from PDF manuals using Ollama
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- 📄 [**paper_metadata**](./paper_metadata) - Extract metadata (title, authors, abstract) from research papers in PDF
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## Custom Sources & Targets
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- 🌐 [**custom_source_hn**](./custom_source_hn) - Custom source example: index HackerNews content via API
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- 🌐 [**hn_trending_topics**](./hn_trending_topics) - Extract trending topics from HackerNews using LLM
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- 📝 [**custom_output_files**](./custom_output_files) - Export markdown files to local HTML with custom targets
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## Database Integration
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- 🗄️ [**postgres_source**](./postgres_source) - Use Postgres tables as source for CocoIndex flows
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## Production & Deployment
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- 🐳 [**fastapi_server_docker**](./fastapi_server_docker) - Run docker container with FastAPI query endpoint
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- 🔄 [**live_updates**](./live_updates) - Demonstrates live update feature to keep index synchronized with local directory
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## Recommendation Systems
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- 🛍️ [**product_recommendation**](./product_recommendation) - Build real-time recommendation engine with LLM and graph database
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---
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> **Note**: New to CocoIndex? Check out the [Getting Started](https://cocoindex.io/docs/getting_started) guide first!
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>
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> **Contribute**: We welcome contributions! Submit a [pull request](https://github.com/cocoindex-io/cocoindex/pulls) to add more examples.

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