George He
Cofounder & CTO of CocoIndex
Posts by George He
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Turn Podcasts into a Knowledge Graph with LLM and CocoIndex
Build a pipeline that converts YouTube podcasts into a structured knowledge graph — extracting speakers, statements, and entities with LLM, then resolving duplicates with embeddings.
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From pickle to type-guided deserialization: safer Python serialization
How CocoIndex evolved from pickle to a type-guided serialization system that uses Python type hints to automatically choose the right serializer — no decorators or registration needed.
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Building an Invisible Daemon: Architecture Patterns for Local Developer Tools
Patterns for building local daemons that start on first use, upgrade transparently, and shut down cleanly — learned from building cocoindex-code's semantic search daemon.
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CocoIndex Changelog 0.3.27 - 0.3.34
Featuring five new target connectors, filesystem-level change detection, Python 3.14 free-threading, and smarter pipeline lifecycle management.
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CocoIndex Changelog 0.3.11 - 0.3.26
Featuring production-ready resilience, structured error system, expanded integrations, and always-fresh structured context for agents operating in the real world.
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CocoIndex Changelog 0.2.21 - 0.3.10
Featuring batching support for CocoIndex functions, execution robustness, schema & type system improvements, custom source support, and more.
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Adaptive Batching - 5x throughput on your data pipelines
CocoIndex now batches GPU and ML workloads automatically — 5x throughput on text embeddings and AI ops, with zero configuration required.
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CocoIndex Changelog 2025-10-19
Production-ready upgrades: durable execution, faster incremental processing over large datasets, GPU isolation, and richer native building blocks.
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Thinking in Rust: Ownership, Access, and Memory Safety
A mental framework for Rust's memory safety concepts. Think systematically about ownership, references, Send, Sync, and Rc, Arc, RefCell, Mutex, etc.
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Control Processing Concurrency in CocoIndex
Learn how CocoIndex's layered concurrency control features help you optimize data processing performance, prevent system overload, and ensure stable, efficient pipelines at scale.