headroom/OSS_PR_STRATEGY.md

2.2 KiB

Headroom OSS PR Strategy

Goal

Contribute to popular LangChain ecosystem repos to demonstrate Headroom's value and drive adoption.

Target Repos (Ranked by Priority)

Priority 1: langchain-ai/how_to_fix_your_context

  • What: LangChain's official repo of context management techniques
  • PR: Add 06-context-compression.ipynb notebook showing Headroom as technique #6
  • Why accept: They're curating techniques, not competing. Compression is genuinely different from pruning/summarization.
  • Status: IN PROGRESS

Priority 2: langchain-ai/langgraph docs/cookbook

  • What: Core LangGraph framework
  • PR: Add compress_tool_messages pre-model hook example
  • Issues it addresses: #3717 (ToolMessage overflow), #11405 (agent token limit), #2140 (127K tokens from plugin)
  • Status: DONE — compress_tool_messages() and create_compress_tool_messages_node() in headroom/integrations/langchain/langgraph.py

Priority 3: langchain-ai/deepagents (~17K stars)

  • What: LangChain's coding agent (like Claude Code but OSS)
  • PR: Integrate Headroom as compression backend (they already claim "automatic compression")
  • Status: TODO

Priority 4: langchain-ai/open-swe

  • What: Async coding agent that resolves GitHub issues
  • PR: Add optional Headroom compression for long-running tasks
  • Status: TODO

Priority 5: assafelovic/gpt-researcher

  • What: Autonomous research agent (explicitly cites token limits as motivation)
  • PR: Add Headroom to compress scraped web content before synthesis
  • Status: TODO

Priority 6: langchain-corecompress_messages utility

  • What: Core LangChain library
  • PR: Add compress_messages() alongside trim_messages()
  • Status: TODO (hardest to land, highest impact)