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v0.5.0 — langchain-golang v0.6.2: reasoning effort & native JSON mode

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@HoweChen HoweChen released this 25 Aug 17:06
· 74 commits to main since this release
v0.5.0
06f624e

Highlight: langchain-golang v0.5.0 → v0.6.2

LadyM's LLM/LangGraph foundation jumps three releases (v0.6.0 → v0.6.1 → v0.6.2) and puts the new capabilities to work:

  • v0.6.0 — Python SDK parity completion: OpenAI tool_choice, native JSON mode / raw response_format passthrough, with_structured_output improvements, model token counting APIs, checkpoint saver management API, prebuilt react agent helpers.
  • v0.6.1 — token counting parity: real tiktoken BPE for OpenAI (cl100k_base / o200k_base, official vision-token formula), Anthropic /messages/count_tokens backing, usage-metadata-scaled approximate counting.
  • v0.6.2 — tiktoken-go/tokenizer v0.8.1. Requires Go ≥ 1.26 (LadyM already targets go 1.26.4).

What's new in LadyM

  • reasoning_effort config knob, plumbed end to end — steer OpenAI o-series / gpt-5 reasoning models (low | medium | high): 
    [llm]
reasoning_effort = "high"
    Also via LADYM_LLM_REASONING_EFFORT and per-operation [agents.<op>] overrides. Validated at provider construction; anthropic / ollama / http accept and ignore it.
  • OpenAI-native JSON mode for structured output — structured_method = "json_mode" now binds the provider-native response_format={"type":"json_object"} on OpenAI partner models (upstream enforcement) while retaining the schema system prompt, replacing the former prompt-only path. Non-OpenAI models are unchanged.

Verification

  • go build / go vet green on both editions (personal + -tags enterprise)
  • make test-all green: personal + live Postgres, enterprise, comment lint
  • Statement coverage 95.8% (personal + PG); providers 99.5%, config 99.1%
  • TDD throughout (RED witnessed per task); two per-task reviews + final whole-branch review: merge-ready

Full Changelog: v0.4.0...v0.5.0

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