langchain-py-pack

Wire LangChain 1.0 / LangGraph 1.0 tests into a GitHub Actions pipeline — unit tests with FakeListChatModel, VCR-gated integration tests, warning-filter policy, and eval-regression merge gates. Complements langchain-local-dev-loop (F23) which covers the inner loop; THIS covers the CI wire-up. Use when setting up GHA for a new LLM service, after a VCR cassette leak incident, or hardening an existing pipeline. Trigger with "langchain ci", "langchain github actions", "langchain test pipeline", "vcr ci", "langchain eval gate", "pytest -W error langchain".

Paste-match catalog of 14 real LangChain 1.0 / LangGraph 1.0 exceptions with named causes and named fixes, plus a triage decision tree. Use when you have a traceback and want the specific fix, not speculative documentation. Covers ImportError (0.2/0.3 → 1.0 migration), AttributeError on AIMessage.content, KeyError in LCEL and prompts, GraphRecursionError, silent thread_id memory loss, JSON-serialization crashes, and graphs that halt without reaching END. Trigger with "langchain error", "langgraph traceback", "OutputParserException", "GraphRecursionError", "ImportError langchain", "AttributeError AIMessage content".

Works correctly with LangChain 1.0's typed content blocks on AIMessage.content — text, tool_use, image, thinking, document — across Claude, GPT-4o, and Gemini, including multi-modal composition and tool-call iteration. Use when composing multi-modal messages, iterating tool_use blocks, handling Claude's thinking content, or unifying image inputs across providers. Trigger with "langchain content blocks", "AIMessage.content", "tool_use block", "claude image input", "langchain multimodal", "thinking block replay", "claude citations".

Compose LangChain 1.0 chains with RunnableParallel, RunnableBranch, RunnablePassthrough.assign, and RunnableLambda — correct input/output shapes, debug probes, and typed composition that catches dict-shape bugs before invocation. Use when wiring multi-step chains, parallel retrievals, conditional routing, or threading state through a chain for RAG, classification, or extraction pipelines. Trigger with "runnable parallel", "runnable branch", "langchain rag composition", "passthrough assign", "langchain lcel", "runnable lambda", "debug probe".

Control LangChain 1.0 AI spend with accurate streaming token accounting, model tiering, provider-specific cache hit tuning, per-tenant budgets, and retry dedup. Use when AI spend grows faster than traffic, a cost regression lands, or you need per-tenant budget enforcement. Trigger with "langchain cost", "langchain token accounting", "langchain per-tenant budget", "langchain model tiering", "prompt cache savings".