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Migrate a LangChain 0.3.x Python codebase to LangChain 1.0 / LangGraph 1.0 without breaking production — named breaking changes, codemod patterns, and a phased rollout.
Passed 22 of 22 test cases with the skill, and 12 of 22 without it.
and 16 more in the full report
10 fixed12 passed either way0 still failing0 broke
Tokens, turns and time describe resource use, not a dollar price.
One of 10 test cases the skill fixed. Same model, same prompt, with and without the skill.
When upgrading `langchain-anthropic` to 1.0, our deploy failed with `AttributeError: module 'anthropic' has no attribute 'AsyncAnthropic'`. Someone suggested upgrading `anthropic` to `anthropic>=0.3.0`. What exact dependency version pin must be added to `requirements.txt` to fix this peer conflict?
| Checked | Without skill | With skill |
|---|---|---|
| Specifies dependency constraint anthropic>=0.40,<1. | Missed | Passed |
The instructions your model reads when the skill loads.
The first deploy after pip install -U langchain crashes on import with:
ImportError: cannot import name 'ChatOpenAI' from 'langchain.chat_models'
Fix the import, restart, and the next error lands:
ImportError: cannot import name 'LLMChain' from 'langchain.chains'
AttributeError: module 'langchain.agents' has no attribute 'initialize_agent'
AttributeError: 'ConversationBufferMemory' object has no attribute 'save_context'
LangChain 1.0 removed four entire public-API surfaces in one release:
langchain.chat_models / langchain.llms (pain code P38).LLMChain family under langchain.chains (P39).ConversationBufferMemory and siblings under langchain.memory (P40).initialize_agent under langchain.agents (P41).Anything that inspected intermediate_steps also breaks because the tuple shape changed from (AgentAction, observation) to (ToolCall, observation) (P42).
This skill walks a reversible, phased migration:
langchain-anthropic 1.0 peer-pin against anthropic >= 0.40, P66).It covers 7 named breaking changes and typically touches 10–100 files in a mid-sized service.
The fix for the error above:
# BEFORE (0.3)
test cases passed, vs 12 / 22 without
More skills from the same source and nearby in the registry, with their headline benchmark lift.