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Feature/Bug: Implement missing Language.PERL separators and fix InMemoryCache maxsize update bug

langchain-ai/langchain#36750·146784·Python·31 天未动·5 条评论·上游最近活跃 ·池内状态:可认领
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上游 issue 正文

### Checked other resources - [x] This is a bug, not a usage question. - [x] I added a clear and descriptive title that summarizes this issue. - [x] I used the GitHub search to find a similar question and didn't find it. - [x] I am sure that this is a bug in LangChain rather than my code. - [x] The bug is not resolved by updating to the latest stable version of LangChain (or the specific integration package). - [x] This is not related to the langchain-community package. - [x] I posted a self-contained, minimal, reproducible example. A maintainer can copy it and run it AS IS. ### Package (Required) - [ ] langchain - [ ] langchain-openai - [ ] langchain-anthropic - [ ] langchain-classic - [x] langchain-core - [ ] langchain-model-profiles - [ ] langchain-tests - [x] langchain-text-splitters - [ ] langchain-chroma - [ ] langchain-deepseek - [ ] langchain-exa - [ ] langchain-fireworks - [ ] langchain-groq - [ ] langchain-huggingface - [ ] langchain-mistralai - [ ] langchain-nomic - [ ] langchain-ollama - [ ] langchain-openrouter - [ ] langchain-perplexity - [ ] langchain-qdrant - [ ] langchain-xai - [ ] Other / not sure / general ### Related Issues / PRs N/A ### Reproduction Steps / Example Code (Python) ```python # ---- Bug 1: Language.PERL not implemented ---- from langchain_text_splitters import RecursiveCharacterTextSplitter, Language try: # PERL exists in enum but is not implemented in separator logic RecursiveCharacterTextSplitter.from_language( Language.PERL, chunk_size=10, chunk_overlap=0 ) except ValueError as e: print(f"Bug 1 Error: {e}") # ---- Bug 2: InMemoryCache eviction bug ---- from langchain_core.caches import InMemoryCache cache = InMemoryCache(maxsize=2) cache.update("prompt_1", "llm_1", "val1") cache.update("prompt_2", "llm_2", "val2") # Cache is now at maxsize. # Updating an existing key SHOULD NOT evict another entry. cache.update("prompt_2", "llm_2", "val2_new_value") # Expected: prompt_1 still exists print("…
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