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docs: Replaced SqliteSaver with MemorySaver and updated installation instru… (#25285)
…ctions to match LangGraph v2 documentation. Corrected code snippet to prevent validation errors. Here's how you can fill out the provided template for your pull request: --- **Thank you for contributing to LangChain!** - [ ] **PR title**: `docs: update checkpointer example in Conversational RAG tutorial` - [ ] **PR message**: - **Description:** Updated the Conversational RAG tutorial to correct the checkpointer example by replacing `SqliteSaver` with `MemorySaver`. Added installation instructions for `langgraph-checkpoint-memory` to match LangGraph v2 documentation and prevent validation errors. - **Issue:** N/A - **Dependencies:** `langgraph-checkpoint-memory` - **Twitter handle:** N/A - [ ] **Add tests and docs**: 1. No new integration tests are required. 2. Updated documentation in the Conversational RAG tutorial. - [ ] **Lint and test**: Run `make format`, `make lint` and `make test` from the root of the package(s) you've modified. See contribution guidelines for more: [LangChain Contribution Guidelines](https://python.langchain.com/docs/contributing/) Additional guidelines: - Make sure optional dependencies are imported within a function. - Please do not add dependencies to pyproject.toml files (even optional ones) unless they are required for unit tests. - Most PRs should not touch more than one package. - Changes should be backwards compatible. - If you are adding something to community, do not re-import it in langchain. If no one reviews your PR within a few days, please @-mention one of baskaryan, efriis, eyurtsev, ccurme, vbarda, hwchase17.
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@ -857,9 +857,9 @@
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"metadata": {},
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"metadata": {},
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"outputs": [],
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"outputs": [],
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"source": [
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"source": [
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"from langgraph.checkpoint.sqlite import SqliteSaver\n",
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"from langgraph.checkpoint.memory import MemorySaver\n",
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"\n",
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"\n",
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"memory = SqliteSaver.from_conn_string(\":memory:\")\n",
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"memory = MemorySaver()\n",
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"\n",
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"\n",
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"agent_executor = create_react_agent(llm, tools, checkpointer=memory)"
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"agent_executor = create_react_agent(llm, tools, checkpointer=memory)"
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]
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]
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"from langchain_core.runnables.history import RunnableWithMessageHistory\n",
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"from langchain_core.runnables.history import RunnableWithMessageHistory\n",
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"from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
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"from langchain_openai import ChatOpenAI, OpenAIEmbeddings\n",
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"from langchain_text_splitters import RecursiveCharacterTextSplitter\n",
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"from langchain_text_splitters import RecursiveCharacterTextSplitter\n",
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"from langgraph.checkpoint.sqlite import SqliteSaver\n",
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"from langgraph.checkpoint.memory import MemorySaver\n",
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"from langgraph.prebuilt import create_react_agent\n",
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"from langgraph.prebuilt import create_react_agent\n",
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"\n",
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"\n",
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"memory = SqliteSaver.from_conn_string(\":memory:\")\n",
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"memory = MemorySaver()\n",
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"llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n",
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"llm = ChatOpenAI(model=\"gpt-3.5-turbo\", temperature=0)\n",
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"\n",
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"\n",
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"\n",
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"\n",
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