langchain/docs/api_reference/guide_imports.json

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{"ChatPromptTemplate": {"\ud83e\udd9c\ufe0f\ud83c\udfd3 LangServe": "https://python.langchain.com/docs/langserve/", "Conceptual guide": "https://python.langchain.com/docs/concepts/", "# Example": "https://python.langchain.com/docs/versions/migrating_chains/map_rerank_docs_chain/", "# Legacy": "https://python.langchain.com/docs/versions/migrating_chains/llm_router_chain/", "Load docs": "https://python.langchain.com/docs/versions/migrating_chains/conversation_retrieval_chain/", "# Basic example (short documents)": "https://python.langchain.com/docs/versions/migrating_chains/map_reduce_chain/", "How to add a semantic layer over graph database": "https://python.langchain.com/docs/how_to/graph_semantic/", "How to handle long text when doing extraction": "https://python.langchain.com/docs/how_to/extraction_long_text/", "How to add values to a chain's state": "https://python.langchain.com/docs/how_to/assign/", "How to do per-user retrieval": "https://python.langchain.com/docs/how_to/qa_per_user/", "How to track token usage in ChatModels": "https://python.langchain.com/docs/how_to/chat_token_usage_tracking/", "How to create a custom LLM class": "https://python.langchain.com/docs/how_to/custom_llm/", "How to inspect runnables": "https://python.langchain.com/docs/how_to/inspect/", "How to handle cases where no queries are generated": "https://python.langchain.com/docs/how_to/query_no_queries/", "How to use few shot examples in chat models": "https://python.langchain.com/docs/how_to/few_shot_examples_chat/", "How to summarize text through iterative refinement": "https://python.langchain.com/docs/how_to/summarize_refine/", "How to do tool/function calling": "https://python.langchain.com/docs/how_to/function_calling/", "How to create tools": "https://python.langchain.com/docs/how_to/custom_tools/", "How to use prompting alone (no tool calling) to do extraction": "https://python.langchain.com/docs/how_to/extraction_parse/", "How to deal with large databases when doing SQL question-answering": "https://python.langchain.com/docs/how_to/sql_large_db/", "How to use reference examples when doing extraction": "https://python.langchain.com/docs/how_to/extraction_examples/", "How to handle multiple queries when doing query analysis": "https://python.langchain.com/docs/how_to/query_multiple_queries/", "How to add fallbacks to a runnable": "https://python.langchain.com/docs/how_to/fallbacks/", "How to propagate callbacks constructor": "https://python.langchain.com/docs/how_to/callbacks_constructor/", "How to map values to a graph database": "https://python.langchain.com/docs/how_to/graph_mapping/", "How to save and load LangChain objects": "https://python.langchain.com/docs/how_to/serialization/", "How to do question answering over CSVs": "https://python.langchain.com/docs/how_to/sql_csv/", "How to stream results from your RAG application": "https://python.langchain.com/docs/how_to/qa_streaming/", "How to get your RAG application to return sources": "https://python.langchain.com/docs/how_to/qa_sources/", "How to summarize text through parallelization": "https://python.langchain.com/docs/how_to/summarize_map_reduce/", "How to attach callbacks to a runnable": "https://python.langchain.com/docs/how_to/callbacks_attach/", "How to handle tool errors": "https://python.langchain.com/docs/how_to/tools_error/", "How to add tools to chatbots": "https://python.langchain.com/docs/how_to/chatbots_tools/", "How to add default invocation args to a Runnable": "https://python.langchain.com/docs/how_to/binding/", "How to convert Runnables as Tools": "https://python.langchain.com/docs/how_to/convert_runnable_to_tool/", "How to stream events from a tool": "https://python.langchain.com/docs/how_to/tool_stream_events/", "How to create a dynamic (self-constructing) chain": "https://python.langchain.com/docs/how_to/dynamic_chain/", "How to create custom callback handlers": "https://python.langchain.com/docs/how_to/custom_callbacks/", "How to stream runnables": "https://python.langchain.com/docs/how_to/streaming/", "How to invoke runnables in parallel": "https://pyth