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Multi-Modal LLM using Anthropic model for image reasoning </span> <span class="md-nav__icon md-icon"></span> </label> <a href="./" class="md-nav__link md-nav__link--active"> <span class="md-ellipsis"> Multi-Modal LLM using Anthropic model for image reasoning </span> </a> <nav class="md-nav md-nav--secondary" aria-label="Table of contents"> <label class="md-nav__title" for="__toc"> <span class="md-nav__icon md-icon"></span> Table of contents </label> <ul class="md-nav__list" data-md-component="toc" data-md-scrollfix> <li class="md-nav__item"> <a href="#use-anthropic-to-understand-images-from-local-directory" class="md-nav__link"> <span class="md-ellipsis"> Use Anthropic to understand Images from Local directory </span> </a> </li> <li class="md-nav__item"> <a href="#use-to-reason-images-from-urls" class="md-nav__link"> <span class="md-ellipsis"> Use to reason images from URLs </span> </a> </li> <li class="md-nav__item"> <a href="#structured-output-parsing-from-an-image" class="md-nav__link"> <span class="md-ellipsis"> Structured Output Parsing from an Image </span> </a> </li> <li class="md-nav__item"> <a href="#index-into-a-vector-store" class="md-nav__link"> <span class="md-ellipsis"> Index into a Vector Store </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item"> <a href="../azure_openai_multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal LLM using Azure OpenAI GPT-4V model for image reasoning </span> </a> </li> <li class="md-nav__item"> <a href="../cohere_multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal Retrieval using Cohere Multi-Modal Embeddings </span> </a> </li> <li class="md-nav__item"> <a href="../dashscope_multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal LLM using DashScope qwen-vl model for image reasoning </span> </a> </li> <li class="md-nav__item"> <a href="../gemini/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal LLM using Google's Gemini 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href="../llava_demo/" class="md-nav__link"> <span class="md-ellipsis"> LlaVa Demo with LlamaIndex </span> </a> </li> <li class="md-nav__item"> <a href="../llava_multi_modal_tesla_10q/" class="md-nav__link"> <span class="md-ellipsis"> Retrieval-Augmented Image Captioning </span> </a> </li> <li class="md-nav__item"> <a href="../mistral_multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal LLM using Mistral for image reasoning </span> </a> </li> <li class="md-nav__item"> <a href="../mm_agent/" class="md-nav__link"> <span class="md-ellipsis"> [Beta] Multi-modal ReAct Agent </span> </a> </li> <li class="md-nav__item"> <a href="../multi_modal_pydantic/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal GPT4V Pydantic Program </span> </a> </li> <li class="md-nav__item"> <a href="../multi_modal_rag_nomic/" class="md-nav__link"> <span class="md-ellipsis"> Multi-Modal RAG using Nomic Embed and Anthropic. </span> </a> </li> <li class="md-nav__item"> <a 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class="md-ellipsis"> Recency Filtering </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/SentenceTransformerRerank/" class="md-nav__link"> <span class="md-ellipsis"> SentenceTransformerRerank </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/TimeWeightedPostprocessorDemo/" class="md-nav__link"> <span class="md-ellipsis"> Time-Weighted Rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/VoyageAIRerank/" class="md-nav__link"> <span class="md-ellipsis"> VoyageAI Rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/openvino_rerank/" class="md-nav__link"> <span class="md-ellipsis"> OpenVINO Rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/rankGPT/" class="md-nav__link"> <span class="md-ellipsis"> RankGPT Reranker Demonstration (Van Gogh Wiki) </span> </a> </li> <li class="md-nav__item"> <a href="../../node_postprocessor/rankLLM/" class="md-nav__link"> <span class="md-ellipsis"> RankLLM Reranker Demonstration (Van Gogh Wiki) </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_24" > <label class="md-nav__link" for="__nav_4_24" id="__nav_4_24_label" tabindex="0"> <span class="md-ellipsis"> Object Stores </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_24_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_24"> <span class="md-nav__icon md-icon"></span> Object Stores </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../objects/object_index/" class="md-nav__link"> <span class="md-ellipsis"> The Class </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_25" > <label 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md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_26_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_26"> <span class="md-nav__icon md-icon"></span> Output Parsers </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../output_parsing/GuardrailsDemo/" class="md-nav__link"> <span class="md-ellipsis"> Guardrails Output Parsing </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/LangchainOutputParserDemo/" class="md-nav__link"> <span class="md-ellipsis"> Langchain Output Parsing </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/df_program/" class="md-nav__link"> <span class="md-ellipsis"> DataFrame Structured Data Extraction </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/evaporate_program/" class="md-nav__link"> <span class="md-ellipsis"> Evaporate Demo </span> </a> </li> <li class="md-nav__item"> <a 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class="md-nav__link"> <span class="md-ellipsis"> LM Format Enforcer Regular Expression Generation </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/nvidia_output_parsing/" class="md-nav__link"> <span class="md-ellipsis"> LLM Pydantic Program - NVIDIA </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/openai_pydantic_program/" class="md-nav__link"> <span class="md-ellipsis"> OpenAI Pydantic Program </span> </a> </li> <li class="md-nav__item"> <a href="../../output_parsing/openai_sub_question/" class="md-nav__link"> <span class="md-ellipsis"> OpenAI function calling for Sub-Question Query Engine </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_27" > <label class="md-nav__link" for="__nav_4_27" id="__nav_4_27_label" tabindex="0"> <span class="md-ellipsis"> Param Optimizer </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_27_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_27"> <span class="md-nav__icon md-icon"></span> Param Optimizer </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../param_optimizer/param_optimizer/" class="md-nav__link"> <span class="md-ellipsis"> [WIP] Hyperparameter Optimization for RAG </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_28" > <label class="md-nav__link" for="__nav_4_28" id="__nav_4_28_label" tabindex="0"> <span class="md-ellipsis"> Prompts </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_28_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_28"> <span class="md-nav__icon md-icon"></span> Prompts </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../prompts/advanced_prompts/" class="md-nav__link"> <span class="md-ellipsis"> Advanced Prompt Techniques (Variable Mappings, Functions) </span> </a> </li> <li class="md-nav__item"> <a href="../../prompts/emotion_prompt/" class="md-nav__link"> <span class="md-ellipsis"> EmotionPrompt in RAG </span> </a> </li> <li class="md-nav__item"> <a href="../../prompts/prompt_mixin/" class="md-nav__link"> <span class="md-ellipsis"> Accessing/Customizing Prompts within Higher-Level Modules </span> </a> </li> <li class="md-nav__item"> <a href="../../prompts/prompt_optimization/" class="md-nav__link"> <span class="md-ellipsis"> "Optimization by Prompting" for RAG </span> </a> </li> <li class="md-nav__item"> <a href="../../prompts/prompts_rag/" class="md-nav__link"> <span class="md-ellipsis"> Prompt Engineering for RAG </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_29" > <label class="md-nav__link" for="__nav_4_29" id="__nav_4_29_label" tabindex="0"> <span class="md-ellipsis"> Property Graph </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_29_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_29"> <span class="md-nav__icon md-icon"></span> Property Graph </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../property_graph/graph_store/" class="md-nav__link"> <span class="md-ellipsis"> Using a Property Graph Store </span> </a> </li> <li class="md-nav__item"> <a href="../../property_graph/property_graph_advanced/" class="md-nav__link"> <span class="md-ellipsis"> Property Graph Construction with Predefined Schemas </span> </a> </li> <li class="md-nav__item"> <a href="../../property_graph/property_graph_basic/" class="md-nav__link"> <span class="md-ellipsis"> Property Graph Index </span> </a> </li> <li class="md-nav__item"> <a href="../../property_graph/property_graph_custom_retriever/" class="md-nav__link"> <span class="md-ellipsis"> Defining a Custom Property Graph Retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../property_graph/property_graph_memgraph/" class="md-nav__link"> <span class="md-ellipsis"> Memgraph Property Graph Index </span> </a> </li> <li class="md-nav__item"> <a href="../../property_graph/property_graph_neo4j/" class="md-nav__link"> <span class="md-ellipsis"> Neo4j Property Graph Index </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_30" > <label class="md-nav__link" for="__nav_4_30" id="__nav_4_30_label" tabindex="0"> <span class="md-ellipsis"> Query Engines </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_30_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_30"> <span class="md-nav__icon md-icon"></span> Query Engines </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../query_engine/CustomRetrievers/" class="md-nav__link"> <span class="md-ellipsis"> Retriever Query Engine with Custom Retrievers - Simple Hybrid Search </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/JSONalyze_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> JSONalyze Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/JointQASummary/" class="md-nav__link"> <span class="md-ellipsis"> Joint QA Summary Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/RetrieverRouterQueryEngine/" class="md-nav__link"> <span class="md-ellipsis"> Retriever Router Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/RouterQueryEngine/" class="md-nav__link"> <span class="md-ellipsis"> Router Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/SQLAutoVectorQueryEngine/" class="md-nav__link"> <span class="md-ellipsis"> SQL Auto Vector Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/SQLJoinQueryEngine/" class="md-nav__link"> <span class="md-ellipsis"> SQL Join Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/SQLRouterQueryEngine/" class="md-nav__link"> <span class="md-ellipsis"> SQL Router Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/citation_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> CitationQueryEngine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/cogniswitch_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Cogniswitch query engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/custom_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Defining a Custom Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/ensemble_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Ensemble Query Engine Guide </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/flare_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> FLARE Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/json_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> JSON Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/knowledge_graph_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Knowledge Graph Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/knowledge_graph_rag_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Knowledge Graph RAG Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/multi_doc_auto_retrieval/multi_doc_auto_retrieval/" class="md-nav__link"> <span class="md-ellipsis"> Structured Hierarchical Retrieval </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/pandas_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Pandas Query Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/pdf_tables/recursive_retriever/" class="md-nav__link"> <span class="md-ellipsis"> Recursive Retriever + Query Engine Demo </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/pgvector_sql_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> [Beta] Text-to-SQL with PGVector </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/pydantic_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Query Engine with Pydantic Outputs </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/recursive_retriever_agents/" class="md-nav__link"> <span class="md-ellipsis"> Recursive Retriever + Document Agents </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/sec_tables/tesla_10q_table/" class="md-nav__link"> <span class="md-ellipsis"> Joint Tabular/Semantic QA over Tesla 10K </span> </a> </li> <li class="md-nav__item"> <a href="../../query_engine/sub_question_query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Sub Question Query Engine </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_31" > <label class="md-nav__link" for="__nav_4_31" id="__nav_4_31_label" tabindex="0"> <span class="md-ellipsis"> Query Pipeline </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_31_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_31"> <span class="md-nav__icon md-icon"></span> Query Pipeline </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline/" class="md-nav__link"> <span class="md-ellipsis"> An Introduction to LlamaIndex Query Pipelines </span> </a> </li> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline_async/" class="md-nav__link"> <span class="md-ellipsis"> Query Pipeline with Async/Parallel Execution </span> </a> </li> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline_memory/" class="md-nav__link"> <span class="md-ellipsis"> Query Pipeline Chat Engine </span> </a> </li> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline_pandas/" class="md-nav__link"> <span class="md-ellipsis"> Query Pipeline over Pandas DataFrames </span> </a> </li> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline_routing/" class="md-nav__link"> <span class="md-ellipsis"> Query Pipeline with Routing </span> </a> </li> <li class="md-nav__item"> <a href="../../pipeline/query_pipeline_sql/" class="md-nav__link"> <span class="md-ellipsis"> Query Pipeline for Advanced Text-to-SQL </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_4_32" > <label class="md-nav__link" for="__nav_4_32" id="__nav_4_32_label" tabindex="0"> <span class="md-ellipsis"> Query Transformations </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_4_32_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_4_32"> <span class="md-nav__icon md-icon"></span> Query Transformations </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../query_transformations/HyDEQueryTransformDemo/" class="md-nav__link"> <span class="md-ellipsis"> HyDE Query Transform </span> </a> </li> <li class="md-nav__item"> <a 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class="md-nav__link md-nav__container"> <a href="../../../api_reference/indices/" class="md-nav__link "> <span class="md-ellipsis"> Indexes </span> </a> <label class="md-nav__link " for="__nav_7_7" id="__nav_7_7_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_7_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_7"> <span class="md-nav__icon md-icon"></span> Indexes </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/indices/bge_m3/" class="md-nav__link"> <span class="md-ellipsis"> Bge m3 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/colbert/" class="md-nav__link"> <span class="md-ellipsis"> Colbert </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/dashscope/" class="md-nav__link"> <span class="md-ellipsis"> Dashscope </span> </a> </li> <li 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href="../../../api_reference/indices/property_graph/" class="md-nav__link"> <span class="md-ellipsis"> Property graph </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/summary/" class="md-nav__link"> <span class="md-ellipsis"> Summary </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/tree/" class="md-nav__link"> <span class="md-ellipsis"> Tree </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/vectara/" class="md-nav__link"> <span class="md-ellipsis"> Vectara </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/vector/" class="md-nav__link"> <span class="md-ellipsis"> Vector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/vertexai/" class="md-nav__link"> <span class="md-ellipsis"> Vertexai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/indices/zilliz/" class="md-nav__link"> <span class="md-ellipsis"> Zilliz </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_8" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/ingestion/" class="md-nav__link "> <span class="md-ellipsis"> Ingestion </span> </a> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_8_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_8"> <span class="md-nav__icon md-icon"></span> Ingestion </label> <ul class="md-nav__list" data-md-scrollfix> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_9" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/instrumentation/" class="md-nav__link "> <span class="md-ellipsis"> Instrumentation </span> </a> <label class="md-nav__link " for="__nav_7_9" id="__nav_7_9_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_9_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_9"> <span class="md-nav__icon md-icon"></span> Instrumentation </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/instrumentation/event_handlers/" class="md-nav__link"> <span class="md-ellipsis"> Event handlers </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/instrumentation/event_types/" class="md-nav__link"> <span class="md-ellipsis"> Event types </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/instrumentation/span_handlers/" class="md-nav__link"> <span class="md-ellipsis"> Span handlers </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/instrumentation/span_types/" class="md-nav__link"> <span class="md-ellipsis"> Span types </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_10" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/llms/" class="md-nav__link "> <span class="md-ellipsis"> LLMs </span> </a> <label class="md-nav__link " for="__nav_7_10" id="__nav_7_10_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_10_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_10"> <span class="md-nav__icon md-icon"></span> LLMs </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/llms/OptimumIntelLLM.md" class="md-nav__link"> <span class="md-ellipsis"> None </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/ai21/" class="md-nav__link"> <span class="md-ellipsis"> Ai21 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/alephalpha/" class="md-nav__link"> <span class="md-ellipsis"> Alephalpha </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/alibabacloud_aisearch/" class="md-nav__link"> <span class="md-ellipsis"> Alibabacloud aisearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/anthropic/" class="md-nav__link"> <span class="md-ellipsis"> Anthropic </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/anyscale/" class="md-nav__link"> <span class="md-ellipsis"> Anyscale </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/azure_inference/" class="md-nav__link"> <span class="md-ellipsis"> Azure inference </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/azure_openai/" class="md-nav__link"> <span class="md-ellipsis"> Azure openai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/bedrock/" class="md-nav__link"> <span class="md-ellipsis"> Bedrock </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/bedrock_converse/" class="md-nav__link"> <span class="md-ellipsis"> Bedrock converse </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/cerebras/" class="md-nav__link"> <span class="md-ellipsis"> Cerebras </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/clarifai/" class="md-nav__link"> <span class="md-ellipsis"> Clarifai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/cleanlab/" class="md-nav__link"> <span class="md-ellipsis"> Cleanlab </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/cohere/" class="md-nav__link"> <span class="md-ellipsis"> Cohere </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/custom_llm/" class="md-nav__link"> <span class="md-ellipsis"> Custom llm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/dashscope/" class="md-nav__link"> <span class="md-ellipsis"> Dashscope </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/databricks/" class="md-nav__link"> <span class="md-ellipsis"> Databricks </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/deepinfra/" class="md-nav__link"> <span class="md-ellipsis"> Deepinfra </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/everlyai/" class="md-nav__link"> <span class="md-ellipsis"> Everlyai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/fireworks/" class="md-nav__link"> <span class="md-ellipsis"> Fireworks </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/friendli/" class="md-nav__link"> <span class="md-ellipsis"> Friendli </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/gaudi/" class="md-nav__link"> <span class="md-ellipsis"> Gaudi </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/gemini/" class="md-nav__link"> <span class="md-ellipsis"> Gemini </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/gigachat/" class="md-nav__link"> <span class="md-ellipsis"> Gigachat </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/gradient.md" class="md-nav__link"> <span class="md-ellipsis"> None </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/groq/" class="md-nav__link"> <span class="md-ellipsis"> Groq </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/huggingface/" class="md-nav__link"> <span class="md-ellipsis"> Huggingface </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/huggingface_api/" class="md-nav__link"> <span class="md-ellipsis"> Huggingface api </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/ibm/" class="md-nav__link"> <span class="md-ellipsis"> Ibm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/ipex_llm/" class="md-nav__link"> <span class="md-ellipsis"> Ipex llm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/konko/" class="md-nav__link"> <span class="md-ellipsis"> Konko </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/langchain/" class="md-nav__link"> <span class="md-ellipsis"> Langchain </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/litellm/" class="md-nav__link"> <span class="md-ellipsis"> Litellm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/llama_api/" class="md-nav__link"> <span class="md-ellipsis"> Llama api </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/llama_cpp/" class="md-nav__link"> <span class="md-ellipsis"> Llama cpp </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/llamafile/" class="md-nav__link"> <span class="md-ellipsis"> Llamafile </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/lmstudio/" class="md-nav__link"> <span class="md-ellipsis"> Lmstudio </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/localai/" class="md-nav__link"> <span class="md-ellipsis"> Localai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/maritalk/" class="md-nav__link"> <span class="md-ellipsis"> Maritalk </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/mistral_rs/" class="md-nav__link"> <span class="md-ellipsis"> Mistral rs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/mistralai/" class="md-nav__link"> <span class="md-ellipsis"> Mistralai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/mlx/" class="md-nav__link"> <span class="md-ellipsis"> Mlx </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/modelscope/" class="md-nav__link"> <span class="md-ellipsis"> Modelscope </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/monsterapi/" class="md-nav__link"> <span class="md-ellipsis"> Monsterapi </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/mymagic/" class="md-nav__link"> <span class="md-ellipsis"> Mymagic </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/nebius/" class="md-nav__link"> <span class="md-ellipsis"> Nebius </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/neutrino/" class="md-nav__link"> <span class="md-ellipsis"> Neutrino </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/nvidia/" class="md-nav__link"> <span class="md-ellipsis"> Nvidia </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/nvidia_tensorrt/" class="md-nav__link"> <span class="md-ellipsis"> Nvidia tensorrt </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/nvidia_triton/" class="md-nav__link"> <span class="md-ellipsis"> Nvidia triton </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/oci_genai/" class="md-nav__link"> <span class="md-ellipsis"> Oci genai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/octoai/" class="md-nav__link"> <span class="md-ellipsis"> Octoai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/ollama/" class="md-nav__link"> <span class="md-ellipsis"> Ollama </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/openai/" class="md-nav__link"> <span class="md-ellipsis"> Openai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/openai_like/" class="md-nav__link"> <span class="md-ellipsis"> Openai like </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/openllm/" class="md-nav__link"> <span class="md-ellipsis"> Openllm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/openrouter/" class="md-nav__link"> <span class="md-ellipsis"> Openrouter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/openvino/" class="md-nav__link"> <span class="md-ellipsis"> Openvino </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/optimum_intel/" class="md-nav__link"> <span class="md-ellipsis"> Optimum intel </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/paieas/" class="md-nav__link"> <span class="md-ellipsis"> Paieas </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/palm/" class="md-nav__link"> <span class="md-ellipsis"> Palm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/perplexity/" class="md-nav__link"> <span class="md-ellipsis"> Perplexity </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/pipeshift/" class="md-nav__link"> <span class="md-ellipsis"> Pipeshift </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/portkey/" class="md-nav__link"> <span class="md-ellipsis"> Portkey </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/predibase/" class="md-nav__link"> <span class="md-ellipsis"> Predibase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/premai/" class="md-nav__link"> <span class="md-ellipsis"> Premai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/qianfan/" class="md-nav__link"> <span class="md-ellipsis"> Qianfan </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/reka/" class="md-nav__link"> <span class="md-ellipsis"> Reka </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/replicate/" class="md-nav__link"> <span class="md-ellipsis"> Replicate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/rungpt/" class="md-nav__link"> <span class="md-ellipsis"> Rungpt </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/sagemaker_endpoint/" class="md-nav__link"> <span class="md-ellipsis"> Sagemaker endpoint </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/sambanovasystems/" class="md-nav__link"> <span class="md-ellipsis"> Sambanovasystems </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/siliconflow/" class="md-nav__link"> <span class="md-ellipsis"> Siliconflow </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/solar/" class="md-nav__link"> <span class="md-ellipsis"> Solar </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/text_generation_inference/" class="md-nav__link"> <span class="md-ellipsis"> Text generation inference </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/together/" class="md-nav__link"> <span class="md-ellipsis"> Together </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/unify/" class="md-nav__link"> <span class="md-ellipsis"> Unify </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/upstage/" class="md-nav__link"> <span class="md-ellipsis"> Upstage </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/vertex/" class="md-nav__link"> <span class="md-ellipsis"> Vertex </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/vllm/" class="md-nav__link"> <span class="md-ellipsis"> Vllm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/xinference/" class="md-nav__link"> <span class="md-ellipsis"> Xinference </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/yi/" class="md-nav__link"> <span class="md-ellipsis"> Yi </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/you/" class="md-nav__link"> <span class="md-ellipsis"> You </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llms/zhipuai/" class="md-nav__link"> <span class="md-ellipsis"> Zhipuai </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_11" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/llama_dataset/" class="md-nav__link "> <span class="md-ellipsis"> Llama Datasets </span> </a> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_11_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_11"> <span class="md-nav__icon md-icon"></span> Llama Datasets </label> <ul class="md-nav__list" data-md-scrollfix> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_12" > <label class="md-nav__link" for="__nav_7_12" id="__nav_7_12_label" tabindex="0"> <span class="md-ellipsis"> Llama Deploy </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_12_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_12"> <span class="md-nav__icon md-icon"></span> Llama Deploy </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/apiserver/" class="md-nav__link"> <span class="md-ellipsis"> apiserver </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/control_plane/" class="md-nav__link"> <span class="md-ellipsis"> control_plane </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/deploy/" class="md-nav__link"> <span class="md-ellipsis"> deploy </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/message_consumers/" class="md-nav__link"> <span class="md-ellipsis"> message_consumers </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/message_publishers/" class="md-nav__link"> <span class="md-ellipsis"> message_publishers </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/messages/" class="md-nav__link"> <span class="md-ellipsis"> messages </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/orchestrators/" class="md-nav__link"> <span class="md-ellipsis"> orchestrators </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/python_sdk/" class="md-nav__link"> <span class="md-ellipsis"> Python SDK </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/services/" class="md-nav__link"> <span class="md-ellipsis"> services </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/llama_deploy/types/" class="md-nav__link"> <span class="md-ellipsis"> types </span> </a> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_12_11" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/llama_deploy/message_queues/" class="md-nav__link "> <span class="md-ellipsis"> message_queues </span> </a> <label class="md-nav__link " for="__nav_7_12_11" id="__nav_7_12_11_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" 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<input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_17" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/node_parsers/" class="md-nav__link "> <span class="md-ellipsis"> Node Parsers & Text Splitters </span> </a> <label class="md-nav__link " for="__nav_7_17" id="__nav_7_17_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_17_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_17"> <span class="md-nav__icon md-icon"></span> Node Parsers & Text Splitters </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/node_parser/alibabacloud_aisearch/" class="md-nav__link"> <span class="md-ellipsis"> Alibabacloud aisearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parser/dashscope/" class="md-nav__link"> <span class="md-ellipsis"> Dashscope 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href="../../../api_reference/node_parsers/langchain/" class="md-nav__link"> <span class="md-ellipsis"> Langchain </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/markdown/" class="md-nav__link"> <span class="md-ellipsis"> Markdown </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/markdown_element/" class="md-nav__link"> <span class="md-ellipsis"> Markdown element </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/semantic_splitter/" class="md-nav__link"> <span class="md-ellipsis"> Semantic splitter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/sentence_splitter/" class="md-nav__link"> <span class="md-ellipsis"> Sentence splitter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/sentence_window/" class="md-nav__link"> <span class="md-ellipsis"> Sentence window </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/token_text_splitter/" class="md-nav__link"> <span class="md-ellipsis"> Token text splitter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/node_parsers/unstructured_element/" class="md-nav__link"> <span class="md-ellipsis"> Unstructured element </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_18" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/postprocessor/" class="md-nav__link "> <span class="md-ellipsis"> Node Postprocessors </span> </a> <label class="md-nav__link " for="__nav_7_18" id="__nav_7_18_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_18_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_18"> <span class="md-nav__icon md-icon"></span> Node Postprocessors </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/NER_PII/" class="md-nav__link"> <span class="md-ellipsis"> NER PII </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/PII/" class="md-nav__link"> <span class="md-ellipsis"> PII </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/alibabacloud_aisearch_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Alibabacloud aisearch rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/auto_prev_next/" class="md-nav__link"> <span class="md-ellipsis"> Auto prev next </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/bedrock_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Bedrock rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/cohere_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Cohere rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/colbert_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Colbert rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/colpali_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Colpali rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/dashscope_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Dashscope rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/embedding_recency/" class="md-nav__link"> <span class="md-ellipsis"> Embedding recency </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/fixed_recency/" class="md-nav__link"> <span class="md-ellipsis"> Fixed recency </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/flag_embedding_reranker/" class="md-nav__link"> <span class="md-ellipsis"> Flag embedding reranker </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/jinaai_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Jinaai rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/keyword/" class="md-nav__link"> <span class="md-ellipsis"> Keyword </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/llm_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Llm rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/long_context_reorder/" class="md-nav__link"> <span class="md-ellipsis"> Long context reorder </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/longllmlingua/" class="md-nav__link"> <span class="md-ellipsis"> Longllmlingua </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/metadata_replacement/" class="md-nav__link"> <span class="md-ellipsis"> Metadata replacement </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/mixedbreadai_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Mixedbreadai rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/nvidia_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Nvidia rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/openvino_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Openvino rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/pinecone_native_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Pinecone native rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/presidio/" class="md-nav__link"> <span class="md-ellipsis"> Presidio </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/prev_next/" class="md-nav__link"> <span class="md-ellipsis"> Prev next </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/rankgpt_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Rankgpt rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/rankllm_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Rankllm rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/sbert_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Sbert rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/sentence_optimizer/" class="md-nav__link"> <span class="md-ellipsis"> Sentence optimizer </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/siliconflow_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Siliconflow rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/similarity/" class="md-nav__link"> <span class="md-ellipsis"> Similarity </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/tei_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Tei rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/time_weighted/" class="md-nav__link"> <span class="md-ellipsis"> Time weighted </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/voyageai_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Voyageai rerank </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/postprocessor/xinference_rerank/" class="md-nav__link"> <span class="md-ellipsis"> Xinference rerank </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_19" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/objects/" class="md-nav__link "> <span class="md-ellipsis"> Object Stores </span> </a> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_19_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_19"> <span class="md-nav__icon md-icon"></span> Object Stores </label> <ul class="md-nav__list" data-md-scrollfix> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_20" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/output_parsers/" class="md-nav__link "> <span class="md-ellipsis"> Output Parsers </span> </a> <label class="md-nav__link " for="__nav_7_20" id="__nav_7_20_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_20_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_20"> <span class="md-nav__icon md-icon"></span> Output Parsers </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/output_parsers/guardrails/" class="md-nav__link"> <span class="md-ellipsis"> Guardrails </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/output_parsers/langchain/" class="md-nav__link"> <span class="md-ellipsis"> Langchain </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/output_parsers/pydantic/" class="md-nav__link"> <span class="md-ellipsis"> Pydantic </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/output_parsers/selection/" class="md-nav__link"> <span class="md-ellipsis"> Selection </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_21" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/program/" class="md-nav__link "> <span class="md-ellipsis"> Programs </span> </a> <label class="md-nav__link " for="__nav_7_21" id="__nav_7_21_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_21_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_21"> <span class="md-nav__icon md-icon"></span> Programs </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/program/evaporate/" class="md-nav__link"> <span class="md-ellipsis"> Evaporate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/program/guidance/" class="md-nav__link"> <span class="md-ellipsis"> Guidance </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/program/llm_text_completion/" class="md-nav__link"> <span class="md-ellipsis"> Llm text completion </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/program/lmformatenforcer/" class="md-nav__link"> <span class="md-ellipsis"> Lmformatenforcer </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/program/multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi modal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/program/openai/" class="md-nav__link"> <span class="md-ellipsis"> Openai </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_22" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/prompts/" class="md-nav__link "> <span class="md-ellipsis"> Prompts </span> </a> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_22_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_22"> <span class="md-nav__icon md-icon"></span> Prompts </label> <ul class="md-nav__list" data-md-scrollfix> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_23" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/query_engine/" class="md-nav__link "> <span class="md-ellipsis"> Query Engines </span> </a> <label class="md-nav__link " for="__nav_7_23" id="__nav_7_23_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_23_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_23"> <span class="md-nav__icon md-icon"></span> Query Engines </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/FLARE/" class="md-nav__link"> <span class="md-ellipsis"> FLARE </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/JSONalayze/" class="md-nav__link"> <span class="md-ellipsis"> JSONalayze </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/NL_SQL_table/" class="md-nav__link"> <span class="md-ellipsis"> NL SQL table </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/PGVector_SQL/" class="md-nav__link"> <span class="md-ellipsis"> PGVector SQL </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/SQL_join/" class="md-nav__link"> <span class="md-ellipsis"> SQL join </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/SQL_table_retriever/" class="md-nav__link"> <span class="md-ellipsis"> SQL table retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/citation/" class="md-nav__link"> <span class="md-ellipsis"> Citation </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/cogniswitch/" class="md-nav__link"> <span class="md-ellipsis"> Cogniswitch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/custom/" class="md-nav__link"> <span class="md-ellipsis"> Custom </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/knowledge_graph/" class="md-nav__link"> <span class="md-ellipsis"> Knowledge graph </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/multi_step/" class="md-nav__link"> <span class="md-ellipsis"> Multi step </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/pandas/" class="md-nav__link"> <span class="md-ellipsis"> Pandas </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/retriever/" class="md-nav__link"> <span class="md-ellipsis"> Retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/retriever_router/" class="md-nav__link"> <span class="md-ellipsis"> Retriever router </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/retry/" class="md-nav__link"> <span class="md-ellipsis"> Retry </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/router/" class="md-nav__link"> <span class="md-ellipsis"> Router </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/simple_multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Simple multi modal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/sub_question/" class="md-nav__link"> <span class="md-ellipsis"> Sub question </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/tool_retriever_router/" class="md-nav__link"> <span class="md-ellipsis"> Tool retriever router </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_engine/transform/" class="md-nav__link"> <span class="md-ellipsis"> Transform </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_24" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/query_pipeline/" class="md-nav__link "> <span class="md-ellipsis"> Query Pipeline </span> </a> <label class="md-nav__link " for="__nav_7_24" id="__nav_7_24_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_24_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_24"> <span class="md-nav__icon md-icon"></span> Query Pipeline </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/agent/" class="md-nav__link"> <span class="md-ellipsis"> Agent </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/arg_pack/" class="md-nav__link"> <span class="md-ellipsis"> Arg pack </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/custom/" class="md-nav__link"> <span class="md-ellipsis"> Custom </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/function/" class="md-nav__link"> <span class="md-ellipsis"> Function </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/input/" class="md-nav__link"> <span class="md-ellipsis"> Input </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/llm/" class="md-nav__link"> <span class="md-ellipsis"> Llm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/multi_modal/" class="md-nav__link"> <span class="md-ellipsis"> Multi modal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/object/" class="md-nav__link"> <span class="md-ellipsis"> Object </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/output_parser/" class="md-nav__link"> <span class="md-ellipsis"> Output parser </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/postprocessor/" class="md-nav__link"> <span class="md-ellipsis"> Postprocessor </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/prompt/" class="md-nav__link"> <span class="md-ellipsis"> Prompt </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/query_engine/" class="md-nav__link"> <span class="md-ellipsis"> Query engine </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/query_transform/" class="md-nav__link"> <span class="md-ellipsis"> Query transform </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/retriever/" class="md-nav__link"> <span class="md-ellipsis"> Retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/router/" class="md-nav__link"> <span class="md-ellipsis"> Router </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/synthesizer/" class="md-nav__link"> <span class="md-ellipsis"> Synthesizer </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/query_pipeline/tool_runner/" class="md-nav__link"> <span class="md-ellipsis"> Tool runner </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_25" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/question_gen/" class="md-nav__link "> <span class="md-ellipsis"> Question Generators </span> </a> <label class="md-nav__link " for="__nav_7_25" id="__nav_7_25_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_25_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_25"> <span class="md-nav__icon md-icon"></span> Question Generators </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/question_gen/guidance/" class="md-nav__link"> <span class="md-ellipsis"> Guidance </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/question_gen/llm_question_gen/" class="md-nav__link"> <span class="md-ellipsis"> Llm question gen </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/question_gen/openai/" class="md-nav__link"> <span class="md-ellipsis"> Openai </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_26" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/readers/" class="md-nav__link "> <span class="md-ellipsis"> Readers </span> </a> <label class="md-nav__link " for="__nav_7_26" id="__nav_7_26_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_26_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_26"> <span class="md-nav__icon md-icon"></span> Readers </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/readers/agent_search/" class="md-nav__link"> <span class="md-ellipsis"> Agent search </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_cdk/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte cdk </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_gong/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte gong </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_hubspot/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte hubspot </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_salesforce/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte salesforce </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_shopify/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte shopify </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_stripe/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte stripe </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_typeform/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte typeform </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airbyte_zendesk_support/" class="md-nav__link"> <span class="md-ellipsis"> Airbyte zendesk support </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/airtable/" class="md-nav__link"> <span class="md-ellipsis"> Airtable </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/alibabacloud_aisearch/" class="md-nav__link"> <span class="md-ellipsis"> Alibabacloud aisearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/apify/" class="md-nav__link"> <span class="md-ellipsis"> Apify </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/arango_db/" class="md-nav__link"> <span class="md-ellipsis"> Arango db </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/arxiv/" class="md-nav__link"> <span class="md-ellipsis"> Arxiv </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/asana/" class="md-nav__link"> <span class="md-ellipsis"> Asana </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/assemblyai/" class="md-nav__link"> <span class="md-ellipsis"> Assemblyai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/astra_db/" class="md-nav__link"> <span class="md-ellipsis"> Astra db </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/athena/" class="md-nav__link"> <span class="md-ellipsis"> Athena </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/awadb/" class="md-nav__link"> <span class="md-ellipsis"> Awadb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/azcognitive_search/" class="md-nav__link"> <span class="md-ellipsis"> Azcognitive search </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/azstorage_blob/" class="md-nav__link"> <span class="md-ellipsis"> Azstorage blob </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/azure_devops/" class="md-nav__link"> <span class="md-ellipsis"> Azure devops </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/bagel/" class="md-nav__link"> <span class="md-ellipsis"> Bagel </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/bilibili/" class="md-nav__link"> <span class="md-ellipsis"> Bilibili </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/bitbucket/" class="md-nav__link"> <span class="md-ellipsis"> Bitbucket </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/boarddocs/" class="md-nav__link"> <span class="md-ellipsis"> Boarddocs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/box/" class="md-nav__link"> <span class="md-ellipsis"> Box </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/chatgpt_plugin/" class="md-nav__link"> <span class="md-ellipsis"> Chatgpt plugin </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/chroma/" class="md-nav__link"> <span class="md-ellipsis"> Chroma </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/clickhouse/" class="md-nav__link"> <span class="md-ellipsis"> Clickhouse </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/confluence/" class="md-nav__link"> <span class="md-ellipsis"> Confluence </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/couchbase/" class="md-nav__link"> <span class="md-ellipsis"> Couchbase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/couchdb/" class="md-nav__link"> <span class="md-ellipsis"> Couchdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/dad_jokes/" class="md-nav__link"> <span class="md-ellipsis"> Dad jokes </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/dashscope/" class="md-nav__link"> <span class="md-ellipsis"> Dashscope </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/dashvector/" class="md-nav__link"> <span class="md-ellipsis"> Dashvector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/database/" class="md-nav__link"> <span class="md-ellipsis"> Database </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/deeplake/" class="md-nav__link"> <span class="md-ellipsis"> Deeplake </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/discord/" class="md-nav__link"> <span class="md-ellipsis"> Discord </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/docling/" class="md-nav__link"> <span class="md-ellipsis"> Docling </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/docstring_walker/" class="md-nav__link"> <span class="md-ellipsis"> Docstring walker </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/docugami/" class="md-nav__link"> <span class="md-ellipsis"> Docugami </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/document360/" class="md-nav__link"> <span class="md-ellipsis"> Document360 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/earnings_call_transcript/" class="md-nav__link"> <span class="md-ellipsis"> Earnings call transcript </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/elasticsearch/" class="md-nav__link"> <span class="md-ellipsis"> Elasticsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/faiss/" class="md-nav__link"> <span class="md-ellipsis"> Faiss </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/feedly_rss/" class="md-nav__link"> <span class="md-ellipsis"> Feedly rss </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/feishu_docs/" class="md-nav__link"> <span class="md-ellipsis"> Feishu docs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/feishu_wiki/" class="md-nav__link"> <span class="md-ellipsis"> Feishu wiki </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/file/" class="md-nav__link"> <span class="md-ellipsis"> File </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/firebase_realtimedb/" class="md-nav__link"> <span class="md-ellipsis"> Firebase realtimedb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/firestore/" class="md-nav__link"> <span class="md-ellipsis"> Firestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/gcs/" class="md-nav__link"> <span class="md-ellipsis"> Gcs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/genius/" class="md-nav__link"> <span class="md-ellipsis"> Genius </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/gitbook/" class="md-nav__link"> <span class="md-ellipsis"> Gitbook </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/github/" class="md-nav__link"> <span class="md-ellipsis"> Github </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/gitlab/" class="md-nav__link"> <span class="md-ellipsis"> Gitlab </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/google/" class="md-nav__link"> <span class="md-ellipsis"> Google </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/gpt_repo/" class="md-nav__link"> <span class="md-ellipsis"> Gpt repo </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/graphdb_cypher/" class="md-nav__link"> <span class="md-ellipsis"> Graphdb cypher </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/graphql/" class="md-nav__link"> <span class="md-ellipsis"> Graphql </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/guru/" class="md-nav__link"> <span class="md-ellipsis"> Guru </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/hatena_blog/" class="md-nav__link"> <span class="md-ellipsis"> Hatena blog </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/hive/" class="md-nav__link"> <span class="md-ellipsis"> Hive </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/hubspot/" class="md-nav__link"> <span class="md-ellipsis"> Hubspot </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/huggingface_fs/" class="md-nav__link"> <span class="md-ellipsis"> Huggingface fs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/hwp/" class="md-nav__link"> <span class="md-ellipsis"> Hwp </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/iceberg/" class="md-nav__link"> <span class="md-ellipsis"> Iceberg </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/imdb_review/" class="md-nav__link"> <span class="md-ellipsis"> Imdb review </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/intercom/" class="md-nav__link"> <span class="md-ellipsis"> Intercom </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/jaguar/" class="md-nav__link"> <span class="md-ellipsis"> Jaguar </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/jira/" class="md-nav__link"> <span class="md-ellipsis"> Jira </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/joplin/" class="md-nav__link"> <span class="md-ellipsis"> Joplin </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/json/" class="md-nav__link"> <span class="md-ellipsis"> Json </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/kaltura_esearch/" class="md-nav__link"> <span class="md-ellipsis"> Kaltura esearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/kibela/" class="md-nav__link"> <span class="md-ellipsis"> Kibela </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/lilac/" class="md-nav__link"> <span class="md-ellipsis"> Lilac </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/linear/" class="md-nav__link"> <span class="md-ellipsis"> Linear </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/llama_parse/" class="md-nav__link"> <span class="md-ellipsis"> Llama parse </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/macrometa_gdn/" class="md-nav__link"> <span class="md-ellipsis"> Macrometa gdn </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/make_com/" class="md-nav__link"> <span class="md-ellipsis"> Make com </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/mangadex/" class="md-nav__link"> <span class="md-ellipsis"> Mangadex </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/mangoapps_guides/" class="md-nav__link"> <span class="md-ellipsis"> Mangoapps guides </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/maps/" class="md-nav__link"> <span class="md-ellipsis"> Maps </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/mbox/" class="md-nav__link"> <span class="md-ellipsis"> Mbox </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/memos/" class="md-nav__link"> <span class="md-ellipsis"> Memos </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/metal/" class="md-nav__link"> <span class="md-ellipsis"> Metal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/microsoft_onedrive/" class="md-nav__link"> <span class="md-ellipsis"> Microsoft onedrive </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/microsoft_outlook/" class="md-nav__link"> <span class="md-ellipsis"> Microsoft outlook </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/microsoft_sharepoint/" class="md-nav__link"> <span class="md-ellipsis"> Microsoft sharepoint </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/milvus/" class="md-nav__link"> <span class="md-ellipsis"> Milvus </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/minio/" class="md-nav__link"> <span class="md-ellipsis"> Minio </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/mondaydotcom/" class="md-nav__link"> <span class="md-ellipsis"> Mondaydotcom </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/mongodb/" class="md-nav__link"> <span class="md-ellipsis"> Mongodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/myscale/" class="md-nav__link"> <span class="md-ellipsis"> Myscale </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/notion/" class="md-nav__link"> <span class="md-ellipsis"> Notion </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/nougat_ocr/" class="md-nav__link"> <span class="md-ellipsis"> Nougat ocr </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/obsidian/" class="md-nav__link"> <span class="md-ellipsis"> Obsidian </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/openalex/" class="md-nav__link"> <span class="md-ellipsis"> Openalex </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/openapi/" class="md-nav__link"> <span class="md-ellipsis"> Openapi </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/opendal/" class="md-nav__link"> <span class="md-ellipsis"> Opendal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/opensearch/" class="md-nav__link"> <span class="md-ellipsis"> Opensearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/oracleai/" class="md-nav__link"> <span class="md-ellipsis"> Oracleai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pandas_ai/" class="md-nav__link"> <span class="md-ellipsis"> Pandas ai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/papers/" class="md-nav__link"> <span class="md-ellipsis"> Papers </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/patentsview/" class="md-nav__link"> <span class="md-ellipsis"> Patentsview </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pathway/" class="md-nav__link"> <span class="md-ellipsis"> Pathway </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pdb/" class="md-nav__link"> <span class="md-ellipsis"> Pdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pdf_marker/" class="md-nav__link"> <span class="md-ellipsis"> Pdf marker </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pdf_table/" class="md-nav__link"> <span class="md-ellipsis"> Pdf table </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pebblo/" class="md-nav__link"> <span class="md-ellipsis"> Pebblo </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/pinecone.md" class="md-nav__link"> <span class="md-ellipsis"> None </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/preprocess/" class="md-nav__link"> <span class="md-ellipsis"> Preprocess </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/psychic/" class="md-nav__link"> <span class="md-ellipsis"> Psychic </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/qdrant/" class="md-nav__link"> <span class="md-ellipsis"> Qdrant </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/quip/" class="md-nav__link"> <span class="md-ellipsis"> Quip </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/rayyan/" class="md-nav__link"> <span class="md-ellipsis"> Rayyan </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/readme/" class="md-nav__link"> <span class="md-ellipsis"> Readme </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/readwise/" class="md-nav__link"> <span class="md-ellipsis"> Readwise </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/reddit/" class="md-nav__link"> <span class="md-ellipsis"> Reddit </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/remote/" class="md-nav__link"> <span class="md-ellipsis"> Remote </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/remote_depth/" class="md-nav__link"> <span class="md-ellipsis"> Remote depth </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/s3/" class="md-nav__link"> <span class="md-ellipsis"> S3 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/sec_filings/" class="md-nav__link"> <span class="md-ellipsis"> Sec filings </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/semanticscholar/" class="md-nav__link"> <span class="md-ellipsis"> Semanticscholar </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/simple_directory_reader/" class="md-nav__link"> <span class="md-ellipsis"> Simple directory reader </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/singlestore/" class="md-nav__link"> <span class="md-ellipsis"> Singlestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/slack/" class="md-nav__link"> <span class="md-ellipsis"> Slack </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/smart_pdf_loader/" class="md-nav__link"> <span class="md-ellipsis"> Smart pdf loader </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/snowflake/" class="md-nav__link"> <span class="md-ellipsis"> Snowflake </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/snscrape_twitter/" class="md-nav__link"> <span class="md-ellipsis"> Snscrape twitter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/spotify/" class="md-nav__link"> <span class="md-ellipsis"> Spotify </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/stackoverflow/" class="md-nav__link"> <span class="md-ellipsis"> Stackoverflow </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/steamship/" class="md-nav__link"> <span class="md-ellipsis"> Steamship </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/string_iterable/" class="md-nav__link"> <span class="md-ellipsis"> String iterable </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/stripe_docs/" class="md-nav__link"> <span class="md-ellipsis"> Stripe docs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/structured_data/" class="md-nav__link"> <span class="md-ellipsis"> Structured data </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/telegram/" class="md-nav__link"> <span class="md-ellipsis"> Telegram </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/toggl/" class="md-nav__link"> <span class="md-ellipsis"> Toggl </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/trello/" class="md-nav__link"> <span class="md-ellipsis"> Trello </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/twitter/" class="md-nav__link"> <span class="md-ellipsis"> Twitter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/txtai/" class="md-nav__link"> <span class="md-ellipsis"> Txtai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/upstage/" class="md-nav__link"> <span class="md-ellipsis"> Upstage </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/weather/" class="md-nav__link"> <span class="md-ellipsis"> Weather </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/weaviate/" class="md-nav__link"> <span class="md-ellipsis"> Weaviate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/web/" class="md-nav__link"> <span class="md-ellipsis"> Web </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/whatsapp/" class="md-nav__link"> <span class="md-ellipsis"> Whatsapp </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/wikipedia/" class="md-nav__link"> <span class="md-ellipsis"> Wikipedia </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/wordlift/" class="md-nav__link"> <span class="md-ellipsis"> Wordlift </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/wordpress/" class="md-nav__link"> <span class="md-ellipsis"> Wordpress </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/youtube_metadata/" class="md-nav__link"> <span class="md-ellipsis"> Youtube metadata </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/youtube_transcript/" class="md-nav__link"> <span class="md-ellipsis"> Youtube transcript </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/zendesk/" class="md-nav__link"> <span class="md-ellipsis"> Zendesk </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/zep/" class="md-nav__link"> <span class="md-ellipsis"> Zep </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/zulip/" class="md-nav__link"> <span class="md-ellipsis"> Zulip </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/readers/zyte_serp/" class="md-nav__link"> <span class="md-ellipsis"> Zyte serp </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_27" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/response_synthesizers/" class="md-nav__link "> <span class="md-ellipsis"> Response Synthesizers </span> </a> <label class="md-nav__link " for="__nav_7_27" id="__nav_7_27_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_27_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_27"> <span class="md-nav__icon md-icon"></span> Response Synthesizers </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/accumulate/" class="md-nav__link"> <span class="md-ellipsis"> Accumulate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/compact_accumulate/" class="md-nav__link"> <span class="md-ellipsis"> Compact accumulate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/compact_and_refine/" class="md-nav__link"> <span class="md-ellipsis"> Compact and refine </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/generation/" class="md-nav__link"> <span class="md-ellipsis"> Generation </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/google/" class="md-nav__link"> <span class="md-ellipsis"> Google </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/refine/" class="md-nav__link"> <span class="md-ellipsis"> Refine </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/simple_summarize/" class="md-nav__link"> <span class="md-ellipsis"> Simple summarize </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/response_synthesizers/tree_summarize/" class="md-nav__link"> <span class="md-ellipsis"> Tree summarize </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_28" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/retrievers/" class="md-nav__link "> <span class="md-ellipsis"> Retrievers </span> </a> <label class="md-nav__link " for="__nav_7_28" id="__nav_7_28_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_28_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_28"> <span class="md-nav__icon md-icon"></span> Retrievers </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/auto_merging/" class="md-nav__link"> <span class="md-ellipsis"> Auto merging </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/bedrock/" class="md-nav__link"> <span class="md-ellipsis"> Bedrock </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/bm25/" class="md-nav__link"> <span class="md-ellipsis"> Bm25 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/duckdb_retriever/" class="md-nav__link"> <span class="md-ellipsis"> Duckdb retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/keyword/" class="md-nav__link"> <span class="md-ellipsis"> Keyword </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/knowledge_graph/" class="md-nav__link"> <span class="md-ellipsis"> Knowledge graph </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/mongodb_atlas_bm25_retriever/" class="md-nav__link"> <span class="md-ellipsis"> Mongodb atlas bm25 retriever </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/pathway/" class="md-nav__link"> <span class="md-ellipsis"> Pathway </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/query_fusion/" class="md-nav__link"> <span class="md-ellipsis"> Query fusion </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/recursive/" class="md-nav__link"> <span class="md-ellipsis"> Recursive </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/router/" class="md-nav__link"> <span class="md-ellipsis"> Router </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/sql/" class="md-nav__link"> <span class="md-ellipsis"> Sql </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/summary/" class="md-nav__link"> <span class="md-ellipsis"> Summary </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/transform/" class="md-nav__link"> <span class="md-ellipsis"> Transform </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/tree/" class="md-nav__link"> <span class="md-ellipsis"> Tree </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/vector/" class="md-nav__link"> <span class="md-ellipsis"> Vector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/vertexai_search/" class="md-nav__link"> <span class="md-ellipsis"> Vertexai search </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/videodb/" class="md-nav__link"> <span class="md-ellipsis"> Videodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/retrievers/you/" class="md-nav__link"> <span class="md-ellipsis"> You </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_29" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/schema/" class="md-nav__link "> <span class="md-ellipsis"> Schema </span> </a> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_29_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_29"> <span class="md-nav__icon md-icon"></span> Schema </label> <ul class="md-nav__list" data-md-scrollfix> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_30" > <label class="md-nav__link" for="__nav_7_30" id="__nav_7_30_label" tabindex="0"> <span class="md-ellipsis"> Selectors </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_30_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_30"> <span class="md-nav__icon md-icon"></span> Selectors </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/selectors/notdiamond/" class="md-nav__link"> <span class="md-ellipsis"> Notdiamond </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_31" > <label class="md-nav__link" for="__nav_7_31" id="__nav_7_31_label" tabindex="0"> <span class="md-ellipsis"> Sparse Embeddings </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_31_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_31"> <span class="md-nav__icon md-icon"></span> Sparse Embeddings </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/sparse_embeddings/fastembed/" class="md-nav__link"> <span class="md-ellipsis"> Fastembed </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32" > <label class="md-nav__link" for="__nav_7_32" id="__nav_7_32_label" tabindex="0"> <span class="md-ellipsis"> Storage </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_32_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32"> <span class="md-nav__icon md-icon"></span> Storage </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_1" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/storage/chat_store/" class="md-nav__link "> <span class="md-ellipsis"> Chat Store </span> </a> <label class="md-nav__link " for="__nav_7_32_1" id="__nav_7_32_1_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_1_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_1"> <span class="md-nav__icon md-icon"></span> Chat Store </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/azure/" class="md-nav__link"> <span class="md-ellipsis"> Azure </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/azurecosmosmongovcore/" class="md-nav__link"> <span class="md-ellipsis"> Azurecosmosmongovcore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/azurecosmosnosql/" class="md-nav__link"> <span class="md-ellipsis"> Azurecosmosnosql </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/dynamodb/" class="md-nav__link"> <span class="md-ellipsis"> Dynamodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/postgres/" class="md-nav__link"> <span class="md-ellipsis"> Postgres </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/redis/" class="md-nav__link"> <span class="md-ellipsis"> Redis </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/simple/" class="md-nav__link"> <span class="md-ellipsis"> Simple </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/chat_store/upstash/" class="md-nav__link"> <span class="md-ellipsis"> Upstash </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_2" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/storage/docstore/" class="md-nav__link "> <span class="md-ellipsis"> Docstore </span> </a> <label class="md-nav__link " for="__nav_7_32_2" id="__nav_7_32_2_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_2_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_2"> <span class="md-nav__icon md-icon"></span> Docstore </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/azure/" class="md-nav__link"> <span class="md-ellipsis"> Azure </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/couchbase/" class="md-nav__link"> <span class="md-ellipsis"> Couchbase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/dynamodb/" class="md-nav__link"> <span class="md-ellipsis"> Dynamodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/elasticsearch/" class="md-nav__link"> <span class="md-ellipsis"> Elasticsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/firestore/" class="md-nav__link"> <span class="md-ellipsis"> Firestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/mongodb/" class="md-nav__link"> <span class="md-ellipsis"> Mongodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/postgres/" class="md-nav__link"> <span class="md-ellipsis"> Postgres </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/redis/" class="md-nav__link"> <span class="md-ellipsis"> Redis </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/docstore/simple/" class="md-nav__link"> <span class="md-ellipsis"> Simple </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_3" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/storage/graph_stores/" class="md-nav__link "> <span class="md-ellipsis"> Graph Stores </span> </a> <label class="md-nav__link " for="__nav_7_32_3" id="__nav_7_32_3_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_3_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_3"> <span class="md-nav__icon md-icon"></span> Graph Stores </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/falkordb/" class="md-nav__link"> <span class="md-ellipsis"> Falkordb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/kuzu/" class="md-nav__link"> <span class="md-ellipsis"> Kuzu </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/memgraph/" class="md-nav__link"> <span class="md-ellipsis"> Memgraph </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/nebula/" class="md-nav__link"> <span class="md-ellipsis"> Nebula </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/neo4j/" class="md-nav__link"> <span class="md-ellipsis"> Neo4j </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/neptune/" class="md-nav__link"> <span class="md-ellipsis"> Neptune </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/simple/" class="md-nav__link"> <span class="md-ellipsis"> Simple </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/graph_stores/tidb/" class="md-nav__link"> <span class="md-ellipsis"> Tidb </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_4" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/storage/index_store/" class="md-nav__link "> <span class="md-ellipsis"> Index Store </span> </a> <label class="md-nav__link " for="__nav_7_32_4" id="__nav_7_32_4_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_4_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_4"> <span class="md-nav__icon md-icon"></span> Index Store </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/azure/" class="md-nav__link"> <span class="md-ellipsis"> Azure </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/azurecosmosnosql/" class="md-nav__link"> <span class="md-ellipsis"> Azurecosmosnosql </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/couchbase/" class="md-nav__link"> <span class="md-ellipsis"> Couchbase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/dynamodb/" class="md-nav__link"> <span class="md-ellipsis"> Dynamodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/elasticsearch/" class="md-nav__link"> <span class="md-ellipsis"> Elasticsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/index_store/firestore/" class="md-nav__link"> <span class="md-ellipsis"> Firestore </span> </a> </li> <li class="md-nav__item"> <a 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</a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/elasticsearch/" class="md-nav__link"> <span class="md-ellipsis"> Elasticsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/firestore/" class="md-nav__link"> <span class="md-ellipsis"> Firestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/mongodb/" class="md-nav__link"> <span class="md-ellipsis"> Mongodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/postgres/" class="md-nav__link"> <span class="md-ellipsis"> Postgres </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/redis/" class="md-nav__link"> <span class="md-ellipsis"> Redis </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/s3/" class="md-nav__link"> <span class="md-ellipsis"> S3 </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/kvstore/simple/" class="md-nav__link"> <span class="md-ellipsis"> Simple </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_6" > <label class="md-nav__link" for="__nav_7_32_6" id="__nav_7_32_6_label" tabindex="0"> <span class="md-ellipsis"> Storage </span> <span class="md-nav__icon md-icon"></span> </label> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_6_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_6"> <span class="md-nav__icon md-icon"></span> Storage </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/storage_context/" class="md-nav__link"> <span class="md-ellipsis"> Storage context </span> </a> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_32_7" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/storage/vector_store/" class="md-nav__link "> <span class="md-ellipsis"> Vector Store </span> </a> <label class="md-nav__link " for="__nav_7_32_7" id="__nav_7_32_7_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="3" aria-labelledby="__nav_7_32_7_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_32_7"> <span class="md-nav__icon md-icon"></span> Vector Store </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/alibabacloud_opensearch/" class="md-nav__link"> <span class="md-ellipsis"> Alibabacloud opensearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/analyticdb/" class="md-nav__link"> <span class="md-ellipsis"> Analyticdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/astra_db/" class="md-nav__link"> <span class="md-ellipsis"> Astra db </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/awadb/" class="md-nav__link"> <span class="md-ellipsis"> Awadb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/awsdocdb/" class="md-nav__link"> <span class="md-ellipsis"> Awsdocdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/azureaisearch/" class="md-nav__link"> <span class="md-ellipsis"> Azureaisearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/azurecosmosmongo/" class="md-nav__link"> <span class="md-ellipsis"> Azurecosmosmongo </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/azurecosmosnosql/" class="md-nav__link"> <span class="md-ellipsis"> Azurecosmosnosql </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/bagel/" class="md-nav__link"> <span class="md-ellipsis"> Bagel </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/baiduvectordb/" class="md-nav__link"> <span class="md-ellipsis"> Baiduvectordb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/cassandra/" class="md-nav__link"> <span class="md-ellipsis"> Cassandra </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/chatgpt_plugin/" class="md-nav__link"> <span class="md-ellipsis"> Chatgpt plugin </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/chroma/" class="md-nav__link"> <span class="md-ellipsis"> Chroma </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/clickhouse/" class="md-nav__link"> <span class="md-ellipsis"> Clickhouse </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/couchbase/" class="md-nav__link"> <span class="md-ellipsis"> Couchbase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/dashvector/" class="md-nav__link"> <span class="md-ellipsis"> Dashvector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/databricks/" class="md-nav__link"> <span class="md-ellipsis"> Databricks </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/deeplake/" class="md-nav__link"> <span class="md-ellipsis"> Deeplake </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/docarray/" class="md-nav__link"> <span class="md-ellipsis"> Docarray </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/duckdb/" class="md-nav__link"> <span class="md-ellipsis"> Duckdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/dynamodb/" class="md-nav__link"> <span class="md-ellipsis"> Dynamodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/elasticsearch/" class="md-nav__link"> <span class="md-ellipsis"> Elasticsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/epsilla/" class="md-nav__link"> <span class="md-ellipsis"> Epsilla </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/faiss/" class="md-nav__link"> <span class="md-ellipsis"> Faiss </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/firestore/" class="md-nav__link"> <span class="md-ellipsis"> Firestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/google/" class="md-nav__link"> <span class="md-ellipsis"> Google </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/hologres/" class="md-nav__link"> <span class="md-ellipsis"> Hologres </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/jaguar/" class="md-nav__link"> <span class="md-ellipsis"> Jaguar </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/kdbai/" class="md-nav__link"> <span class="md-ellipsis"> Kdbai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/lancedb/" class="md-nav__link"> <span class="md-ellipsis"> Lancedb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/lantern/" class="md-nav__link"> <span class="md-ellipsis"> Lantern </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/lindorm/" class="md-nav__link"> <span class="md-ellipsis"> Lindorm </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/mariadb/" class="md-nav__link"> <span class="md-ellipsis"> Mariadb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/metal/" class="md-nav__link"> <span class="md-ellipsis"> Metal </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/milvus/" class="md-nav__link"> <span class="md-ellipsis"> Milvus </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/mongodb/" class="md-nav__link"> <span class="md-ellipsis"> Mongodb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/myscale/" class="md-nav__link"> <span class="md-ellipsis"> Myscale </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/neo4jvector/" class="md-nav__link"> <span class="md-ellipsis"> Neo4jvector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/neptune/" class="md-nav__link"> <span class="md-ellipsis"> Neptune </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/nile/" class="md-nav__link"> <span class="md-ellipsis"> Nile </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/objectbox/" class="md-nav__link"> <span class="md-ellipsis"> Objectbox </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/oceanbase/" class="md-nav__link"> <span class="md-ellipsis"> Oceanbase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/opensearch/" class="md-nav__link"> <span class="md-ellipsis"> Opensearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/oracledb/" class="md-nav__link"> <span class="md-ellipsis"> Oracledb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/pgvecto_rs/" class="md-nav__link"> <span class="md-ellipsis"> Pgvecto rs </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/pinecone/" class="md-nav__link"> <span class="md-ellipsis"> Pinecone </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/postgres/" class="md-nav__link"> <span class="md-ellipsis"> Postgres </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/qdrant/" class="md-nav__link"> <span class="md-ellipsis"> Qdrant </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/redis/" class="md-nav__link"> <span class="md-ellipsis"> Redis </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/relyt/" class="md-nav__link"> <span class="md-ellipsis"> Relyt </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/rocksetdb/" class="md-nav__link"> <span class="md-ellipsis"> Rocksetdb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/simple/" class="md-nav__link"> <span class="md-ellipsis"> Simple </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/singlestoredb/" class="md-nav__link"> <span class="md-ellipsis"> Singlestoredb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/sqlalchemy.md" class="md-nav__link"> <span class="md-ellipsis"> None </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/supabase/" class="md-nav__link"> <span class="md-ellipsis"> Supabase </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/tablestore/" class="md-nav__link"> <span class="md-ellipsis"> Tablestore </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/tair/" class="md-nav__link"> <span class="md-ellipsis"> Tair </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/tencentvectordb/" class="md-nav__link"> <span class="md-ellipsis"> Tencentvectordb </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/tidbvector/" class="md-nav__link"> <span class="md-ellipsis"> Tidbvector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/timescalevector/" class="md-nav__link"> <span class="md-ellipsis"> Timescalevector </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/txtai/" class="md-nav__link"> <span class="md-ellipsis"> Txtai </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/typesense/" class="md-nav__link"> <span class="md-ellipsis"> Typesense </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/upstash/" class="md-nav__link"> <span class="md-ellipsis"> Upstash </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/vearch/" class="md-nav__link"> <span class="md-ellipsis"> Vearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/vertexaivectorsearch/" class="md-nav__link"> <span class="md-ellipsis"> Vertexaivectorsearch </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/vespa/" class="md-nav__link"> <span class="md-ellipsis"> Vespa </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/weaviate/" class="md-nav__link"> <span class="md-ellipsis"> Weaviate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/wordlift/" class="md-nav__link"> <span class="md-ellipsis"> Wordlift </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/storage/vector_store/zep/" class="md-nav__link"> <span class="md-ellipsis"> Zep </span> </a> </li> </ul> </nav> </li> </ul> </nav> </li> <li class="md-nav__item md-nav__item--nested"> <input class="md-nav__toggle md-toggle " type="checkbox" id="__nav_7_33" > <div class="md-nav__link md-nav__container"> <a href="../../../api_reference/tools/" class="md-nav__link "> <span class="md-ellipsis"> Tools </span> </a> <label class="md-nav__link " for="__nav_7_33" id="__nav_7_33_label" tabindex="0"> <span class="md-nav__icon md-icon"></span> </label> </div> <nav class="md-nav" data-md-level="2" aria-labelledby="__nav_7_33_label" aria-expanded="false"> <label class="md-nav__title" for="__nav_7_33"> <span class="md-nav__icon md-icon"></span> Tools </label> <ul class="md-nav__list" data-md-scrollfix> <li class="md-nav__item"> <a href="../../../api_reference/tools/arxiv/" class="md-nav__link"> <span class="md-ellipsis"> Arxiv </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/tools/azure_code_interpreter/" class="md-nav__link"> <span class="md-ellipsis"> Azure code interpreter </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/tools/azure_cv/" class="md-nav__link"> <span class="md-ellipsis"> Azure cv </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/tools/azure_speech/" class="md-nav__link"> <span class="md-ellipsis"> Azure speech </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/tools/azure_translate/" class="md-nav__link"> <span class="md-ellipsis"> Azure translate </span> </a> </li> <li class="md-nav__item"> <a href="../../../api_reference/tools/bing_search/" class="md-nav__link"> <span class="md-ellipsis"> Bing search </span> </a> </li> <li 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#45d4ff;--jp-collaborator-color6: #e2b1ff;--jp-collaborator-color7: #ff9de6;--jp-vega-background: white;--jp-sidebar-min-width: 250px;--jp-search-toggle-off-opacity: .5;--jp-search-toggle-hover-opacity: .8;--jp-search-toggle-on-opacity: 1;--jp-search-selected-match-background-color: rgb(245, 200, 0);--jp-search-selected-match-color: black;--jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 );--jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);--jp-icon-contrast-color0: var(--md-purple-600);--jp-icon-contrast-color1: var(--md-green-600);--jp-icon-contrast-color2: var(--md-pink-600);--jp-icon-contrast-color3: var(--md-blue-600);--jp-jupyter-icon-color: #f37626;--jp-notebook-icon-color: #f37626;--jp-json-icon-color: var(--md-orange-700);--jp-console-icon-background-color: var(--md-blue-700);--jp-console-icon-color: white;--jp-terminal-icon-background-color: var(--md-grey-800);--jp-terminal-icon-color: var(--md-grey-200);--jp-text-editor-icon-color: var(--md-grey-700);--jp-inspector-icon-color: var(--md-grey-700);--jp-switch-color: var(--md-grey-400);--jp-switch-true-position-color: var(--md-orange-900)}[data-md-color-scheme=slate] .jupyter-wrapper{--jp-shadow-base-lightness: 32;--jp-shadow-umbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), .2 );--jp-shadow-penumbra-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), .14 );--jp-shadow-ambient-color: rgba( var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), var(--jp-shadow-base-lightness), .12 );--jp-elevation-z0: none;--jp-elevation-z1: 0px 2px 1px -1px var(--jp-shadow-umbra-color), 0px 1px 1px 0px var(--jp-shadow-penumbra-color), 0px 1px 3px 0px var(--jp-shadow-ambient-color);--jp-elevation-z2: 0px 3px 1px -2px var(--jp-shadow-umbra-color), 0px 2px 2px 0px var(--jp-shadow-penumbra-color), 0px 1px 5px 0px var(--jp-shadow-ambient-color);--jp-elevation-z4: 0px 2px 4px -1px var(--jp-shadow-umbra-color), 0px 4px 5px 0px var(--jp-shadow-penumbra-color), 0px 1px 10px 0px var(--jp-shadow-ambient-color);--jp-elevation-z6: 0px 3px 5px -1px var(--jp-shadow-umbra-color), 0px 6px 10px 0px var(--jp-shadow-penumbra-color), 0px 1px 18px 0px var(--jp-shadow-ambient-color);--jp-elevation-z8: 0px 5px 5px -3px var(--jp-shadow-umbra-color), 0px 8px 10px 1px var(--jp-shadow-penumbra-color), 0px 3px 14px 2px var(--jp-shadow-ambient-color);--jp-elevation-z12: 0px 7px 8px -4px var(--jp-shadow-umbra-color), 0px 12px 17px 2px var(--jp-shadow-penumbra-color), 0px 5px 22px 4px var(--jp-shadow-ambient-color);--jp-elevation-z16: 0px 8px 10px -5px var(--jp-shadow-umbra-color), 0px 16px 24px 2px var(--jp-shadow-penumbra-color), 0px 6px 30px 5px var(--jp-shadow-ambient-color);--jp-elevation-z20: 0px 10px 13px -6px var(--jp-shadow-umbra-color), 0px 20px 31px 3px var(--jp-shadow-penumbra-color), 0px 8px 38px 7px var(--jp-shadow-ambient-color);--jp-elevation-z24: 0px 11px 15px -7px var(--jp-shadow-umbra-color), 0px 24px 38px 3px var(--jp-shadow-penumbra-color), 0px 9px 46px 8px var(--jp-shadow-ambient-color);--jp-border-width: 1px;--jp-border-color0: var(--md-grey-700);--jp-border-color1: var(--md-grey-700);--jp-border-color2: var(--md-grey-800);--jp-border-color3: var(--md-grey-900);--jp-inverse-border-color: var(--md-grey-600);--jp-border-radius: 2px;--jp-ui-font-scale-factor: 1.2;--jp-ui-font-size0: .83333em;--jp-ui-font-size1: 13px;--jp-ui-font-size2: 1.2em;--jp-ui-font-size3: 1.44em;--jp-ui-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";--jp-ui-font-color0: rgba(255, 255, 255, 1);--jp-ui-font-color1: rgba(255, 255, 255, .87);--jp-ui-font-color2: rgba(255, 255, 255, .54);--jp-ui-font-color3: rgba(255, 255, 255, .38);--jp-ui-inverse-font-color0: rgba(0, 0, 0, 1);--jp-ui-inverse-font-color1: rgba(0, 0, 0, .8);--jp-ui-inverse-font-color2: rgba(0, 0, 0, .5);--jp-ui-inverse-font-color3: rgba(0, 0, 0, .3);--jp-content-line-height: 1.6;--jp-content-font-scale-factor: 1.2;--jp-content-font-size0: .83333em;--jp-content-font-size1: 14px;--jp-content-font-size2: 1.2em;--jp-content-font-size3: 1.44em;--jp-content-font-size4: 1.728em;--jp-content-font-size5: 2.0736em;--jp-content-presentation-font-size1: 17px;--jp-content-heading-line-height: 1;--jp-content-heading-margin-top: 1.2em;--jp-content-heading-margin-bottom: .8em;--jp-content-heading-font-weight: 500;--jp-content-font-color0: rgba(255, 255, 255, 1);--jp-content-font-color1: rgba(255, 255, 255, 1);--jp-content-font-color2: rgba(255, 255, 255, .7);--jp-content-font-color3: rgba(255, 255, 255, .5);--jp-content-link-color: var(--md-blue-300);--jp-content-font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Helvetica, Arial, sans-serif, "Apple Color Emoji", "Segoe UI Emoji", "Segoe UI Symbol";--jp-code-font-size: 13px;--jp-code-line-height: 1.3077;--jp-code-padding: 5px;--jp-code-font-family-default: Menlo, Consolas, "DejaVu Sans Mono", monospace;--jp-code-font-family: var(--jp-code-font-family-default);--jp-code-presentation-font-size: 16px;--jp-code-cursor-width0: 1.4px;--jp-code-cursor-width1: 2px;--jp-code-cursor-width2: 4px;--jp-layout-color0: #111111;--jp-layout-color1: var(--md-grey-900);--jp-layout-color2: var(--md-grey-800);--jp-layout-color3: var(--md-grey-700);--jp-layout-color4: var(--md-grey-600);--jp-inverse-layout-color0: white;--jp-inverse-layout-color1: white;--jp-inverse-layout-color2: var(--md-grey-200);--jp-inverse-layout-color3: var(--md-grey-400);--jp-inverse-layout-color4: var(--md-grey-600);--jp-brand-color0: var(--md-blue-700);--jp-brand-color1: var(--md-blue-500);--jp-brand-color2: var(--md-blue-300);--jp-brand-color3: var(--md-blue-100);--jp-brand-color4: var(--md-blue-50);--jp-accent-color0: var(--md-green-700);--jp-accent-color1: var(--md-green-500);--jp-accent-color2: var(--md-green-300);--jp-accent-color3: var(--md-green-100);--jp-warn-color0: var(--md-orange-700);--jp-warn-color1: var(--md-orange-500);--jp-warn-color2: var(--md-orange-300);--jp-warn-color3: var(--md-orange-100);--jp-error-color0: var(--md-red-700);--jp-error-color1: var(--md-red-500);--jp-error-color2: var(--md-red-300);--jp-error-color3: var(--md-red-100);--jp-success-color0: var(--md-green-700);--jp-success-color1: var(--md-green-500);--jp-success-color2: var(--md-green-300);--jp-success-color3: var(--md-green-100);--jp-info-color0: var(--md-cyan-700);--jp-info-color1: var(--md-cyan-500);--jp-info-color2: var(--md-cyan-300);--jp-info-color3: var(--md-cyan-100);--jp-cell-padding: 5px;--jp-cell-collapser-width: 8px;--jp-cell-collapser-min-height: 20px;--jp-cell-collapser-not-active-hover-opacity: .6;--jp-cell-editor-background: var(--jp-layout-color1);--jp-cell-editor-border-color: var(--md-grey-700);--jp-cell-editor-box-shadow: inset 0 0 2px var(--md-blue-300);--jp-cell-editor-active-background: var(--jp-layout-color0);--jp-cell-editor-active-border-color: var(--jp-brand-color1);--jp-cell-prompt-width: 64px;--jp-cell-prompt-font-family: var(--jp-code-font-family-default);--jp-cell-prompt-letter-spacing: 0px;--jp-cell-prompt-opacity: 1;--jp-cell-prompt-not-active-opacity: 1;--jp-cell-prompt-not-active-font-color: var(--md-grey-300);--jp-cell-inprompt-font-color: #307fc1;--jp-cell-outprompt-font-color: #bf5b3d;--jp-notebook-padding: 10px;--jp-notebook-select-background: var(--jp-layout-color1);--jp-notebook-multiselected-color: rgba(33, 150, 243, .24);--jp-notebook-scroll-padding: calc( 100% - var(--jp-code-font-size) * var(--jp-code-line-height) - var(--jp-code-padding) - var(--jp-cell-padding) - 1px );--jp-rendermime-error-background: rgba(244, 67, 54, .28);--jp-rendermime-table-row-background: var(--md-grey-900);--jp-rendermime-table-row-hover-background: rgba(3, 169, 244, .2);--jp-dialog-background: rgba(0, 0, 0, .6);--jp-console-padding: 10px;--jp-toolbar-border-color: var(--jp-border-color2);--jp-toolbar-micro-height: 8px;--jp-toolbar-background: var(--jp-layout-color1);--jp-toolbar-box-shadow: 0px 0px 2px 0px rgba(0, 0, 0, .8);--jp-toolbar-header-margin: 4px 4px 0px 4px;--jp-toolbar-active-background: var(--jp-layout-color0);--jp-statusbar-height: 24px;--jp-input-box-shadow: inset 0 0 2px var(--md-blue-300);--jp-input-active-background: var(--jp-layout-color0);--jp-input-hover-background: var(--jp-layout-color2);--jp-input-background: var(--md-grey-800);--jp-input-border-color: var(--jp-inverse-border-color);--jp-input-active-border-color: var(--jp-brand-color1);--jp-input-active-box-shadow-color: rgba(19, 124, 189, .3);--jp-editor-selected-background: var(--jp-layout-color2);--jp-editor-selected-focused-background: rgba(33, 150, 243, .24);--jp-editor-cursor-color: var(--jp-ui-font-color0);--jp-mirror-editor-keyword-color: var(--md-green-500);--jp-mirror-editor-atom-color: var(--md-blue-300);--jp-mirror-editor-number-color: var(--md-green-400);--jp-mirror-editor-def-color: var(--md-blue-600);--jp-mirror-editor-variable-color: var(--md-grey-300);--jp-mirror-editor-variable-2-color: var(--md-blue-400);--jp-mirror-editor-variable-3-color: var(--md-green-600);--jp-mirror-editor-punctuation-color: var(--md-blue-400);--jp-mirror-editor-property-color: var(--md-blue-400);--jp-mirror-editor-operator-color: #aa22ff;--jp-mirror-editor-comment-color: #408080;--jp-mirror-editor-string-color: #ff7070;--jp-mirror-editor-string-2-color: var(--md-purple-300);--jp-mirror-editor-meta-color: #aa22ff;--jp-mirror-editor-qualifier-color: #555;--jp-mirror-editor-builtin-color: var(--md-green-600);--jp-mirror-editor-bracket-color: #997;--jp-mirror-editor-tag-color: var(--md-green-700);--jp-mirror-editor-attribute-color: var(--md-blue-700);--jp-mirror-editor-header-color: var(--md-blue-500);--jp-mirror-editor-quote-color: var(--md-green-300);--jp-mirror-editor-link-color: var(--md-blue-700);--jp-mirror-editor-error-color: #f00;--jp-mirror-editor-hr-color: #999;--jp-collaborator-color1: #ad4a00;--jp-collaborator-color2: #7b6a00;--jp-collaborator-color3: #007e00;--jp-collaborator-color4: #008772;--jp-collaborator-color5: #0079b9;--jp-collaborator-color6: #8b45c6;--jp-collaborator-color7: #be208b;--jp-vega-background: var(--md-grey-400);--jp-sidebar-min-width: 250px;--jp-search-toggle-off-opacity: .6;--jp-search-toggle-hover-opacity: .8;--jp-search-toggle-on-opacity: 1;--jp-search-selected-match-background-color: rgb(255, 225, 0);--jp-search-selected-match-color: black;--jp-search-unselected-match-background-color: var( --jp-inverse-layout-color0 );--jp-search-unselected-match-color: var(--jp-ui-inverse-font-color0);--jp-scrollbar-background-color: #3f4244;--jp-scrollbar-thumb-color: 88, 96, 97;--jp-scrollbar-endpad: 3px;--jp-scrollbar-thumb-margin: 3.5px;--jp-scrollbar-thumb-radius: 9px;--jp-icon-contrast-color0: var(--md-purple-600);--jp-icon-contrast-color1: var(--md-green-600);--jp-icon-contrast-color2: var(--md-pink-600);--jp-icon-contrast-color3: var(--md-blue-600);--jp-jupyter-icon-color: #f37626;--jp-notebook-icon-color: #f37626;--jp-json-icon-color: var(--md-orange-500);--jp-console-icon-background-color: var(--md-blue-500);--jp-console-icon-color: white;--jp-terminal-icon-background-color: var(--md-grey-200);--jp-terminal-icon-color: var(--md-grey-800);--jp-text-editor-icon-color: var(--md-grey-200);--jp-inspector-icon-color: var(--md-grey-200);--jp-switch-color: var(--md-grey-400);--jp-switch-true-position-color: var(--md-orange-700)}.jupyter-wrapper [data-jp-theme-scrollbars=true]{scrollbar-color:rgb(var(--jp-scrollbar-thumb-color)) var(--jp-scrollbar-background-color)}.jupyter-wrapper [data-jp-theme-scrollbars=true] .CodeMirror-hscrollbar,.jupyter-wrapper [data-jp-theme-scrollbars=true] .CodeMirror-vscrollbar{scrollbar-color:rgba(var(--jp-scrollbar-thumb-color),.5) 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</script> <style> .jp-Mermaid:not(.jp-RenderedMermaid) { display: none; } .jp-RenderedMermaid { overflow: auto; display: flex; } .jp-RenderedMermaid.jp-mod-warning { width: auto; padding: 0.5em; margin-top: 0.5em; border: var(--jp-border-width) solid var(--jp-warn-color2); border-radius: var(--jp-border-radius); color: var(--jp-ui-font-color1); font-size: var(--jp-ui-font-size1); white-space: pre-wrap; word-wrap: break-word; } .jp-RenderedMermaid figure { margin: 0; overflow: auto; max-width: 100%; } .jp-RenderedMermaid img { max-width: 100%; } .jp-RenderedMermaid-Details > pre { margin-top: 1em; } .jp-RenderedMermaid-Summary { color: var(--jp-warn-color2); } .jp-RenderedMermaid:not(.jp-mod-warning) pre { display: none; } .jp-RenderedMermaid-Summary > pre { display: inline-block; white-space: normal; } </style> <div class="jupyter-wrapper"> <div class="jp-Notebook" data-jp-theme-light="true" data-jp-theme-name="JupyterLab Light"> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=368686b4-f487-4dd4-aeff-37823976529d"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> <p><a href="https://colab.research.google.com/github/run-llama/llama_index/blob/main/docs/docs/examples/multi_modal/anthropic_multi_modal.ipynb" target="_parent"><img alt="Open In Colab" src="https://colab.research.google.com/assets/colab-badge.svg"/></a></p> <h1 id="multi-modal-llm-using-anthropic-model-for-image-reasoning">Multi-Modal LLM using Anthropic model for image reasoning<a class="anchor-link" href="#multi-modal-llm-using-anthropic-model-for-image-reasoning">¶</a></h1><p>Anthropic has recently released its latest Multi modal models: Claude 3 Opus, Claude 3 Sonnet.</p> <ol> <li><p>Claude 3 Opus - claude-3-opus-20240229</p> </li> <li><p>Claude 3 Sonnet - claude-3-sonnet-20240229</p> </li> </ol> <p>In this notebook, we show how to use Anthropic MultiModal LLM class/abstraction for image understanding/reasoning.</p> <p>We also show several functions we are now supporting for Anthropic MultiModal LLM:</p> <ul> <li><code>complete</code> (both sync and async): for a single prompt and list of images</li> <li><code>chat</code> (both sync and async): for multiple chat messages</li> <li><code>stream complete</code> (both sync and async): for steaming output of complete</li> <li><code>stream chat</code> (both sync and async): for steaming output of chat</li> </ul> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=396d319e"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-1"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="err">!</span><span class="n">pip</span> <span class="n">install</span> <span class="n">llama</span><span class="o">-</span><span class="n">index</span><span class="o">-</span><span class="n">multi</span><span class="o">-</span><span class="n">modal</span><span class="o">-</span><span class="n">llms</span><span class="o">-</span><span class="n">anthropic</span> <span class="err">!</span><span class="n">pip</span> <span class="n">install</span> <span class="n">llama</span><span class="o">-</span><span class="n">index</span><span class="o">-</span><span class="n">vector</span><span class="o">-</span><span class="n">stores</span><span class="o">-</span><span class="n">qdrant</span> <span class="err">!</span><span class="n">pip</span> <span class="n">install</span> <span class="n">matplotlib</span> </pre></div> <div class="clipboard-copy-txt" id="cell-1">!pip install llama-index-multi-modal-llms-anthropic !pip install llama-index-vector-stores-qdrant !pip install matplotlib</div> </div> </div> </div> </div> </div> </div> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=4479bf64"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> <h2 id="use-anthropic-to-understand-images-from-local-directory">Use Anthropic to understand Images from Local directory<a class="anchor-link" href="#use-anthropic-to-understand-images-from-local-directory">¶</a></h2> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=5455d8c6"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-2"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">import</span> <span class="nn">os</span> <span class="n">os</span><span class="o">.</span><span class="n">environ</span><span class="p">[</span><span class="s2">"ANTHROPIC_API_KEY"</span><span class="p">]</span> <span class="o">=</span> <span class="s2">""</span> <span class="c1"># Your ANTHROPIC API key here</span> </pre></div> <div class="clipboard-copy-txt" id="cell-2">import os os.environ["ANTHROPIC_API_KEY"] = "" # Your ANTHROPIC API key here</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=4990a807"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-3"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span> <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span> <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s2">"../data/images/prometheus_paper_card.png"</span><span class="p">)</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-3">from PIL import Image import matplotlib.pyplot as plt img = Image.open("../data/images/prometheus_paper_card.png") plt.imshow(img)</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child jp-OutputArea-executeResult"> <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[ ]:</div> <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0"> <pre><matplotlib.image.AxesImage at 0x10f4ee2d0></pre> </div> </div> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedImage jp-OutputArea-output" tabindex="0"> <img alt="No description has been provided for this image" class="" 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"/> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=e9fab9ec"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-4"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">SimpleDirectoryReader</span> <span class="kn">from</span> <span class="nn">llama_index.multi_modal_llms.anthropic</span> <span class="kn">import</span> <span class="n">AnthropicMultiModal</span> <span class="c1"># put your local directore here</span> <span class="n">image_documents</span> <span class="o">=</span> <span class="n">SimpleDirectoryReader</span><span class="p">(</span> <span class="n">input_files</span><span class="o">=</span><span class="p">[</span><span class="s2">"../data/images/prometheus_paper_card.png"</span><span class="p">]</span> <span class="p">)</span><span class="o">.</span><span class="n">load_data</span><span class="p">()</span> <span class="c1"># Initiated Anthropic MultiModal class</span> <span class="n">anthropic_mm_llm</span> <span class="o">=</span> <span class="n">AnthropicMultiModal</span><span class="p">(</span><span class="n">max_tokens</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-4">from llama_index.core import SimpleDirectoryReader from llama_index.multi_modal_llms.anthropic import AnthropicMultiModal # put your local directore here image_documents = SimpleDirectoryReader( input_files=["../data/images/prometheus_paper_card.png"] ).load_data() # Initiated Anthropic MultiModal class anthropic_mm_llm = AnthropicMultiModal(max_tokens=300)</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=7f783f64"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-5"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="n">response</span> <span class="o">=</span> <span class="n">anthropic_mm_llm</span><span class="o">.</span><span class="n">complete</span><span class="p">(</span> <span class="n">prompt</span><span class="o">=</span><span class="s2">"Describe the images as an alternative text"</span><span class="p">,</span> <span class="n">image_documents</span><span class="o">=</span><span class="n">image_documents</span><span class="p">,</span> <span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="n">response</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-5">response = anthropic_mm_llm.complete( prompt="Describe the images as an alternative text", image_documents=image_documents, ) print(response)</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre>The image is a diagram titled "Prometheus: Inducing Fine-Grained Evaluation Capability In Language Models". It outlines the key components and workflow of the Prometheus system. The main sections are: 1. Contributions: Describes Prometheus as an open-source LLM evaluator using custom rubrics and a feedback collection dataset. 2. Results: States that Prometheus matches or outperforms GPT-4 on 3 evaluation datasets and can function as a reward model. It also enabled reference answers for LM evaluations. 3. Insights: Notes that strong LLMs show high agreement with human evaluations but their close-to-source nature and uncontrolled versioning make them a less than ideal choice for LLM evaluation. 4. Technical Bits: Diagrams the Feedback Collection pipeline which uses GPT-4 to generate score rubrics and instructions, then collects human feedback to train the final Prometheus model. The bottom includes logos, model details, and a small fire graphic. Overall, it provides a high-level technical overview of the Prometheus LLM evaluation system. </pre> </div> </div> </div> </div> </div> </div> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=f43c0b06"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> <h2 id="use-anthropicmultimodal-to-reason-images-from-urls">Use <code>AnthropicMultiModal</code> to reason images from URLs<a class="anchor-link" href="#use-anthropicmultimodal-to-reason-images-from-urls">¶</a></h2> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=40d526d2"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-6"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span> <span class="kn">import</span> <span class="nn">requests</span> <span class="kn">from</span> <span class="nn">io</span> <span class="kn">import</span> <span class="n">BytesIO</span> <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span> <span class="kn">from</span> <span class="nn">llama_index.core.multi_modal_llms.generic_utils</span> <span class="kn">import</span> <span class="n">load_image_urls</span> <span class="n">image_urls</span> <span class="o">=</span> <span class="p">[</span> <span class="s2">"https://venturebeat.com/wp-content/uploads/2024/03/Screenshot-2024-03-04-at-12.49.41</span><span class="si">%E</span><span class="s2">2</span><span class="si">%80%</span><span class="s2">AFAM.png"</span><span class="p">,</span> <span class="c1"># Add yours here!</span> <span class="p">]</span> <span class="n">img_response</span> <span class="o">=</span> <span class="n">requests</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="n">image_urls</span><span class="p">[</span><span class="mi">0</span><span class="p">])</span> <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="n">BytesIO</span><span class="p">(</span><span class="n">img_response</span><span class="o">.</span><span class="n">content</span><span class="p">))</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> <span class="n">image_url_documents</span> <span class="o">=</span> <span class="n">load_image_urls</span><span class="p">(</span><span class="n">image_urls</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-6">from PIL import Image import requests from io import BytesIO import matplotlib.pyplot as plt from llama_index.core.multi_modal_llms.generic_utils import load_image_urls image_urls = [ "https://venturebeat.com/wp-content/uploads/2024/03/Screenshot-2024-03-04-at-12.49.41%E2%80%AFAM.png", # Add yours here! ] img_response = requests.get(image_urls[0]) img = Image.open(BytesIO(img_response.content)) plt.imshow(img) image_url_documents = load_image_urls(image_urls)</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedImage jp-OutputArea-output" tabindex="0"> <img alt="No description has been provided for this image" class="" 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"/> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=22fcd5fe"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-7"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="n">response</span> <span class="o">=</span> <span class="n">anthropic_mm_llm</span><span class="o">.</span><span class="n">complete</span><span class="p">(</span> <span class="n">prompt</span><span class="o">=</span><span class="s2">"Describe the images as an alternative text"</span><span class="p">,</span> <span class="n">image_documents</span><span class="o">=</span><span class="n">image_url_documents</span><span class="p">,</span> <span class="p">)</span> <span class="nb">print</span><span class="p">(</span><span class="n">response</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-7">response = anthropic_mm_llm.complete( prompt="Describe the images as an alternative text", image_documents=image_url_documents, ) print(response)</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre>The image shows a table comparing the benchmark scores of various Claude 3 AI models (Opus, Sonnet, Haiku) against GPT-4, GPT-3.5, and two versions of Gemini (1.0 Ultra and 1.0 Pro) across different academic subjects and tests. The subjects covered include undergraduate and graduate level knowledge, grade school math, math problem-solving, multilingual math, code, reasoning over text, mixed evaluations, knowledge Q&A, and common knowledge. The scores are presented as percentages, except for the "Reasoning over text" row which shows raw scores out of a certain number of shots. The Claude 3 models generally perform comparably to GPT-3.5 and GPT-4 on most benchmarks, and outperform the Gemini models on the tasks where scores are available for comparison. </pre> </div> </div> </div> </div> </div> </div> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=0ff6a440-ed96-4ae7-88e4-26929822874c"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> <h2 id="structured-output-parsing-from-an-image">Structured Output Parsing from an Image<a class="anchor-link" href="#structured-output-parsing-from-an-image">¶</a></h2><p>In this section, we use our multi-modal Pydantic program to generate structured output from an image.</p> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=84c712df-9457-4d25-8b6c-525aaf00f45a"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-8"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">SimpleDirectoryReader</span> <span class="c1"># put your local directore here</span> <span class="n">image_documents</span> <span class="o">=</span> <span class="n">SimpleDirectoryReader</span><span class="p">(</span> <span class="n">input_files</span><span class="o">=</span><span class="p">[</span><span class="s2">"../data/images/ark_email_sample.PNG"</span><span class="p">]</span> <span class="p">)</span><span class="o">.</span><span class="n">load_data</span><span class="p">()</span> </pre></div> <div class="clipboard-copy-txt" id="cell-8">from llama_index.core import SimpleDirectoryReader # put your local directore here image_documents = SimpleDirectoryReader( input_files=["../data/images/ark_email_sample.PNG"] ).load_data()</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="application/vnd.jupyter.stderr" tabindex="0"> <pre>/Users/jerryliu/Programming/gpt_index/.venv/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html from .autonotebook import tqdm as notebook_tqdm </pre> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=ddba6422-4fb0-4a0a-b89e-03eeb0ab840a"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-9"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">PIL</span> <span class="kn">import</span> <span class="n">Image</span> <span class="kn">import</span> <span class="nn">matplotlib.pyplot</span> <span class="k">as</span> <span class="nn">plt</span> <span class="n">img</span> <span class="o">=</span> <span class="n">Image</span><span class="o">.</span><span class="n">open</span><span class="p">(</span><span class="s2">"../data/images/ark_email_sample.PNG"</span><span class="p">)</span> <span class="n">plt</span><span class="o">.</span><span class="n">imshow</span><span class="p">(</span><span class="n">img</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-9">from PIL import Image import matplotlib.pyplot as plt img = Image.open("../data/images/ark_email_sample.PNG") plt.imshow(img)</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child jp-OutputArea-executeResult"> <div class="jp-OutputPrompt jp-OutputArea-prompt">Out[ ]:</div> <div class="jp-RenderedText jp-OutputArea-output jp-OutputArea-executeResult" data-mime-type="text/plain" tabindex="0"> <pre><matplotlib.image.AxesImage at 0x2a629db40></pre> </div> </div> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedImage jp-OutputArea-output" tabindex="0"> <img alt="No description has been provided for this image" class="" 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"/> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=a4604a04-10b8-4284-be99-fd219fb43492"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-10"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">pydantic</span> <span class="kn">import</span> <span class="n">BaseModel</span> <span class="kn">from</span> <span class="nn">typing</span> <span class="kn">import</span> <span class="n">List</span> <span class="k">class</span> <span class="nc">TickerInfo</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span> <span class="w"> </span><span class="sd">"""List of ticker info."""</span> <span class="n">direction</span><span class="p">:</span> <span class="nb">str</span> <span class="n">ticker</span><span class="p">:</span> <span class="nb">str</span> <span class="n">company</span><span class="p">:</span> <span class="nb">str</span> <span class="n">shares_traded</span><span class="p">:</span> <span class="nb">int</span> <span class="n">percent_of_total_etf</span><span class="p">:</span> <span class="nb">float</span> <span class="k">class</span> <span class="nc">TickerList</span><span class="p">(</span><span class="n">BaseModel</span><span class="p">):</span> <span class="w"> </span><span class="sd">"""List of stock tickers."""</span> <span class="n">fund</span><span class="p">:</span> <span class="nb">str</span> <span class="n">tickers</span><span class="p">:</span> <span class="n">List</span><span class="p">[</span><span class="n">TickerInfo</span><span class="p">]</span> </pre></div> <div class="clipboard-copy-txt" id="cell-10">from pydantic import BaseModel from typing import List class TickerInfo(BaseModel): """List of ticker info.""" direction: str ticker: str company: str shares_traded: int percent_of_total_etf: float class TickerList(BaseModel): """List of stock tickers.""" fund: str tickers: List[TickerInfo]</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=b6f87b00-b8f1-4455-97b3-6384429364e2"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-11"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.multi_modal_llms.anthropic</span> <span class="kn">import</span> <span class="n">AnthropicMultiModal</span> <span class="kn">from</span> <span class="nn">llama_index.core.program</span> <span class="kn">import</span> <span class="n">MultiModalLLMCompletionProgram</span> <span class="kn">from</span> <span class="nn">llama_index.core.output_parsers</span> <span class="kn">import</span> <span class="n">PydanticOutputParser</span> <span class="n">prompt_template_str</span> <span class="o">=</span> <span class="s2">"""</span><span class="se">\</span> <span class="s2">Can you get the stock information in the image </span><span class="se">\</span> <span class="s2">and return the answer? Pick just one fund. </span> <span class="s2">Make sure the answer is a JSON format corresponding to a Pydantic schema. The Pydantic schema is given below.</span> <span class="s2">"""</span> <span class="c1"># Initiated Anthropic MultiModal class</span> <span class="n">anthropic_mm_llm</span> <span class="o">=</span> <span class="n">AnthropicMultiModal</span><span class="p">(</span><span class="n">max_tokens</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span> <span class="n">llm_program</span> <span class="o">=</span> <span class="n">MultiModalLLMCompletionProgram</span><span class="o">.</span><span class="n">from_defaults</span><span class="p">(</span> <span class="n">output_cls</span><span class="o">=</span><span class="n">TickerList</span><span class="p">,</span> <span class="n">image_documents</span><span class="o">=</span><span class="n">image_documents</span><span class="p">,</span> <span class="n">prompt_template_str</span><span class="o">=</span><span class="n">prompt_template_str</span><span class="p">,</span> <span class="n">multi_modal_llm</span><span class="o">=</span><span class="n">anthropic_mm_llm</span><span class="p">,</span> <span class="n">verbose</span><span class="o">=</span><span class="kc">True</span><span class="p">,</span> <span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-11">from llama_index.multi_modal_llms.anthropic import AnthropicMultiModal from llama_index.core.program import MultiModalLLMCompletionProgram from llama_index.core.output_parsers import PydanticOutputParser prompt_template_str = """\ Can you get the stock information in the image \ and return the answer? Pick just one fund. Make sure the answer is a JSON format corresponding to a Pydantic schema. The Pydantic schema is given below. """ # Initiated Anthropic MultiModal class anthropic_mm_llm = AnthropicMultiModal(max_tokens=300) llm_program = MultiModalLLMCompletionProgram.from_defaults( output_cls=TickerList, image_documents=image_documents, prompt_template_str=prompt_template_str, multi_modal_llm=anthropic_mm_llm, verbose=True, )</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=1b2985e5-c4b8-4860-9140-bba9813e345b"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-12"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="n">response</span> <span class="o">=</span> <span class="n">llm_program</span><span class="p">()</span> </pre></div> <div class="clipboard-copy-txt" id="cell-12">response = llm_program()</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre><span class="ansi-bold" style="color: rgb(90,149,237)">> Raw output: { "fund": "ARKK", "tickers": [ { "direction": "Buy", "ticker": "TSLA", "company": "TESLA INC", "shares_traded": 93664, "percent_of_total_etf": 0.2453 }, { "direction": "Buy", "ticker": "TXG", "company": "10X GENOMICS INC", "shares_traded": 159506, "percent_of_total_etf": 0.0907 }, { "direction": "Buy", "ticker": "CRSP", "company": "CRISPR THERAPEUTICS AG", "shares_traded": 86268, "percent_of_total_etf": 0.0669 }, { "direction": "Buy", "ticker": "RXRX", "company": "RECURSION PHARMACEUTICALS", "shares_traded": 289619, "percent_of_total_etf": 0.0391 } ] } </span></pre> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=0304aeac-89b4-4aea-8209-7c7fbf3af5d7"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-13"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">response</span><span class="p">))</span> </pre></div> <div class="clipboard-copy-txt" id="cell-13">print(str(response))</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre>fund='ARKK' tickers=[TickerInfo(direction='Buy', ticker='TSLA', company='TESLA INC', shares_traded=93664, percent_of_total_etf=0.2453), TickerInfo(direction='Buy', ticker='TXG', company='10X GENOMICS INC', shares_traded=159506, percent_of_total_etf=0.0907), TickerInfo(direction='Buy', ticker='CRSP', company='CRISPR THERAPEUTICS AG', shares_traded=86268, percent_of_total_etf=0.0669), TickerInfo(direction='Buy', ticker='RXRX', company='RECURSION PHARMACEUTICALS', shares_traded=289619, percent_of_total_etf=0.0391)] </pre> </div> </div> </div> </div> </div> </div> <div class="jp-Cell jp-MarkdownCell jp-Notebook-cell" id="cell-id=19d296f0-81f1-4f9a-80b0-05ccb7482569"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"><div class="jp-InputPrompt jp-InputArea-prompt"> </div><div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-MarkdownOutput" data-mime-type="text/markdown"> <h2 id="index-into-a-vector-store">Index into a Vector Store<a class="anchor-link" href="#index-into-a-vector-store">¶</a></h2><p>In this section we show you how to use Claude 3 to build a RAG pipeline over image data. We first use Claude to extract text from a set of images. We then index the text with an embedding model. Finally, we build a query pipeline over the data.</p> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=150d3627-43ec-40cc-b901-09d559840a25"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-14"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="c1"># !wget "https://www.dropbox.com/scl/fi/pvxgohp5ts5mcj2js8drk/mixed_wiki_images_small.zip?rlkey=3zf0z0n2etsjp19tofasaf4vy&dl=1" -O mixed_wiki_images_small.zip</span> <span class="c1"># !wget "https://www.dropbox.com/scl/fi/vg2h92owduqmarwj7fxnc/mixed_wiki_images_small.zip?rlkey=fejq570ehhil3qgv3gibaliqu&dl=1" -O mixed_wiki_images_small.zip</span> <span class="err">!</span><span class="n">wget</span> <span class="s2">"https://www.dropbox.com/scl/fi/c1ec6osn0r2ggnitijqhl/mixed_wiki_images_small.zip?rlkey=swwxc7h4qtwlnhmby5fsnderd&dl=1"</span> <span class="o">-</span><span class="n">O</span> <span class="n">mixed_wiki_images_small</span><span class="o">.</span><span class="n">zip</span> <span class="err">!</span><span class="n">unzip</span> <span class="n">mixed_wiki_images_small</span><span class="o">.</span><span class="n">zip</span> </pre></div> <div class="clipboard-copy-txt" id="cell-14"># !wget "https://www.dropbox.com/scl/fi/pvxgohp5ts5mcj2js8drk/mixed_wiki_images_small.zip?rlkey=3zf0z0n2etsjp19tofasaf4vy&dl=1" -O mixed_wiki_images_small.zip # !wget "https://www.dropbox.com/scl/fi/vg2h92owduqmarwj7fxnc/mixed_wiki_images_small.zip?rlkey=fejq570ehhil3qgv3gibaliqu&dl=1" -O mixed_wiki_images_small.zip !wget "https://www.dropbox.com/scl/fi/c1ec6osn0r2ggnitijqhl/mixed_wiki_images_small.zip?rlkey=swwxc7h4qtwlnhmby5fsnderd&dl=1" -O mixed_wiki_images_small.zip !unzip mixed_wiki_images_small.zip</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=acb73dab-ef81-4e09-8b74-dc2dd22526ee"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-15"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.multi_modal_llms.anthropic</span> <span class="kn">import</span> <span class="n">AnthropicMultiModal</span> <span class="n">anthropic_mm_llm</span> <span class="o">=</span> <span class="n">AnthropicMultiModal</span><span class="p">(</span><span class="n">max_tokens</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-15">from llama_index.multi_modal_llms.anthropic import AnthropicMultiModal anthropic_mm_llm = AnthropicMultiModal(max_tokens=300)</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=b84bdfe2-0907-4c61-bad3-19d924787e19"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-16"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.core.schema</span> <span class="kn">import</span> <span class="n">TextNode</span> <span class="kn">from</span> <span class="nn">pathlib</span> <span class="kn">import</span> <span class="n">Path</span> <span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">SimpleDirectoryReader</span> <span class="n">nodes</span> <span class="o">=</span> <span class="p">[]</span> <span class="k">for</span> <span class="n">img_file</span> <span class="ow">in</span> <span class="n">Path</span><span class="p">(</span><span class="s2">"mixed_wiki_images_small"</span><span class="p">)</span><span class="o">.</span><span class="n">glob</span><span class="p">(</span><span class="s2">"*.png"</span><span class="p">):</span> <span class="nb">print</span><span class="p">(</span><span class="n">img_file</span><span class="p">)</span> <span class="c1"># put your local directore here</span> <span class="n">image_documents</span> <span class="o">=</span> <span class="n">SimpleDirectoryReader</span><span class="p">(</span><span class="n">input_files</span><span class="o">=</span><span class="p">[</span><span class="n">img_file</span><span class="p">])</span><span class="o">.</span><span class="n">load_data</span><span class="p">()</span> <span class="n">response</span> <span class="o">=</span> <span class="n">anthropic_mm_llm</span><span class="o">.</span><span class="n">complete</span><span class="p">(</span> <span class="n">prompt</span><span class="o">=</span><span class="s2">"Describe the images as an alternative text"</span><span class="p">,</span> <span class="n">image_documents</span><span class="o">=</span><span class="n">image_documents</span><span class="p">,</span> <span class="p">)</span> <span class="n">metadata</span> <span class="o">=</span> <span class="p">{</span><span class="s2">"img_file"</span><span class="p">:</span> <span class="n">img_file</span><span class="p">}</span> <span class="n">nodes</span><span class="o">.</span><span class="n">append</span><span class="p">(</span><span class="n">TextNode</span><span class="p">(</span><span class="n">text</span><span class="o">=</span><span class="nb">str</span><span class="p">(</span><span class="n">response</span><span class="p">),</span> <span class="n">metadata</span><span class="o">=</span><span class="n">metadata</span><span class="p">))</span> </pre></div> <div class="clipboard-copy-txt" id="cell-16">from llama_index.core.schema import TextNode from pathlib import Path from llama_index.core import SimpleDirectoryReader nodes = [] for img_file in Path("mixed_wiki_images_small").glob("*.png"): print(img_file) # put your local directore here image_documents = SimpleDirectoryReader(input_files=[img_file]).load_data() response = anthropic_mm_llm.complete( prompt="Describe the images as an alternative text", image_documents=image_documents, ) metadata = {"img_file": img_file} nodes.append(TextNode(text=str(response), metadata=metadata))</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre>mixed_wiki_images_small/8.png mixed_wiki_images_small/14.png mixed_wiki_images_small/28.png mixed_wiki_images_small/15.png mixed_wiki_images_small/11.png mixed_wiki_images_small/10.png mixed_wiki_images_small/20.png mixed_wiki_images_small/23.png mixed_wiki_images_small/26.png mixed_wiki_images_small/19.png mixed_wiki_images_small/4.png mixed_wiki_images_small/5.png mixed_wiki_images_small/7.png mixed_wiki_images_small/6.png mixed_wiki_images_small/2.png </pre> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=818b7a22-62e2-4e17-94fb-091229493374"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-17"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">VectorStoreIndex</span><span class="p">,</span> <span class="n">StorageContext</span> <span class="kn">from</span> <span class="nn">llama_index.embeddings.openai</span> <span class="kn">import</span> <span class="n">OpenAIEmbedding</span> <span class="kn">from</span> <span class="nn">llama_index.llms.anthropic</span> <span class="kn">import</span> <span class="n">Anthropic</span> <span class="kn">from</span> <span class="nn">llama_index.vector_stores.qdrant</span> <span class="kn">import</span> <span class="n">QdrantVectorStore</span> <span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">Settings</span> <span class="kn">from</span> <span class="nn">llama_index.core</span> <span class="kn">import</span> <span class="n">StorageContext</span> <span class="kn">import</span> <span class="nn">qdrant_client</span> <span class="c1"># Create a local Qdrant vector store</span> <span class="n">client</span> <span class="o">=</span> <span class="n">qdrant_client</span><span class="o">.</span><span class="n">QdrantClient</span><span class="p">(</span><span class="n">path</span><span class="o">=</span><span class="s2">"qdrant_mixed_img"</span><span class="p">)</span> <span class="n">vector_store</span> <span class="o">=</span> <span class="n">QdrantVectorStore</span><span class="p">(</span><span class="n">client</span><span class="o">=</span><span class="n">client</span><span class="p">,</span> <span class="n">collection_name</span><span class="o">=</span><span class="s2">"collection"</span><span class="p">)</span> <span class="c1"># Using the embedding model to Gemini</span> <span class="n">embed_model</span> <span class="o">=</span> <span class="n">OpenAIEmbedding</span><span class="p">()</span> <span class="n">anthropic_mm_llm</span> <span class="o">=</span> <span class="n">AnthropicMultiModal</span><span class="p">(</span><span class="n">max_tokens</span><span class="o">=</span><span class="mi">300</span><span class="p">)</span> <span class="n">storage_context</span> <span class="o">=</span> <span class="n">StorageContext</span><span class="o">.</span><span class="n">from_defaults</span><span class="p">(</span><span class="n">vector_store</span><span class="o">=</span><span class="n">vector_store</span><span class="p">)</span> <span class="n">index</span> <span class="o">=</span> <span class="n">VectorStoreIndex</span><span class="p">(</span> <span class="n">nodes</span><span class="o">=</span><span class="n">nodes</span><span class="p">,</span> <span class="n">storage_context</span><span class="o">=</span><span class="n">storage_context</span><span class="p">,</span> <span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-17">from llama_index.core import VectorStoreIndex, StorageContext from llama_index.embeddings.openai import OpenAIEmbedding from llama_index.llms.anthropic import Anthropic from llama_index.vector_stores.qdrant import QdrantVectorStore from llama_index.core import Settings from llama_index.core import StorageContext import qdrant_client # Create a local Qdrant vector store client = qdrant_client.QdrantClient(path="qdrant_mixed_img") vector_store = QdrantVectorStore(client=client, collection_name="collection") # Using the embedding model to Gemini embed_model = OpenAIEmbedding() anthropic_mm_llm = AnthropicMultiModal(max_tokens=300) storage_context = StorageContext.from_defaults(vector_store=vector_store) index = VectorStoreIndex( nodes=nodes, storage_context=storage_context, )</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell jp-mod-noOutputs" id="cell-id=a89b3256-f361-4ef9-8ed1-55a26b9430ce"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-18"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.llms.anthropic</span> <span class="kn">import</span> <span class="n">Anthropic</span> <span class="n">query_engine</span> <span class="o">=</span> <span class="n">index</span><span class="o">.</span><span class="n">as_query_engine</span><span class="p">(</span><span class="n">llm</span><span class="o">=</span><span class="n">Anthropic</span><span class="p">())</span> <span class="n">response</span> <span class="o">=</span> <span class="n">query_engine</span><span class="o">.</span><span class="n">query</span><span class="p">(</span><span class="s2">"Tell me more about the porsche"</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-18">from llama_index.llms.anthropic import Anthropic query_engine = index.as_query_engine(llm=Anthropic()) response = query_engine.query("Tell me more about the porsche")</div> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=f182c1e6-f66b-4e6b-9b8f-98925acea4ee"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-19"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="nb">print</span><span class="p">(</span><span class="nb">str</span><span class="p">(</span><span class="n">response</span><span class="p">))</span> </pre></div> <div class="clipboard-copy-txt" id="cell-19">print(str(response))</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedText jp-OutputArea-output" data-mime-type="text/plain" tabindex="0"> <pre>Unfortunately I cannot directly reference the provided context in my answer. However, from the details given, it appears there are images showing a white Porsche Taycan electric sports car. The Taycan seems to have a sleek, aerodynamic design with features like LED headlights, alloy wheels, and a full-width rear light bar. The photos show the Taycan parked indoors, likely a garage or showroom, as well as outdoors on a street in what looks like a residential area. Additional relevant details about the Porsche are not provided in the context, so I cannot elaborate further on the specific vehicle model or its characteristics. Please let me know if you have any other questions! </pre> </div> </div> </div> </div> </div> </div><div class="jp-Cell jp-CodeCell jp-Notebook-cell"> <div class="jp-Cell jp-CodeCell jp-Notebook-cell" id="cell-id=f3764d8d-62ae-4195-af74-4103af3972f5"> <div class="jp-Cell-inputWrapper" tabindex="0"> <div class="jp-Collapser jp-InputCollapser jp-Cell-inputCollapser"> </div> <div class="jp-InputArea jp-Cell-inputArea"> <div class="jp-InputPrompt jp-InputArea-prompt">In [ ]:</div><div class="jp-CodeMirrorEditor jp-Editor jp-InputArea-editor" data-type="inline"> <div class="CodeMirror cm-s-jupyter"> <div class="zeroclipboard-container"> <clipboard-copy for="cell-20"> <div> <span class="notice" hidden="">Copied!</span> <svg aria-hidden="true" class="clipboard-copy-icon" data-view-component="true" height="20" version="1.1" viewbox="0 0 16 16" width="20"> <path d="M0 6.75C0 5.784.784 5 1.75 5h1.5a.75.75 0 010 1.5h-1.5a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-1.5a.75.75 0 011.5 0v1.5A1.75 1.75 0 019.25 16h-7.5A1.75 1.75 0 010 14.25v-7.5z" fill="currentColor" fill-rule="evenodd"></path> <path d="M5 1.75C5 .784 5.784 0 6.75 0h7.5C15.216 0 16 .784 16 1.75v7.5A1.75 1.75 0 0114.25 11h-7.5A1.75 1.75 0 015 9.25v-7.5zm1.75-.25a.25.25 0 00-.25.25v7.5c0 .138.112.25.25.25h7.5a.25.25 0 00.25-.25v-7.5a.25.25 0 00-.25-.25h-7.5z" fill="currentColor" fill-rule="evenodd"></path> </svg> </div> </clipboard-copy> </div> <div class="highlight-ipynb hl-python"><pre><span></span><span class="kn">from</span> <span class="nn">llama_index.core.response.notebook_utils</span> <span class="kn">import</span> <span class="n">display_source_node</span> <span class="k">for</span> <span class="n">n</span> <span class="ow">in</span> <span class="n">response</span><span class="o">.</span><span class="n">source_nodes</span><span class="p">:</span> <span class="n">display_source_node</span><span class="p">(</span><span class="n">n</span><span class="p">,</span> <span class="n">metadata_mode</span><span class="o">=</span><span class="s2">"all"</span><span class="p">)</span> </pre></div> <div class="clipboard-copy-txt" id="cell-20">from llama_index.core.response.notebook_utils import display_source_node for n in response.source_nodes: display_source_node(n, metadata_mode="all")</div> </div> </div> </div> </div> <div class="jp-Cell-outputWrapper"> <div class="jp-Collapser jp-OutputCollapser jp-Cell-outputCollapser"> </div> <div class="jp-OutputArea jp-Cell-outputArea"> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-OutputArea-output" data-mime-type="text/markdown" tabindex="0"> <p><strong>Node ID:</strong> e04f2364-8fa2-413c-8d76-4981990e49b9<br/><strong>Similarity:</strong> 0.83693930783145<br/><strong>Text:</strong> img_file: mixed_wiki_images_small/11.png</p> <p>The image shows a white Porsche Taycan Turbo electric s...<br/></p> </div> </div> <div class="jp-OutputArea-child"> <div class="jp-OutputPrompt jp-OutputArea-prompt"></div> <div class="jp-RenderedHTMLCommon jp-RenderedMarkdown jp-OutputArea-output" data-mime-type="text/markdown" tabindex="0"> <p><strong>Node ID:</strong> e2de0d05-2e97-43bb-80dd-f28c4e9bcb28<br/><strong>Similarity:</strong> 0.8357091967156951<br/><strong>Text:</strong> img_file: mixed_wiki_images_small/2.png</p> <p>The image shows a white Porsche Taycan electric sports c...<br/></p> </div> </div> </div> </div> </div> </div> </div>  </div>  <style> ['pre { line-height: 125%; }\ntd.linenos .normal { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }\nspan.linenos { color: inherit; background-color: transparent; padding-left: 5px; padding-right: 5px; }\ntd.linenos .special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; }\nspan.linenos.special { color: #000000; background-color: #ffffc0; padding-left: 5px; padding-right: 5px; 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