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"suggestFollowupQuestions": "Asks the LLM to suggest follow-up questions based on the user's query.",
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"textEmbeddings": "When selected, search will use embeddings from the text-only embeddings model of extracted text chunks.",
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"imageEmbeddings": "When selected, search will use embeddings from the multimodal embeddings model of extracted images.",
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"llmInputs":
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"Sets what will be sent to the vision model. 'Images and text' sends both images and text to the model, 'Images' sends only images, and 'Text' sends only text.",
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"llmTextInputs": "When selected, text content from the search results will be sent to the LLM as context.",
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"llmImageInputs": "When selected, images from the search results will be sent to the LLM as context.",
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"retrievalMode":
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"Sets the retrieval mode for the Azure AI Search query. `Vectors + Text (Hybrid)` uses a combination of vector search and full text search, `Vectors` uses only vector search, and `Text` uses only full text search. Hybrid is generally optimal.",
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"streamChat": "Continuously streams the response to the chat UI as it is generated.",
Copy file name to clipboardExpand all lines: todo.txt
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@@ -10,8 +10,13 @@ TODO:
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# Inputs for LLM:
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# [X] text sources , use_text_sources = True
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# [X] image sources , use_image_sources = True
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Update:
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// Set default LLM inputs based on config override or fallback to Texts
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setSendTextSources(true);
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setSendImageSources(true);
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// Set default vector field settings
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setSearchTextEmbeddings(true);
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setSearchImageEmbeddings(true);
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To decide:
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* For user data lake client, how often should we double check the ACL matches the oid, versus assuming the URLs convey that? (Like when fetching the image?)
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* add a note that we only check owner, not full access control
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