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Using the provided context, answer the user's question to the best of your ability using the resources provided.\nIf there is nothing in the context relevant to the question at hand, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.\n------------\n{context}\n------------\nREMEMBER: If there is no relevant information within the context, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.", "id": "conversationalRetrievalQAChain_0-input-responsePrompt-string" } ], "inputAnchors": [ { "label": "Chat Model", "name": "model", "type": "BaseChatModel", "id": "conversationalRetrievalQAChain_0-input-model-BaseChatModel" }, { "label": "Vector Store Retriever", "name": "vectorStoreRetriever", "type": "BaseRetriever", "id": "conversationalRetrievalQAChain_0-input-vectorStoreRetriever-BaseRetriever" }, { "label": "Memory", "name": "memory", "type": "BaseMemory", "optional": true, "description": "If left empty, a default BufferMemory will be used", "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory" } ], "inputs": { "model": "{{chatOpenAI_0.data.instance}}", "vectorStoreRetriever": "{{memoryVectorStore_0.data.instance}}", "memory": "", "rephrasePrompt": "Given the following conversation and a follow up question, rephrase the follow up question to be a standalone question.\n\nChat History:\n{chat_history}\nFollow Up Input: {question}\nStandalone Question:", "responsePrompt": "You are a helpful assistant. Using the provided context, answer the user's question to the best of your ability using the resources provided.\nIf there is nothing in the context relevant to the question at hand, just say \"Hmm, I'm not sure.\" Don't try to make up an answer.\n------------\n{context}\n------------\nREMEMBER: If there is no relevant information within the context, just say \"Hmm, I'm not sure.\" Don't try to make up an answer." }, "outputAnchors": [ { "id": "conversationalRetrievalQAChain_0-output-conversationalRetrievalQAChain-ConversationalRetrievalQAChain|BaseChain|Runnable", "name": "conversationalRetrievalQAChain", "label": "ConversationalRetrievalQAChain", "type": "ConversationalRetrievalQAChain | BaseChain | Runnable" } ], "outputs": {}, "selected": false }, "selected": false, "positionAbsolute": { "x": 1499.2693059023254, "y": 430.03911199833317 }, "dragging": false }, { "width": 300, "height": 408, "id": "memoryVectorStore_0", "position": { "x": 1082.0280622332507, "y": 589.9990964387842 }, "type": "customNode", "data": { "id": "memoryVectorStore_0", "label": "In-Memory Vector Store", "version": 1, "name": "memoryVectorStore", "type": "Memory", "baseClasses": ["Memory", "VectorStoreRetriever", "BaseRetriever"], "category": "Vector Stores", "description": "In-memory vectorstore that stores embeddings and does an exact, linear search for the most similar embeddings.", "inputParams": [ { "label": "Top K", "name": "topK", "description": "Number of top results to fetch. 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"additionalParams": true, "id": "searchApi_0-input-customParameters-json" }, { "label": "Metadata", "name": "metadata", "type": "json", "optional": true, "additionalParams": true, "id": "searchApi_0-input-metadata-json" } ], "inputAnchors": [ { "label": "Text Splitter", "name": "textSplitter", "type": "TextSplitter", "optional": true, "id": "searchApi_0-input-textSplitter-TextSplitter" } ], "inputs": { "query": "", "customParameters": "{\"engine\":\"youtube_transcripts\",\"video_id\":\"0e3GPea1Tyg\"}", "textSplitter": "{{characterTextSplitter_0.data.instance}}", "metadata": "" }, "outputAnchors": [ { "id": "searchApi_0-output-searchApi-Document", "name": "searchApi", "label": "Document", "type": "Document" } ], "outputs": {}, "selected": false }, "selected": false, "positionAbsolute": { "x": 680.1258121447145, "y": 144.9905217023999 }, "dragging": false } ], "edges": [ { "source": "memoryVectorStore_0", "sourceHandle": 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