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        "description": "Wrapper around Groq API with LPU Inference Engine",
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            "type": "asyncOptions",
            "loadMethod": "listModels",
            "placeholder": "llama3-70b-8192",
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            "label": "Temperature",
            "name": "temperature",
            "type": "number",
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            "optional": true,
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        ],
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            "label": "Cache",
            "name": "cache",
            "type": "BaseCache",
            "optional": true,
            "id": "groqChat_0-input-cache-BaseCache"
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        ],
        "inputs": {
          "cache": "",
          "modelName": "meta-llama/llama-4-scout-17b-16e-instruct",
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            "type": "GroqChat | BaseChatModel | BaseLanguageModel | Runnable"
          }
        ],
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        "selected": false
      },
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      "selected": false,
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            "id": "bufferWindowMemory_0-input-k-number"
          },
          {
            "label": "Session Id",
            "name": "sessionId",
            "type": "string",
            "description": "If not specified, a random id will be used. Learn <a target=\"_blank\" href=\"https://docs.flowiseai.com/memory#ui-and-embedded-chat\">more</a>",
            "default": "",
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            "additionalParams": true,
            "id": "bufferWindowMemory_0-input-sessionId-string"
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            "additionalParams": true,
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          "k": "5",
          "sessionId": "",
          "memoryKey": "chat_history"
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            "type": "BufferWindowMemory | BaseChatMemory | BaseMemory"
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      "positionAbsolute": {
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    },
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        ],
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        "description": "Search and retrieve documents from Document Store",
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            "label": "Select Store",
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                "label": "Retriever",
                "description": "",
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                "id": "documentStoreVS_0-output-vectorStore-VectorStore",
                "name": "vectorStore",
                "label": "Vector Store",
                "description": "",
                "type": "VectorStore"
              }
            ],
            "default": "retriever"
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        ],
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        "label": "Conversational Retrieval QA Chain",
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        "name": "conversationalRetrievalQAChain",
        "type": "ConversationalRetrievalQAChain",
        "baseClasses": [
          "ConversationalRetrievalQAChain",
          "BaseChain",
          "Runnable"
        ],
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            "label": "Return Source Documents",
            "name": "returnSourceDocuments",
            "type": "boolean",
            "optional": true,
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            "additionalParams": true,
            "optional": true,
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            "label": "Response Prompt",
            "name": "responsePrompt",
            "type": "string",
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            "rows": 4,
            "additionalParams": true,
            "optional": true,
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            "type": "BaseChatModel",
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            "label": "Vector Store Retriever",
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            "description": "If left empty, a default BufferMemory will be used",
            "id": "conversationalRetrievalQAChain_0-input-memory-BaseMemory"
          },
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            "label": "Input Moderation",
            "description": "Detect text that could generate harmful output and prevent it from being sent to the language model",
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            "type": "Moderation",
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