Create Agent Response Log

POST

/v2/api/agent/{agent_id}/response/log

Logs a response generated by an agent along with metadata including tokens, sources, user, and timestamps.

Request

Path Params

Header Params

Body Params application/json

Examples

Responses

🟢201Created

application/json

Response Log Created Successfully

Body

🟠400Bad Request

🟠404Record Not Found

🔴500Server Error

Request Example

Shell

JavaScript

Java

Swift

curl --location -g --request POST 'https:///v2/api/agent/0/response/log' \
--header 'Ocp-Apim-Subscription-Key: ' \
--header 'Authorization: Bearer ' \
--header 'Content-Type: application/json' \
--data-raw '{
    "chat_thread_id": 4354,
    "user_id": 147,
    "question": "Can you tell me how RAG works from the sources given?",
    "response": {
        "query": "Explain how Retrieval-Augmented Generation (RAG) works.",
        "answer": "Retrieval-Augmented Generation (RAG) is a technique in natural language processing that enhances the capabilities of generative language models by integrating real-time data retrieval...\n",
        "run_id": "bb7b49f8-fa06-4504-9e39-dec8f10cb0b9",
        "history": [
            {
                "bot": "Hello! How can I assist you today?",
                "user": "hi"
            }
        ],
        "indexes": [
            0
        ],
        "sources": "[0]",
        "success": true,
        "thoughts": "",
        "cache_hit": false,
        "agent_mode": "QnA",
        "corpus_ids": [
            645
        ],
        "references": [
            {
                "url": "Introduction to RAG1738098993.txt",
                "order": 1,
                "number": 0
            }
        ],
        "data_points": [
            {}
        ],
        "instructions": [
            ""
        ],
        "total_tokens": 4809,
        "prompt_prefix": "You are an AI assistant specializing in providing legal advice...",
        "prompt_tokens": 4329,
        "completion_tokens": 480,
        "followup_questions": [
            "What are the components involved in the RAG process?",
            "How does RAG ensure responses are contextually appropriate?",
            "In what domains is RAG particularly useful?"
        ]
    },
    "total_tokens": 4809,
    "prompt_tokens": 4329,
    "completion_tokens": 480,
    "created_by": "[email protected]",
    "cache_hit": false,
    "query_source": "web",
    "llm_config_id": 8
}'

Response Example

201 - Example 1

{
    "success": true,
    "message": "Response Log Created Successfully.",
    "data": {
        "id": 25248,
        "question": "Can you tell me how RAG works from the sources given?",
        "response": {
            "query": "Explain how Retrieval-Augmented Generation (RAG) works.",
            "answer": "Retrieval-Augmented Generation (RAG) is a technique in natural language processing that enhances the capabilities of generative language models by integrating real-time data retrieval...\n",
            "run_id": "bb7b49f8-fa06-4504-9e39-dec8f10cb0b9",
            "history": [
                {
                    "bot": "Hello! How can I assist you today?",
                    "user": "hi"
                }
            ],
            "indexes": [
                0
            ],
            "sources": "[0]",
            "success": true,
            "thoughts": "",
            "cache_hit": false,
            "agent_mode": "QnA",
            "corpus_ids": [
                645
            ],
            "references": [
                {
                    "url": "Introduction to RAG1738098993.txt",
                    "order": 1,
                    "number": 0
                }
            ],
            "data_points": [
                {}
            ],
            "instructions": [
                "string"
            ],
            "total_tokens": 4809,
            "prompt_prefix": "You are an AI assistant specializing in providing legal advice...",
            "prompt_tokens": 4329,
            "completion_tokens": 480,
            "followup_questions": [
                "string"
            ]
        },
        "created_by": "[email protected]",
        "created_on": "2025-04-04T18:32:35.981741Z",
        "is_deleted": false,
        "total_tokens": 4809,
        "prompt_tokens": 4329,
        "completion_tokens": 480,
        "cache_hit": false,
        "query_source": "web",
        "message_id": null,
        "cost": "0.02404",
        "pinned": false,
        "chat_thread": 4354,
        "agent": 1297,
        "user": 147,
        "llm_config": 8
    }
}

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