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Create a SQL query

Create a SQL query#

This endpoint can be used to create a SQL query for a given prompt.

SQL generation parameters#

The following parameters are used for SQL generation:

  • finetuning_id: the id of the finetuning model. If this is not provided we use a reasoning LLM with retrieval augmented generation. If specified we use the finetuning model for sql generation.

  • low_latency_mode: When this flag is set, some of the agent steps are removed, which can lead to faster responses but reduce the accuracy. This is only supported for our new agent.

  • evaluate: whether to evaluate the generated SQL query.

  • sql: if you want to manually create the SQL query you can provide it here. If this is not provided we use the prompt to generate the SQL query.

Request this POST endpoint to create a SQL query for a given prompt:

api/v1/prompts/{prompt_id}/sql-generations

Parameters

Name

Type

Description

prompt_id

string

the prompt id of the prompt that you want to generate a SQL query for, Required

Request body

{
     "finetuning_id": "string",
     "low_latency_mode": false,
     "llm_config": {
         "llm_name": "gpt-4-turbo-preview"
     },
     "evaluate": false,
     "sql": "string",
     "metadata": {}
 }

Responses

HTTP 201 code response

{
    "id": "string",
    "metadata": {},
    "created_at": "string",
    "prompt_id": "string",
    "finetuning_id": "string",
    "status": "string",
    "completed_at": "string",
    "llm_config": {
        "llm_name": "gpt-4-turbo-preview",
        "api_base": "string"
    },
    "intermediate_steps": [
        {
            "action": "string",
            "action_input": "string",
            "observation": "string"
        }
    ],
    "sql": "string",
    "tokens_used": 0,
    "confidence_score": 0,
    "error": "string"
}

Request example

curl -X 'POST' \
'http://localhost/api/v1/prompts/65bbb224142cc9bea23e2a07/sql-generations' \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"low_latency_mode": false,
"llm_config": {
    "llm_name": "mistralai/Mixtral-8x7B-Instruct-v0.1",
    "api_base": "https://tt5h145hsc119q-8000.proxy.runpod.net/v1"
},
"evaluate": false,
"metadata": {}
}'

Response example

{
"id": "65bbb400142cc9bea23e2a0c",
"metadata": {},
"created_at": "2024-02-01T15:08:48.370228+00:00",
"prompt_id": "65bbb224142cc9bea23e2a07",
"finetuning_id": null,
"status": "VALID",
"completed_at": "2024-02-01T15:09:10.474942+00:00",
"llm_config": {
    "llm_name": "mistralai/Mixtral-8x7B-Instruct-v0.1",
    "api_base": "https://tt5h145hsc119q-8000.proxy.runpod.net/v1"
},
intermediate_steps": [
        {
        "thought": "I should Collect examples of Question/SQL pairs to check if there is a similar question among the examples.\n",
        "action": "FewshotExamplesRetriever",
        "action_input": "5",
        "observation": "samples ... "
        },
        ...
],
"sql": "SELECT metric_value \nFROM renthub_median_rent \nWHERE period_type = 'monthly' \nAND geo_type = 'city' \nAND location_name = 'Miami' \nAND property_type = 'All Residential' \nAND period_end = (SELECT DATE_TRUNC('MONTH', CURRENT_DATE()) - INTERVAL '1 day')\nLIMIT 10",
"tokens_used": 18115,
"confidence_score": null,
"error": null
}
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