RestAPI interface document

Prerequisites

This interface document only provides AI call-related interfaces. There are two modes for AI interface calls:

The first mode is to use it with the data source management and AI data set management functions of the Chat2DB product, and Chat2DB completes the management of the database table structure.

The second mode is to manage your own database table structure by yourself, and only use Chat2DB's natural language to SQL function.

The first mode can use Chat2DB's natural language to SQL, natural language to report and other AI capabilities; the second mode cannot use the natural language to report capability, and other AI capabilities can be used.

The specific usage process is divided into the following steps. The first mode requires the execution of all the following steps, and none of them can be omitted; the second mode only requires the execution of the steps marked as (required);

Step 1: Create a data source

Create a data source in the Chat2DB product. The creation of a data source does not provide a rest interface. It must be created using the product interactive interface within the product. For specific creation methods, please refer to Create MySql Data Source (opens in a new tab)

Step 2: Create an AI dataset

After creating a data source, you need to create an AI dataset to synchronize the relevant table structure to AI. This interface does not provide a rest interface. It must be created using the product interactive interface within the product. For specific usage methods, please refer to AI dataset (opens in a new tab)

After creating the dataset, copy the dataset ID. Right-click the AI ​​dataset and select Copy dataset ID

Step 3: Create an API for the Rest interface call key (required)

The API for creating ApiKey does not provide a rest interface. You must use the product interactive interface to create it within the product. Refer to the picture below and click the avatar, then click Create ApiKey. After creating ApiKey, please save it locally. The specific content of ApiKey cannot be viewed on this platform later.

Step 4: Query the table matched by natural language

Get the AI ​​dataset ID created in the second step and the API key created in the third step, enter the natural language, and query the library table structure that may be used by the natural language. The specific API interface definition is as follows.

Get the matching table interface

Interface address: https://app.chat2db-ai.com/api/ai/rest/mapping_a (opens in a new tab)

Interface method: POST

Authentication method

Get the API key obtained in the second step, add Authorization to the Header in the request interface, and the value is Bearer API key

Request parameters

Body request parameter example

{
"input": "Sales in the past 3 days",
"tableSize": "10",
"dataSourceCollectionId": 12
}

Return example

The return result is a list of database table structures matched by natural language. The following is a sample json of the return result. Each object in data is a table structure related data.

Success:

{
"success": true,
"errorCode": "",
"errorMessage": "",
"data": [
{
"dataSourceId": 0,
"databaseName": "",
"schemaName": "",
"tableName": "",
"tableSchema": ""
}
],
"traceId": "",
"errorDetail": "",
"solutionLink": ""
}

Return the properties of the object in the result data

Step 5: Get the token for AI call (required)

Pass in the database table structure and AI type to get the token for AI call. The database table structure in this step can be obtained from Step 4 or the database table structure managed by the user

Get the token for AI call

Interface address: https://api.chat2db-ai.com/api/ai/rest/prompt_a (opens in a new tab)

Interface method: POST

Authentication method

Get the API key obtained in Step 3, add Authorization to the Header in the request interface, and the value is Bearer API key

Request parameters

RestPromptTableRequest properties

Body request parameter example

{
"questionType": "NL_2_SQL",
"input": "Sales in the past three months",
"databaseType": "MYSQL",
"tableSchemas": [
{
"dataSourceId": 0,
"databaseName": "Database database name",
"schemaName": "Database schema name",
"tableName": "Table name",
"tableSchema": "Table ddl"
}
],
"language": "ZH"
}

Return example

Success:

{
"success": true,
"errorCode": "",
"errorMessage": "",
"errorDetail": "",
"solutionLink": "",
"data": {
"token": "API call token",
"apiParams": ""
},
"traceId": ""
}

Return result attributes

RestPromptVO attributes

Step 6: AI call (required)

Use the token obtained in Step 5 to call the AI ​​interface. The AI ​​interface supports streaming and non-streaming calls

AI call interface

Interface address: https://api.chat2db-ai.com/api/ai/rest/chat_a (opens in a new tab)

Interface method: GET

Authentication method

Get the API key obtained in the second step, add Authorization to the Header in the request interface, and the value is Bearer API key

Request parameters

Request example

https://api.chat2db-ai.com/api/ai/rest/chat_a?token=sd***as&stream=true&timeout=30

Return example

This interface uses the SseEmitter protocol. The example of the result object returned by SseEmitter each time is as follows. When the output result is [DONE], it means the output is finished, otherwise one data object is output each time. The value of content is the content output by AI.

Streaming output example:

First output
{
"role": "assistant",
"content": "SELECT "
}
Second output
{
"role": "assistant",
"content": "*\n"
}
Third output
{
"role": "assistant",
"content": "FROM "
}
Fourth output
{
"role": "assistant",
"content": "table_name;\n"
}
Final output
[DONE]

Non-streaming output example:

Output all results
{
"role": "assistant",
"content": "SELECT *\nFROM table_name;\n"
}
Final output
[DONE]