Extruct AI

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### Successful Authentication Response Example

Source: https://www.extruct.ai/docs/api-reference/authentication

Provides an example of a successful JSON response when authenticating with the '/v1/user' endpoint. This response includes user-specific information such as user ID, email, and available credits.

```json
{
  "user_id": "user_123456",
  "email": "example@gmail.com",
  "available_credits": 1000,
  "organization_id": null,
  "organization_name": null,
  "organization_slug": null
}
```

--------------------------------

### HTTP Authorization Header Example

Source: https://www.extruct.ai/docs/api-reference/authentication

Demonstrates the correct format for the 'Authorization' header using Bearer Token Authentication. This header is required for all API requests to identify and authenticate the user.

```http
Authorization: Bearer YOUR_API_TOKEN
```

--------------------------------

### Test Authentication with cURL

Source: https://www.extruct.ai/docs/api-reference/authentication

Shows how to test your API authentication by making a GET request to the '/v1/user' endpoint using cURL. This request includes the 'Authorization' header with your API token and expects user details in the response.

```bash
curl -X GET "https://api.extruct.ai/v1/user" \
  -H "Authorization: Bearer YOUR_API_TOKEN"
```

--------------------------------

### GET /websites/extruct_ai/discovery/tasks

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task-results

Retrieves a list of discovery tasks. This endpoint allows users to fetch all created discovery tasks, providing a summary of each task's status and configuration.

```APIDOC
## GET /websites/extruct_ai/discovery/tasks

### Description
Retrieves a list of discovery tasks. This endpoint allows users to fetch all created discovery tasks, providing a summary of each task's status and configuration.

### Method
GET

### Endpoint
/websites/extruct_ai/discovery/tasks

### Parameters

#### Query Parameters
- **is_exhausted** (boolean) - Optional - Filters tasks by their exhaustion status.
- **auto_data_sources** (boolean) - Optional - Filters tasks based on whether auto data sources are enabled.
- **data_sources** (enum<string>[]) - Optional - Filters tasks by the data sources used (e.g., `web_search`, `linkedin`, `maps`).

### Request Example
```json
{
  "example": ""
}
```

### Response
#### Success Response (200)
- **id** (string) - Required - Unique identifier for the discovery task.
- **created_at** (string<date-time>) - Required - Timestamp when the task was created.
- **status** (enum<string>) - Required - Current status of the task (`created`, `in_progress`, `done`, `failed`).
- **query** (string) - Required - The search query used for the task.
- **desired_num_results** (integer) - Required - The desired number of results for the task.
- **results** (DiscoveryTaskResultOutput[]) - Required - An array of results obtained from the discovery task.
- **is_exhausted** (boolean) - Optional - Indicates if the search has exhausted all possible results (defaults to false).
- **num_results_discovered** (integer) - Optional - Total number of company candidates discovered (defaults to 0).
- **num_results_enriched** (integer) - Optional - Number of candidates enriched with company profiles (defaults to 0).
- **num_results_evaluated** (integer) - Optional - Number of candidates that had criteria evaluation completed (defaults to 0).
- **num_results** (integer) - Optional - Total number of results returned (defaults to 0).
- **table_id** (string | null) - Optional - Identifier for an associated table.
- **auto_data_sources** (boolean) - Optional - Flag indicating if data sources were automatically determined (defaults to true).
- **data_sources** (enum<string>[] | null) - Optional - List of data sources used for the task.
- **criteria** (CriterionDefinition[]) - Optional - Definitions of the criteria used in the task.

#### Response Example
```json
{
  "example": "{\n  \"id\": \"a1b2c3d4-e5f6-7890-1234-567890abcdef\",\n  \"created_at\": \"2023-10-27T10:00:00Z\",\n  \"status\": \"done\",\n  \"query\": \"AI companies in San Francisco\",\n  \"desired_num_results\": 10,\n  \"results\": [\n    {\n      \"id\": \"result-1\",\n      \"task_id\": \"a1b2c3d4-e5f6-7890-1234-567890abcdef\",\n      \"company_name\": \"Innovatech AI\",\n      \"company_description\": \"Leading AI solutions provider.\",\n      \"company_website\": \"https://innovatechai.com\",\n      \"relevance\": 95,\n      \"created_at\": \"2023-10-27T10:05:00Z\",\n      \"company_profile_id\": \"profile-abc\",\n      \"source\": \"web_search\",\n      \"scores\": {\n        \"is_ai_company\": {\n          \"grade\": 5,\n          \"explanation\": \"Company focuses heavily on AI research and development.\",\n          \"sources\": [\"https://innovatechai.com/about\", \"https://news.com/article\"]\n        }\n      }\n    }\n  ],\n  \"is_exhausted\": false,\n  \"num_results_discovered\": 50,\n  \"num_results_enriched\": 20,\n  \"num_results_evaluated\": 15,\n  \"num_results\": 1,\n  \"table_id\": null,\n  \"auto_data_sources\": true,\n  \"data_sources\": [\"web_search\"],\n  \"criteria\": [\n    {\n      \"key\": \"is_ai_company\",\n      \"name\": \"AI Company\",\n      \"criterion\": \"Does the company primarily focus on artificial intelligence technologies?\"\n    }\n  ]\n}"        
}
```
```

--------------------------------

### GET /v1/discovery_tasks/{task_id}

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task

Retrieves details of a specific discovery task by its ID. It returns information about the task's progress, discovered results, and configuration.

```APIDOC
## GET /v1/discovery_tasks/{task_id}

### Description
Retrieves details of a specific discovery task by its ID. It returns information about the task's progress, discovered results, and configuration.

### Method
GET

### Endpoint
/v1/discovery_tasks/{task_id}

### Parameters
#### Path Parameters
- **task_id** (string) - Required - The unique identifier of the discovery task.

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **id** (string) - The unique identifier of the discovery task.
- **created_at** (string, date-time) - The timestamp when the task was created.
- **status** (Status) - The current status of the discovery task.
- **query** (string) - The search query used for the discovery task.
- **desired_num_results** (integer) - The desired number of results for the task.
- **is_exhausted** (boolean) - Indicates if the discovery has reached its limit.
- **num_results_discovered** (integer) - Total number of company candidates discovered from the search.
- **num_results_enriched** (integer) - Number of candidates enriched with company profiles.
- **num_results_evaluated** (integer) - Number of candidates that had criteria evaluation completed.
- **num_results** (integer) - Total number of results.
- **table_id** (string or null) - The ID of the table associated with the task.
- **auto_data_sources** (boolean) - Whether to automatically use data sources.
- **data_sources** (array of DiscoveryDataSource or null) - List of data sources used in the task.
- **criteria** (array of CriterionDefinition or null) - List of criteria applied to the task.

#### Response Example
```json
{
  "id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "status": "created",
  "query": "<string>",
  "desired_num_results": 123,
  "is_exhausted": false,
  "num_results_discovered": 0,
  "num_results_enriched": 0,
  "num_results_evaluated": 0,
  "num_results": 0,
  "table_id": "<string>",
  "auto_data_sources": true,
  "data_sources": [
    "web_search"
  ],
  "criteria": [
    {
      "key": "<string>",
      "name": "<string>",
      "criterion": "<string>"
    }
  ]
}
```

#### Error Response (422)
- **detail** (array of ValidationError) - A list of validation errors.

#### Error Response Example
```json
{
  "detail": [
    {
      "loc": [
        "<string>"
      ],
      "msg": "<string>",
      "type": "<string>"
    }
  ]
}
```
```

--------------------------------

### GET /v1/healthcheck

Source: https://www.extruct.ai/docs/api-reference/healthcheck

Checks the health status of the Extruct.ai API.

```APIDOC
## GET /v1/healthcheck

### Description
Checks the health status of the API.

### Method
GET

### Endpoint
/v1/healthcheck

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
None

### Response
#### Success Response (200)
- **any** (any) - Successful Response

#### Response Example
```json
{
  "example": "<any>"
}
```
```

--------------------------------

### Documentation Fetching

Source: https://www.extruct.ai/docs/api-reference/tables/create-table-columns

Instructions on how to fetch additional documentation files for Extruct.ai.

```APIDOC
## Fetching Documentation

To find navigation and other pages in this documentation, fetch the `llms.txt` file at:

- **URL**: https://extruct.ai/docs/llms.txt
```

--------------------------------

### GET /v1/discovery_tasks/{task_id}/results

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task-results

Retrieves the results of a company discovery task by its ID. The results are ordered by relevance and can be paginated using offset and limit query parameters.

```APIDOC
## GET /v1/discovery_tasks/{task_id}/results

### Description
Returns a company discovery task results by ID. You can use this endpoint to get the results of the task. Results are ordered by relevance (desc) and can be paginated.

### Method
GET

### Endpoint
/v1/discovery_tasks/{task_id}/results

### Parameters
#### Path Parameters
- **task_id** (string) - Required - The ID of the discovery task.

#### Query Parameters
- **offset** (integer | null) - Optional - The number of results to skip.
- **limit** (integer | null) - Optional - The maximum number of results to return.

#### Request Body
This endpoint does not require a request body.

### Request Example
```bash
curl --request GET \
  --url https://api.extruct.ai/v1/discovery_tasks/{task_id}/results \
  --header 'Authorization: Bearer <token>'
```

### Response
#### Success Response (200)
- **id** (string) - The unique identifier for the discovery task.
- **created_at** (string) - The timestamp when the task was created.
- **status** (string) - The current status of the task (e.g., "created").
- **query** (string) - The original query used for the discovery task.
- **desired_num_results** (integer) - The desired number of results for the task.
- **results** (array) - A list of discovered company results.
  - **id** (string) - The unique identifier for a result.
  - **task_id** (string) - The ID of the task this result belongs to.
  - **company_name** (string) - The name of the company.
  - **company_description** (string) - A description of the company.
  - **company_website** (string) - The website of the company.
  - **relevance** (integer) - The relevance score of the result.
  - **created_at** (string) - The timestamp when the result was created.
  - **company_profile_id** (string) - The ID of the company profile.
  - **source** (string) - The source of the data (e.g., "web_search").
  - **scores** (object) - Additional scores associated with the result.
- **is_exhausted** (boolean) - Indicates if all possible results have been retrieved.
- **num_results_discovered** (integer) - The number of results discovered.
- **num_results_enriched** (integer) - The number of results enriched.
- **num_results_evaluated** (integer) - The number of results evaluated.
- **num_results** (integer) - The total number of results.
- **table_id** (string) - The ID of the table associated with the task.
- **auto_data_sources** (boolean) - Indicates if data sources were automatically determined.
- **data_sources** (array) - A list of data sources used for the task.
- **criteria** (array) - The criteria used for the discovery task.
  - **key** (string) - The key for the criterion.
  - **name** (string) - The name of the criterion.
  - **criterion** (string) - The criterion itself.

#### Response Example
```json
{
  "id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "status": "created",
  "query": "<string>",
  "desired_num_results": 123,
  "results": [
    {
      "id": "<string>",
      "task_id": "<string>",
      "company_name": "<string>",
      "company_description": "<string>",
      "company_website": "<string>",
      "relevance": 123,
      "created_at": "2023-11-07T05:31:56Z",
      "company_profile_id": "<string>",
      "source": "web_search",
      "scores": {}
    }
  ],
  "is_exhausted": false,
  "num_results_discovered": 0,
  "num_results_enriched": 0,
  "num_results_evaluated": 0,
  "num_results": 0,
  "table_id": "<string>",
  "auto_data_sources": true,
  "data_sources": [
    "web_search"
  ],
  "criteria": [
    {
      "key": "<string>",
      "name": "<string>",
      "criterion": "<string>"
    }
  ]
}
```

### Authorizations
- **Authorization** (string) - Required - Header 'Authorization: Bearer <token>'
```

--------------------------------

### Data Schemas and Configurations

Source: https://www.extruct.ai/docs/api-reference/tables/clone-table

This section details the various data schemas and column configurations used within the Extruct AI project. It includes schemas for agents, discovery scores, input columns, owner information, people finder, and table relationships.

```APIDOC
## Data Schemas and Configurations

### Description
This section details the various data schemas and column configurations used within the Extruct AI project. It includes schemas for agents, discovery scores, input columns, owner information, people finder, and table relationships.

### Schemas and Configurations:

*   **CriterionGradeColumnConfig**: Configuration for grading criteria columns.
*   **CriterionGraderAgentSchema**: Schema for the Criterion Grader Agent.
    *   `criterion` (string) - Required - The grading criterion.
*   **DiscoveryScoresColumnConfig**: Configuration for discovery scores columns.
    *   `kind` (string) - `discovery_scores` - The type of column, fixed to 'discovery_scores'.
    *   `name` (string) - Required - The name of the column.
    *   `key` (string) - Required - The key associated with the discovery score.
*   **InputColumnConfig**: Configuration for input columns.
    *   `kind` (string) - `input` - The type of column, fixed to 'input'.
    *   `name` (string) - Required - The name of the column.
    *   `key` (string) - Required - The key associated with the input data.
*   **OwnerInfo**: Schema for owner information.
    *   `id` (string) - Required - The unique identifier of the owner.
    *   `email` (string) - Required - The email address of the owner.
*   **PeopleFinderAgentSchema**: Schema for the People Finder Agent.
    *   `roles` (array of strings) - Required - A list of roles.
*   **PeopleFinderColumnConfig**: Configuration for people finder columns.
    *   `kind` (string) - `company_people_finder` - The type of column, fixed to 'company_people_finder'.
    *   `name` (string) - Required - The name of the column.
    *   `key` (string) - Required - The key associated with the people finder data.
    *   `value` - Required - The PeopleFinderAgentSchema defining the details.
*   **TableKind**: Enum for table types.
    *   `generic`
    *   `company`
    *   `people`
*   **TableRelationshipOutput**: Output schema for table relationships.
    *   `table_id` (string) - Required - ID of the related table.
    *   `relationship_type` - Required - The type of relationship (e.g., `company_people`).
*   **TableRelationshipType**: Enum for table relationship types.
    *   `company_people`
*   **TableSettings**: Settings for tables.
    *   `exclude_from_search` (boolean) - Optional - Whether to exclude the table from search (defaults to false).
*   **ValidationError**: Schema for validation errors.
    *   `loc` (array) - Required - The location of the error.
    *   `msg` (string) - Required - The error message.
    *   `type` (string) - Required - The type of error.

### Fetching Documentation

To find navigation and other pages in this documentation, fetch the llms.txt file at: https://extruct.ai/docs/llms.txt
```

--------------------------------

### Get Discovery Task Results (cURL)

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task-results

This snippet shows how to retrieve the results of a company discovery task using cURL. It requires the task ID and an authorization token. The endpoint returns a JSON object containing the task details and the discovered company results.

```curl
curl --request GET \
  --url https://api.extruct.ai/v1/discovery_tasks/{task_id}/results \
  --header 'Authorization: Bearer <token>'
```

--------------------------------

### Create Table using cURL

Source: https://www.extruct.ai/docs/api-reference/tables/create-table

This snippet demonstrates how to create a new table using the Extruct AI API via cURL. It includes setting the authorization token, content type, and providing a JSON payload for table configuration, such as defining columns with agent-based data extraction.

```cURL
curl --request POST \
  --url https://api.extruct.ai/v1/tables \
  --header 'Authorization: Bearer <token>' \
  --header 'Content-Type: application/json' \
  --data '
{
  "name": "Supercharged Research",
  "kind": "company",
  "notify": false,
  "column_configs": [
    {
      "kind": "agent",
      "name": "Company Description",
      "key": "description",
      "value": {
        "agent_type": "research_pro",
        "prompt": "Research the company {company_name} ({company_website}) and provide a short description.",
        "output_format": "text"
      }
    }
  ]
}'

```

--------------------------------

### Company Website Column Configuration

Source: https://www.extruct.ai/docs/api-reference/tables/create-table-columns

Configuration for a column storing company websites, automatically populated from company enrichment.

```APIDOC
## Company Website Column Configuration (CompanyWebsiteColumnConfig)

### Description
Configuration for a column storing company websites, automatically populated from company enrichment.

### Method
N/A (This is a schema definition)

### Endpoint
N/A (This is a schema definition)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **name** (string) - Required - The name of the company website column.
- **key** (string) - Required - The key associated with the company website column.

### Request Example
```json
{
  "name": "Company Website",
  "key": "company_website_key"
}
```

### Response
#### Success Response (200)
- **kind** (string) - The type of column, always "company_website".
- **name** (string) - The name of the company website column.
- **key** (string) - The key associated with the company website column.

#### Response Example
```json
{
  "kind": "company_website",
  "name": "Company Website",
  "key": "company_website_key"
}
```
```

--------------------------------

### CompanyWebsiteColumnConfig Schema

Source: https://www.extruct.ai/docs/api-reference/tables/clone-table

Configuration for a system column storing company websites, automatically populated from company enrichment data.

```APIDOC
## CompanyWebsiteColumnConfig Schema

### Description
Configuration for a system column that stores the company website. This information is automatically populated from company enrichment.

### Properties
- **kind** (string, const: 'company_website') - The type of column, fixed to 'company_website'.
- **name** (string) - The user-defined name of the column.
- **key** (string) - A unique key for the column.

### Required
- name
- key
```

--------------------------------

### Discovery Task Results Response Structure (JSON)

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task-results

This JSON object represents the structure of the response when fetching discovery task results. It includes information about the task itself, such as its ID, status, and query, as well as an array of discovered company results, each with details like name, description, website, and relevance.

```json
{
  "id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "status": "created",
  "query": "<string>",
  "desired_num_results": 123,
  "results": [
    {
      "id": "<string>",
      "task_id": "<string>",
      "company_name": "<string>",
      "company_description": "<string>",
      "company_website": "<string>",
      "relevance": 123,
      "created_at": "2023-11-07T05:31:56Z",
      "company_profile_id": "<string>",
      "source": "web_search",
      "scores": {}
    }
  ],
  "is_exhausted": false,
  "num_results_discovered": 0,
  "num_results_enriched": 0,
  "num_results_evaluated": 0,
  "num_results": 0,
  "table_id": "<string>",
  "auto_data_sources": true,
  "data_sources": [
    "web_search"
  ],
  "criteria": [
    {
      "key": "<string>",
      "name": "<string>",
      "criterion": "<string>"
    }
  ]
}
```

--------------------------------

### POST /v1/discovery_tasks Endpoint

Source: https://www.extruct.ai/docs/api-reference/discover/create-company-discovery-task

Defines the POST /v1/discovery_tasks endpoint for initiating discovery tasks. It includes request body schemas for input parameters like query, desired results, notification preferences, table details, auto data source determination, manual data source selection, and evaluation criteria. The response schema details the output, including task ID, creation timestamp, status, and counts of discovered, enriched, evaluated, and final results.

```yaml
paths:
  path: /v1/discovery_tasks
  method: post
  request:
    security:
      - title: HTTPBearer
        parameters:
          query: {}
          header:
            Authorization:
              type: http
              scheme: bearer
          cookie: {}
    parameters:
      path: {}
      query: {}
      header: {}
      cookie: {}
    body:
      application/json:
        schemaArray:
          - type: object
            properties:
              query:
                allOf:
                  - type: string
                    title: Query
                    description: Ideal description of companies to find
              desired_num_results:
                allOf:
                  - type: integer
                    maximum: 10000
                    minimum: 1
                    title: Desired Num Results
                    default: 100
              notify:
                allOf:
                  - type: boolean
                    title: Notify
                    default: true
              table:
                allOf:
                  - anyOf:
                      - $ref: '#/components/schemas/TableForDiscoveryTaskInput'
                      - type: 'null'
              auto_data_sources:
                allOf:
                  - type: boolean
                    title: Auto Data Sources
                    description: Automatically determine best data sources based on query
                    default: true
              data_sources:
                allOf:
                  - anyOf:
                      - items:
                          $ref: '#/components/schemas/DiscoveryDataSource'
                        type: array
                      - type: 'null'
                    description: >-
                      Manual data source selection (ignored if
                      auto_data_sources=True)
              criteria:
                allOf:
                  - anyOf:
                      - items:
                          $ref: '#/components/schemas/CriterionDefinition'
                        type: array
                      - type: 'null'
                    description: >-
                      Optional criteria for evaluating discovered companies. Each criterion will be graded on a 1-5 scale.
            required: true
            title: DiscoveryTaskInput
            refIdentifier: '#/components/schemas/DiscoveryTaskInput'
            requiredProperties:
              - query
        examples:
          example:
            value:
              query: <string>
              desired_num_results: 100
              notify: true
              table:
                id: 3c90c3cc-0d44-4b50-8888-8dd25736052a
                run: false
                columns:
                  - 3c90c3cc-0d44-4b50-8888-8dd25736052a
                auto_import: false
              auto_data_sources: true
              data_sources:
                - web_search
              criteria:
                - key: <string>
                  name: <string>
                  criterion: <string>
  response:
    '200':
      application/json:
        schemaArray:
          - type: object
            properties:
              id:
                allOf:
                  - type: string
                    title: Id
              created_at:
                allOf:
                  - type: string
                    format: date-time
                    title: Created At
              status:
                allOf:
                  - $ref: '#/components/schemas/Status'
              query:
                allOf:
                  - type: string
                    title: Query
              desired_num_results:
                allOf:
                  - type: integer
                    title: Desired Num Results
              is_exhausted:
                allOf:
                  - type: boolean
                    title: Is Exhausted
                    default: false
              num_results_discovered:
                allOf:
                  - type: integer
                    title: Num Results Discovered
                    description: Total number of company candidates discovered from search
                    default: 0
              num_results_enriched:
                allOf:
                  - type: integer
                    title: Num Results Enriched
                    description: Number of candidates enriched with company profiles
                    default: 0
              num_results_evaluated:
                allOf:
                  - type: integer
                    title: Num Results Evaluated
                    description: >-
                      Number of candidates that had criteria evaluation
                      completed
                    default: 0
              num_results:
                allOf:
                  - type: integer
                    title: Num Results

```

--------------------------------

### POST /v1/tables

Source: https://www.extruct.ai/docs/api-reference/tables/create-table

Creates a new table within the Extruct.ai platform. This endpoint allows for detailed configuration of table properties, including name, kind, notification settings, and column definitions.

```APIDOC
## POST /v1/tables

### Description
Creates a new table with specified configurations. You can define the table's name, type (kind), notification preferences, and detailed column settings, including AI-driven configurations.

### Method
POST

### Endpoint
/v1/tables

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
- **name** (string) - Optional - The name of the table. Defaults to 'Untitled Table'.
- **description** (string | null) - Optional - A description for the table.
- **tags** (string[] | null) - Optional - An array of tags for the table.
- **kind** (enum<string>) - Required - The type of the table. Available options: `generic`, `company`, `people`.
- **notify** (boolean) - Optional - Whether to notify the user when a table run completes with 5 minutes of inactivity. Defaults to `false`.
- **settings** (object | null) - Optional - Table settings, potentially including blacklist configuration.
- **column_configs** ((InputColumnConfig · object | AgentColumnConfig · object | CriterionGradeColumnConfig · object | PeopleFinderColumnConfig · object | DiscoveryScoresColumnConfig · object | CompanyNameColumnConfig · object | CompanyWebsiteColumnConfig · object | CompanyProfileColumnConfig · object)[]) - Optional - An array of column configurations. This can include various types like `InputColumnConfig`, `AgentColumnConfig`, etc.
- **num_rows** (integer | null) - Optional - The number of empty rows to create initially.

### Request Example
```json
{
  "name": "Supercharged Research",
  "kind": "company",
  "notify": false,
  "column_configs": [
    {
      "kind": "agent",
      "name": "Company Description",
      "key": "description",
      "value": {
        "agent_type": "research_pro",
        "prompt": "Research the company {company_name} ({company_website}) and provide a short description.",
        "output_format": "text"
      }
    }
  ]
}
```

### Response
#### Success Response (200)
- **id** (string) - Required - The unique identifier for the created table.
- **created_at** (string<date-time>) - Required - The timestamp when the table was created.
- **name** (string) - Required - The name of the table.
- **kind** (enum<string>) - Required - The type of the table (`generic`, `company`, or `people`).
- **columns** (ColumnOutputSchema · object[]) - Required - An array of the table's column configurations.
- **owner** (object) - Required - Information about the table owner.
- **description** (string | null) - Optional - The description of the table.
- **tags** (string[] | null) - Optional - Tags associated with the table.
- **notify** (boolean) - Optional - Notification setting for table completion.
- **settings** (object | null) - Optional - Table settings.
- **child_relationships** (TableRelationshipOutput · object[]) - Optional - Relationships to child tables.
- **parent_relationships** (TableRelationshipOutput · object[]) - Optional - Relationships to parent tables.

#### Response Example
```json
{
  "id": "<string>",
  "created_at": "2023-11-07T05:31:56Z",
  "name": "Supercharged Research",
  "description": "<string>",
  "tags": [
    "<string>"
  ],
  "kind": "company",
  "notify": false,
  "settings": {
    "exclude_from_search": false
  },
  "columns": [
    {
      "id": "<string>",
      "created_at": "2023-11-07T05:31:56Z",
      "config": {
        "kind": "input",
        "name": "Company Description",
        "key": "description"
      }
    }
  ],
  "owner": {
    "id": "<string>",
    "email": "<string>"
  },
  "child_relationships": [],
  "parent_relationships": []
}
```

#### Errors
- **422 Unprocessable Entity**: Indicates an issue with the request data, such as invalid field values or missing required fields.
```

--------------------------------

### Data Schemas

Source: https://www.extruct.ai/docs/api-reference/tables/create-table-columns

This section details the various data schemas used within the Extruct.ai API, including configurations for CriterionGradeColumnConfig, CriterionGraderAgentSchema, DiscoveryScoresColumnConfig, InputColumnConfig, PeopleFinderAgentSchema, and PeopleFinderColumnConfig.

```APIDOC
## Data Schemas

### CriterionGradeColumnConfig

This schema is not fully defined in the provided text, but it is referenced.

### CriterionGraderAgentSchema

Schema for configuring a criterion grader agent.

- **criterion** (string) - The criterion to be used for grading.

### DiscoveryScoresColumnConfig

Configuration for a column that stores discovery scores.

- **kind** (string, default: "discovery_scores") - Specifies the type of column.
- **name** (string) - The name of the column.
- **key** (string) - The key associated with the discovery scores.

### InputColumnConfig

Configuration for a column that accepts input.

- **kind** (string, default: "input") - Specifies the type of column.
- **name** (string) - The name of the input column.
- **key** (string) - The key associated with the input.

### PeopleFinderAgentSchema

Schema for configuring a people finder agent.

- **roles** (array of strings) - A list of roles to search for.

### PeopleFinderColumnConfig

Configuration for a column that uses the People Finder agent.

- **kind** (string, default: "company_people_finder") - Specifies the type of column.
- **name** (string) - The name of the column.
- **key** (string) - The key associated with the people finder.
- **value** (object) - The configuration for the People Finder Agent. (See `PeopleFinderAgentSchema`)

### ValidationError

Schema for API validation errors.

- **loc** (array of strings or integers) - The location of the validation error.
- **msg** (string) - The error message.
- **type** (string) - The type of validation error.
```

--------------------------------

### Project Schemas

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task

Defines the data structures used within the Extruct AI project, including criteria definitions, data sources, status types, and validation errors.

```APIDOC
## Project Schemas

### CriterionDefinition

#### Description
Definition of a criterion for evaluating companies in discovery tasks.

#### Properties
- **key** (string) - Required - Unique identifier for this criterion (e.g., "is_ai_company"). Pattern: `^[a-zA-Z][a-zA-Z0-9_]*$`
- **name** (string) - Required - Human-readable name for this criterion (e.g., "AI Company"). Max length: 100, Min length: 1
- **criterion** (string) - Required - The actual criterion text to evaluate against companies. Max length: 500, Min length: 10

### DiscoveryDataSource

#### Description
Enum representing the possible sources for discovery data.

#### Enum Values
- `web_search`
- `linkedin`
- `maps`

### Status

#### Description
Enum representing the possible status of a task or process.

#### Enum Values
- `created`
- `in_progress`
- `done`
- `failed`

### ValidationError

#### Description
Structure for reporting validation errors.

#### Properties
- **loc** (array) - Required - Location of the error in the data structure. Items can be string or integer.
- **msg** (string) - Required - The error message.
- **type** (string) - Required - The type of error.
```

--------------------------------

### Navigation Data

Source: https://www.extruct.ai/docs/api-reference/discover/get-company-discovery-task

Information on how to find navigation and other pages within the project documentation.

```APIDOC
## Navigation Data

### Fetch Navigation

#### Description
To find navigation and other pages in this documentation, fetch the `llms.txt` file from the specified URL.

### Endpoint
`https://extruct.ai/docs/llms.txt`

### Method
GET
```

--------------------------------

### POST /v1/discovery_tasks/{task_id}/resume

Source: https://www.extruct.ai/docs/api-reference/discover/resume-company-discovery-task

Resumes a discovery task, allowing for the retrieval of additional results beyond the initial batch. You can specify how many new results you'd like to fetch and whether to receive a notification upon completion.

```APIDOC
## POST /v1/discovery_tasks/{task_id}/resume

### Description
Resumes a discovery task to fetch more results. Allows specifying the number of new results and notification preferences.

### Method
POST

### Endpoint
/v1/discovery_tasks/{task_id}/resume

### Parameters
#### Path Parameters
- **task_id** (string) - Required - The ID of the discovery task to resume.

#### Query Parameters
None

#### Request Body
- **desired_new_results** (integer) - Optional - The maximum number of new results to fetch. Defaults to 25. Maximum value is 10000.
- **notify** (boolean) - Optional - Whether to send a notification when the task is complete. Defaults to true.

### Request Example
```json
{
  "desired_new_results": 50,
  "notify": false
}
```

### Response
#### Success Response (200)
- **id** (string) - The unique identifier for the discovery task.
- **created_at** (string) - The timestamp when the task was created (ISO 8601 format).
- **status** (string) - The current status of the discovery task (e.g., 'created').
- **query** (string) - The search query used for the discovery task.
- **desired_num_results** (integer) - The total number of results desired for the task.
- **is_exhausted** (boolean) - Indicates if the task has exhausted all possible results.
- **num_results_discovered** (integer) - The total number of company candidates discovered.
- **num_results_enriched** (integer) - The number of discovered candidates enriched with company profiles.
- **num_results_evaluated** (integer) - The number of candidates that had criteria evaluation completed.
- **num_results** (integer) - The total number of results found.
- **table_id** (string or null) - The ID of the table where results are stored, if applicable.
- **auto_data_sources** (boolean) - Indicates if data sources were automatically determined.
- **data_sources** (array of strings or null) - A list of data sources used or to be used for the discovery.
- **criteria** (array of objects or null) - A list of criteria definitions applied to the task.

#### Response Example
```json
{
  "id": "task_abc123",
  "created_at": "2023-11-07T05:31:56Z",
  "status": "resumed",
  "query": "technology companies in San Francisco",
  "desired_num_results": 50,
  "is_exhausted": false,
  "num_results_discovered": 15,
  "num_results_enriched": 10,
  "num_results_evaluated": 8,
  "num_results": 12,
  "table_id": "table_xyz789",
  "auto_data_sources": true,
  "data_sources": [
    "web_search",
    "linkedin"
  ],
  "criteria": [
    {
      "key": "employee_count",
      "name": "Employee Count",
      "criterion": ">= 100"
    }
  ]
}
```
```

--------------------------------

### POST /v1/discovery_tasks

Source: https://www.extruct.ai/docs/api-reference/discover/create-company-discovery-task

Initiates a new discovery task to find companies matching a given query. You can specify the desired number of results, notification preferences, and optionally provide manual data sources or evaluation criteria.

```APIDOC
## POST /v1/discovery_tasks

### Description
Initiates a new discovery task to find companies matching a given query. You can specify the desired number of results, notification preferences, and optionally provide manual data sources or evaluation criteria.

### Method
POST

### Endpoint
/v1/discovery_tasks

### Parameters
#### Query Parameters
None

#### Headers
- **Authorization** (string, required) - Bearer token for authentication.

#### Request Body
- **query** (string, required) - Ideal description of companies to find.
- **desired_num_results** (integer, optional, default: 100) - The maximum number of results to aim for (max 10000).
- **notify** (boolean, optional, default: true) - Whether to send a notification when the task is complete.
- **table** (object | null, optional) - Table object for discovery task input.
  - **id** (string) - Table ID.
  - **run** (boolean) - Whether to run the table.
  - **columns** (array of strings) - List of column IDs.
  - **auto_import** (boolean) - Whether to auto-import the table.
- **auto_data_sources** (boolean, optional, default: true) - Automatically determine the best data sources based on the query.
- **data_sources** (array of strings | null, optional) - Manual data source selection. Ignored if `auto_data_sources` is true. Example: `["web_search"]`.
- **criteria** (array of objects | null, optional) - Optional criteria for evaluating discovered companies. Each criterion will be graded on a 1-5 scale.
  - **key** (string) - Criterion key.
  - **name** (string) - Criterion name.
  - **criterion** (string) - The criterion description.

### Request Example
```json
{
  "query": "Technology startups in the San Francisco Bay Area",
  "desired_num_results": 50,
  "notify": true,
  "table": {
    "id": "3c90c3cc-0d44-4b50-8888-8dd25736052a",
    "run": false,
    "columns": ["3c90c3cc-0d44-4b50-8888-8dd25736052a"],
    "auto_import": false
  },
  "auto_data_sources": true,
  "data_sources": [
    "web_search"
  ],
  "criteria": [
    {
      "key": "funding",
      "name": "Recent Funding Rounds",
      "criterion": "Companies that have raised significant funding in the last 12 months."
    }
  ]
}
```

### Response
#### Success Response (200)
- **id** (string) - The unique identifier for the discovery task.
- **created_at** (string, date-time) - The timestamp when the task was created.
- **status** (string) - The current status of the task (e.g., `pending`, `running`, `completed`, `failed`).
- **query** (string) - The original query used for the task.
- **desired_num_results** (integer) - The desired number of results.
- **is_exhausted** (boolean) - Indicates if the search has exhausted all possible results.
- **num_results_discovered** (integer) - Total number of company candidates discovered from the search.
- **num_results_enriched** (integer) - Number of candidates enriched with company profiles.
- **num_results_evaluated** (integer) - Number of candidates that had criteria evaluation completed.
- **num_results** (integer) - The final number of results.

#### Response Example
```json
{
  "id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "created_at": "2023-10-27T10:00:00Z",
  "status": "pending",
  "query": "Technology startups in the San Francisco Bay Area",
  "desired_num_results": 50,
  "is_exhausted": false,
  "num_results_discovered": 0,
  "num_results_enriched": 0,
  "num_results_evaluated": 0,
  "num_results": 0
}
```
```

--------------------------------

### Column Output Schema

Source: https://www.extruct.ai/docs/api-reference/tables/create-table-columns

The base schema for any column output, including its ID, creation timestamp, and configuration details.

```APIDOC
## Column Output Schema

### Description
The base schema for any column output, including its ID, creation timestamp, and configuration details.

### Method
N/A (This is a schema definition)

### Endpoint
N/A (This is a schema definition)

### Parameters
#### Path Parameters
None

#### Query Parameters
None

#### Request Body
None

### Request Example
```json
{
  "id": "string",
  "created_at": "string (date-time)",
  "config": "object"
}
```

### Response
#### Success Response (200)
- **id** (string) - Unique identifier for the column output.
- **created_at** (string) - Timestamp when the column output was created.
- **config** (object) - The configuration details of the column, which can be one of several specific types (e.g., AgentColumnConfig, CompanyNameColumnConfig).

#### Response Example
```json
{
  "id": "col_123abc",
  "created_at": "2023-10-27T10:00:00Z",
  "config": {}
}
```
```

--------------------------------

### Table for Discovery Task Input Schema

Source: https://www.extruct.ai/docs/api-reference/discover/create-company-discovery-task

Defines the structure for associating a table with discovery task inputs.

```APIDOC
## Table for Discovery Task Input Schema

### Description
Specifies how to associate a table with discovery task inputs. It allows for providing the table ID, and optional settings for running the table and auto-importing discovered companies.

### Method
N/A (Schema definition)

### Endpoint
N/A (Schema definition)

### Parameters
N/A

### Request Example
N/A

### Response
#### Success Response
- **id** (string) - UUID of the table to associate with discovery results.
- **run** (boolean) - Whether to run the table after adding the results. Defaults to false.
- **columns** (array of strings or null) - List of column UUIDs to associate with the discovered data. Can be null.
- **auto_import** (boolean) - Whether to automatically import discovered companies to the table. Defaults to false.

#### Response Example
```json
{
  "id": "a1b2c3d4-e5f6-7890-1234-567890abcdef",
  "run": true,
  "columns": [
    "f0e1d2c3-b4a5-6789-0123-456789abcdef"
  ],
  "auto_import": true
}
```
```
Tokens:
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