Powerdrill Enterprise API V2

https://docs.powerdrill.ai/api-reference/v2
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Powerdrill Enterprise API V2 provides a robust set of API endpoints for managing datasets, data...
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### GET /api/v2/team/datasets/{id}/overview

Source: https://docs.powerdrill.ai/api-reference/v2/get-dataset-overview

Obtains the basic information about the dataset, including the keywords, description, and pre-generated questions. Requires a dataset ID and a user ID.

```APIDOC
## GET /api/v2/team/datasets/{id}/overview

### Description
Obtains the basic information about the dataset, including the keywords, description, and pre-generated questions.

### Method
GET

### Endpoint
/api/v2/team/datasets/{id}/overview

### Parameters
#### Path Parameters
- **id** (string) - Required - The unique identifier for the dataset.

#### Query Parameters
- **user_id** (string) - Required - The identifier for the user making the request.

#### Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key.

### Request Example
```json
{
  "method": "GET",
  "url": "https://ai.data.cloud/api/v2/team/datasets/{id}/overview?user_id=tmm-dafasdfasdfasdf",
  "headers": {
    "x-pd-api-key": "<api-key>"
  }
}
```

### Response
#### Success Response (200)
- **code** (integer) - 0 indicates success.
- **data** (object) - Contains the dataset overview details.
  - **id** (string) - The dataset ID.
  - **name** (string) - The name of the dataset.
  - **description** (string) - A detailed description of the dataset.
  - **summary** (string) - A brief summary of the dataset.
  - **exploration_questions** (array of strings) - A list of AI-generated questions to explore the dataset.
  - **keywords** (array of strings) - Relevant keywords associated with the dataset.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "id": "dset-cm5axptyyxxx298",
    "name": "sales_indicators_2024",
    "description": "A dataset comprising 373 travel bookings with 15 attributes, offering insights into booking patterns, pricing strategies, and more",
    "summary": "This dataset contains 373 travel bookings with 15 attributes, enabling analysis of booking trends, pricing strategies, and travel agency dynamics.",
    "exploration_questions": [
      "How does the booking price trend over time based on the BookingTimestamp?",
      "How does the average booking price change with respect to the TravelDate?",
      "Are there any significant outliers in the booking prices, and what might be causing them?",
      "How does the average price vary between one-way and round-trip bookings?"
    ],
    "keywords": [
      "Travel Bookings",
      "Booking Trends",
      "Travel Agencies"
    ]
  }
}
```
```

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

### Get Dataset Overview (cURL, Python)

Source: https://docs.powerdrill.ai/api-reference/v2/get-dataset-overview

Fetches the basic information of a dataset, such as its keywords, description, and automatically generated questions. This endpoint requires a user ID and an API key for authentication. The response contains metadata about the dataset.

```curl
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/datasets/{id}/overview?user_id=tmm-dafasdfasdfasdf \
  --header 'x-pd-api-key: <api-key>'
```

```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets/{id}/overview?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### List Data Sources (cURL)

Source: https://docs.powerdrill.ai/api-reference/v2/list-data-sources

Example request to list data sources in a specified dataset using cURL. Requires a dataset ID and an API key. Returns a JSON object containing data source details.

```curl
curl --request GET \
    --url https://ai.data.cloud/api/v2/team/datasets/{id}/datasources?user_id=tmm-dafasdfasdfasdf \
    --header 'x-pd-api-key: <api-key>'
```

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

### List Data Sources - Response Example

Source: https://docs.powerdrill.ai/api-reference/v2/list-data-sources

Sample JSON response for the 'List data sources' API endpoint. Includes status code, total items, page size, page number, and a list of data source records with their respective details.

```json
{
  "code": 0,
  "data": {
    "total_items": 1,
    "page_size": 10,
    "page_number": 1,
    "records": [
      {
        "code": 0,
        "data": {
          "id": "ds-cm7aedl58000501fc52hjj5c3",
          "name": "ds1.xlsx",
          "type": "FILE",
          "status": "synched",
          "size": 14435,
          "dataset_id": "dset-cm7ae4d77028n01l1cnapd5si"
        }
      }
    ]
  }
}
```

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

### List Data Sources (Python)

Source: https://docs.powerdrill.ai/api-reference/v2/list-data-sources

Example request to list data sources in a specified dataset using Python. Utilizes the 'requests' library. Requires a dataset ID and an API key. Returns a JSON object containing data source details.

```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets/{id}/datasources?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### Get Dataset Status Summary (cURL)

Source: https://docs.powerdrill.ai/api-reference/v2/get-dataset-status

This cURL command demonstrates how to make a GET request to the Powerdrill AI API to retrieve the status summary of data sources for a given dataset ID. It requires an API key and a user ID.

```curl
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/datasets/{id}/status?user_id=tmm-dafasdfasdfasdf \
  --header 'x-pd-api-key: <api-key>'
```

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

### Get Data Source Information (cURL, Python)

Source: https://docs.powerdrill.ai/api-reference/v2/get-data-source

Demonstrates how to fetch details for a specific data source using its dataset and datasource IDs. Requires API key authentication. The request includes the dataset ID, datasource ID, and user ID, returning a JSON object with the data source's properties.

```curl
curl --request GET \
  --url 'https://ai.data.cloud/api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}?user_id=tmm-dafasdfasdfasdf' \
  --header 'x-pd-api-key: <api-key>' \
  --header 'x-pd-external-trace-id: '
```

```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}?user_id=tmm-dafasdfasdfasdf"

headers = {
    "x-pd-api-key": "gegeege",
    "x-pd-external-trace-id": ""
}

response = requests.request("GET", url, headers=headers, params=querystring)

print(response.text)
```

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

### GET /api/v2/team/sessions/{id}

Source: https://docs.powerdrill.ai/api-reference/v2/get-session

Retrieves detailed information about a specific session using its unique identifier.

```APIDOC
## GET /api/v2/team/sessions/{id}

### Description
Obtains information about a session you created.

### Method
GET

### Endpoint
`/api/v2/team/sessions/{id}`

### Parameters
#### Path Parameters
- **id** (string) - Required - The unique identifier of the session.

#### Query Parameters
- **user_id** (string) - Required - The identifier of the user associated with the session.

#### Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key.

### Request Example
```json
{
  "example": "curl --request GET --url https://ai.data.cloud/api/v2/team/sessions/{id}?user_id=tmm-dafasdfasdfasdf --header 'x-pd-api-key: <api-key>'"
}
```

### Response
#### Success Response (200)
- **code** (integer) - A status code indicating the result of the operation. 0 typically means success.
- **data** (object) - An object containing the session details.
  - **id** (string) - The unique identifier of the session.
  - **name** (string) - The name of the session.
  - **output_language** (string) - The language setting for the session output.
  - **job_mode** (string) - The mode in which the job was executed.
  - **max_contextual_job_history** (integer) - The maximum number of contextual job history entries.
  - **agent_id** (string) - The identifier of the agent used for the session.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "id": "cckrXXg68P8lmb59dg4yO",
    "name": "Analyze performance",
    "output_language": "HI",
    "job_mode": "AUTO",
    "max_contextual_job_history": 76,
    "agent_id": "DATA_ANALYSIS_AGENT"
  }
}
```
```

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

### GET /v2/team/datasets/{id}/datasources

Source: https://docs.powerdrill.ai/api-reference/v2/list-data-sources

Retrieves a list of data sources within a specified dataset. Ensure the dataset belongs to the same project as your API key. To check accessible datasets, use GET /v2/team/datasets.

```APIDOC
## GET /v2/team/datasets/{id}/datasources

### Description
Lists data sources in the specified dataset. Requires the dataset to belong to the same project as the API key.

### Method
GET

### Endpoint
/v2/team/datasets/{id}/datasources

### Parameters
#### Path Parameters
- **id** (string) - Required - The unique identifier of the dataset.

#### Query Parameters
- **user_id** (string) - Required - The ID of the user to associate with the request.

#### Header Parameters
- **x-pd-api-key** (string) - Required - Your Powerdrill API key.

### Request Example
```json
{
  "method": "GET",
  "url": "https://ai.data.cloud/api/v2/team/datasets/{id}/datasources?user_id=tmm-dafasdfasdfasdf",
  "headers": {
    "x-pd-api-key": "<api-key>"
  }
}
```

### Response
#### Success Response (200)
- **code** (integer) - Indicates the success of the operation (0 for success).
- **data** (object) - Contains the list of data sources.
  - **total_items** (integer) - The total number of data sources found.
  - **page_size** (integer) - The number of items per page.
  - **page_number** (integer) - The current page number.
  - **records** (array) - An array of data source objects.
    - **code** (integer) - Indicates the success of the operation for the record.
    - **data** (object) - Contains details of a specific data source.
      - **id** (string) - The unique identifier of the data source.
      - **name** (string) - The name of the data source.
      - **type** (string) - The type of the data source (e.g., "FILE").
      - **status** (string) - The status of the data source (e.g., "synched").
      - **size** (integer) - The size of the data source in bytes.
      - **dataset_id** (string) - The identifier of the dataset this source belongs to.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "total_items": 1,
    "page_size": 10,
    "page_number": 1,
    "records": [
      {
        "code": 0,
        "data": {
          "id": "ds-cm7aedl58000501fc52hjj5c3",
          "name": "ds1.xlsx",
          "type": "FILE",
          "status": "synched",
          "size": 14435,
          "dataset_id": "dset-cm7ae4d77028n01l1cnapd5si"
        }
      }
    ]
  }
}
```
```

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

### GET /api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}

Source: https://docs.powerdrill.ai/api-reference/v2/get-data-source

Obtains information about the specified data source, identified by its dataset ID and datasource ID.

```APIDOC
## GET /api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}

### Description
Obtains information about the specified data source.

### Method
GET

### Endpoint
`/api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}`

### Parameters
#### Path Parameters
- **dataset_id** (string) - Required - The ID of the dataset.
- **datasource_id** (string) - Required - The ID of the data source.

#### Query Parameters
- **user_id** (string) - Required - The ID of the user.

#### Headers
- **x-pd-api-key** (string) - Required - Your API key.
- **x-pd-external-trace-id** (string) - Optional - An external trace ID for correlation.

### Request Example
```json
{
  "curl": "curl --request GET \
    --url 'https://ai.data.cloud/api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}?user_id=tmm-dafasdfasdfasdf' \
    --header 'x-pd-api-key: <api-key>' \
    --header 'x-pd-external-trace-id: '",
  "python": "import requests\n\nurl = \"https://ai.data.cloud/api/v2/team/datasets/{dataset_id}/datasources/{datasource_id}?user_id=tmm-dafasdfasdfasdf\"\n\nheaders = {\"x-pd-api-key\": \"gegeege\",\"x-pd-external-trace-id\": \"\"}\n\nresponse = requests.request(\"GET\", url, headers=headers)\n\nprint(response.text)"
}
```

### Response
#### Success Response (200)
- **code** (integer) - The status code of the operation.
- **data** (object) - Contains the data source details.
  - **id** (string) - The ID of the data source.
  - **name** (string) - The name of the data source.
  - **type** (string) - The type of the data source (e.g., FILE).
  - **status** (string) - The current status of the data source (e.g., synched).
  - **size** (integer) - The size of the data source in bytes.
  - **dataset_id** (string) - The ID of the dataset this data source belongs to.

#### Response Example
```json
{
    "code": 0,
    "data": {
        "id": "ds-cm7aedl58000501fc52hjj5c3",
        "name": "ds1.xlsx",
        "type": "FILE",
        "status": "synched",
        "size": 14435,
        "dataset_id": "dset-cm7ae4d77028n01l1cnapd5si"
    }
}
```
```

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

### List Datasets (Python)

Source: https://docs.powerdrill.ai/api-reference/v2/list-datasets

Retrieves a list of datasets using the Python requests library. This script sends a GET request to the API endpoint with the necessary API key and user ID. The response, containing dataset details, is printed to the console.

```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### Get status summary of data sources in dataset

Source: https://docs.powerdrill.ai/api-reference/v2/get-dataset-status

Retrieves the count of data sources for each status within a specified dataset.

```APIDOC
## GET /api/v2/team/datasets/{id}/status

### Description
Retrieves the count of data sources for each status within a specified dataset. This is useful for checking synchronization status before running data analysis jobs.

### Method
GET

### Endpoint
/api/v2/team/datasets/{id}/status

#### Query Parameters
- **user_id** (string) - Required - The ID of the user.

#### Request Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key.

### Response
#### Success Response (200)
- **code** (integer) - A status code indicating success (0 for success).
- **data** (object) - An object containing the counts of data sources by status.
  - **synched_count** (integer) - The number of data sources that are synchronized.
  - **invalid_count** (integer) - The number of data sources that are invalid.
  - **synching_count** (integer) - The number of data sources that are currently synchronizing.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "synched_count": 5,
    "invalid_count": 0,
    "synching_count": 0
  }
}
```
```

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

### GET /api/v2/team/sessions

Source: https://docs.powerdrill.ai/api-reference/v2/list-sessions

Retrieves a list of sessions created by a specific user. Supports pagination and filtering by user ID.

```APIDOC
## GET /api/v2/team/sessions

### Description
Lists sessions that you created. This endpoint allows you to retrieve a paginated list of sessions associated with a given user ID.

### Method
GET

### Endpoint
/api/v2/team/sessions

### Parameters
#### Query Parameters
- **user_id** (string) - Required - The ID of the user whose sessions are to be listed.

#### Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key for authentication.

### Request Example
```json
{
  "request": "GET https://ai.data.cloud/api/v2/team/sessions?user_id=tmm-dafasdfasdfasdf\nHeaders: {\"x-pd-api-key\": \"<api-key>\"}"
}
```

### Response
#### Success Response (200)
- **code** (integer) - Indicates the status of the request. 0 for success.
- **data** (object) - Contains the session data.
  - **page_number** (integer) - The current page number of the results.
  - **page_size** (integer) - The number of items per page.
  - **total_items** (integer) - The total number of sessions found.
  - **records** (array) - A list of session objects.
    - **id** (string) - The unique identifier for the session.
    - **name** (string) - The name of the session.
    - **description** (string) - A description of the session.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "page_number": 1,
    "page_size": 10,
    "total_items": 1,
    "records": [
      {
        "id": "dataset-dasfadsgadsgas",
        "name": "mysql",
        "description": "mysql databases"
      }
    ]
  }
}
```
```

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

### Get Session - cURL and Python

Source: https://docs.powerdrill.ai/api-reference/v2/get-session

Fetches information about a specific session identified by its ID. Requires an API key for authentication. The request targets the /api/v2/team/sessions/{id} endpoint and accepts a user_id as a query parameter. The response includes session details such as ID, name, and agent configuration.

```cURL
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/sessions/{id}?user_id=tmm-dafasdfasdfasdf  \
  --header 'x-pd-api-key: <api-key>'
```

```Python
import requests

url = "https://ai.data.cloud/api/v2/team/sessions/{id}?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### GET /api/v2/team/datasets/{id}/status

Source: https://docs.powerdrill.ai/api-reference/v2/how-to-check-data-sources

Retrieves the synchronization status summary for all data sources within a specified dataset. This endpoint is crucial for ensuring that all data sources are ready before initiating data analysis jobs.

```APIDOC
## GET /api/v2/team/datasets/{id}/status

### Description
This endpoint retrieves the synchronization status of data sources within a given dataset. It helps users verify that all uploaded data sources are fully synchronized and ready for analysis, preventing exclusion of unsynchronized sources from jobs.

### Method
GET

### Endpoint
`/api/v2/team/datasets/{id}/status`

### Parameters
#### Path Parameters
- **id** (string) - Required - The unique identifier of the dataset.

#### Query Parameters
- **user_id** (string) - Required - The user ID associated with the request.

#### Headers
- **x-pd-api-key** (string) - Required - The API key for the target project.

### Request Example
```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets/{id}/status?user_id=tmm-dafasdfasdfasdf"
hdrs = {"x-pd-api-key": "<api-key>"}
response = requests.request("GET", url, headers=hdrs)
print(response.text)
```

### Response
#### Success Response (200)
- **code** (integer) - An integer code indicating the status of the operation. `0` typically means success.
- **data** (object) - Contains the synchronization counts.
  - **synched_count** (integer) - The number of data sources that are fully synchronized.
  - **invalid_count** (integer) - The number of data sources that are invalid.
  - **synching_count** (integer) - The number of data sources currently in the process of synchronizing.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "synched_count": 5,
    "invalid_count": 0,
    "synching_count": 0
  }
}
```

**Interpretation**: If `invalid_count` and `synching_count` are both `0`, all data sources in the dataset are fully synchronized.
```

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

### List Sessions API Request (cURL, Python)

Source: https://docs.powerdrill.ai/api-reference/v2/list-sessions

Demonstrates how to list sessions using the Powerdrill AI API v2. This involves making a GET request to the /api/v2/team/sessions endpoint, optionally filtering by user_id. Authentication is handled via an x-pd-api-key header. The response contains session details including ID, name, and description.

```cURL
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/sessions?user_id=tmm-dafasdfasdfasdf  \
  --header 'x-pd-api-key: <api-key>'
```

```Python
import requests

url = "https://ai.data.cloud/api/v2/team/sessions?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### Get Data Source Status Summary - Python

Source: https://docs.powerdrill.ai/api-reference/v2/how-to-check-data-sources

Retrieves the synchronization status summary for data sources in a given dataset. This endpoint requires the dataset ID, user ID, and an API key. It returns counts of synchronized, invalid, and synchronizing data sources.

```python
import requests

url = "https://ai.data.cloud/api/v2/team/datasets/{id}/status?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### Get Session Job History (cURL and Python)

Source: https://docs.powerdrill.ai/api-reference/v2/get-job-history

This snippet demonstrates how to retrieve the job history for a specific session using the Powerdrill AI API. It includes a cURL command for direct API interaction and a Python script using the 'requests' library. Both require a session ID and an API key, and they fetch a list of job records associated with the session.

```cURL
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/sessions/{id}/history?user_id=tmm-dafasdfasdfasdf \
  --header 'x-pd-api-key: <api-key>'
```

```Python
import requests

url = "https://ai.data.cloud/api/v2/team/sessions/{id}/history?user_id=tmm-dafasdfasdfasdf"

headers = {"x-pd-api-key": "<api-key>"}

response = requests.request("GET", url, headers=headers)

print(response.text)
```

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

### Compare Sales Trends With and Without Negative Values (Python)

Source: https://docs.powerdrill.ai/api-reference/v2/get-job-history

This function compares sales trends by merging two datasets: one including negative sales and another excluding them. It calculates the difference in total sales for each channel and returns a DataFrame containing the channel name and the sales difference. Dependencies include the pandas library.

```python
import pandas as pd

def invoke(sales_trend_with_negatives: pd.DataFrame, sales_trend_without_negatives: pd.DataFrame) -> pd.DataFrame:
    # Merge the two DataFrames on the 'Channel' column
    merged_df = pd.merge(sales_trend_with_negatives, sales_trend_without_negatives, on='Channel', suffixes=('_with_negatives', '_without_negatives'))
    
    # Calculate the difference in 'Total Sales' between the two DataFrames
    merged_df['Sales Difference'] = merged_df['Total Sales_without_negatives'] - merged_df['Total Sales_with_negatives']
    
    # Create a new DataFrame to store the results
    output = merged_df[['Channel', 'Sales Difference']]
    
    return output
```

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

### Authenticate API Request with API Key (cURL)

Source: https://docs.powerdrill.ai/api-reference/v2/authentication

This cURL command demonstrates how to make a POST request to create a new session, including the 'x-pd-api-key' header for authentication. Replace '$PROJECT_API_KEY' and '$USER_ID' with your actual credentials.

```shell
curl --request POST \
  --url https://ai.data.cloud/api/v2/team/sessions \
  --header 'Content-Type: application/json' \
  --header 'x-pd-api-key: $PROJECT_API_KEY' \
  --data '{
    "name": "My session",
    "output_language": "EN",
    "job_mode": "AUTO",
    "max_contextual_job_history": 10,
    "agent_id": "DATA_ANALYSIS_AGENT",
    "user_id": "$USER_ID"
  }'
```

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

### POST /api/v2/team/file/upload-datasource

Source: https://docs.powerdrill.ai/api-reference/v2/upload-file

Uploads a local file to the system. The response includes a file key that can be used to create a data source.

```APIDOC
## POST /api/v2/team/file/upload-datasource

### Description
Uploads a local file. The `file_key` obtained can be used to create a data source via the Create data source endpoint. Supported file extensions: .csv, .tsv, .md, .mdx, .json, .txt, .pdf, .pptx, .ppt, .doc, .docx, .xls, or .xlsx. Recommended for files smaller than 1 MB; for larger files, use initiate-multipart-upload.

### Method
POST

### Endpoint
/api/v2/team/file/upload-datasource

### Parameters
#### Query Parameters
- **user_id** (string) - Required - The ID of the user uploading the file.

#### Request Body
- **file** (file) - Required - The local file to upload.

### Request Example
```json
{
  "file": "/Users/username/Downloads/c5168946-8f1a-4c92-a167-5e3be57745be.csv",
  "user_id": "tmm-cm5ao3yoe00zm01l1u1e7p3pj"
}
```

### Response
#### Success Response (200)
- **code** (integer) - A status code indicating success (0 for success).
- **data** (object) - Contains the file object key.
  - **file_object_key** (string) - The key identifier for the uploaded file.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "file_object_key": "/tmp/sdgsagdsgsadgasdg.csv"
  }
}
```
```

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

### Upload Local File using Python

Source: https://docs.powerdrill.ai/api-reference/v2/upload-file

This Python script utilizes the requests library to upload a local file to the Powerdrill AI API. It sets up the request URL, payload, file object, and headers, including the API key and tracing information. The script prints the response text from the server.

```python
import requests

url = "http://ai.data.cloud/api/v2/team/file/upload-datasource"

payload = {'user_id': 'tmm-cm5ao3yoe00zm01l1u1e7p3pj'}
files=[('file',('c5168946-8f1a-4c92-a167-5e3be57745be.csv',open('/Users/jiaoqi/Downloads/c5168946-8f1a-4c92-a167-5e3be57745be.csv','rb'),'text/csv'))]
headers = {
  'x-pd-api-key': '<api-key>',
  'x-pd-external-trace-id': '',
  'Cookie': 'Cookie_1=value; metabase.DEVICE=f3cb3dbb-ef62-4026-845e-1480431c751d'
}

response = requests.request("POST", url, headers=headers, data=payload, files=files)

print(response.text)
```

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

### GET /api/v2/team/sessions/{id}/history

Source: https://docs.powerdrill.ai/api-reference/v2/get-job-history

Retrieves the job history for a given session ID. This endpoint allows you to fetch a chronological record of jobs executed within a specific session, including details like job ID, the question posed, and the corresponding answer or output.

```APIDOC
## GET /api/v2/team/sessions/{id}/history

### Description
Retrieves the job history for a given session ID. This endpoint allows you to fetch a chronological record of jobs executed within a specific session, including details like job ID, the question posed, and the corresponding answer or output.

### Method
GET

### Endpoint
`/api/v2/team/sessions/{id}/history`

#### Query Parameters
- **user_id** (string) - Required - The ID of the user for whom the history is being retrieved.

#### Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key for authentication.

### Request Example
```curl
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/sessions/{id}/history?user_id=tmm-dafasdfasdfasdf \
  --header 'x-pd-api-key: <api-key>'
```

### Response
#### Success Response (200)
- **code** (integer) - Indicates the status of the request. 0 typically means success.
- **data** (object) - Contains the job history details.
  - **total_items** (integer) - The total number of job history items.
  - **page_number** (integer) - The current page number of the results.
  - **page_size** (integer) - The number of items per page.
  - **records** (array) - A list of job history records.
    - **job_id** (string) - The unique identifier for the job.
    - **question** (object) - The question that was posed for this job.
      - **blocks** (array) - An array of content blocks that form the question.
        - **type** (string) - The type of content block (e.g., MESSAGE, CODE).
        - **content** (string) - The actual content of the block.
    - **answer** (object) - The answer or output generated for this job.
      - **blocks** (array) - An array of content blocks that form the answer.
        - **type** (string) - The type of content block (e.g., MESSAGE, CODE, TABLE).
        - **content** (string) - The actual content of the block (e.g., text, code, URL to a file).
        - **group_id** (string) - Identifier for grouping related blocks.
        - **group_name** (string) - Name of the group.
        - **stage** (string) - The stage of the process this block relates to (e.g., Analyze).

#### Response Example
```json
{
  "code": 0,
  "data": {
    "total_items": 1,
    "page_number": 1,
    "page_size": 10,
    "records": [
      {
        "job_id": "job-1dsfasddfasgddsaffds",
        "question": {
          "blocks": [
            {
              "type": "MESSAGE",
              "content": "Check for negative values across all sales columns"
            }
          ]
        },
        "answer": {
          "blocks": [
            {
              "type": "MESSAGE",
              "content": "- Check for negative values across all sales columns.\n- Filter the DataFrame to retain only rows with no negative sales values.",
              "group_id": "ba582fc9-bb36-4c5d-a8e8-d35bda6389cd",
              "group_name": "Identify the channels with negative sales values by examining each day's sales data. Filter out the rows where any sales value is negative.",
              "stage": "Analyze"
            },
            {
              "type": "CODE",
              "content": "```python\n\nimport pandas as pd\n\ndef invoke(input_0: pd.DataFrame) -> pd.DataFrame:\n    \'\'\'\n    input_0: pd.DataFrame  SalesByChannelByDay_Summary_Demo.Sheet1_0_table_1.csv\n    \'\'\'
    # Identify columns that represent sales data (all except the first column)\n    sales_columns = input_0.columns[1:]\n    \n    # Filter rows where any sales value is negative\n    filtered_df = input_0[~(input_0[sales_columns] < 0).any(axis=1)]\n    \n    # Assign the result to the output variable\n    output = filtered_df\n    \n    return output\n\n```",
              "group_id": "ba582fc9-bb36-4c5d-a8e8-d35bda6389cd",
              "group_name": "Identify the channels with negative sales values by examining each day's sales data. Filter out the rows where any sales value is negative.",
              "stage": "Analyze"
            },
            {
              "type": "TABLE",
              "content": "https://s3.amazonaws.com/powerdrilltest/tmp_datasource_cache/code_result/clvl4cad2001q01l1m522hxlu/baf7d6d1-fb81-4fdb-bcdd-32923d214c7b.csv?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Date=20241018T104617Z&X-Amz-SignedHeaders=host&X-Amz-Expires=599&X-Amz-Credential=AKIARLSQLXURHEIDN4OZ%2F20241018%2Fus-east-1%2Fs3%2Faws4_request&X-Amz-Signature=9bcb5af552793f162e35f41d62fb9306cf90888924bfbdce81ea687265fddf83",
              "group_id": "ba582fc9-bb36-4c5d-a8e8-d35bda6389cd",
              "group_name": "Identify the channels with negative sales values by examining each day's sales data. Filter out the rows where any sales value is negative.",
              "stage": "Analyze"
            },
            {
              "type": "MESSAGE",
              "content": "- Sum the sales across all days for each channel.\n- Create a new DataFrame with the channel names and their corresponding total sales.",
              "group_id": "47183fd1-307b-4408-9986-e9238d952ec1",
              "group_name": "Calculate the overall sales trend for the identified channels with negative sales values. This involves summing up the sales across all days for each channel and analyzing the trend.",
              "stage": "Analyze"
            },
            {
              "type": "CODE",
              "content": "```python\n\nimport pandas as pd\n\ndef invoke(negative_sales_channels: pd.DataFrame) -> pd.DataFrame:\n    \'\'\'\n    negative_sales_channels: pd.DataFrame  negative_sales_channels.csv\n    \'\'\'
    # Sum the sales across all days for each channel\n    total_sales = negative_sales_channels.iloc[:, 1:].sum(axis=1)\n    \n    # Create a new DataFrame with the channel names and their corresponding total sales\n    output = pd.DataFrame({
        'Channel': negative_sales_channels.iloc[:, 0],
        'Total Sales': total_sales
    })\n    \n    return output\n\n```",
              "group_id": "47183fd1-307b-4408-9986-e9238d952ec1",
              "group_name": "Calculate the overall sales trend for the identified channels with negative sales values. This involves summing up the sales across all days for each channel and analyzing the trend.",
              "stage": "Analyze"
            },
            {
              "type": "TABLE",

```

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

### Upload Local File using cURL

Source: https://docs.powerdrill.ai/api-reference/v2/upload-file

This cURL command demonstrates how to upload a local file to the Powerdrill AI API. It includes necessary headers for API key and tracing, and form data for the file and user ID. Ensure the file path is correct and replace placeholders.

```curl
curl --location 'http://ai.data.cloud/api/v2/team/file/upload-datasource' \
--header 'x-pd-api-key: <api-key>' \
--header 'x-pd-external-trace-id;' \
--header 'Cookie: Cookie_1=value; metabase.DEVICE=f3cb3dbb-ef62-4026-845e-1480431c751d' \
--form 'file=@"/Users/username/Downloads/c5168946-8f1a-4c92-a167-5e3be57745be.csv"' \
--form 'user_id="tmm-cm5ao3yoe00zm01l1u1e7p3pj"'
```

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

### POST /api/v2/initiate-multipart-upload

Source: https://docs.powerdrill.ai/api-reference/v2/initiate-multipart-upload

Initiates a multipart upload for supported file types. It returns a unique upload ID necessary for the 'Complete multipart upload' endpoint.

```APIDOC
## POST /api/v2/initiate-multipart-upload

### Description
Initiates a multipart upload task for local files. Supported formats include .csv, .tsv, .md, .mdx, .json, .txt, .pdf, .pptx, .docx, .xls, and .xlsx. The response includes a unique upload ID required for the complete multipart upload operation.

### Method
POST

### Endpoint
/api/v2/initiate-multipart-upload

### Parameters
#### Query Parameters
- **fileName** (string) - Required - The name of the file to be uploaded.
- **fileSize** (integer) - Required - The total size of the file in bytes.

#### Request Body
This endpoint does not typically require a request body for initiating the upload. The file content is sent in subsequent upload parts.

### Request Example
```
POST /api/v2/initiate-multipart-upload?fileName=example.csv&fileSize=102400 HTTP/1.1
Host: api.powerdrill.ai
Content-Type: application/json

```

### Response
#### Success Response (200)
- **uploadId** (string) - The unique identifier for the multipart upload task.
- **fileName** (string) - The name of the file being uploaded.
- **fileSize** (integer) - The total size of the file in bytes.

#### Response Example
```json
{
  "uploadId": "your-unique-upload-id",
  "fileName": "example.csv",
  "fileSize": 102400
}
```

#### Error Handling
- **400 Bad Request**: If required query parameters are missing or invalid.
- **415 Unsupported Media Type**: If the file format is not supported.
```

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

### List Datasets

Source: https://docs.powerdrill.ai/api-reference/v2/list-datasets

Retrieves a list of datasets created within the same project as your API key. Supports filtering by a search keyword.

```APIDOC
## GET /api/v2/team/datasets

### Description
Lists datasets created within the same project as your API key. You can specify a search keyword to filter datasets by name and description.

### Method
GET

### Endpoint
/api/v2/team/datasets

### Query Parameters
- **user_id** (string) - Required - The ID of the user associated with the API key.

### Request Headers
- **x-pd-api-key** (string) - Required - Your Powerdrill API key.

### Request Example
```json
{
  "method": "GET",
  "url": "https://ai.data.cloud/api/v2/team/datasets?user_id=tmm-dafasdfasdfasdf",
  "headers": {
    "x-pd-api-key": "<api-key>"
  }
}
```

### Response
#### Success Response (200)
- **code** (integer) - 0 for success.
- **data** (object) - Contains dataset information.
  - **page_number** (integer) - The current page number.
  - **page_size** (integer) - The number of items per page.
  - **total_items** (integer) - The total number of datasets available.
  - **records** (array) - An array of dataset objects.
    - **id** (string) - The unique identifier of the dataset.
    - **name** (string) - The name of the dataset.
    - **description** (string) - The description of the dataset.

#### Response Example
```json
{
  "code": 0,
  "data": {
    "page_number": 1,
    "page_size": 10,
    "total_items": 1,
    "records": [
      {
        "id": "dataset-dasfadsgadsgas",
        "name": "mysql",
        "description": "mysql databases"
      }
    ]
  }
}
```
```

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

### Authenticate API Request with API Key (Python)

Source: https://docs.powerdrill.ai/api-reference/v2/authentication

This Python script uses the 'requests' library to send a POST request for creating a new session. It includes the 'x-pd-api-key' in the request headers for authentication. Ensure you replace '$PROJECT_API_KEY' with your actual key.

```python
import requests

url = "https://ai.data.cloud/api/v2/team/sessions"

payload = {
    "name": "My session",
    "output_language": "EN",
    "job_mode": "AUTO",
    "max_contextual_job_history": 10,
    "agent_id": "DATA_ANALYSIS_AGENT",
    "user_id": "tmm-dafasdfasdfasdf"
}
headers = {
    "x-pd-api-key": "$PROJECT_API_KEY",
    "Content-Type": "application/json"
}

response = requests.request("POST", url, json=payload, headers=headers)

print(response.text)
```

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

### Create Job using Python Requests

Source: https://docs.powerdrill.ai/api-reference/v2/streaming

This Python code snippet demonstrates how to create a job using the Powerdrill AI API's POST /v2/team/jobs endpoint. It utilizes the 'requests' library to send a POST request with a JSON payload containing session ID, user ID, streaming preferences, the user's question, and dataset/datasource identifiers. Ensure you replace '<api-key>' with your actual API key.

```python
import requests

url = "https://ai.data.cloud/api/v2/team/jobs"

payload = {
    "session_id": "cxxdgegeegeg3433fff",
    "user_id": "tmm-dafasdfasdfasdf",
    "stream": True,
    "question": "Which travel agency has the highest average booking price?",
    "dataset_id": "cm1gjmg8e0057r3x22v1fdu8m",
    "datasource_ids": ["cm1gjmmoo0001h0x24uk1xgu9"],
    "output_language": "AUTO",
    "job_mode": "AUTO"
}
headers = {
    "x-pd-api-key": "<api-key>",
    "Content-Type": "application/json"
}

response = requests.request("POST", url, json=payload, headers=headers)

print(response.text)
```

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

### List Datasets (cURL)

Source: https://docs.powerdrill.ai/api-reference/v2/list-datasets

Fetches a list of datasets associated with the authenticated user's project. Requires an API key and user ID. Returns a JSON object containing dataset information.

```curl
curl --request GET \
  --url https://ai.data.cloud/api/v2/team/datasets?user_id=tmm-dafasdfasdfasdf \
  --header 'x-pd-api-key: <api-key>'
```
Tokens:
Raw