> ## Documentation Index
> Fetch the complete documentation index at: https://docs-docflow.textin.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Quick Start

> Reference examples to quickly integrate Docflow functionality with APIs

<Tip>
  This document provides examples on how to quickly integrate with the DocFlow workflow via APIs.\
  If you have not used DocFlow in the Web UI before, we recommend uploading a file on the [Web page](https://docflow.textin.ai/) first to get a clear idea of how DocFlow works.
</Tip>

## 01 Prerequisites: Obtain Access Credentials

### 1.1 Public Cloud Usage

When using the Docflow API, you need to obtain an API Key first.\
Please log in first and go to [TextIn Console - Account & Developer Information](https://textin.ai/console/dashboard/setting) to obtain your `x-ti-app-id` and `x-ti-secret-code`.

### 1.2 Private Cloud Usage

Please contact the technical support personnel you are working with to obtain API call credentials for private deployment.

## 02 Preparation

### 2.1 Configure Docflow Workspace and Classification

First, refer to the [Get Workspace ID](../100-faq/get_workspace_id) and [Configure File Categories](../100-faq/setup_category) documents to complete the configuration and obtain the workspace ID.

## 2.2 Upload Files

Example:

<CodeGroup>
  ```bash curl icon=terminal wrap theme={null}
  curl \
    -H "x-ti-app-id: <your-app-id>" \
    -H "x-ti-secret-code: <your-secret-code>" \
    -F file=@</path/to/your/file.pdf \
    "https://docflow.textin.ai/api/app-api/sip/platform/v2/file/upload?workspace_id=<your-workspace-id>"
  ```

  ```python Python expandable {6,7,8,9} icon=python lines theme={null}
  import requests
  import json
  from requests_toolbelt.multipart.encoder import MultipartEncoder
  import os

  ti_app_id = "your-app-id"
  ti_secret_code = "your-app-secret"
  workspace_id = "your-workspace-id"
  filepath = "/your/file/path.pdf"

  host = "https://docflow.textin.ai"
  url = "/api/app-api/sip/platform/v2/file/upload"
  params = { "workspace_id":workspace_id}

  # determine filepath is image or pdf
  if filepath.endswith(".jpg") or filepath.endswith(".jpeg") or filepath.endswith(".png"):
      mime_type = "image/jpeg"
  else:
      mime_type = "application/pdf"

  payload = MultipartEncoder(
      fields=[
          "file": (os.path.basename(filepath), open(filepath, "rb"), mime_type),
      ]
  )

  resp = requests.post(url=f"{host}{url}", 
                       params=params, 
                       data=payload.to_string(), 
                       headers={"Content-Type": payload.content_type,
                                "x-ti-app-id": ti_app_id,
                                "x-ti-secret-code": ti_secret_code,
                                })

  print(resp.text)
  resp_json = json.loads(resp.text)
  ```
</CodeGroup>

After executing the above example code with your parameters, you can view the just uploaded file in the corresponding workspace on the Web page.

## 2.3 Retrieve Results

Example:

<CodeGroup>
  ```bash curl icon=terminal wrap theme={null}
  curl \
    -H "x-ti-app-id: <your-app-id>" \
    -H "x-ti-secret-code: <your-secret-code>" \
    "https://docflow.textin.ai/api/app-api/sip/platform/v2/file/fetch?workspace_id=<your-workspace-id>"
  ```

  ```python Python expandable {4,5,6} icon=python lines theme={null}
  import requests
  import json

  ti_app_id = "your-app-id"
  ti_secret_code = "your-app-secret"
  workspace_id = "your-workspace-id"

  host = "https://docflow.textin.ai"
  url = "/api/app-api/sip/platform/v2/file/fetch"
  params = { "workspace_id":workspace_id}

  resp = requests.get(url=f"{host}{url}", 
                      params=params, 
                      data=payload.to_string(), 
                      headers={"Content-Type": payload.content_type,
                               "x-ti-app-id": ti_app_id,
                               "x-ti-secret-code": ti_secret_code,
                               })

  print(resp.text)
  resp_json = json.loads(resp.text)
  ```
</CodeGroup>

## 2.4 Result Parsing

The retrieved result is in JSON format containing the processed document results. You can obtain the document parsing, classification, and extraction results by parsing the JSON.

<Tip>
  The example below shows the extracted document fields in the output. For parsing of other information, refer to the relevant sections of this documentation.
</Tip>

<CodeGroup>
  ```python Python icon=python lines theme={null}
  # Continuing from the "Retrieve Results" example code

  for file in resp_json["result"]["files"]:
    for item in file["data"]["items"]:
      print(f"{item["key"]}: {item["value"]}")
  ```
</CodeGroup>