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POST
/
project-setup
Create Project
curl --request POST \
  --url https://client.camb.ai/apis/project-setup \
  --header 'Content-Type: application/json' \
  --header 'x-api-key: <api-key>' \
  --data '
{
  "media_url": "<string>",
  "source_language": 1,
  "target_languages": [
    1
  ],
  "project_name": "<string>",
  "project_description": "<string>",
  "selected_audio_tracks": null,
  "add_output_as_an_audio_track": null,
  "chosen_dictionaries": null,
  "folder_id": 2
}
'
{
  "task_id": "<string>"
}

Documentation Index

Fetch the complete documentation index at: https://docs.camb.ai/llms.txt

Use this file to discover all available pages before exploring further.

Bridge the gap between API automation and hands-on creative control with our Project Setup endpoint. This powerful tool allows you to programmatically initialize dubbing projects that seamlessly integrate with CAMB.AI Studio, giving you the best of both worlds: automated project creation through your existing workflows and the flexibility to fine-tune results through our visual interface. Think of this endpoint as your content’s intelligent onboarding system. It analyzes your media, validates configurations, and creates a fully-prepared project ready for detailed editing in CAMB.AI Studio. This approach transforms how content teams work, enabling developers to handle project initialization while creative professionals focus on perfecting the final output.

​
Why Project Setup Matters for API Users

The traditional dubbing workflow often creates friction between technical teams managing content pipelines and creative teams perfecting the final product. Project Setup eliminates this friction by establishing a clear handoff point where technical configuration meets creative refinement. When you submit a project through this endpoint, you’re not just uploading media—you’re creating a structured workspace in CAMB.AI Studio that contains all the analysis, configuration, and preparation work needed for efficient dubbing. Your creative team receives a project that’s already optimized and ready for detailed editing, rather than starting from scratch with raw media files.

​
The API-to-Studio Workflow

Understanding how Project Setup connects API automation with Studio editing helps you design more efficient content workflows. The process creates a seamless bridge between programmatic project creation and visual editing tools. Automated Project Initialization: Your API request handles all the technical groundwork—media analysis, language configuration, and optimization parameter selection. This automation ensures consistent project setup across your entire content library while eliminating manual configuration errors. Studio-Ready Project Creation: The endpoint generates a fully-prepared project workspace in CAMB.AI Studio, complete with analyzed audio tracks, configured language settings, and optimized processing parameters. Your creative team can immediately begin working with the content rather than spending time on technical setup. Preserved Configuration Context: All API-specified parameters, including custom dictionaries and advanced audio track settings, carry forward into the Studio environment. This continuity ensures that your technical requirements remain intact while enabling creative refinement.

​
Media Source Compatibility

Project Setup accommodates diverse media sources, making it easy to integrate with existing content management systems. Whether your media lives on YouTube, Google Drive, or professional storage systems, the endpoint handles ingestion automatically. The system supports both consumer formats like MP4 and professional broadcast formats including MXF files for Enterprise customers. This broad compatibility means you can standardize your project creation process regardless of your content’s origin or quality level.
Enterprise plan customers enjoy exclusive access to MXF format support, bringing professional broadcast standards to organizations with specialized media requirements.

​
Implementation Example

Let’s examine how to create a project that leverages both API efficiency and Studio flexibility. This example demonstrates the essential parameters while showing how your configuration translates into a Studio-ready workspace. 
import requests
import json

# Configure API authentication
headers = {
    "x-api-key": "your-api-key",  # Replace with your actual API key
    "Content-Type": "application/json"
}

# Define project configuration
# This setup creates a project optimized for Studio editing
project_config = {
    "project_name": "Product Launch Campaign",  # Project name visible in Studio
    "project_description": "Multi-language product demo for global markets",  # Context for Studio users
    "media_url": "https://your-storage.com/product-demo.mp4",  # Source media location
    "source_language": 1,      # English - get IDs from /source-languages
    "target_languages": [5, 76, 12],   # Spanish, French, German - check /target-languages
}

def create_studio_project(payload):
    """
    Creates a project configured for optimal Studio editing experience.
    The resulting project appears in CAMB.AI Studio with all technical setup complete.
    """
    try:
        response = requests.post(
            "https://client.camb.ai/apis/project-setup",
            headers=headers,
            data=json.dumps(payload)
        )

        response.raise_for_status()
        result = response.json()

        task_id = result.get("task_id")
        return task_id

    except requests.exceptions.RequestException as e:
        print(f"Project creation failed: {e}")
        return None

# Create the project
project_setup_task_id = create_studio_project(project_config)

if not project_setup_task_id:
    print(f"Failed to create project '{project_config['project_name']}'. Please check your API key and configuration.")
else:
    print(f"Project '{project_config['project_name']}' task is created successfully! Task ID: {project_setup_task_id}")

​
Best Practices for API-Studio Integration

Successful integration between API project creation and Studio editing depends on understanding how your configuration choices impact the creative editing experience. Several strategies can significantly improve your team’s efficiency and output quality. Descriptive Project Naming: Use clear, descriptive names and descriptions that help Studio users understand project context immediately. This clarity becomes crucial when managing multiple projects or coordinating between team members with different responsibilities. Optimal Language Configuration: Verify language IDs using the dedicated endpoints before submitting projects. Accurate language configuration ensures that Studio users receive projects with properly configured voice options and translation models. Quality-Focused Media Selection: Choose the highest quality source media available, as compression artifacts and audio issues in source material become more apparent during the detailed editing process in Studio. Starting with quality media enables better creative decisions throughout the editing workflow. Project Setup represents the ideal fusion of API automation and creative control. By handling the technical groundwork programmatically, you enable your creative team to focus on the nuanced decisions that determine final quality, while ensuring consistent, professional results across your entire content pipeline.

Authorizations

​
x-api-key
string
header
required

The x-api-key is a custom header required for authenticating requests to our API. Include this header in your request with the appropriate API key value to securely access our endpoints. You can find your API key(s) in the 'API' section of our studio website.

Body

application/json
​
media_url
string<uri>
required

The source location of your media content. This URI can point to YouTube videos, Google Drive files, or direct media file URLs. The system validates accessibility and begins media analysis immediately upon receipt. Think of this as telling the system where to find your raw material for processing

​
source_language
enum<integer>
required

The language identifier for the original audio in your media. This selection determines which speech recognition models and analysis approaches the system applies to your content. Accurate source language specification ensures optimal transcription quality, which directly impacts the final dubbing results your team will work with in Studio.

Available options:
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77,
78,
79,
80,
81,
82,
83,
84,
85,
86,
87,
88,
89,
90,
91,
92,
93,
94,
95,
96,
97,
98,
99,
100,
101,
102,
103,
104,
105,
106,
107,
108,
109,
110,
111,
112,
113,
114,
115,
116,
117,
118,
119,
120,
121,
122,
123,
124,
125,
126,
127,
128,
129,
130,
131,
132,
133,
134,
135,
136,
139,
140,
141,
142,
143,
144,
145,
146,
147,
148,
149,
150
​
target_languages
enum<integer>[]
required

An array of language identifiers representing the languages you want your content dubbed into. Each language in this array creates a separate dubbing track in your Studio project, giving your creative team complete control over each language version. The system optimizes voice selection and translation models based on these choices.

Available options:
1,
2,
3,
4,
5,
6,
7,
8,
9,
10,
11,
12,
13,
14,
15,
16,
17,
18,
19,
20,
21,
22,
23,
24,
25,
26,
27,
28,
29,
30,
31,
32,
33,
34,
35,
36,
37,
38,
39,
40,
41,
42,
43,
44,
45,
46,
47,
48,
49,
50,
51,
52,
53,
54,
55,
56,
57,
58,
59,
60,
61,
62,
63,
64,
65,
66,
67,
68,
69,
70,
71,
72,
73,
74,
75,
76,
77,
78,
79,
80,
81,
82,
83,
84,
85,
86,
87,
88,
89,
90,
91,
92,
93,
94,
95,
96,
97,
98,
99,
100,
101,
102,
103,
104,
105,
106,
107,
108,
109,
110,
111,
112,
113,
114,
115,
116,
117,
118,
119,
120,
121,
122,
123,
124,
125,
126,
127,
128,
129,
130,
131,
132,
133,
134,
135,
136,
139,
140,
141,
142,
143,
144,
145,
146,
147,
148,
149,
150
​
project_name
string | null

Enter a distinctive name for your project that reflects its purpose or content. This name will be displayed in your CAMB.AI workspace dashboard and used to organize related assets, transcriptions, etc.. . Choose something memorable that helps you quickly identify this specific project among your other voice, audio and localization tasks.

Required string length: 3 - 255
​
project_description
string | null

Provide details about your project's goals and specifications. Include information such as the target languages for translation or dubbing, desired voice characteristics, emotional tones to capture, or specific audio processing requirements, outlining the workflow here can serve as valuable documentation for organizational purposes.

Required string length: 3 - 5000
​
selected_audio_tracks
integer[] | null

Optional array of one or two zero‑based audio track indices to dub. Only supported for MXF files. If omitted, the first audio track (index 0) is used by default.

Required array length: 1 - 2 elements
​
add_output_as_an_audio_track
boolean | null

Optional flag to append the dubbed audio as a new audio track in the output file. Only supported for MXF files. If true, the dubbed audio is added as an additional track; if false or omitted, the source would be returned with only dubbed audio.

​
chosen_dictionaries
integer[] | null

An optional list of dictionary IDs selected by the user. Each entry must be an integer corresponding to a valid dictionary ID. If provided, at least one ID is required.

Minimum array length: 1
​
folder_id
integer | null

Specify the organizational folder within your CAMB.AI workspace where this task should be created and stored. The folder must already exist in your workspace and be accessible through your current API key authentication. This helps maintain project organization by grouping related tasks together, making it easier to manage and locate your projects.

Required range: x >= 1

Response

Successful Response

A JSON that contains the unique identifier for the task. This is used to query the status of the text to voice task that is running. It is returned when a create request is made for setting up a project task.

​
task_id
string