Synthesia Python API Docs | dltHub

Synthesia is an AI video generation platform that exposes a REST API to create, manage, and download synthetic videos, templates, assets, webhooks, dubbing and translation jobs. The REST API base URL is https://api.synthesia.io (primary REST API). Upload API base_url (media uploads): https://upload.api.synthesia.io/v2 and all requests require an API key supplied in the Authorization header..

dlt is an open-source Python library that handles authentication, pagination, and schema evolution automatically. dlthub provides AI context files that enable code assistants to generate production-ready pipelines. Install with uv pip install "dlt[workspace]" and start loading Synthesia data in under 10 minutes.

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What data can I load from Synthesia?

Here are some of the endpoints you can load from Synthesia:

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How do I authenticate with the Synthesia API?

Create an API key in your Synthesia account Integrations page and include it in every request’s Authorization header.

1. Get your credentials

1. Sign in to Synthesia web app. 2) Click your account in the upper-right. 3) Select Integrations. 4) Click Add to create a new Synthesia API key. 5) Copy the key using the 3-dot button next to the key; use it in the Authorization header.

2. Add them to .dlt/secrets.toml

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[sources.synthesia_source]
api_key = "your_synthesia_api_key_here"

dlt reads this automatically at runtime — never hardcode tokens in your pipeline script. For production environments, see setting up credentials with dlt for environment variable and vault-based options.

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How do I set up and run the pipeline?

Set up a virtual environment and install dlt:

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uv venv && source .venv/bin/activate
uv pip install "dlt[workspace]"

1. Install the dlt AI Workbench:

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dlt ai init --agent <your-agent> # <agent>: claude | cursor | codex

This installs project rules, a secrets management skill, appropriate ignore files, and configures the dlt MCP server for your agent. Learn more →

2. Install the rest-api-pipeline toolkit:

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dlt ai toolkit rest-api-pipeline install

This loads the skills and context about dlt the agent uses to build the pipeline iteratively, efficiently, and safely. The agent uses MCP tools to inspect credentials — it never needs to read your secrets.toml directly. Learn more →

3. Start LLM-assisted coding:

Use /find-source to load data from the Synthesia API into DuckDB.

The rest-api-pipeline toolkit takes over from here — it reads relevant API documentation, presents you with options for which endpoints to load, and follows a structured workflow to scaffold, debug, and validate the pipeline step by step.

4. Run the pipeline:

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python synthesia_pipeline.py

If everything is configured correctly, you'll see output like this:

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Pipeline synthesia_pipeline load step completed in 0.26 seconds
1 load package(s) were loaded to destination duckdb and into dataset synthesia_data
The duckdb destination used duckdb:/synthesia.duckdb location to store data
Load package 1749667187.541553 is LOADED and contains no failed jobs

Inspect your pipeline and data:

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dlt pipeline synthesia_pipeline show

This opens the Pipeline Dashboard where you can verify pipeline state, load metrics, schema (tables, columns, types), and query the loaded data directly.

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Python pipeline example

This example loads videos and templates from the Synthesia API into DuckDB. It mirrors the endpoint and data selector configuration from the table above:

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import dlt
from dlt.sources.rest_api import RESTAPIConfig, rest_api_resources

@dlt.source
def synthesia_source(api_key=dlt.secrets.value):
    config: RESTAPIConfig = {
        "client": {
            "base_url": "https://api.synthesia.io (primary REST API). Upload API base_url (media uploads): https://upload.api.synthesia.io/v2",
            "auth": {
                "type": "api_key",
                "api_key": api_key,
            },
        },
        "resources": [
            {"name": "videos", "endpoint": {"path": "v1/videos", "data_selector": "data"}},
            {"name": "templates", "endpoint": {"path": "v1/templates", "data_selector": "data"}}
        ],
    }
    yield from rest_api_resources(config)


def get_data() -> None:
    pipeline = dlt.pipeline(
        pipeline_name="synthesia_pipeline",
        destination="duckdb",
        dataset_name="synthesia_data",
    )
    load_info = pipeline.run(synthesia_source())
    print(load_info)

To add more endpoints, append entries from the resource table to the "resources" list using the same name, path, and data_selector pattern.

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How do I query the loaded data?

Once the pipeline runs, dlt creates one table per resource. You can query with Python or SQL.

Python (pandas DataFrame):

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import dlt

data = dlt.pipeline("synthesia_pipeline").dataset()
sessions_df = data.videos.df()
print(sessions_df.head())

SQL (DuckDB example):

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SELECT * FROM synthesia_data.videos LIMIT 10;

In a marimo or Jupyter notebook:

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import dlt

data = dlt.pipeline("synthesia_pipeline").dataset()
data.videos.df().head()

See how to explore your data in marimo Notebooks and how to query your data in Python with dataset.

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What destinations can I load Synthesia data to?

dlt supports loading into any of these destinations — only the destination parameter changes:

Change the destination in dlt.pipeline(destination="snowflake") and add credentials in .dlt/secrets.toml. See the full destinations list.

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Troubleshooting

Authentication failures

If you receive 401 Unauthorized, confirm you created an API key under Account → Integrations and that you include the key in the Authorization header for every request. Ensure you copied the full key and that the key has not been revoked.

Rate limits

Synthesia enforces tier-based rate limits (Creator/Enterprise tiers). If you exceed limits the API returns 429 Too Many Requests and headers RateLimit-Limit and RateLimit-Reset indicating the breached limit and wait time. Back off and retry after RateLimit-Reset seconds.

Video processing / polling vs webhooks

Video creation is asynchronous. Poll the GET /v1/videos/{id} endpoint to inspect the status field; when status equals "complete" the response includes a time-limited download URL in the download attribute. Alternatively configure webhooks to receive completion notifications (note: API keys belong to the account that creates them; webhooks created with an API key are tied to that account).

Ensure that the API key is valid to avoid 401 Unauthorized errors. Also, verify endpoint paths and parameters to avoid 404 Not Found errors.

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Next steps

Continue your data engineering journey with the other toolkits of the dltHub AI Workbench:

• data-exploration — Build custom notebooks, charts, and dashboards for deeper analysis with marimo notebooks.
• dlthub-runtime — Deploy, schedule, and monitor your pipeline in production.

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dlt ai toolkit data-exploration install
dlt ai toolkit dlthub-runtime install

• How to deploy a pipeline
• How to explore your data in marimo Notebooks
• How to query your data in Python with dataset
• Join the dlt community on Slack