> ## Documentation Index > Fetch the complete documentation index at: https://docs.dedaluslabs.ai/llms.txt > Use this file to discover all available pages before exploring further. # Python SDK > Models API Python SDK v0.1.0 **v0.1.0** | [GitHub](https://github.com/dedalus-labs/dedalus-sdk-python) | [Changelog](https://github.com/dedalus-labs/dedalus-sdk-python/blob/main/CHANGELOG.md) ## Installation ```bash theme={"theme":{"light":"github-light","dark":"github-dark"}} pip install dedalus-labs ``` ```bash theme={"theme":{"light":"github-light","dark":"github-dark"}} uv add dedalus-labs ``` ## Usage See the full method reference in the [API Reference](/api-reference/dcs) tab. The full API of this library can be found in [api.md](api.md). ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} import os from dedalus_labs import Dedalus client = Dedalus( api_key=os.environ.get("DEDALUS_API_KEY"), # This is the default and can be omitted # defaults to "production". environment="development", ) chat_completion = client.chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) print(chat_completion.id) ``` While you can provide an `api_key` keyword argument, we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/) to add `DEDALUS_API_KEY="My API Key"` to your `.env` file so that your API Key is not stored in source control. ## Async Usage Simply import `AsyncDedalus` instead of `Dedalus` and use `await` with each API call: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} import os import asyncio from dedalus_labs import AsyncDedalus client = AsyncDedalus( api_key=os.environ.get("DEDALUS_API_KEY"), # This is the default and can be omitted # defaults to "production". environment="development", ) async def main() -> None: chat_completion = await client.chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) print(chat_completion.id) asyncio.run(main()) ``` Functionality between the synchronous and asynchronous clients is otherwise identical. ### With aiohttp By default, the async client uses `httpx` for HTTP requests. However, for improved concurrency performance you may also use `aiohttp` as the HTTP backend. You can enable this by installing `aiohttp`: ```sh theme={"theme":{"light":"github-light","dark":"github-dark"}} # install from PyPI pip install dedalus_labs[aiohttp] ``` Then you can enable it by instantiating the client with `http_client=DefaultAioHttpClient()`: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} import os import asyncio from dedalus_labs import DefaultAioHttpClient from dedalus_labs import AsyncDedalus async def main() -> None: async with AsyncDedalus( api_key=os.environ.get("DEDALUS_API_KEY"), # This is the default and can be omitted http_client=DefaultAioHttpClient(), ) as client: chat_completion = await client.chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) print(chat_completion.id) asyncio.run(main()) ``` ## Streaming We provide support for streaming responses using Server Side Events (SSE). ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus client = Dedalus() stream = client.chat.completions.create( model="openai/gpt-5-nano", stream=True, messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "What do you think of artificial intelligence?", }, ], ) for chat_completion in stream: print(chat_completion.id) ``` The async client uses the exact same interface. ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import AsyncDedalus client = AsyncDedalus() stream = await client.chat.completions.create( model="openai/gpt-5-nano", stream=True, messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "What do you think of artificial intelligence?", }, ], ) async for chat_completion in stream: print(chat_completion.id) ``` ## Using types Nested request parameters are [TypedDicts](https://docs.python.org/3/library/typing.html#typing.TypedDict). Responses are [Pydantic models](https://docs.pydantic.dev) which also provide helper methods for things like: * Serializing back into JSON, `model.to_json()` * Converting to a dictionary, `model.to_dict()` Typed requests and responses provide autocomplete and documentation within your editor. If you would like to see type errors in VS Code to help catch bugs earlier, set `python.analysis.typeCheckingMode` to `basic`. ## Nested params Nested parameters are dictionaries, typed using `TypedDict`, for example: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus client = Dedalus() chat_completion = client.chat.completions.create( model="openai/gpt-5", audio={ "format": "wav", "voice": "string", }, ) print(chat_completion.audio) ``` ## File uploads Request parameters that correspond to file uploads can be passed as `bytes`, or a [`PathLike`](https://docs.python.org/3/library/os.html#os.PathLike) instance or a tuple of `(filename, contents, media type)`. ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from pathlib import Path from dedalus_labs import Dedalus client = Dedalus() client.audio.transcriptions.create( file=Path("/path/to/file"), model="model", ) ``` The async client uses the exact same interface. If you pass a [`PathLike`](https://docs.python.org/3/library/os.html#os.PathLike) instance, the file contents will be read asynchronously automatically. ## Error Handling Always wrap API calls in try/catch. The SDK throws typed errors for HTTP failures. When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of `dedalus_labs.APIConnectionError` is raised. When the API returns a non-success status code (that is, 4xx or 5xx response), a subclass of `dedalus_labs.APIStatusError` is raised, containing `status_code` and `response` properties. All errors inherit from `dedalus_labs.APIError`. ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} import dedalus_labs from dedalus_labs import Dedalus client = Dedalus() try: client.chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) except dedalus_labs.APIConnectionError as e: print("The server could not be reached") print(e.__cause__) # an underlying Exception, likely raised within httpx. except dedalus_labs.RateLimitError as e: print("A 429 status code was received; we should back off a bit.") except dedalus_labs.APIStatusError as e: print("Another non-200-range status code was received") print(e.status_code) print(e.response) ``` Error codes are as follows: | Status Code | Error Type | | ----------- | -------------------------- | | 400 | `BadRequestError` | | 401 | `AuthenticationError` | | 403 | `PermissionDeniedError` | | 404 | `NotFoundError` | | 422 | `UnprocessableEntityError` | | 429 | `RateLimitError` | | >=500 | `InternalServerError` | | N/A | `APIConnectionError` | ### Retries Certain errors are automatically retried 2 times by default, with a short exponential backoff. Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict, 429 Rate Limit, and >=500 Internal errors are all retried by default. You can use the `max_retries` option to configure or disable retry settings: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus # Configure the default for all requests: client = Dedalus( # default is 2 max_retries=0, ) # Or, configure per-request: client.with_options(max_retries=5).chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) ``` ### Timeouts By default requests time out after 1 minute. You can configure this with a `timeout` option, which accepts a float or an [`httpx.Timeout`](https://www.python-httpx.org/advanced/timeouts/#fine-tuning-the-configuration) object: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus # Configure the default for all requests: client = Dedalus( # 20 seconds (default is 1 minute) timeout=20.0, ) # More granular control: client = Dedalus( timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0), ) # Override per-request: client.with_options(timeout=5.0).chat.completions.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) ``` On timeout, an `APITimeoutError` is thrown. Note that requests that time out are [retried twice by default](#retries). ## Default Headers We automatically send the following headers with all requests. | Header | Value | | --------------- | ------------- | | `User-Agent` | `Dedalus-SDK` | | `X-SDK-Version` | `1.0.0` | If you need to, you can override these headers by setting default headers per-request or on the client object. ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus client = Dedalus( default_headers={"User-Agent": "My-Custom-Value"}, ) ``` ### Logging We use the standard library [`logging`](https://docs.python.org/3/library/logging.html) module. You can enable logging by setting the environment variable `DEDALUS_LOG` to `info`. ```shell theme={"theme":{"light":"github-light","dark":"github-dark"}} $ export DEDALUS_LOG=info ``` Or to `debug` for more verbose logging. ### How to tell whether `None` means `null` or missing In an API response, a field may be explicitly `null`, or missing entirely; in either case, its value is `None` in this library. You can differentiate the two cases with `.model_fields_set`: ```py theme={"theme":{"light":"github-light","dark":"github-dark"}} if response.my_field is None: if 'my_field' not in response.model_fields_set: print('Got json like {}, without a "my_field" key present at all.') else: print('Got json like {"my_field": null}.') ``` ### Accessing raw response data (e.g. headers) The "raw" Response object can be accessed by prefixing `.with_raw_response.` to any HTTP method call, e.g., ```py theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus client = Dedalus() response = client.chat.completions.with_raw_response.create( model="openai/gpt-5-nano", messages=[{ "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }], ) print(response.headers.get('X-My-Header')) completion = response.parse() # get the object that `chat.completions.create()` would have returned print(completion.id) ``` These methods return an [`APIResponse`](https://github.com/dedalus-labs/dedalus-sdk-python/tree/main/src/dedalus_labs/_response.py) object. The async client returns an [`AsyncAPIResponse`](https://github.com/dedalus-labs/dedalus-sdk-python/tree/main/src/dedalus_labs/_response.py) with the same structure, the only difference being `await`able methods for reading the response content. #### `.with_streaming_response` The above interface eagerly reads the full response body when you make the request, which may not always be what you want. To stream the response body, use `.with_streaming_response` instead, which requires a context manager and only reads the response body once you call `.read()`, `.text()`, `.json()`, `.iter_bytes()`, `.iter_text()`, `.iter_lines()` or `.parse()`. In the async client, these are async methods. ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} with client.chat.completions.with_streaming_response.create( model="openai/gpt-5-nano", messages=[ { "role": "system", "content": "You are Stephen Dedalus. Respond in morose Joycean malaise.", }, { "role": "user", "content": "Hello, how are you today?", }, ], ) as response: print(response.headers.get("X-My-Header")) for line in response.iter_lines(): print(line) ``` The context manager is required so that the response will reliably be closed. ### Making custom/undocumented requests This library is typed for convenient access to the documented API. If you need to access undocumented endpoints, params, or response properties, the library can still be used. #### Undocumented endpoints To make requests to undocumented endpoints, you can make requests using `client.get`, `client.post`, and other http verbs. Options on the client will be respected (such as retries) when making this request. ```py theme={"theme":{"light":"github-light","dark":"github-dark"}} import httpx response = client.post( "/foo", cast_to=httpx.Response, body={"my_param": True}, ) print(response.headers.get("x-foo")) ``` #### Undocumented request params If you want to explicitly send an extra param, you can do so with the `extra_query`, `extra_body`, and `extra_headers` request options. #### Undocumented response properties To access undocumented response properties, you can access the extra fields like `response.unknown_prop`. You can also get all the extra fields on the Pydantic model as a dict with [`response.model_extra`](https://docs.pydantic.dev/latest/api/base_model/#pydantic.BaseModel.model_extra). ### Configuring the HTTP client You can directly override the [httpx client](https://www.python-httpx.org/api/#client) to customize it for your use case, including: * Support for [proxies](https://www.python-httpx.org/advanced/proxies/) * Custom [transports](https://www.python-httpx.org/advanced/transports/) * Additional [advanced](https://www.python-httpx.org/advanced/clients/) functionality ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} import httpx from dedalus_labs import Dedalus, DefaultHttpxClient client = Dedalus( # Or use the `DEDALUS_BASE_URL` env var base_url="http://my.test.server.example.com:8083", http_client=DefaultHttpxClient( proxy="http://my.test.proxy.example.com", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), ) ``` You can also customize the client on a per-request basis by using `with_options()`: ```python theme={"theme":{"light":"github-light","dark":"github-dark"}} client.with_options(http_client=DefaultHttpxClient(...)) ``` ### Managing HTTP resources By default the library closes underlying HTTP connections whenever the client is [garbage collected](https://docs.python.org/3/reference/datamodel.html#object.__del__). You can manually close the client using the `.close()` method if desired, or with a context manager that closes when exiting. ```py theme={"theme":{"light":"github-light","dark":"github-dark"}} from dedalus_labs import Dedalus with Dedalus() as client: # make requests here ... # HTTP client is now closed ``` ## Versioning This package generally follows [SemVer](https://semver.org/spec/v2.0.0.html) conventions, though certain backwards-incompatible changes may be released as minor versions: 1. Changes that only affect static types, without breaking runtime behavior. 2. Changes to library internals which are technically public but not intended or documented for external use. *(Please open a GitHub issue to let us know if you are relying on such internals.)* 3. Changes that we do not expect to impact the vast majority of users in practice. We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience. We are keen for your feedback; please open an [issue](https://www.github.com/dedalus-labs/dedalus-sdk-python/issues) with questions, bugs, or suggestions. ### Determining the installed version If you've upgraded to the latest version but aren't seeing any new features you were expecting then your python environment is likely still using an older version. You can determine the version that is being used at runtime with: ```py theme={"theme":{"light":"github-light","dark":"github-dark"}} import dedalus_labs print(dedalus_labs.__version__) ``` Python 3.9 or higher.