# Writer Python API library [![PyPI version](https://img.shields.io/pypi/v/writer-sdk.svg)](https://pypi.org/project/writer-sdk/) The Writer Python library provides convenient access to the Writer REST API from any Python 3.7+ application. The library includes type definitions for all request params and response fields, and offers both synchronous and asynchronous clients powered by [httpx](https://github.com/encode/httpx). It is generated with [Stainless](https://www.stainlessapi.com/). ## Documentation The REST API documentation can be found [on dev.writer.com](https://dev.writer.com/api-guides/introduction). The full API of this library can be found in [api.md](api.md). ## Installation To install the package from PyPI, use the following command: ```sh pip install writer-sdk ``` ## Usage The full API of this library can be found in [api.md](api.md). ```python import os from writerai import Writer client = Writer( # This is the default and can be omitted api_key=os.environ.get("WRITER_API_KEY"), ) chat = client.chat.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) print(chat.id) ``` While you can provide an `api_key` keyword argument, we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/) to add `WRITER_API_KEY="My API Key"` to your `.env` file so that your API Key is not stored in source control. ## Async usage Simply import `AsyncWriter` instead of `Writer` and use `await` with each API call: ```python import os import asyncio from writerai import AsyncWriter client = AsyncWriter( # This is the default and can be omitted api_key=os.environ.get("WRITER_API_KEY"), ) async def main() -> None: chat = await client.chat.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) print(chat.id) asyncio.run(main()) ``` Functionality between the synchronous and asynchronous clients is otherwise identical. ## Streaming responses We provide support for streaming responses using Server Side Events (SSE). ```python from writerai import Writer client = Writer() stream = client.completions.create( model="palmyra-x-002-instruct", prompt="Hi, my name is", stream=True, ) for completion in stream: print(completion.value) ``` The async client uses the exact same interface. ```python import asyncio from writerai import AsyncWriter client = AsyncWriter() async def main() -> None: stream = await client.completions.create( model="palmyra-x-002-instruct", prompt="Hi, my name is", stream=True, ) async for completion in stream: print(completion.value) asyncio.run(main()) ``` ## 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`. ## Handling errors When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of `writerai.APIConnectionError` is raised. When the API returns a non-success status code (that is, 4xx or 5xx response), a subclass of `writerai.APIStatusError` is raised, containing `status_code` and `response` properties. All errors inherit from `writerai.APIError`. ```python import writerai from writerai import Writer client = Writer() try: client.chat.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) except writerai.APIConnectionError as e: print("The server could not be reached") print(e.__cause__) # an underlying Exception, likely raised within httpx. except writerai.RateLimitError as e: print("A 429 status code was received; we should back off a bit.") except writerai.APIStatusError as e: print("Another non-200-range status code was received") print(e.status_code) print(e.response) ``` Error codes are as followed: | 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 from writerai import Writer # Configure the default for all requests: client = Writer( # default is 2 max_retries=0, ) # Or, configure per-request: client.with_options(max_retries=5).chat.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) ``` ### 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/#fine-tuning-the-configuration) object: ```python from writerai import Writer # Configure the default for all requests: client = Writer( # 20 seconds (default is 1 minute) timeout=20.0, ) # More granular control: client = Writer( timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0), ) # Override per-request: client.with_options(timeout=5.0).chat.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) ``` On timeout, an `APITimeoutError` is thrown. Note that requests that time out are [retried twice by default](#retries). ## Advanced ### 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 `WRITER_LOG` to `debug`. ```shell $ export WRITER_LOG=debug ``` ### 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 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 from writerai import Writer client = Writer() response = client.chat.with_raw_response.chat( messages=[{ "content": "string", "role": "user", }], model="palmyra-x-002-32k", ) print(response.headers.get('X-My-Header')) chat = response.parse() # get the object that `chat.chat()` would have returned print(chat.id) ``` These methods return an [`APIResponse`](https://github.com/writer/writer-python/tree/main/src/writerai/_response.py) object. The async client returns an [`AsyncAPIResponse`](https://github.com/writer/writer-python/tree/main/src/writerai/_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 with client.chat.with_streaming_response.chat( messages=[ { "content": "string", "role": "user", } ], model="palmyra-x-002-32k", ) 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) will be respected when making this request. ```py 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 - Custom transports - Additional [advanced](https://www.python-httpx.org/advanced/clients/) functionality ```python from writerai import Writer, DefaultHttpxClient client = Writer( # Or use the `WRITER_BASE_URL` env var base_url="http://my.test.server.example.com:8083", http_client=DefaultHttpxClient( proxies="http://my.test.proxy.example.com", transport=httpx.HTTPTransport(local_address="0.0.0.0"), ), ) ``` ### 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. ## 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/writer/writer-python/issues) with questions, bugs, or suggestions. ## Requirements Python 3.7 or higher.