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@@ -6,6 +6,8 @@ The Maisa Python library provides convenient access to the Maisa REST API from a
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application. The library includes type definitions for all request params and response fields,
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and offers both synchronous and asynchronous clients powered by [httpx](https://github.com/encode/httpx).
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It is generated with [Stainless](https://www.stainlessapi.com/).
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## Documentation
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The REST API documentation can be found [on docs.maisa.ai](https://docs.maisa.ai/). The full API of this library can be found in [api.md](api.md).
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The full API of this library can be found in [api.md](api.md).
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```python
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import os
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from maisa import Maisa
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client = Maisa(
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# This is the default and can be omitted
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api_key=os.environ.get("MAISA_API_KEY"),
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)
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client = Maisa()
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text_summary = client.capabilities.summarize(
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text="Example long text...",
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Simply import `AsyncMaisa` instead of `Maisa` and use `await` with each API call:
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```python
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import os
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import asyncio
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from maisa import AsyncMaisa
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client = AsyncMaisa(
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# This is the default and can be omitted
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api_key=os.environ.get("MAISA_API_KEY"),
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)
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client = AsyncMaisa()
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asyncdefmain() -> None:
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## Using types
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Nested request parameters are [TypedDicts](https://docs.python.org/3/library/typing.html#typing.TypedDict). Responses are [Pydantic models](https://docs.pydantic.dev), which provide helper methods for things like:
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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:
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- Serializing back into JSON, `model.model_dump_json(indent=2, exclude_unset=True)`
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- Converting to a dictionary, `model.model_dump(exclude_unset=True)`
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- Serializing back into JSON, `model.to_json()`
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- Converting to a dictionary, `model.to_dict()`
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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`.
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@@ -235,6 +229,41 @@ with client.capabilities.with_streaming_response.summarize(
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The context manager is required so that the response will reliably be closed.
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### Making custom/undocumented requests
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This library is typed for convenient access the documented API.
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If you need to access undocumented endpoints, params, or response properties, the library can still be used.
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#### Undocumented endpoints
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To make requests to undocumented endpoints, you can make requests using `client.get`, `client.post`, and other
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http verbs. Options on the client will be respected (such as retries) will be respected when making this
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request.
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```py
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import httpx
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response = client.post(
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"/foo",
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cast_to=httpx.Response,
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body={"my_param": True},
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)
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print(response.headers.get("x-foo"))
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```
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#### Undocumented request params
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If you want to explicitly send an extra param, you can do so with the `extra_query`, `extra_body`, and `extra_headers` request
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options.
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#### Undocumented response properties
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To access undocumented response properties, you can access the extra fields like `response.unknown_prop`. You
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can also get all the extra fields on the Pydantic model as a dict with
"functools.lru_cache".msg = "This function does not retain type information for the wrapped function's arguments; The `lru_cache` function from `_utils` should be used instead"
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