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diff --git a/apps/docs/memory-api/sdks/python.mdx b/apps/docs/memory-api/sdks/python.mdx new file mode 100644 index 00000000..2b1f56fc --- /dev/null +++ b/apps/docs/memory-api/sdks/python.mdx @@ -0,0 +1,349 @@ +--- +title: 'Python SDK' +sidebarTitle: "Python" +description: 'Learn how to use supermemory with Python' +--- + +## Installation + +```sh +# install from PyPI +pip install --pre supermemory +``` + +## Usage + + +```python +import os +from supermemory import Supermemory + +client = supermemory( + api_key=os.environ.get("SUPERMEMORY_API_KEY"), # This is the default and can be omitted +) + +response = client.search.execute( + q="documents related to python", +) +print(response.results) +``` + +While you can provide an `api_key` keyword argument, +we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/) +to add `SUPERMEMORY_API_KEY="My API Key"` to your `.env` file +so that your API Key is not stored in source control. + +## Async usage + +Simply import `AsyncSupermemory` instead of `supermemory` and use `await` with each API call: + +```python +import os +import asyncio +from supermemory import AsyncSupermemory + +client = AsyncSupermemory( + api_key=os.environ.get("SUPERMEMORY_API_KEY"), # This is the default and can be omitted +) + + +async def main() -> None: + response = await client.search.execute( + q="documents related to python", + ) + print(response.results) + + +asyncio.run(main()) +``` + +Functionality between the synchronous and asynchronous clients is otherwise identical. + +## 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`. + +## 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 +from pathlib import Path +from supermemory import Supermemory + +client = supermemory() + +client.memories.upload_file( + file=Path("/path/to/file"), +) +``` + +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. + +## 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 `supermemory.APIConnectionError` is raised. + +When the API returns a non-success status code (that is, 4xx or 5xx +response), a subclass of `supermemory.APIStatusError` is raised, containing `status_code` and `response` properties. + +All errors inherit from `supermemory.APIError`. + +```python +import supermemory +from supermemory import Supermemory + +client = supermemory() + +try: + client.memories.add( + content="This is a detailed article about machine learning concepts...", + ) +except supermemory.APIConnectionError as e: + print("The server could not be reached") + print(e.__cause__) # an underlying Exception, likely raised within httpx. +except supermemory.RateLimitError as e: + print("A 429 status code was received; we should back off a bit.") +except supermemory.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 +from supermemory import Supermemory + +# Configure the default for all requests: +client = supermemory( + # default is 2 + max_retries=0, +) + +# Or, configure per-request: +client.with_options(max_retries=5).memories.add( + content="This is a detailed article about machine learning concepts...", +) +``` + +### 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 supermemory import Supermemory + +# Configure the default for all requests: +client = supermemory( + # 20 seconds (default is 1 minute) + timeout=20.0, +) + +# More granular control: +client = supermemory( + timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0), +) + +# Override per-request: +client.with_options(timeout=5.0).memories.add( + content="This is a detailed article about machine learning concepts...", +) +``` + +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 `SUPERMEMORY_LOG` to `info`. + +```shell +$ export SUPERMEMORY_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 +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 supermemory import Supermemory + +client = supermemory() +response = client.memories.with_raw_response.add( + content="This is a detailed article about machine learning concepts...", +) +print(response.headers.get('X-My-Header')) + +memory = response.parse() # get the object that `memories.add()` would have returned +print(memory.id) +``` + +These methods return an [`APIResponse`](https://github.com/supermemoryai/python-sdk/tree/main/src/supermemory/_response.py) object. + +The async client returns an [`AsyncAPIResponse`](https://github.com/supermemoryai/python-sdk/tree/main/src/supermemory/_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.memories.with_streaming_response.add( + content="This is a detailed article about machine learning concepts...", +) 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 +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 +import httpx +from supermemory import Supermemory, DefaultHttpxClient + +client = supermemory( + # Or use the `SUPERMEMORY_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 +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 +from supermemory import Supermemory + +with supermemory() 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/supermemoryai/python-sdk/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 +import supermemory +print(supermemory.__version__) +``` + +## Requirements + +Python 3.8 or higher.
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