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The Agentex Python library provides convenient access to the Agentex REST API from any Python 3.9+
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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.stainless.com/).
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The Agentex Python library provides convenient access to the Agentex REST API from any Python 3.9+ application.
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## Documentation
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The REST API documentation can be found on [docs.gp.scale.com](https://docs.gp.scale.com). The full API of this library can be found in[api.md](api.md).
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API documentation: [docs.gp.scale.com](https://docs.gp.scale.com). Full library API reference:[api.md](api.md).
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## Installation
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```sh
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# install from PyPI
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pip install agentex-sdk
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```
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## Usage
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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 agentex import Agentex
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client = Agentex(
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api_key=os.environ.get("AGENTEX_SDK_API_KEY"), # This is the default and can be omitted
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# defaults to "production".
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environment="development",
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api_key=os.environ.get("AGENTEX_SDK_API_KEY"),
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)
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tasks = client.tasks.list()
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```
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While you can provide an `api_key` keyword argument,
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we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/)
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to add `AGENTEX_SDK_API_KEY="My API Key"` to your `.env` file
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so that your API Key is not stored in source control.
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Store your API key in a `.env` file as `AGENTEX_SDK_API_KEY="My API Key"` and use [python-dotenv](https://pypi.org/project/python-dotenv/) to avoid storing it in source control.
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## Async usage
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Simply import `AsyncAgentex` instead of `Agentex` 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 agentex import AsyncAgentex
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client = AsyncAgentex(
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api_key=os.environ.get("AGENTEX_SDK_API_KEY"), # This is the default and can be omitted
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# defaults to "production".
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environment="development",
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api_key=os.environ.get("AGENTEX_SDK_API_KEY"),
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)
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asyncdefmain() -> None:
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tasks =await client.tasks.list()
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asyncio.run(main())
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```
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Functionality between the synchronous and asynchronous clients is otherwise identical.
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## Debugging
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AgentEx provides built-in debugging support for **temporal projects** during local development.
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```bash
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# Basic debugging
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uv run agentex agents run --manifest manifest.yaml --debug-worker
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# Wait for debugger to attach before starting
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uv run agentex agents run --manifest manifest.yaml --debug-worker --wait-for-debugger
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# Custom debug port
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uv run agentex agents run --manifest manifest.yaml --debug-worker --debug-port 5679
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```
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For **VS Code**, add this configuration to `.vscode/launch.json`:
The debug server automatically finds an available port starting from 5678 and prints connection details when starting.
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### With aiohttp
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By default, the async client uses `httpx` for HTTP requests. However, for improved concurrency performance you may also use `aiohttp` as the HTTP backend.
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You can enable this by installing `aiohttp`:
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```sh
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# install from PyPI
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pip install agentex-sdk[aiohttp]
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```
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Then you can enable it by instantiating the client with `http_client=DefaultAioHttpClient()`:
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```python
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import os
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import asyncio
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from agentex import DefaultAioHttpClient
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from agentex import AsyncAgentex
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asyncdefmain() -> None:
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asyncwith AsyncAgentex(
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api_key=os.environ.get("AGENTEX_SDK_API_KEY"), # This is the default and can be omitted
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http_client=DefaultAioHttpClient(),
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) as client:
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tasks =await client.tasks.list()
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asyncio.run(main())
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```
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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 also provide helper methods for things like:
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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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## Handling errors
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When the library is unable to connect to the API (for example, due to network connection problems or a timeout), a subclass of `agentex.APIConnectionError` is raised.
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When the API returns a non-success status code (that is, 4xx or 5xx
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response), a subclass of `agentex.APIStatusError` is raised, containing `status_code` and `response` properties.
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All errors inherit from `agentex.APIError`.
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```python
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import agentex
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from agentex import Agentex
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client.tasks.list()
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except agentex.APIConnectionError as e:
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print("The server could not be reached")
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print(e.__cause__) # an underlying Exception, likely raised within httpx.
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except agentex.RateLimitError as e:
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print("A 429 status code was received; we should back off a bit.")
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print("Rate limited (429)")
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except agentex.APIStatusError as e:
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print("Another non-200-range status code was received")
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print(e.status_code)
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print(e.response)
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```
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Error codes are as follows:
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| Status Code | Error Type |
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| ----------- | -------------------------- |
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| 400 |`BadRequestError`|
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| 401 |`AuthenticationError`|
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| 403 |`PermissionDeniedError`|
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| 404 |`NotFoundError`|
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| 422 |`UnprocessableEntityError`|
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| 429 |`RateLimitError`|
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| >=500 |`InternalServerError`|
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| N/A |`APIConnectionError`|
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### Retries
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Certain errors are automatically retried 2 times by default, with a short exponential backoff.
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Connection errors (for example, due to a network connectivity problem), 408 Request Timeout, 409 Conflict,
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429 Rate Limit, and >=500 Internal errors are all retried by default.
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You can use the `max_retries` option to configure or disable retry settings:
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```python
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from agentex import Agentex
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# Configure the default for all requests:
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client = Agentex(
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# default is 2
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max_retries=0,
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)
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# Or, configure per-request:
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client.with_options(max_retries=5).tasks.list()
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```
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### Timeouts
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By default requests time out after 1 minute. You can configure this with a `timeout` option,
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which accepts a float or an [`httpx.Timeout`](https://www.python-httpx.org/advanced/timeouts/#fine-tuning-the-configuration) object:
Note that requests that time out are [retried twice by default](#retries).
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## Advanced
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### Logging
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We use the standard library [`logging`](https://docs.python.org/3/library/logging.html) module.
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You can enable logging by setting the environment variable `AGENTEX_LOG` to `info`.
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```shell
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$ export AGENTEX_LOG=info
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```
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Or to `debug` for more verbose logging.
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### How to tell whether `None` means `null` or missing
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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`:
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```py
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if response.my_field isNone:
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if'my_field'notin response.model_fields_set:
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print('Got json like {}, without a "my_field" key present at all.')
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else:
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print('Got json like {"my_field": null}.')
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```
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### Accessing raw response data (e.g. headers)
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The "raw" Response object can be accessed by prefixing `.with_raw_response.` to any HTTP method call, e.g.,
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```py
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from agentex import Agentex
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client = Agentex()
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response = client.tasks.with_raw_response.list()
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print(response.headers.get('X-My-Header'))
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task = response.parse() # get the object that `tasks.list()` would have returned
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print(task)
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```
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These methods return an [`APIResponse`](https://github.com/scaleapi/scale-agentex-python/tree/main/src/agentex/_response.py) object.
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The async client returns an [`AsyncAPIResponse`](https://github.com/scaleapi/scale-agentex-python/tree/main/src/agentex/_response.py) with the same structure, the only difference being `await`able methods for reading the response content.
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#### `.with_streaming_response`
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The above interface eagerly reads the full response body when you make the request, which may not always be what you want.
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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.
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```python
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with client.tasks.with_streaming_response.list() as response:
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print(response.headers.get("X-My-Header"))
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for line in response.iter_lines():
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print(line)
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```
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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 to 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) when making this 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
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.
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```py
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from agentex import Agentex
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with Agentex() as client:
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# make requests here
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...
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# HTTP client is now closed
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```
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## Versioning
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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:
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1. Changes that only affect static types, without breaking runtime behavior.
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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.)_
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3. Changes that we do not expect to impact the vast majority of users in practice.
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We take backwards-compatibility seriously and work hard to ensure you can rely on a smooth upgrade experience.
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We are keen for your feedback; please open an [issue](https://www.github.com/scaleapi/scale-agentex-python/issues) with questions, bugs, or suggestions.
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### Determining the installed version
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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.
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You can determine the version that is being used at runtime with:
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```py
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import agentex
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print(agentex.__version__)
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```
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Errors automatically retry 2 times by default for connection errors, timeouts, 429, and 5xx responses.
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