ClickUp Operator

Metadata-Version: 2.3 Name: anthropic Version: 0.25.9 Summary: The official Python library for the anthropic API Project-URL: Homepage, https://github.com/anthropics/anthropic-sdk-python Project-URL: Repository, https://github.com/anthropics/anthropic-sdk-python Author-email: Anthropic <support@anthropic.com> License-Expression: MIT License-File: LICENSE Classifier: Intended Audience :: Developers Classifier: License :: OSI Approved :: MIT License Classifier: Operating System :: MacOS Classifier: Operating System :: Microsoft :: Windows Classifier: Operating System :: OS Independent Classifier: Operating System :: POSIX Classifier: Operating System :: POSIX :: Linux Classifier: Programming Language :: Python :: 3.7 Classifier: Programming Language :: Python :: 3.8 Classifier: Programming Language :: Python :: 3.9 Classifier: Programming Language :: Python :: 3.10 Classifier: Programming Language :: Python :: 3.11 Classifier: Programming Language :: Python :: 3.12 Classifier: Topic :: Software Development :: Libraries :: Python Modules Classifier: Typing :: Typed Requires-Python: >=3.7 Requires-Dist: anyio<5,>=3.5.0 Requires-Dist: cached-property; python_version < '3.8' Requires-Dist: distro<2,>=1.7.0 Requires-Dist: httpx<1,>=0.23.0 Requires-Dist: pydantic<3,>=1.9.0 Requires-Dist: sniffio Requires-Dist: tokenizers>=0.13.0 Requires-Dist: typing-extensions<5,>=4.7 Provides-Extra: bedrock Requires-Dist: boto3>=1.28.57; extra == 'bedrock' Requires-Dist: botocore>=1.31.57; extra == 'bedrock' Provides-Extra: vertex Requires-Dist: google-auth<3,>=2; extra == 'vertex' Description-Content-Type: text/markdown # Anthropic Python API library [](https://pypi.org/project/anthropic/) The Anthropic Python library provides convenient access to the Anthropic REST API from any Python 3.7+ application. It 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). ## Documentation The REST API documentation can be found [on docs.anthropic.com](https://docs.anthropic.com/claude/reference/). The full API of this library can be found in [api.md](https://github.com/anthropics/anthropic-sdk-python/tree/main/api.md). ## Installation ```sh # install from PyPI pip install anthropic ``` ## Usage The full API of this library can be found in [api.md](https://github.com/anthropics/anthropic-sdk-python/tree/main/api.md). ```python import os from anthropic import Anthropic client = Anthropic( # This is the default and can be omitted api_key=os.environ.get("ANTHROPIC_API_KEY"), ) message = client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) print(message.content) ``` While you can provide an `api_key` keyword argument, we recommend using [python-dotenv](https://pypi.org/project/python-dotenv/) to add `ANTHROPIC_API_KEY="my-anthropic-api-key"` to your `.env` file so that your API Key is not stored in source control. ## Async usage Simply import `AsyncAnthropic` instead of `Anthropic` and use `await` with each API call: ```python import os import asyncio from anthropic import AsyncAnthropic client = AsyncAnthropic( # This is the default and can be omitted api_key=os.environ.get("ANTHROPIC_API_KEY"), ) async def main() -> None: message = await client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) print(message.content) 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 anthropic import Anthropic client = Anthropic() stream = client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", stream=True, ) for event in stream: print(event.type) ``` The async client uses the exact same interface. ```python from anthropic import AsyncAnthropic client = AsyncAnthropic() stream = await client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", stream=True, ) async for event in stream: print(event.type) ``` ### Streaming Helpers This library provides several conveniences for streaming messages, for example: ```py import asyncio from anthropic import AsyncAnthropic client = AsyncAnthropic() async def main() -> None: async with client.messages.stream( max_tokens=1024, messages=[ { "role": "user", "content": "Say hello there!", } ], model="claude-3-opus-20240229", ) as stream: async for text in stream.text_stream: print(text, end="", flush=True) print() message = await stream.get_final_message() print(message.to_json()) asyncio.run(main()) ``` Streaming with `client.messages.stream(...)` exposes [various helpers for your convenience](https://github.com/anthropics/anthropic-sdk-python/tree/main/helpers.md) including event handlers and accumulation. Alternatively, you can use `client.messages.create(..., stream=True)` which only returns an async iterable of the events in the stream and thus uses less memory (it does not build up a final message object for you). ## Token counting You can see the exact usage for a given request through the `usage` response property, e.g. ```py message = client.messages.create(...) message.usage # Usage(input_tokens=25, output_tokens=13) ``` ## Tool use beta This SDK provides beta support for tool use, aka function calling. More details can be found in [the documentation](https://docs.anthropic.com/claude/docs/tool-use). ## AWS Bedrock This library also provides support for the [Anthropic Bedrock API](https://aws.amazon.com/bedrock/claude/) if you install this library with the `bedrock` extra, e.g. `pip install -U anthropic[bedrock]`. You can then import and instantiate a separate `AnthropicBedrock` class, the rest of the API is the same. ```py from anthropic import AnthropicBedrock client = AnthropicBedrock() message = client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello!", } ], model="anthropic.claude-3-sonnet-20240229-v1:0", ) print(message) ``` For a more fully fledged example see [`examples/bedrock.py`](https://github.com/anthropics/anthropic-sdk-python/blob/main/examples/bedrock.py). ## Google Vertex This library also provides support for the [Anthropic Vertex API](https://cloud.google.com/vertex-ai?hl=en) if you install this library with the `vertex` extra, e.g. `pip install -U anthropic[vertex]`. You can then import and instantiate a separate `AnthropicVertex`/`AsyncAnthropicVertexAsync` class, which has the same API as the base `Anthropic`/`AsyncAnthropic` class. ```py from anthropic import AnthropicVertex client = AnthropicVertex() message = client.messages.create( model="claude-3-sonnet@20240229", max_tokens=100, messages=[ { "role": "user", "content": "Hello!", } ], ) print(message) ``` For a more complete example see [`examples/vertex.py`](https://github.com/anthropics/anthropic-sdk-python/blob/main/examples/vertex.py). ## 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 `anthropic.APIConnectionError` is raised. When the API returns a non-success status code (that is, 4xx or 5xx response), a subclass of `anthropic.APIStatusError` is raised, containing `status_code` and `response` properties. All errors inherit from `anthropic.APIError`. ```python import anthropic from anthropic import Anthropic client = Anthropic() try: client.messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) except anthropic.APIConnectionError as e: print("The server could not be reached") print(e.__cause__) # an underlying Exception, likely raised within httpx. except anthropic.RateLimitError as e: print("A 429 status code was received; we should back off a bit.") except anthropic.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 anthropic import Anthropic # Configure the default for all requests: client = Anthropic( # default is 2 max_retries=0, ) # Or, configure per-request: client.with_options(max_retries=5).messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) ``` ### Timeouts By default requests time out after 10 minutes. 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 anthropic import Anthropic # Configure the default for all requests: client = Anthropic( # 20 seconds (default is 10 minutes) timeout=20.0, ) # More granular control: client = Anthropic( timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0), ) # Override per-request: client.with_options(timeout=5.0).messages.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) ``` On timeout, an `APITimeoutError` is thrown. Note that requests that time out are [retried twice by default](https://github.com/anthropics/anthropic-sdk-python/tree/main/#retries). ## Default Headers We automatically send the `anthropic-version` header set to `2023-06-01`. If you need to, you can override it by setting default headers per-request or on the client object. Be aware that doing so may result in incorrect types and other unexpected or undefined behavior in the SDK. ```python from anthropic import Anthropic client = Anthropic( default_headers={"anthropic-version": "My-Custom-Value"}, ) ``` ## 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 `ANTHROPIC_LOG` to `debug`. ```shell $ export ANTHROPIC_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 anthropic import Anthropic client = Anthropic() response = client.messages.with_raw_response.create( max_tokens=1024, messages=[{ "role": "user", "content": "Hello, Claude", }], model="claude-3-opus-20240229", ) print(response.headers.get('X-My-Header')) message = response.parse() # get the object that `messages.create()` would have returned print(message.content) ``` These methods return an [`LegacyAPIResponse`](https://github.com/anthropics/anthropic-sdk-python/tree/main/src/anthropic/_legacy_response.py) object. This is a legacy class as we're changing it slightly in the next major version. For the sync client this will mostly be the same with the exception of `content` & `text` will be methods instead of properties. In the async client, all methods will be async. A migration script will be provided & the migration in general should be smooth. #### `.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. As such, `.with_streaming_response` methods return a different [`APIResponse`](https://github.com/anthropics/anthropic-sdk-python/tree/main/src/anthropic/_response.py) object, and the async client returns an [`AsyncAPIResponse`](https://github.com/anthropics/anthropic-sdk-python/tree/main/src/anthropic/_response.py) object. ```python with client.messages.with_streaming_response.create( max_tokens=1024, messages=[ { "role": "user", "content": "Hello, Claude", } ], model="claude-3-opus-20240229", ) 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/#client-instances) functionality ```python from anthropic import Anthropic, DefaultHttpxClient client = Anthropic( # Or use the `ANTHROPIC_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/anthropics/anthropic-sdk-python/issues) with questions, bugs, or suggestions. ## Requirements Python 3.7 or higher.