506 lines
15 KiB
Plaintext
506 lines
15 KiB
Plaintext
Metadata-Version: 2.1
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Name: anthropic
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Version: 0.18.1
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Summary: The official Python library for the anthropic API
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Project-URL: Homepage, https://github.com/anthropics/anthropic-sdk-python
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Project-URL: Repository, https://github.com/anthropics/anthropic-sdk-python
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Author-email: Anthropic <support@anthropic.com>
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License-Expression: MIT
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License-File: LICENSE
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Classifier: Intended Audience :: Developers
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Classifier: License :: OSI Approved :: MIT License
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Classifier: Operating System :: MacOS
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Classifier: Operating System :: Microsoft :: Windows
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Classifier: Operating System :: OS Independent
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Classifier: Operating System :: POSIX
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Classifier: Operating System :: POSIX :: Linux
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Classifier: Programming Language :: Python :: 3.7
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Classifier: Programming Language :: Python :: 3.8
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Classifier: Programming Language :: Python :: 3.9
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Classifier: Programming Language :: Python :: 3.10
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Classifier: Programming Language :: Python :: 3.11
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Classifier: Programming Language :: Python :: 3.12
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Classifier: Topic :: Software Development :: Libraries :: Python Modules
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Classifier: Typing :: Typed
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Requires-Python: >=3.7
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Requires-Dist: anyio<5,>=3.5.0
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Requires-Dist: cached-property; python_version < '3.8'
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Requires-Dist: distro<2,>=1.7.0
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Requires-Dist: httpx<1,>=0.23.0
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Requires-Dist: pydantic<3,>=1.9.0
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Requires-Dist: sniffio
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Requires-Dist: tokenizers>=0.13.0
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Requires-Dist: typing-extensions<5,>=4.7
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Provides-Extra: bedrock
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Requires-Dist: boto3>=1.28.57; extra == 'bedrock'
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Requires-Dist: botocore>=1.31.57; extra == 'bedrock'
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Provides-Extra: vertex
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Requires-Dist: google-auth<3,>=2; extra == 'vertex'
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Description-Content-Type: text/markdown
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# Anthropic Python API library
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[](https://pypi.org/project/anthropic/)
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The Anthropic Python library provides convenient access to the Anthropic REST API from any Python 3.7+
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application. It 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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## Documentation
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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](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 anthropic
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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 anthropic import Anthropic
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client = Anthropic(
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# This is the default and can be omitted
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api_key=os.environ.get("ANTHROPIC_API_KEY"),
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)
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message = client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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)
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print(message.content)
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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 `ANTHROPIC_API_KEY="my-anthropic-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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## Async usage
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Simply import `AsyncAnthropic` instead of `Anthropic` 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 anthropic import AsyncAnthropic
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client = AsyncAnthropic(
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# This is the default and can be omitted
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api_key=os.environ.get("ANTHROPIC_API_KEY"),
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)
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async def main() -> None:
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message = await client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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)
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print(message.content)
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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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## Streaming Responses
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We provide support for streaming responses using Server Side Events (SSE).
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```python
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from anthropic import Anthropic
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client = Anthropic()
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stream = client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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stream=True,
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)
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for event in stream:
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print(event.type)
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```
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The async client uses the exact same interface.
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```python
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from anthropic import Anthropic
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client = Anthropic()
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stream = await client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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stream=True,
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)
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async for event in stream:
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print(event.type)
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```
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### Streaming Helpers
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This library provides several conveniences for streaming messages, for example:
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```py
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import asyncio
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from anthropic import AsyncAnthropic
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client = AsyncAnthropic()
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async def main() -> None:
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async with client.messages.stream(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Say hello there!",
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}
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],
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model="claude-3-opus-20240229",
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) as stream:
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async for text in stream.text_stream:
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print(text, end="", flush=True)
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print()
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message = await stream.get_final_message()
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print(message.model_dump_json(indent=2))
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asyncio.run(main())
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```
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Streaming with `client.messages.stream(...)` exposes [various helpers for your convenience](helpers.md) including event handlers and accumulation.
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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).
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## AWS Bedrock
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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]`.
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You can then import and instantiate a separate `AnthropicBedrock` class, the rest of the API is the same.
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```py
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from anthropic import AnthropicBedrock
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client = AnthropicBedrock()
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message = client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello!",
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}
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],
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model="anthropic.claude-3-sonnet-20240229-v1:0",
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)
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print(message)
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```
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For a more fully fledged example see [`examples/bedrock.py`](https://github.com/anthropics/anthropic-sdk-python/blob/main/examples/bedrock.py).
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## Token counting
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You can see the exact usage for a given request through the `usage` response property, e.g.
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```py
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message = client.messages.create(...)
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message.usage
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# Usage(input_tokens=25, output_tokens=13)
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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 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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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 `anthropic.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 `anthropic.APIStatusError` is raised, containing `status_code` and `response` properties.
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All errors inherit from `anthropic.APIError`.
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```python
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import anthropic
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from anthropic import Anthropic
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client = Anthropic()
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try:
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client.messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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)
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except anthropic.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 anthropic.RateLimitError as e:
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print("A 429 status code was received; we should back off a bit.")
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except anthropic.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 followed:
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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 anthropic import Anthropic
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# Configure the default for all requests:
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client = Anthropic(
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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).messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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)
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```
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### Timeouts
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By default requests time out after 10 minutes. 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/#fine-tuning-the-configuration) object:
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```python
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from anthropic import Anthropic
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# Configure the default for all requests:
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client = Anthropic(
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# 20 seconds (default is 10 minutes)
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timeout=20.0,
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)
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# More granular control:
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client = Anthropic(
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timeout=httpx.Timeout(60.0, read=5.0, write=10.0, connect=2.0),
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)
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# Override per-request:
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client.with_options(timeout=5 * 1000).messages.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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)
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```
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On timeout, an `APITimeoutError` is thrown.
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Note that requests that time out are [retried twice by default](#retries).
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## Default Headers
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We automatically send the `anthropic-version` header set to `2023-06-01`.
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If you need to, you can override it by setting default headers per-request or on the client object.
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Be aware that doing so may result in incorrect types and other unexpected or undefined behavior in the SDK.
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```python
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from anthropic import Anthropic
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client = Anthropic(
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default_headers={"anthropic-version": "My-Custom-Value"},
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)
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```
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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 `ANTHROPIC_LOG` to `debug`.
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```shell
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$ export ANTHROPIC_LOG=debug
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```
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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 is None:
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if 'my_field' not in 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 anthropic import Anthropic
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client = Anthropic()
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response = client.messages.with_raw_response.create(
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max_tokens=1024,
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messages=[{
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"role": "user",
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"content": "Hello, Claude",
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}],
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model="claude-3-opus-20240229",
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)
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print(response.headers.get('X-My-Header'))
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message = response.parse() # get the object that `messages.create()` would have returned
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print(message.content)
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```
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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.
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For the sync client this will mostly be the same with the exception
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of `content` & `text` will be methods instead of properties. In the
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async client, all methods will be async.
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A migration script will be provided & the migration in general should
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be smooth.
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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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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.
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```python
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with client.messages.with_streaming_response.create(
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max_tokens=1024,
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messages=[
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{
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"role": "user",
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"content": "Hello, Claude",
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}
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],
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model="claude-3-opus-20240229",
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) 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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### Configuring the HTTP client
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You can directly override the [httpx client](https://www.python-httpx.org/api/#client) to customize it for your use case, including:
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- Support for proxies
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- Custom transports
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- Additional [advanced](https://www.python-httpx.org/advanced/#client-instances) functionality
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```python
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import httpx
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from anthropic import Anthropic
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client = Anthropic(
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# Or use the `ANTHROPIC_BASE_URL` env var
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base_url="http://my.test.server.example.com:8083",
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http_client=httpx.Client(
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proxies="http://my.test.proxy.example.com",
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transport=httpx.HTTPTransport(local_address="0.0.0.0"),
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),
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)
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```
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### Managing HTTP resources
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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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## 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/anthropics/anthropic-sdk-python/issues) with questions, bugs, or suggestions.
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## Requirements
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Python 3.7 or higher.
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