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release: 1.14.2 (openai#1244)
* perf: cache TypeAdapters (openai#1114) * perf: cache TypeAdapters (openai#1243) * docs: fix typo in CONTRIBUTING.md (openai#1245) * chore(internal): update generated pragma comment (openai#1247) * docs: assistant improvements (openai#1249) * release: 1.14.2 --------- Co-authored-by: vvanglro <[email protected]>
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Diff for: ‎.release-please-manifest.json

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{
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".": "1.14.1"
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".": "1.14.2"
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}

Diff for: ‎CHANGELOG.md

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# Changelog
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## 1.14.2 (2024-03-19)
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Full Changelog: [v1.14.1...v1.14.2](https://github.com/openai/openai-python/compare/v1.14.1...v1.14.2)
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### Performance Improvements
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* cache TypeAdapters ([#1114](https://github.com/openai/openai-python/issues/1114)) ([41b6fee](https://github.com/openai/openai-python/commit/41b6feec70d3f203e36ba9a92205389bafce930c))
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* cache TypeAdapters ([#1243](https://github.com/openai/openai-python/issues/1243)) ([2005076](https://github.com/openai/openai-python/commit/2005076f500bef6e0a6cc8f935b9cc9fef65ab5b))
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### Chores
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* **internal:** update generated pragma comment ([#1247](https://github.com/openai/openai-python/issues/1247)) ([3eeb9b3](https://github.com/openai/openai-python/commit/3eeb9b3a71e01c2593be443a97a353371466d01a))
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### Documentation
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* assistant improvements ([#1249](https://github.com/openai/openai-python/issues/1249)) ([e7a3176](https://github.com/openai/openai-python/commit/e7a3176b7606822bd5ad8f7fece87de6aad1e5b6))
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* fix typo in CONTRIBUTING.md ([#1245](https://github.com/openai/openai-python/issues/1245)) ([adef57a](https://github.com/openai/openai-python/commit/adef57ae5c71734873ba49bccd92fa7f28068d28))
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## 1.14.1 (2024-03-15)
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Full Changelog: [v1.14.0...v1.14.1](https://github.com/openai/openai-python/compare/v1.14.0...v1.14.1)

Diff for: ‎CONTRIBUTING.md

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```bash
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# you will need npm installed
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npx prism path/to/your/openapi.yml
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npx prism mock path/to/your/openapi.yml
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```
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```bash

Diff for: ‎README.md

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to add `OPENAI_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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### Streaming Helpers
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The SDK also includes helpers to process streams and handle the incoming events.
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```python
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with client.beta.threads.runs.create_and_stream(
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thread_id=thread.id,
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assistant_id=assistant.id,
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instructions="Please address the user as Jane Doe. The user has a premium account.",
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) as stream:
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for event in stream:
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# Print the text from text delta events
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if event.type == "thread.message.delta" and event.data.delta.content:
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print(event.data.delta.content[0].text)
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```
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More information on streaming helpers can be found in the dedicated documentation: [helpers.md](helpers.md)
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## Async usage
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Simply import `AsyncOpenAI` instead of `OpenAI` and use `await` with each API call:

Diff for: ‎helpers.md

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```python
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from typing_extensions import override
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from openai import AssistantEventHandler
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from openai import AssistantEventHandler, OpenAI
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from openai.types.beta.threads import Text, TextDelta
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from openai.types.beta.threads.runs import ToolCall, ToolCallDelta
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client = openai.OpenAI()
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# First, we create a EventHandler class to define
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# how we want to handle the events in the response stream.
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class EventHandler(AssistantEventHandler):
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@override
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def on_text_created(self, text) -> None:
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def on_text_created(self, text: Text) -> None:
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print(f"\nassistant > ", end="", flush=True)
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@override
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def on_text_delta(self, delta, snapshot):
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def on_text_delta(self, delta: TextDelta, snapshot: Text):
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print(delta.value, end="", flush=True)
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def on_tool_call_created(self, tool_call):
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def on_tool_call_created(self, tool_call: ToolCall):
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print(f"\nassistant > {tool_call.type}\n", flush=True)
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def on_tool_call_delta(self, delta, snapshot):
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def on_tool_call_delta(self, delta: ToolCallDelta, snapshot: ToolCall):
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assistant_id=assistant.id,
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instructions="Please address the user as Jane Doe. The user has a premium account.",
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thread_id="thread_id",
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assistant_id="assistant_id",
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event_handler=EventHandler(),
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) as stream:
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stream.until_done()
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```
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#### An example of iterating over events
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You can also iterate over all the streamed events.
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```python
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with client.beta.threads.runs.create_and_stream(
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thread_id=thread.id,
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assistant_id=assistant.id
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) as stream:
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for event in stream:
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# Print the text from text delta events
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if event.type == "thread.message.delta" and event.data.delta.content:
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print(event.data.delta.content[0].text)
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```
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#### An example of iterating over text
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You can also iterate over just the text deltas received
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```python
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with client.beta.threads.runs.create_and_stream(
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thread_id=thread.id,
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assistant_id=assistant.id
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) as stream:
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for text in stream.text_deltas:
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print(text)
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```
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### Creating Streams
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There are three helper methods for creating streams:
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```python
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client.beta.threads.runs.create_and_stream()
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```
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This method can be used to start and stream the response to an existing run with an associated thread
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that is already populated with messages.
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```python
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client.beta.threads.create_and_run_stream()
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```
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This method can be used to add a message to a thread, start a run and then stream the response.
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```python
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client.beta.threads.runs.submit_tool_outputs_stream()
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```
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This method can be used to submit a tool output to a run waiting on the output and start a stream.
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### Assistant Events
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The assistant streaming object also provides a few methods for convenience:
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def current_run_step_snapshot()
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def current_event() -> AssistantStreamEvent | None
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def current_run() -> Run | None
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def current_message_snapshot() -> Message | None
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def current_run_step_snapshot() -> RunStep | None
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```
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These methods are provided to allow you to access additional context from within event handlers. In many cases
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the handlers should include all the information you need for processing, but if additional context is required it
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Note: There is not always a relevant context in certain situations (these will be `None` in those cases).
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```python
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def get_final_run(self)
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def get_final_messages(self)
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def get_final_run(self) -> Run
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def get_final_run_steps(self) -> List[RunStep]
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def get_final_messages(self) -> List[Message]
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```
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These methods are provided for convenience to collect information at the end of a stream. Calling these events

Diff for: ‎pyproject.toml

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[project]
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name = "openai"
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version = "1.14.1"
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version = "1.14.2"
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description = "The official Python library for the openai API"
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readme = "README.md"
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license = "Apache-2.0"

Diff for: ‎src/openai/__init__.py

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# File generated from our OpenAPI spec by Stainless.
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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import httpx
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Diff for: ‎src/openai/_exceptions.py

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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from __future__ import annotations
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Diff for: ‎src/openai/_models.py

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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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Diff for: ‎src/openai/_version.py

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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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__title__ = "openai"
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__version__ = "1.14.2" # x-release-please-version

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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from typing import Any, List, Generic, TypeVar, Optional, cast
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# File generated from our OpenAPI spec by Stainless. See CONTRIBUTING.md for details.
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from .audio import (
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Diff for: ‎src/openai/resources/audio/audio.py

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Diff for: ‎src/openai/resources/chat/__init__.py

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from .chat import (
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