litellm is a library that abstracts away details/differences for a lot
of model providers. Adding an extension, so that any provider can easily
be integrated.
---
[//]: # (BEGIN SAPLING FOOTER)
* #532
* __->__ #524
The current ChatCompletion API supports only `parallel_tool_calls=True`
or `parallel_tool_calls=NOT_GIVEN`
This PR is to support setting `parallel_tool_calls=False`, a common
requirement in controlling agent tool use patterns (e.g. ensuring one
tool call at the time, to facilitate desired tool calling sequence).
I followed the merged
[PR#333](https://github.com/openai/openai-agents-python/pull/333) for
consistency.
Allows passing in the previous_response_id to reduce sending the same
data again and again.
Test plan:
Examples. Adding tests in next PR shortly.
---
[//]: # (BEGIN SAPLING FOOTER)
* __->__ #509
* #508
Added the possibility to pass `extra_query` and `extra_body` parameters
when sending a request.
In this implementation I added the attributes to `ModelSettings` as
suggested by @rm-openai in #487 .
I'll be happy to add some tests if you have any suggestions.
fix issue https://github.com/openai/openai-agents-python/issues/442
below is an example to overwrite include_usage
```
result = Runner.run_streamed(
agent,
"Write a haiku about recursion in programming.",
run_config=RunConfig(
model_provider=CUSTOM_MODEL_PROVIDER,
model_settings=ModelSettings(include_usage=True)
),
)
```
- The _Converter.items_to_messages method was incorrectly rejecting 'assistant'
as a valid role in conversation messages, causing runtime errors when processing
standard chat completion message formats.
- This fix enables proper handling of
complete conversation contexts that include both user and assistant messages.
