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Got multi-tool OpenAI chat working, in no-stream mode too

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Refs #1017, #1019
This commit is contained in:
Simon Willison 2025-05-13 12:18:26 -07:00
parent 5ae20bd549
commit 88b806ae1a
4 changed files with 387 additions and 6 deletions
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3
docs/plugins/advanced-model-plugins.md
View file

@ -81,7 +81,8 @@ class MyAsyncModel(llm.AsyncModel):
messages=messages,
stream=False,
)
yield completion.choices[0].message.content
if completion.choices[0].message.content is not None:
yield completion.choices[0].message.content
```
If your model takes an API key you should instead subclass `llm.AsyncKeyModel` and have a `key=` parameter on your `.execute()` method:

28
llm/default_plugins/openai_models.py
View file

@ -524,9 +524,17 @@ class _Shared:
messages.append(
{"role": "user", "content": prev_response.prompt.prompt}
)
messages.append(
{"role": "assistant", "content": prev_response.text_or_raise()}
)
for tool_result in prev_response.prompt.tool_results:
messages.append(
{
"role": "tool",
"tool_call_id": tool_result.tool_call_id,
"content": tool_result.output,
}
)
prev_text = prev_response.text_or_raise()
if prev_text:
messages.append({"role": "assistant", "content": prev_text})
tool_calls = prev_response.tool_calls_or_raise()
if tool_calls:
messages.append(
@ -697,7 +705,16 @@ class Chat(_Shared, KeyModel):
)
usage = completion.usage.model_dump()
response.response_json = remove_dict_none_values(completion.model_dump())
yield completion.choices[0].message.content
for tool_call in completion.choices[0].message.tool_calls or []:
response.add_tool_call(
llm.ToolCall(
tool_call_id=tool_call.id,
name=tool_call.function.name,
arguments=json.loads(tool_call.function.arguments),
)
)
if completion.choices[0].message.content is not None:
yield completion.choices[0].message.content
self.set_usage(response, usage)
response._prompt_json = redact_data({"messages": messages})
@ -750,7 +767,8 @@ class AsyncChat(_Shared, AsyncKeyModel):
)
response.response_json = remove_dict_none_values(completion.model_dump())
usage = completion.usage.model_dump()
yield completion.choices[0].message.content
if completion.choices[0].message.content is not None:
yield completion.choices[0].message.content
self.set_usage(response, usage)
response._prompt_json = redact_data({"messages": messages})

330
tests/cassettes/test_tools/test_tool_use_chain_of_two_calls.yaml Normal file
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@ -0,0 +1,330 @@
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32
tests/test_tools.py
View file

@ -60,3 +60,35 @@ def test_tool_use_basic(vcr):
assert tool_results[0]["response_id"] == second_response["id"]
assert tool_results[0]["output"] == "2869461"
assert tool_results[0]["tool_call_id"] == tool_calls[0]["tool_call_id"]
@pytest.mark.vcr
def test_tool_use_chain_of_two_calls(vcr):
model = llm.get_model("gpt-4o-mini")
def lookup_population(country: str) -> int:
"Returns the current population of the specified fictional country"
return 123124
def can_have_dragons(population: int) -> bool:
"Returns True if the specified population can have dragons, False otherwise"
return population > 10000
chain_response = model.chain(
"Can the country of Crumpet have dragons? Answer with only YES or NO",
tools=[lookup_population, can_have_dragons],
stream=False,
key=API_KEY,
)
output = chain_response.text()
assert output == "YES"
assert len(chain_response._responses) == 3
first, second, third = chain_response._responses
assert first.tool_calls()[0].arguments == {"country": "Crumpet"}
assert first.prompt.tool_results == []
assert second.prompt.tool_results[0].output == "123124"
assert second.tool_calls()[0].arguments == {"population": 123124}
assert third.prompt.tool_results[0].output == "true"
assert third.tool_calls() == []