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Transform and to text parts for Google models that don't support tools #3591

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d5d85c2
Transform and to text parts for Google models that don't support to…
sidg1215 Nov 28, 2025
aa07602
Added more testing.
sidg1215 Dec 4, 2025
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62 changes: 41 additions & 21 deletions pydantic_ai_slim/pydantic_ai/models/google.py
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Original file line number Diff line number Diff line change
Expand Up @@ -549,15 +549,25 @@ async def _map_messages(
elif isinstance(part, UserPromptPart):
message_parts.extend(await self._map_user_prompt(part))
elif isinstance(part, ToolReturnPart):
message_parts.append(
{
'function_response': {
'name': part.tool_name,
'response': part.model_response_object(),
'id': part.tool_call_id,
if self.profile.supports_tools:
message_parts.append(
{
'function_response': {
'name': part.tool_name,
'response': part.model_response_object(),
'id': part.tool_call_id,
}
}
}
)
)
else:
text = '\n'.join(
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@DouweM DouweM Dec 9, 2025

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Let's move this to an as_text() method on ToolCallPart and explain in the docstring what it's for. In case we want to someday do this in other models as well. Same for ToolReturnPart

[
f'-----BEGIN TOOL RETURN name="{part.tool_name}" id="{part.tool_call_id}"-----',
f'response: {part.model_response_object()}',
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Let's just use part.model_response_str() without the response: prefix

f'-----END TOOL RETURN id="{part.tool_call_id}"-----',
]
)
message_parts.append({'text': text})
elif isinstance(part, RetryPromptPart):
if part.tool_name is None:
message_parts.append({'text': part.model_response()})
Expand All @@ -577,7 +587,7 @@ async def _map_messages(
if message_parts:
contents.append({'role': 'user', 'parts': message_parts})
elif isinstance(m, ModelResponse):
maybe_content = _content_model_response(m, self.system)
maybe_content = _content_model_response(m, self.system, self.profile.supports_tools)
if maybe_content:
contents.append(maybe_content)
else:
Expand Down Expand Up @@ -786,7 +796,7 @@ def timestamp(self) -> datetime:
return self._timestamp


def _content_model_response(m: ModelResponse, provider_name: str) -> ContentDict | None: # noqa: C901
def _content_model_response(m: ModelResponse, provider_name: str, supports_tools: bool) -> ContentDict | None: # noqa: C901
parts: list[PartDict] = []
thinking_part_signature: str | None = None
function_call_requires_signature: bool = True
Expand All @@ -803,17 +813,27 @@ def _content_model_response(m: ModelResponse, provider_name: str) -> ContentDict
thinking_part_signature = None

if isinstance(item, ToolCallPart):
function_call = FunctionCallDict(name=item.tool_name, args=item.args_as_dict(), id=item.tool_call_id)
part['function_call'] = function_call
if function_call_requires_signature and not part.get('thought_signature'):
# Per https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high#migrating_from_other_models:
# > If you are transferring a conversation trace from another model (e.g., Gemini 2.5) or injecting
# > a custom function call that was not generated by Gemini 3, you will not have a valid signature.
# > To bypass strict validation in these specific scenarios, populate the field with this specific
# > dummy string: "thoughtSignature": "context_engineering_is_the_way_to_go"
part['thought_signature'] = b'context_engineering_is_the_way_to_go'
# Only the first function call requires a signature
function_call_requires_signature = False
if supports_tools:
function_call = FunctionCallDict(name=item.tool_name, args=item.args_as_dict(), id=item.tool_call_id)
part['function_call'] = function_call
if function_call_requires_signature and not part.get('thought_signature'):
# Per https://ai.google.dev/gemini-api/docs/gemini-3?thinking=high#migrating_from_other_models:
# > If you are transferring a conversation trace from another model (e.g., Gemini 2.5) or injecting
# > a custom function call that was not generated by Gemini 3, you will not have a valid signature.
# > To bypass strict validation in these specific scenarios, populate the field with this specific
# > dummy string: "thoughtSignature": "context_engineering_is_the_way_to_go"
part['thought_signature'] = b'context_engineering_is_the_way_to_go'
# Only the first function call requires a signature
function_call_requires_signature = False
else:
text = '\n'.join(
[
f'-----BEGIN TOOL CALL name="{item.tool_name} "id="{item.tool_call_id}""-----',
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@DouweM DouweM Dec 9, 2025

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We've got a few too many quotes here

f'args: {item.args_as_json_str()}',
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@DouweM DouweM Dec 9, 2025

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We can drop the args: prefix

f'-----END TOOL CALL id="{item.tool_call_id}"-----',
]
)
part['text'] = text
elif isinstance(item, TextPart):
part['text'] = item.content
elif isinstance(item, ThinkingPart):
Expand Down
111 changes: 111 additions & 0 deletions tests/models/test_google.py
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Original file line number Diff line number Diff line change
Expand Up @@ -4307,6 +4307,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
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@DouweM DouweM Dec 9, 2025

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Let's default the arg to True so we don't have to pass it here

)
new_google_response = _content_model_response(
ModelResponse(
Expand All @@ -4318,6 +4319,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
)
assert old_google_response == snapshot(
{
Expand All @@ -4342,6 +4344,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
)
new_google_response = _content_model_response(
ModelResponse(
Expand All @@ -4352,6 +4355,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
)
assert old_google_response == snapshot(
{
Expand All @@ -4376,6 +4380,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
)
new_google_response = _content_model_response(
ModelResponse(
Expand All @@ -4386,6 +4391,7 @@ def test_google_thought_signature_on_thinking_part():
provider_name='google-gla',
),
'google-gla',
True,
)
assert old_google_response == snapshot(
{
Expand All @@ -4412,6 +4418,7 @@ def test_google_missing_tool_call_thought_signature():
provider_name='openai',
),
'google-gla',
True,
)
assert google_response == snapshot(
{
Expand All @@ -4425,3 +4432,107 @@ def test_google_missing_tool_call_thought_signature():
],
}
)


async def test_google_mapping_messages_no_tool_support(google_provider: GoogleProvider):
old_messages = [
ModelRequest(
parts=[
UserPromptPart(
content='What is the largest city in the user country?',
timestamp=IsDatetime(),
)
],
run_id=IsStr(),
),
ModelResponse(parts=[ToolCallPart(tool_name='get_user_country', args={}, tool_call_id=IsStr())]),
ModelRequest(
parts=[
ToolReturnPart(
tool_name='get_user_country',
content='Mexico',
tool_call_id=IsStr(),
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Let's use an actual dummy value here that we'll see in the output below, instead of literal IsStr()

timestamp=IsDatetime(),
)
],
run_id=IsStr(),
),
ModelResponse(
parts=[
ToolCallPart(
tool_name='final_result',
args={'city': 'Mexico City', 'country': 'Mexico'},
tool_call_id=IsStr(),
)
],
),
ModelRequest(
parts=[
ToolReturnPart(
tool_name='final_result',
content='Final result processed.',
tool_call_id=IsStr(),
timestamp=IsDatetime(),
)
],
run_id=IsStr(),
),
]
model = GoogleModel('gemini-2.5-flash-image-preview', provider=google_provider)
new_messages = await model._map_messages(old_messages, ModelRequestParameters()) # pyright: ignore[reportPrivateUsage]
assert new_messages == snapshot(
(
None,
[
{'role': 'user', 'parts': [{'text': 'What is the largest city in the user country?'}]},
{
'role': 'model',
'parts': [
{
'text': """\
-----BEGIN TOOL CALL name="get_user_country "id="IsStr()""-----
args: {}
-----END TOOL CALL id="IsStr()"-----\
"""
}
],
},
{
'role': 'user',
'parts': [
{
'text': """\
-----BEGIN TOOL RETURN name="get_user_country" id="IsStr()"-----
response: {'return_value': 'Mexico'}
-----END TOOL RETURN id="IsStr()"-----\
"""
}
],
},
{
'role': 'model',
'parts': [
{
'text': """\
-----BEGIN TOOL CALL name="final_result "id="IsStr()""-----
args: {"city":"Mexico City","country":"Mexico"}
-----END TOOL CALL id="IsStr()"-----\
"""
}
],
},
{
'role': 'user',
'parts': [
{
'text': """\
-----BEGIN TOOL RETURN name="final_result" id="IsStr()"-----
response: {'return_value': 'Final result processed.'}
-----END TOOL RETURN id="IsStr()"-----\
"""
}
],
},
],
)
)