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376 | @dataclass(init=False)
class GroqModel(Model):
"""A model that uses the Groq API.
Internally, this uses the [Groq Python client](https://github.com/groq/groq-python) to interact with the API.
Apart from `__init__`, all methods are private or match those of the base class.
"""
client: AsyncGroq = field(repr=False)
_model_name: GroqModelName = field(repr=False)
_system: str = field(default='groq', repr=False)
@overload
def __init__(
self,
model_name: GroqModelName,
*,
provider: Literal['groq'] | Provider[AsyncGroq] = 'groq',
) -> None: ...
@deprecated('Use the `provider` parameter instead of `api_key`, `groq_client`, and `http_client`.')
@overload
def __init__(
self,
model_name: GroqModelName,
*,
provider: None = None,
api_key: str | None = None,
groq_client: AsyncGroq | None = None,
http_client: AsyncHTTPClient | None = None,
) -> None: ...
def __init__(
self,
model_name: GroqModelName,
*,
provider: Literal['groq'] | Provider[AsyncGroq] | None = None,
api_key: str | None = None,
groq_client: AsyncGroq | None = None,
http_client: AsyncHTTPClient | None = None,
):
"""Initialize a Groq model.
Args:
model_name: The name of the Groq model to use. List of model names available
[here](https://console.groq.com/docs/models).
provider: The provider to use for authentication and API access. Can be either the string
'groq' or an instance of `Provider[AsyncGroq]`. If not provided, a new provider will be
created using the other parameters.
api_key: The API key to use for authentication, if not provided, the `GROQ_API_KEY` environment variable
will be used if available.
groq_client: An existing
[`AsyncGroq`](https://github.com/groq/groq-python?tab=readme-ov-file#async-usage)
client to use, if provided, `api_key` and `http_client` must be `None`.
http_client: An existing `httpx.AsyncClient` to use for making HTTP requests.
"""
self._model_name = model_name
if provider is not None:
if isinstance(provider, str):
provider = infer_provider(provider)
self.client = provider.client
elif groq_client is not None:
assert http_client is None, 'Cannot provide both `groq_client` and `http_client`'
assert api_key is None, 'Cannot provide both `groq_client` and `api_key`'
self.client = groq_client
elif http_client is not None:
self.client = AsyncGroq(api_key=api_key, http_client=http_client)
else:
self.client = AsyncGroq(api_key=api_key, http_client=cached_async_http_client())
@property
def base_url(self) -> str:
return str(self.client.base_url)
async def request(
self,
messages: list[ModelMessage],
model_settings: ModelSettings | None,
model_request_parameters: ModelRequestParameters,
) -> tuple[ModelResponse, usage.Usage]:
check_allow_model_requests()
response = await self._completions_create(
messages, False, cast(GroqModelSettings, model_settings or {}), model_request_parameters
)
return self._process_response(response), _map_usage(response)
@asynccontextmanager
async def request_stream(
self,
messages: list[ModelMessage],
model_settings: ModelSettings | None,
model_request_parameters: ModelRequestParameters,
) -> AsyncIterator[StreamedResponse]:
check_allow_model_requests()
response = await self._completions_create(
messages, True, cast(GroqModelSettings, model_settings or {}), model_request_parameters
)
async with response:
yield await self._process_streamed_response(response)
@property
def model_name(self) -> GroqModelName:
"""The model name."""
return self._model_name
@property
def system(self) -> str:
"""The system / model provider."""
return self._system
@overload
async def _completions_create(
self,
messages: list[ModelMessage],
stream: Literal[True],
model_settings: GroqModelSettings,
model_request_parameters: ModelRequestParameters,
) -> AsyncStream[chat.ChatCompletionChunk]:
pass
@overload
async def _completions_create(
self,
messages: list[ModelMessage],
stream: Literal[False],
model_settings: GroqModelSettings,
model_request_parameters: ModelRequestParameters,
) -> chat.ChatCompletion:
pass
async def _completions_create(
self,
messages: list[ModelMessage],
stream: bool,
model_settings: GroqModelSettings,
model_request_parameters: ModelRequestParameters,
) -> chat.ChatCompletion | AsyncStream[chat.ChatCompletionChunk]:
tools = self._get_tools(model_request_parameters)
# standalone function to make it easier to override
if not tools:
tool_choice: Literal['none', 'required', 'auto'] | None = None
elif not model_request_parameters.allow_text_result:
tool_choice = 'required'
else:
tool_choice = 'auto'
groq_messages = list(chain(*(self._map_message(m) for m in messages)))
try:
return await self.client.chat.completions.create(
model=str(self._model_name),
messages=groq_messages,
n=1,
parallel_tool_calls=model_settings.get('parallel_tool_calls', NOT_GIVEN),
tools=tools or NOT_GIVEN,
tool_choice=tool_choice or NOT_GIVEN,
stream=stream,
max_tokens=model_settings.get('max_tokens', NOT_GIVEN),
temperature=model_settings.get('temperature', NOT_GIVEN),
top_p=model_settings.get('top_p', NOT_GIVEN),
timeout=model_settings.get('timeout', NOT_GIVEN),
seed=model_settings.get('seed', NOT_GIVEN),
presence_penalty=model_settings.get('presence_penalty', NOT_GIVEN),
frequency_penalty=model_settings.get('frequency_penalty', NOT_GIVEN),
logit_bias=model_settings.get('logit_bias', NOT_GIVEN),
)
except APIStatusError as e:
if (status_code := e.status_code) >= 400:
raise ModelHTTPError(status_code=status_code, model_name=self.model_name, body=e.body) from e
raise
def _process_response(self, response: chat.ChatCompletion) -> ModelResponse:
"""Process a non-streamed response, and prepare a message to return."""
timestamp = datetime.fromtimestamp(response.created, tz=timezone.utc)
choice = response.choices[0]
items: list[ModelResponsePart] = []
if choice.message.content is not None:
items.append(TextPart(content=choice.message.content))
if choice.message.tool_calls is not None:
for c in choice.message.tool_calls:
items.append(ToolCallPart(tool_name=c.function.name, args=c.function.arguments, tool_call_id=c.id))
return ModelResponse(items, model_name=response.model, timestamp=timestamp)
async def _process_streamed_response(self, response: AsyncStream[chat.ChatCompletionChunk]) -> GroqStreamedResponse:
"""Process a streamed response, and prepare a streaming response to return."""
peekable_response = _utils.PeekableAsyncStream(response)
first_chunk = await peekable_response.peek()
if isinstance(first_chunk, _utils.Unset):
raise UnexpectedModelBehavior('Streamed response ended without content or tool calls')
return GroqStreamedResponse(
_response=peekable_response,
_model_name=self._model_name,
_timestamp=datetime.fromtimestamp(first_chunk.created, tz=timezone.utc),
)
def _get_tools(self, model_request_parameters: ModelRequestParameters) -> list[chat.ChatCompletionToolParam]:
tools = [self._map_tool_definition(r) for r in model_request_parameters.function_tools]
if model_request_parameters.result_tools:
tools += [self._map_tool_definition(r) for r in model_request_parameters.result_tools]
return tools
def _map_message(self, message: ModelMessage) -> Iterable[chat.ChatCompletionMessageParam]:
"""Just maps a `pydantic_ai.Message` to a `groq.types.ChatCompletionMessageParam`."""
if isinstance(message, ModelRequest):
yield from self._map_user_message(message)
elif isinstance(message, ModelResponse):
texts: list[str] = []
tool_calls: list[chat.ChatCompletionMessageToolCallParam] = []
for item in message.parts:
if isinstance(item, TextPart):
texts.append(item.content)
elif isinstance(item, ToolCallPart):
tool_calls.append(self._map_tool_call(item))
else:
assert_never(item)
message_param = chat.ChatCompletionAssistantMessageParam(role='assistant')
if texts:
# Note: model responses from this model should only have one text item, so the following
# shouldn't merge multiple texts into one unless you switch models between runs:
message_param['content'] = '\n\n'.join(texts)
if tool_calls:
message_param['tool_calls'] = tool_calls
yield message_param
else:
assert_never(message)
@staticmethod
def _map_tool_call(t: ToolCallPart) -> chat.ChatCompletionMessageToolCallParam:
return chat.ChatCompletionMessageToolCallParam(
id=_guard_tool_call_id(t=t, model_source='Groq'),
type='function',
function={'name': t.tool_name, 'arguments': t.args_as_json_str()},
)
@staticmethod
def _map_tool_definition(f: ToolDefinition) -> chat.ChatCompletionToolParam:
return {
'type': 'function',
'function': {
'name': f.name,
'description': f.description,
'parameters': f.parameters_json_schema,
},
}
@classmethod
def _map_user_message(cls, message: ModelRequest) -> Iterable[chat.ChatCompletionMessageParam]:
for part in message.parts:
if isinstance(part, SystemPromptPart):
yield chat.ChatCompletionSystemMessageParam(role='system', content=part.content)
elif isinstance(part, UserPromptPart):
yield cls._map_user_prompt(part)
elif isinstance(part, ToolReturnPart):
yield chat.ChatCompletionToolMessageParam(
role='tool',
tool_call_id=_guard_tool_call_id(t=part, model_source='Groq'),
content=part.model_response_str(),
)
elif isinstance(part, RetryPromptPart):
if part.tool_name is None:
yield chat.ChatCompletionUserMessageParam(role='user', content=part.model_response())
else:
yield chat.ChatCompletionToolMessageParam(
role='tool',
tool_call_id=_guard_tool_call_id(t=part, model_source='Groq'),
content=part.model_response(),
)
@staticmethod
def _map_user_prompt(part: UserPromptPart) -> chat.ChatCompletionUserMessageParam:
content: str | list[chat.ChatCompletionContentPartParam]
if isinstance(part.content, str):
content = part.content
else:
content = []
for item in part.content:
if isinstance(item, str):
content.append(chat.ChatCompletionContentPartTextParam(text=item, type='text'))
elif isinstance(item, ImageUrl):
image_url = ImageURL(url=item.url)
content.append(chat.ChatCompletionContentPartImageParam(image_url=image_url, type='image_url'))
elif isinstance(item, BinaryContent):
base64_encoded = base64.b64encode(item.data).decode('utf-8')
if item.is_image:
image_url = ImageURL(url=f'data:{item.media_type};base64,{base64_encoded}')
content.append(chat.ChatCompletionContentPartImageParam(image_url=image_url, type='image_url'))
else:
raise RuntimeError('Only images are supported for binary content in Groq.')
elif isinstance(item, DocumentUrl): # pragma: no cover
raise RuntimeError('DocumentUrl is not supported in Groq.')
else: # pragma: no cover
raise RuntimeError(f'Unsupported content type: {type(item)}')
return chat.ChatCompletionUserMessageParam(role='user', content=content)
|