mirror of
https://github.com/EvolutionAPI/adk-python.git
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88 lines
2.6 KiB
Python
88 lines
2.6 KiB
Python
# Copyright 2025 Google LLC
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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from __future__ import annotations
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from abc import abstractmethod
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from typing import AsyncGenerator
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from typing import TYPE_CHECKING
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from pydantic import BaseModel
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from pydantic import ConfigDict
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from .base_llm_connection import BaseLlmConnection
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if TYPE_CHECKING:
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from .llm_request import LlmRequest
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from .llm_response import LlmResponse
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class BaseLlm(BaseModel):
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"""The BaseLLM class.
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Attributes:
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model: The name of the LLM, e.g. gemini-1.5-flash or gemini-1.5-flash-001.
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model_config: The model config
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"""
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model_config = ConfigDict(
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# This allows us to use arbitrary types in the model. E.g. PIL.Image.
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arbitrary_types_allowed=True,
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)
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"""The model config."""
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model: str
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"""The name of the LLM, e.g. gemini-1.5-flash or gemini-1.5-flash-001."""
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@classmethod
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def supported_models(cls) -> list[str]:
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"""Returns a list of supported models in regex for LlmRegistry."""
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return []
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@abstractmethod
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async def generate_content_async(
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self, llm_request: LlmRequest, stream: bool = False
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) -> AsyncGenerator[LlmResponse, None]:
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"""Generates one content from the given contents and tools.
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Args:
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llm_request: LlmRequest, the request to send to the LLM.
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stream: bool = False, whether to do streaming call.
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Yields:
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a generator of types.Content.
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For non-streaming call, it will only yield one Content.
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For streaming call, it may yield more than one content, but all yielded
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contents should be treated as one content by merging the
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parts list.
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"""
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raise NotImplementedError(
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f'Async generation is not supported for {self.model}.'
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)
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yield # AsyncGenerator requires a yield statement in function body.
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def connect(self, llm_request: LlmRequest) -> BaseLlmConnection:
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"""Creates a live connection to the LLM.
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Args:
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llm_request: LlmRequest, the request to send to the LLM.
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Returns:
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BaseLlmConnection, the connection to the LLM.
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"""
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raise NotImplementedError(
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f'Live connection is not supported for {self.model}.'
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)
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