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- from __future__ import annotations
- import base64
- import json
- from aiohttp import ClientSession, BaseConnector
- from ...typing import AsyncResult, Messages, ImageType
- from ..base_provider import AsyncGeneratorProvider, ProviderModelMixin
- from ...image import to_bytes, is_accepted_format
- from ...errors import MissingAuthError
- from ..helper import get_connector
- class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
- label = "Gemini API"
- url = "https://ai.google.dev"
- working = True
- supports_message_history = True
- needs_auth = True
- default_model = "gemini-1.5-pro"
- default_vision_model = default_model
- models = [default_model, "gemini-pro", "gemini-1.5-flash", "gemini-1.5-flash-8b"]
- @classmethod
- async def create_async_generator(
- cls,
- model: str,
- messages: Messages,
- stream: bool = False,
- proxy: str = None,
- api_key: str = None,
- api_base: str = "https://generativelanguage.googleapis.com/v1beta",
- use_auth_header: bool = False,
- image: ImageType = None,
- connector: BaseConnector = None,
- **kwargs
- ) -> AsyncResult:
- model = cls.get_model(model)
- if not api_key:
- raise MissingAuthError('Add a "api_key"')
- headers = params = None
- if use_auth_header:
- headers = {"Authorization": f"Bearer {api_key}"}
- else:
- params = {"key": api_key}
- method = "streamGenerateContent" if stream else "generateContent"
- url = f"{api_base.rstrip('/')}/models/{model}:{method}"
- async with ClientSession(headers=headers, connector=get_connector(connector, proxy)) as session:
- contents = [
- {
- "role": "model" if message["role"] == "assistant" else "user",
- "parts": [{"text": message["content"]}]
- }
- for message in messages
- if message["role"] != "system"
- ]
- if image is not None:
- image = to_bytes(image)
- contents[-1]["parts"].append({
- "inline_data": {
- "mime_type": is_accepted_format(image),
- "data": base64.b64encode(image).decode()
- }
- })
- data = {
- "contents": contents,
- "generationConfig": {
- "stopSequences": kwargs.get("stop"),
- "temperature": kwargs.get("temperature"),
- "maxOutputTokens": kwargs.get("max_tokens"),
- "topP": kwargs.get("top_p"),
- "topK": kwargs.get("top_k"),
- }
- }
- system_prompt = "\n".join(
- message["content"]
- for message in messages
- if message["role"] == "system"
- )
- if system_prompt:
- data["system_instruction"] = {"parts": {"text": system_prompt}}
- async with session.post(url, params=params, json=data) as response:
- if not response.ok:
- data = await response.json()
- data = data[0] if isinstance(data, list) else data
- raise RuntimeError(f"Response {response.status}: {data['error']['message']}")
- if stream:
- lines = []
- async for chunk in response.content:
- if chunk == b"[{\n":
- lines = [b"{\n"]
- elif chunk == b",\r\n" or chunk == b"]":
- try:
- data = b"".join(lines)
- data = json.loads(data)
- yield data["candidates"][0]["content"]["parts"][0]["text"]
- except:
- data = data.decode(errors="ignore") if isinstance(data, bytes) else data
- raise RuntimeError(f"Read chunk failed: {data}")
- lines = []
- else:
- lines.append(chunk)
- else:
- data = await response.json()
- candidate = data["candidates"][0]
- if candidate["finishReason"] == "STOP":
- yield candidate["content"]["parts"][0]["text"]
- else:
- yield candidate["finishReason"] + ' ' + candidate["safetyRatings"]
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