mirror of
https://github.com/xtekky/gpt4free.git
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86 lines
3.4 KiB
Python
86 lines
3.4 KiB
Python
from __future__ import annotations
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import base64
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import json
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from aiohttp import ClientSession
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from ..typing import AsyncResult, Messages, ImageType
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..image import to_bytes, is_accepted_format
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class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://ai.google.dev"
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working = True
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supports_message_history = True
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default_model = "gemini-pro"
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models = ["gemini-pro", "gemini-pro-vision"]
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@classmethod
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async def create_async_generator(
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cls,
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model: str,
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messages: Messages,
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stream: bool = False,
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proxy: str = None,
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api_key: str = None,
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image: ImageType = None,
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**kwargs
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) -> AsyncResult:
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model = "gemini-pro-vision" if not model and image else model
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model = cls.get_model(model)
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api_key = api_key if api_key else kwargs.get("access_token")
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headers = {
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"Content-Type": "application/json",
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}
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async with ClientSession(headers=headers) as session:
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method = "streamGenerateContent" if stream else "generateContent"
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url = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:{method}"
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contents = [
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{
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"role": "model" if message["role"] == "assistant" else message["role"],
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"parts": [{"text": message["content"]}]
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}
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for message in messages
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]
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if image:
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image = to_bytes(image)
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contents[-1]["parts"].append({
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"inline_data": {
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"mime_type": is_accepted_format(image),
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"data": base64.b64encode(image).decode()
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}
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})
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data = {
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"contents": contents,
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# "generationConfig": {
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# "stopSequences": kwargs.get("stop"),
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# "temperature": kwargs.get("temperature"),
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# "maxOutputTokens": kwargs.get("max_tokens"),
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# "topP": kwargs.get("top_p"),
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# "topK": kwargs.get("top_k"),
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# }
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}
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async with session.post(url, params={"key": api_key}, json=data, proxy=proxy) as response:
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if not response.ok:
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data = await response.json()
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raise RuntimeError(data[0]["error"]["message"])
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if stream:
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lines = []
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async for chunk in response.content:
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if chunk == b"[{\n":
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lines = [b"{\n"]
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elif chunk == b",\r\n" or chunk == b"]":
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try:
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data = b"".join(lines)
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data = json.loads(data)
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yield data["candidates"][0]["content"]["parts"][0]["text"]
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except:
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data = data.decode() if isinstance(data, bytes) else data
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raise RuntimeError(f"Read text failed. data: {data}")
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lines = []
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else:
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lines.append(chunk)
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else:
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data = await response.json()
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yield data["candidates"][0]["content"]["parts"][0]["text"] |