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from __future__ import annotations
import base64
import json
from aiohttp import ClientSession
from ..typing import AsyncResult, Messages, ImageType
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from ..image import to_bytes, is_accepted_format
class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://ai.google.dev"
working = True
supports_message_history = True
default_model = "gemini-pro"
models = ["gemini-pro", "gemini-pro-vision"]
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
stream: bool = False,
proxy: str = None,
api_key: str = None,
image: ImageType = None,
**kwargs
) -> AsyncResult:
model = "gemini-pro-vision" if not model and image else model
model = cls.get_model(model)
api_key = api_key if api_key else kwargs.get("access_token")
headers = {
"Content-Type": "application/json",
}
async with ClientSession(headers=headers) as session:
method = "streamGenerateContent" if stream else "generateContent"
url = f"https://generativelanguage.googleapis.com/v1beta/models/{model}:{method}"
contents = [
{
"role": "model" if message["role"] == "assistant" else message["role"],
"parts": [{"text": message["content"]}]
}
for message in messages
]
if image:
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"),
# }
}
async with session.post(url, params={"key": api_key}, json=data, proxy=proxy) as response:
if not response.ok:
data = await response.json()
raise RuntimeError(data[0]["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() if isinstance(data, bytes) else data
raise RuntimeError(f"Read text failed. data: {data}")
lines = []
else:
lines.append(chunk)
else:
data = await response.json()
yield data["candidates"][0]["content"]["parts"][0]["text"]
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