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"]