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from __future__ import annotations |
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import base64 |
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import json |
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from aiohttp import ClientSession, BaseConnector |
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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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from ...errors import MissingAuthError |
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from ..helper import get_connector |
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class GeminiPro(AsyncGeneratorProvider, ProviderModelMixin): |
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label = "Gemini API" |
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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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needs_auth = True |
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default_model = "gemini-1.5-pro" |
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default_vision_model = default_model |
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models = [default_model, "gemini-pro", "gemini-1.5-flash", "gemini-1.5-flash-8b"] |
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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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api_base: str = "https://generativelanguage.googleapis.com/v1beta", |
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use_auth_header: bool = False, |
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image: ImageType = None, |
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connector: BaseConnector = None, |
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**kwargs |
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) -> AsyncResult: |
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model = cls.get_model(model) |
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if not api_key: |
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raise MissingAuthError('Add a "api_key"') |
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headers = params = None |
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if use_auth_header: |
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headers = {"Authorization": f"Bearer {api_key}"} |
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else: |
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params = {"key": api_key} |
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method = "streamGenerateContent" if stream else "generateContent" |
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url = f"{api_base.rstrip('/')}/models/{model}:{method}" |
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async with ClientSession(headers=headers, connector=get_connector(connector, proxy)) as session: |
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contents = [ |
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{ |
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"role": "model" if message["role"] == "assistant" else "user", |
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"parts": [{"text": message["content"]}] |
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} |
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for message in messages |
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if message["role"] != "system" |
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] |
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if image is not None: |
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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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system_prompt = "\n".join( |
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message["content"] |
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for message in messages |
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if message["role"] == "system" |
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) |
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if system_prompt: |
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data["system_instruction"] = {"parts": {"text": system_prompt}} |
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async with session.post(url, params=params, json=data) as response: |
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if not response.ok: |
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data = await response.json() |
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data = data[0] if isinstance(data, list) else data |
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raise RuntimeError(f"Response {response.status}: {data['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(errors="ignore") if isinstance(data, bytes) else data |
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raise RuntimeError(f"Read chunk failed: {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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candidate = data["candidates"][0] |
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if candidate["finishReason"] == "STOP": |
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yield candidate["content"]["parts"][0]["text"] |
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else: |
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yield candidate["finishReason"] + ' ' + candidate["safetyRatings"] |
