mirror of
https://github.com/xtekky/gpt4free.git
synced 2024-12-25 04:01:52 +03:00
ffb4b0d162
* Improve download of generated images, serve images in the api Add support for conversation handling in the api * Add orginal prompt to image response * Add download images option in gui, fix loading model list in Airforce * Add download images option in gui, fix loading model list in Airforce
138 lines
5.1 KiB
Python
138 lines
5.1 KiB
Python
from __future__ import annotations
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import json
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import asyncio
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from aiohttp import ClientSession, ContentTypeError
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from ..typing import AsyncResult, Messages
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from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
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from ..requests.aiohttp import get_connector
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from ..requests.raise_for_status import raise_for_status
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from .helper import format_prompt
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from ..image import ImageResponse
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class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
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url = "https://replicate.com"
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api_endpoint = "https://homepage.replicate.com/api/prediction"
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working = True
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supports_stream = True
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supports_system_message = True
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supports_message_history = True
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default_model = 'yorickvp/llava-13b'
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image_models = [
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'stability-ai/stable-diffusion-3',
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'bytedance/sdxl-lightning-4step',
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'playgroundai/playground-v2.5-1024px-aesthetic',
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]
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text_models = [
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'meta/meta-llama-3-70b-instruct',
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'mistralai/mixtral-8x7b-instruct-v0.1',
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'google-deepmind/gemma-2b-it',
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'yorickvp/llava-13b',
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]
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models = text_models + image_models
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model_aliases = {
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# image_models
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"sd-3": "stability-ai/stable-diffusion-3",
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"sdxl": "bytedance/sdxl-lightning-4step",
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"playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic",
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# text_models
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"gemma-2b": "google-deepmind/gemma-2b-it",
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"llava-13b": "yorickvp/llava-13b",
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}
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model_versions = {
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# image_models
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'stability-ai/stable-diffusion-3': "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f",
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'bytedance/sdxl-lightning-4step': "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f",
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'playgroundai/playground-v2.5-1024px-aesthetic': "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
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# text_models
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"google-deepmind/gemma-2b-it": "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626",
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"yorickvp/llava-13b": "80537f9eead1a5bfa72d5ac6ea6414379be41d4d4f6679fd776e9535d1eb58bb",
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}
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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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prompt: str = None,
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proxy: str = None,
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**kwargs
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) -> AsyncResult:
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model = cls.get_model(model)
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headers = {
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"accept": "*/*",
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"accept-language": "en-US,en;q=0.9",
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"cache-control": "no-cache",
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"content-type": "application/json",
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"origin": "https://replicate.com",
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"pragma": "no-cache",
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"priority": "u=1, i",
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"referer": "https://replicate.com/",
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"sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
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"sec-ch-ua-mobile": "?0",
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"sec-ch-ua-platform": '"Linux"',
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"sec-fetch-dest": "empty",
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"sec-fetch-mode": "cors",
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"sec-fetch-site": "same-site",
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"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"
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}
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async with ClientSession(headers=headers, connector=get_connector(proxy=proxy)) as session:
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if prompt is None:
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if model in cls.image_models:
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prompt = messages[-1]['content']
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else:
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prompt = format_prompt(messages)
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data = {
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"model": model,
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"version": cls.model_versions[model],
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"input": {"prompt": prompt},
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}
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async with session.post(cls.api_endpoint, json=data) as response:
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await raise_for_status(response)
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result = await response.json()
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prediction_id = result['id']
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poll_url = f"https://homepage.replicate.com/api/poll?id={prediction_id}"
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max_attempts = 30
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delay = 5
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for _ in range(max_attempts):
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async with session.get(poll_url) as response:
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await raise_for_status(response)
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try:
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result = await response.json()
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except ContentTypeError:
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text = await response.text()
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try:
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result = json.loads(text)
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except json.JSONDecodeError:
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raise ValueError(f"Unexpected response format: {text}")
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if result['status'] == 'succeeded':
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if model in cls.image_models:
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image_url = result['output'][0]
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yield ImageResponse(image_url, prompt)
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return
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else:
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for chunk in result['output']:
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yield chunk
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break
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elif result['status'] == 'failed':
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raise Exception(f"Prediction failed: {result.get('error')}")
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await asyncio.sleep(delay)
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if result['status'] != 'succeeded':
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raise Exception("Prediction timed out")
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