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from __future__ import annotations
import json
import asyncio
from aiohttp import ClientSession, ContentTypeError
from ..typing import AsyncResult, Messages
from .base_provider import AsyncGeneratorProvider, ProviderModelMixin
from .helper import format_prompt
from ..image import ImageResponse
class ReplicateHome(AsyncGeneratorProvider, ProviderModelMixin):
url = "https://replicate.com"
api_endpoint = "https://homepage.replicate.com/api/prediction"
working = True
supports_stream = True
supports_system_message = True
supports_message_history = True
default_model = 'meta/meta-llama-3-70b-instruct'
text_models = [
'meta/meta-llama-3-70b-instruct',
'mistralai/mixtral-8x7b-instruct-v0.1',
'google-deepmind/gemma-2b-it',
'yorickvp/llava-13b',
]
image_models = [
'black-forest-labs/flux-schnell',
'stability-ai/stable-diffusion-3',
'bytedance/sdxl-lightning-4step',
'playgroundai/playground-v2.5-1024px-aesthetic',
]
models = text_models + image_models
model_aliases = {
"flux-schnell": "black-forest-labs/flux-schnell",
"sd-3": "stability-ai/stable-diffusion-3",
"sdxl": "bytedance/sdxl-lightning-4step",
"playground-v2.5": "playgroundai/playground-v2.5-1024px-aesthetic",
"llama-3-70b": "meta/meta-llama-3-70b-instruct",
"mixtral-8x7b": "mistralai/mixtral-8x7b-instruct-v0.1",
"gemma-2b": "google-deepmind/gemma-2b-it",
"llava-13b": "yorickvp/llava-13b",
}
model_versions = {
"meta/meta-llama-3-70b-instruct": "fbfb20b472b2f3bdd101412a9f70a0ed4fc0ced78a77ff00970ee7a2383c575d",
"mistralai/mixtral-8x7b-instruct-v0.1": "5d78bcd7a992c4b793465bcdcf551dc2ab9668d12bb7aa714557a21c1e77041c",
"google-deepmind/gemma-2b-it": "dff94eaf770e1fc211e425a50b51baa8e4cac6c39ef074681f9e39d778773626",
"yorickvp/llava-13b": "80537f9eead1a5bfa72d5ac6ea6414379be41d4d4f6679fd776e9535d1eb58bb",
'black-forest-labs/flux-schnell': "f2ab8a5bfe79f02f0789a146cf5e73d2a4ff2684a98c2b303d1e1ff3814271db",
'stability-ai/stable-diffusion-3': "527d2a6296facb8e47ba1eaf17f142c240c19a30894f437feee9b91cc29d8e4f",
'bytedance/sdxl-lightning-4step': "5f24084160c9089501c1b3545d9be3c27883ae2239b6f412990e82d4a6210f8f",
'playgroundai/playground-v2.5-1024px-aesthetic': "a45f82a1382bed5c7aeb861dac7c7d191b0fdf74d8d57c4a0e6ed7d4d0bf7d24",
}
@classmethod
def get_model(cls, model: str) -> str:
if model in cls.models:
return model
elif model in cls.model_aliases:
return cls.model_aliases[model]
else:
return cls.default_model
@classmethod
async def create_async_generator(
cls,
model: str,
messages: Messages,
proxy: str = None,
**kwargs
) -> AsyncResult:
model = cls.get_model(model)
headers = {
"accept": "*/*",
"accept-language": "en-US,en;q=0.9",
"cache-control": "no-cache",
"content-type": "application/json",
"origin": "https://replicate.com",
"pragma": "no-cache",
"priority": "u=1, i",
"referer": "https://replicate.com/",
"sec-ch-ua": '"Not;A=Brand";v="24", "Chromium";v="128"',
"sec-ch-ua-mobile": "?0",
"sec-ch-ua-platform": '"Linux"',
"sec-fetch-dest": "empty",
"sec-fetch-mode": "cors",
"sec-fetch-site": "same-site",
"user-agent": "Mozilla/5.0 (X11; Linux x86_64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/128.0.0.0 Safari/537.36"
}
async with ClientSession(headers=headers) as session:
if model in cls.image_models:
prompt = messages[-1]['content'] if messages else ""
else:
prompt = format_prompt(messages)
data = {
"model": model,
"version": cls.model_versions[model],
"input": {"prompt": prompt},
}
async with session.post(cls.api_endpoint, json=data, proxy=proxy) as response:
response.raise_for_status()
result = await response.json()
prediction_id = result['id']
poll_url = f"https://homepage.replicate.com/api/poll?id={prediction_id}"
max_attempts = 30
delay = 5
for _ in range(max_attempts):
async with session.get(poll_url, proxy=proxy) as response:
response.raise_for_status()
try:
result = await response.json()
except ContentTypeError:
text = await response.text()
try:
result = json.loads(text)
except json.JSONDecodeError:
raise ValueError(f"Unexpected response format: {text}")
if result['status'] == 'succeeded':
if model in cls.image_models:
image_url = result['output'][0]
yield ImageResponse(image_url, "Generated image")
return
else:
for chunk in result['output']:
yield chunk
break
elif result['status'] == 'failed':
raise Exception(f"Prediction failed: {result.get('error')}")
await asyncio.sleep(delay)
if result['status'] != 'succeeded':
raise Exception("Prediction timed out")
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