1 files changed, 143 insertions, 0 deletions
diff --git a/g4f/Provider/ReplicateHome.py b/g4f/Provider/ReplicateHome.py
new file mode 100644
index 00000000..7f443a7d
--- /dev/null
+++ b/g4f/Provider/ReplicateHome.py
@@ -0,0 +1,143 @@
+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")