File size: 3,737 Bytes
e700505 af5e18d f866f5e e700505 f866f5e e700505 af5e18d e700505 af5e18d e700505 af5e18d e700505 0f00e90 e700505 af5e18d e700505 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 |
from fastapi import FastAPI, Request
from fastapi.responses import StreamingResponse
from fastapi.middleware.cors import CORSMiddleware
from models.text.together.main import TogetherAPI
from models.text.vercel.main import XaiAPI, GroqAPI, DeepinfraAPI
from models.image.vercel.main import FalAPI
from models.image.together.main import TogetherImageAPI
app = FastAPI()
app.add_middleware(
CORSMiddleware,
allow_origins=["*"], # Allows all origins
allow_credentials=True,
allow_methods=["*"], # Allows all methods
allow_headers=["*"], # Allows all headers
)
@app.get("/")
async def root():
return {"status":"ok", "routes":{"/":"GET", "/api/v1/generate":"POST", "/api/v1/models":"GET", "/api/v1/generate-images":"POST"}, "models": ["text", "image"]}
@app.post("/api/v1/generate")
async def generate(request: Request):
data = await request.json()
messages = data['messages']
model = data['model']
if not messages or not model:
return {"error": "Invalid request. 'messages' and 'model' are required."}
try:
query = {
'model': model,
'max_tokens': None,
'temperature': 0.7,
'top_p': 0.7,
'top_k': 50,
'repetition_penalty': 1,
'stream_tokens': True,
'stop': ['<|eot_id|>', '<|eom_id|>'],
'messages': messages,
'stream': True,
}
together_models = TogetherAPI().get_model_list()
xai_models = XaiAPI().get_model_list()
groq_models = GroqAPI().get_model_list()
deepinfra_models = DeepinfraAPI().get_model_list()
if model in together_models:
streamModel = TogetherAPI()
elif model in xai_models:
streamModel = XaiAPI()
elif model in groq_models:
streamModel = GroqAPI()
elif model in deepinfra_models:
streamModel = DeepinfraAPI()
else:
return {"error": f"Model '{model}' is not supported."}
response = streamModel.generate(query)
return StreamingResponse(response, media_type="text/event-stream")
except Exception as e:
return {"error": f"An error occurred: {str(e)}"}
@app.get("/api/v1/models")
async def get_models():
try:
models = {
'text': {
'together': TogetherAPI().get_model_list(),
'xai': XaiAPI().get_model_list(),
'groq': GroqAPI().get_model_list(),
'deepinfra': DeepinfraAPI().get_model_list()
},
'image': {
'fal': FalAPI().get_model_list(),
'together': TogetherImageAPI().get_model_list()
}
}
return {"models": models}
except Exception as e:
return {"error": f"An error occurred: {str(e)}"}
@app.post('/api/v1/generate-images')
async def generate_images(request: Request):
data = await request.json()
prompt = data['prompt']
model = data['model']
print(model)
fal_models = FalAPI().get_model_list()
together_models = TogetherImageAPI().get_model_list()
if not prompt or not model:
return {"error": "Invalid request. 'prompt' and 'model' are required."}
if model in fal_models:
streamModel = FalAPI()
elif model in together_models:
streamModel = TogetherImageAPI()
else:
return {"error": f"Model '{model}' is not supported."}
try:
query = {
'prompt': prompt,
'modelId': model,
}
response = await streamModel.generate(query)
return response
except Exception as e:
return {"error": f"An error occurred: {str(e)}"} |