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import fastapi
import json
import markdown
import uvicorn
from fastapi import HTTPException
from fastapi.responses import HTMLResponse, HTTPException
from fastapi.middleware.cors import CORSMiddleware
from sse_starlette.sse import EventSourceResponse
from ctransformers import AutoModelForCausalLM
from pydantic import BaseModel
from typing import List, Dict, Any
llm = AutoModelForCausalLM.from_pretrained("TheBloke/WizardCoder-15B-1.0-GGML",
model_file="WizardCoder-15B-1.0.ggmlv3.q4_0.bin",
model_type="starcoder")
app = fastapi.FastAPI(title="WizardCoder")
app.add_middleware(
CORSMiddleware,
allow_origins=["*"],
allow_credentials=True,
allow_methods=["*"],
allow_headers=["*"],
)
@app.get("/")
async def index():
html_content = """
<html>
<head>
</head>
<body style="background-color:black">
<h2 style="font-family:system-ui"><a href="https://huggingface.co/TheBloke/WizardCoder-15B-1.0-GGML">wizardcoder-ggml</a></h2>
<iframe
src="https://matthoffner-monacopilot.hf.space"
frameborder="0"
width="95%"
height="90%"
></iframe>
<h2 style="font-family:system-ui"><a href="https://matthoffner-wizardcoder-ggml.hf.space/docs">FastAPI Docs</a></h2>
</body>
</html>
"""
return HTMLResponse(content=html_content, status_code=200)
class ChatCompletionRequest(BaseModel):
prompt: str
class Message(BaseModel):
role: str
content: str
class ChatCompletionRequestV2(BaseModel):
messages: List[Message]
max_tokens: int = 100
@app.post("/v1/completions")
async def completion(request: ChatCompletionRequest, response_mode=None):
response = llm(request.prompt)
return response
@app.post("/v2/chat/completions")
async def chat(request: ChatCompletionRequestV2):
tokens = llm.tokenize([message.content for message in request.messages])
try:
chat_chunks = llm.generate(tokens, max_tokens=request.max_tokens)
except Exception as e:
raise HTTPException(status_code=500, detail=str(e))
def format_response(chat_chunks) -> Dict[str, Any]:
response = {
'choices': []
}
for chat_chunk in chat_chunks:
response['choices'].append({
'message': {
'role': 'system',
'content': llm.detokenize(chat_chunk)
},
'finish_reason': 'stop' if llm.detokenize(chat_chunk) == "[DONE]" else 'unknown'
})
return response
return format_response(chat_chunks)
@app.post("/v1/chat/completions")
async def chat(request: ChatCompletionRequest, response_mode=None):
tokens = llm.tokenize(request.prompt)
async def server_sent_events(chat_chunks, llm):
for chat_chunk in llm.generate(chat_chunks):
yield dict(data=json.dumps(llm.detokenize(chat_chunk)))
yield dict(data="[DONE]")
return EventSourceResponse(server_sent_events(tokens, llm))
if __name__ == "__main__":
uvicorn.run(app, host="0.0.0.0", port=8000) |