| import json |
| import markdown |
| from typing import Callable, List, Dict, Any, Generator |
| from functools import partial |
|
|
| import fastapi |
| import uvicorn |
| from fastapi import HTTPException, Depends, Request |
| from fastapi.responses import HTMLResponse |
| from fastapi.middleware.cors import CORSMiddleware |
| from sse_starlette.sse import EventSourceResponse |
| from anyio import create_memory_object_stream |
| from anyio.to_thread import run_sync |
| from ctransformers import AutoModelForCausalLM |
| from pydantic import BaseModel |
|
|
| llm = AutoModelForCausalLM.from_pretrained("TheBloke/WizardCoder-15B-1.0-GGML", |
| model_file="WizardCoder-15B-1.0.ggmlv3.q5_0.bin", |
| model_type="starcoder", |
| threads=8) |
| 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="font-family:system-ui"> |
| <h2><a href="https://huggingface.co/TheBloke/WizardCoder-15B-1.0-GGML">wizardcoder-ggml</a></h2> |
| <h2><a href="https://matthoffner-wizardcoder-ggml.hf.space/docs">FastAPI Docs</a></h2> |
| <h2><a href="https://matthoffner-monacopilot.hf.space">monacopilot</a></h2> |
| </body> |
| </html> |
| """ |
| return HTMLResponse(content=html_content, status_code=200) |
|
|
| class ChatCompletionRequestV0(BaseModel): |
| prompt: str |
|
|
| class Message(BaseModel): |
| role: str |
| content: str |
|
|
| class ChatCompletionRequest(BaseModel): |
| messages: List[Message] |
| max_tokens: int = 250 |
|
|
| @app.post("/v1/completions") |
| async def completion(request: ChatCompletionRequestV0, response_mode=None): |
| response = llm(request.prompt) |
| return response |
|
|
| async def generate_response(chat_chunks, llm): |
| for chat_chunk in chat_chunks: |
| response = { |
| 'choices': [ |
| { |
| 'message': { |
| 'role': 'system', |
| 'content': llm.detokenize(chat_chunk) |
| }, |
| 'finish_reason': 'stop' if llm.is_eos_token(chat_chunk) else 'unknown' |
| } |
| ] |
| } |
| yield dict(data=json.dumps(response)) |
| yield dict(data="[DONE]") |
|
|
| @app.post("/v1/chat/completions") |
| async def chat(request: ChatCompletionRequest): |
| combined_messages = ' '.join([message.content for message in request.messages]) |
| tokens = llm.tokenize(combined_messages) |
| |
| try: |
| chat_chunks = llm.generate(tokens) |
| except Exception as e: |
| raise HTTPException(status_code=500, detail=str(e)) |
|
|
| return EventSourceResponse(generate_response(chat_chunks, llm)) |
|
|
| async def stream_response(tokens, llm): |
| try: |
| iterator: Generator = llm.generate(tokens) |
| for chat_chunk in iterator: |
| response = { |
| 'choices': [ |
| { |
| 'message': { |
| 'role': 'system', |
| 'content': llm.detokenize(chat_chunk) |
| }, |
| 'finish_reason': 'stop' if llm.is_eos_token(chat_chunk) else 'unknown' |
| } |
| ] |
| } |
| yield dict(data=json.dumps(response)) |
| yield dict(data="[DONE]") |
| except Exception as e: |
| print(f"Exception in event publisher: {str(e)}") |
|
|
| @app.post("/v2/chat/completions") |
| async def chatV2_endpoint(request: Request, body: ChatCompletionRequest): |
| combined_messages = ' '.join([message.content for message in body.messages]) |
| tokens = llm.tokenize(combined_messages) |
|
|
| return EventSourceResponse(stream_response(tokens, llm)) |
|
|
| @app.post("/v0/chat/completions") |
| async def chat(request: ChatCompletionRequestV0, 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) |
|
|
