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Duplicate from matthoffner/ggml-ctransformers-fastapi
Browse files- .gitattributes +34 -0
- Dockerfile +29 -0
- README.md +19 -0
- main.py +43 -0
- requirements.txt +11 -0
.gitattributes
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Dockerfile
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FROM python:latest
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ENV PYTHONUNBUFFERED 1
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EXPOSE 8000
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WORKDIR /app
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RUN wget -qO- "https://cmake.org/files/v3.17/cmake-3.17.0-Linux-x86_64.tar.gz" | tar --strip-components=1 -xz -C /usr/local
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COPY requirements.txt ./
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RUN pip install --upgrade pip && \
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pip install -r requirements.txt
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RUN curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | bash
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RUN apt-get install git-lfs
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RUN git clone https://github.com/ggerganov/ggml && cd ggml && mkdir build && cd build && cmake ..
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RUN git clone https://huggingface.co/bigcode/gpt_bigcode-santacoder
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RUN python ggml/examples/starcoder/convert-hf-to-ggml.py ./gpt_bigcode-santacoder/
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RUN cd ggml/build && make -j4 starcoder starcoder-quantize
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RUN ggml/build/bin/starcoder-quantize models/./gpt_bigcode-santacoder/-ggml.bin ggml-model-q4_1.bin 3
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COPY . .
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RUN ls -al
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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README.md
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---
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title: ggml-ctransformers-fastapi
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emoji: 🐳🤗⚡️
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sdk: docker
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app_port: 8000
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duplicated_from: matthoffner/ggml-ctransformers-fastapi
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---
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# ggml-ctransformers-fastapi
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## <a href="https://github.com/ggerganov/ggml" target="_blank">ggml</a>
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## <a href="https://github.com/marella/ctransformers" target="_blank">ctransformers</a>
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## [FastAPI Docs](https://matthoffner-ggml-ctransformers-fastapi.hf.space/docs)
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### Updates
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* Added /v1/chat/completions
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* [Start using ctransformers](https://github.com/marella/ctransformers)
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* [Added starcoder example](https://github.com/ggerganov/ggml/tree/master/examples/starcoder)
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main.py
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import fastapi
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import json
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import markdown
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import uvicorn
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from fastapi.responses import HTMLResponse
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from fastapi.middleware.cors import CORSMiddleware
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from sse_starlette.sse import EventSourceResponse
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from ctransformers.langchain import CTransformers
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from pydantic import BaseModel
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llm = CTransformers(model='ggml-model-q4_1.bin', model_type='starcoder')
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app = fastapi.FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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allow_credentials=True,
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allow_methods=["*"],
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allow_headers=["*"],
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)
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@app.get("/")
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async def index():
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with open("README.md", "r", encoding="utf-8") as readme_file:
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md_template_string = readme_file.read()
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html_content = markdown.markdown(md_template_string)
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return HTMLResponse(content=html_content, status_code=200)
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class ChatCompletionRequest(BaseModel):
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prompt: str
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@app.post("/v1/chat/completions")
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async def chat(request: ChatCompletionRequest, response_mode=None):
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completion = llm(request.prompt)
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async def server_sent_events(chat_chunks):
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for chat_chunk in chat_chunks:
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yield dict(data=json.dumps(chat_chunk))
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yield dict(data="[DONE]")
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return EventSourceResponse(server_sent_events(completion))
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if __name__ == "__main__":
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uvicorn.run(app, host="0.0.0.0", port=8000)
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requirements.txt
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uvicorn
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markdown
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fastapi
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loguru
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torch
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numpy
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transformers
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ctransformers
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accelerate
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langchain
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sse_starlette
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