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ffreemt
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Commit
•
cde2d91
1
Parent(s):
0e238ed
Update
Browse files- Dockerfile +4 -3
- m3_server.py +3 -1
Dockerfile
CHANGED
@@ -1,6 +1,7 @@
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FROM python:3.10
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ENV PIP_ROOT_USER_ACTION=ignore \
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TZ=Asia/Shanghai
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WORKDIR /app
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COPY . .
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@@ -20,8 +21,8 @@ RUN pip install --no-cache-dir --upgrade pip && \
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# CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
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# CMD ["TRANSFORMERS_CACHE=./", "infinity_emb", "--model-name-or-path", "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", "--port", "7860"]
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-
# x ["sh", "-c", "'FOO=BAR python app.py'"]
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# CMD ["python", "m3_server.py"]
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-
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CMD ["sh", "-c", "HF_HOME=/tmp/cache", "python", "m3_server.py"]
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FROM python:3.10
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ENV PIP_ROOT_USER_ACTION=ignore \
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TZ=Asia/Shanghai
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RUN ln -snf /usr/share/zoneinfo/$TZ /etc/localtime && echo $TZ > /etc/timezone
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WORKDIR /app
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COPY . .
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# CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "7860"]
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# CMD ["TRANSFORMERS_CACHE=./", "infinity_emb", "--model-name-or-path", "sentence-transformers/paraphrase-multilingual-MiniLM-L12-v2", "--port", "7860"]
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# CMD ["python", "m3_server.py"]
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# x ["sh", "-c", "'FOO=BAR python m3_server.py'"]
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# CMD ["sh", "-c", "HF_HOME=/tmp/cache", "python", "m3_server.py"]
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CMD ["sh", "start-m3-server.sh"] # OK
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m3_server.py
CHANGED
@@ -14,10 +14,12 @@ from FlagEmbedding import BGEM3FlagModel
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from pydantic import BaseModel
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from starlette.status import HTTP_504_GATEWAY_TIMEOUT
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Path("/tmp/cache").mkdir(exist_ok=True)
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os.environ["HF_HOME"] = "/tmp/cache"
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os.environ["TRANSFORMERS_CACHE"] = "/tmp/cache"
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# does not quite work
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batch_size = 2 # gpu batch_size in order of your available vram
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max_request = 10 # max request for future improvements on api calls / gpu batches (for now is pretty basic)
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@@ -242,5 +244,5 @@ async def rerank(request: RerankRequest):
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=port)
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from pydantic import BaseModel
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from starlette.status import HTTP_504_GATEWAY_TIMEOUT
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_ = """
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Path("/tmp/cache").mkdir(exist_ok=True)
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os.environ["HF_HOME"] = "/tmp/cache"
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os.environ["TRANSFORMERS_CACHE"] = "/tmp/cache"
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# does not quite work
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# """
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batch_size = 2 # gpu batch_size in order of your available vram
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max_request = 10 # max request for future improvements on api calls / gpu batches (for now is pretty basic)
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if __name__ == "__main__":
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import uvicorn
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print("started")
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uvicorn.run(app, host="0.0.0.0", port=port)
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