Spaces:
Sleeping
Sleeping
Fix for MODEL_PATH export
Browse files- app/main.py +2 -1
- app/utils/download_model.py +9 -7
- entrypoint.sh +14 -21
app/main.py
CHANGED
@@ -1,3 +1,4 @@
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import chromadb
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from fastapi import FastAPI, Request, Form, File, UploadFile, Depends
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@@ -38,7 +39,7 @@ async def startup_event():
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db_path = CHROMADB_LOC
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chromadb_face_helper = ChromaDBFaceHelper(db_path) # Used by APIs
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# Perform any other startup tasks here
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-
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# Mount static files
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app.mount("/static", StaticFiles(directory="static"), name="static")
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import os
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import chromadb
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from fastapi import FastAPI, Request, Form, File, UploadFile, Depends
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db_path = CHROMADB_LOC
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chromadb_face_helper = ChromaDBFaceHelper(db_path) # Used by APIs
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# Perform any other startup tasks here
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print(f"MODEL_PATH in main.py = {os.getenv('MODEL_PATH')} ")
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# Mount static files
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app.mount("/static", StaticFiles(directory="static"), name="static")
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app/utils/download_model.py
CHANGED
@@ -2,13 +2,15 @@ import os
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import requests
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from transformers import AutoModel
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'''
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DO NOT PRINT ANYTHING OTHER THAN MODEL PATH IN THIS SCRIPT, THIS IS BEING EXPORTED BY DOCKER ENTRY POINT!
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'''
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def model_file_exists_and_valid(model_file_path):
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# Check if the model file exists and has a size greater than 0
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return os.path.exists(model_file_path) and os.path.getsize(model_file_path) > 0
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def download_hf_model():
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'''
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Model File Path for HF Models: The download_hf_model function now includes a default model file path (pytorch_model.bin) check.
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@@ -20,7 +22,7 @@ def download_hf_model():
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if model_file_exists_and_valid(model_file_path):
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print(f"Model {model_name} already downloaded.")
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-
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return
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# Authenticate with Hugging Face using the token, if available
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@@ -33,7 +35,7 @@ def download_hf_model():
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model = AutoModel.from_pretrained(model_name)
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model.save_pretrained(model_dir)
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print(f"Model {model_name} downloaded and saved to {model_dir}")
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def download_gguf_model():
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model_name = os.getenv("HF_MODEL_NAME")
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@@ -45,7 +47,7 @@ def download_gguf_model():
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if model_file_exists_and_valid(model_file_path):
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print(f"Model {model_name} already downloaded.")
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-
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return
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print(f"Downloading model from {model_url}...")
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@@ -56,7 +58,7 @@ def download_gguf_model():
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print(f"Model downloaded and saved to {model_file_path}")
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else:
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print(f"Failed to download the model. Status code: {response.status_code}")
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def download_model():
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model_class = os.getenv("MODEL_CLASS")
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import requests
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from transformers import AutoModel
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def model_file_exists_and_valid(model_file_path):
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# Check if the model file exists and has a size greater than 0
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return os.path.exists(model_file_path) and os.path.getsize(model_file_path) > 0
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def write_model_path_to_txt_file(model_file_path):
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# Write the model path to model_path.txt
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with open('/home/user/data/models/model_path.txt', 'w') as f:
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f.write(model_file_path)
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def download_hf_model():
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'''
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Model File Path for HF Models: The download_hf_model function now includes a default model file path (pytorch_model.bin) check.
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if model_file_exists_and_valid(model_file_path):
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print(f"Model {model_name} already downloaded.")
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write_model_path_to_txt_file(model_file_path)
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return
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# Authenticate with Hugging Face using the token, if available
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model = AutoModel.from_pretrained(model_name)
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model.save_pretrained(model_dir)
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print(f"Model {model_name} downloaded and saved to {model_dir}")
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write_model_path_to_txt_file(model_file_path)
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def download_gguf_model():
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model_name = os.getenv("HF_MODEL_NAME")
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if model_file_exists_and_valid(model_file_path):
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print(f"Model {model_name} already downloaded.")
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write_model_path_to_txt_file(model_file_path)
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return
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print(f"Downloading model from {model_url}...")
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print(f"Model downloaded and saved to {model_file_path}")
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else:
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print(f"Failed to download the model. Status code: {response.status_code}")
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write_model_path_to_txt_file(model_file_path)
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def download_model():
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model_class = os.getenv("MODEL_CLASS")
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entrypoint.sh
CHANGED
@@ -6,27 +6,20 @@ export HF_HOME=/home/user/data/hf_cache
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# Assuming HF_TOKEN is already exported to the environment
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echo "Using Hugging Face API token for authentication"
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#
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#
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# Navigate back to the app directory
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cd /home/user/app
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else
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echo "Model ${HF_MODEL_NAME} already present."
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fi
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# Execute the main command of the container
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exec "$@"
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# Assuming HF_TOKEN is already exported to the environment
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echo "Using Hugging Face API token for authentication"
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# Navigate to the directory where download_model.py is located
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echo "Determining model path..."
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cd /home/user/app/app/utils
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# Execute the download_model script
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python download_model.py || { echo "Model download failed"; exit 1; }
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# export MODEL_PATH
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# Read the model path from model_path.txt and export it
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MODEL_PATH=$(cat /home/user/data/models/model_path.txt)
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export MODEL_PATH
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echo "@ Entrypoint - MODEL_PATH exported=${MODEL_PATH}"
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# Navigate back to the app directory
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cd /home/user/app
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# Execute the main command of the container
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exec "$@"
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