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Update app.py
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app.py
CHANGED
@@ -3,7 +3,6 @@ import pickle
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import os
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import re
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import numpy as np
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from fastapi.responses import HTMLResponse
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import torchvision
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import nltk
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import torch
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@@ -35,7 +34,6 @@ from safetensors.torch import safe_open
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nltk.download('punkt_tab')
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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@@ -507,8 +505,6 @@ def translate_en_to_ar(text):
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async def root():
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return {"message": "Welcome to the FastAPI application! Use the /health endpoint to check health, and /api/query for processing queries."}
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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@@ -602,8 +598,7 @@ async def resources_endpoint(profile: MedicalProfile):
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for i, resource in enumerate(resources):
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resource["score"] = scores[i] if i < len(scores) else 0.0
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resources.sort(key=lambda x: x["score"], reverse=True)
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output = [{"title": resource["title"], "url": resource["url"]} for resource in resources]
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print (output)
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return output
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except ValueError as ve:
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raise HTTPException(status_code=400, detail=str(ve))
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@@ -632,18 +627,20 @@ async def recipes_endpoint(profile: MedicalProfile):
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print("Initial results (document indices and similarities):")
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print(initial_results)
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document_indices = [doc_id for doc_id, _ in initial_results]
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print("Document indices:", document_indices)
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metadata_path = 'recipes_metadata.xlsx'
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metadata = retrieve_metadata(document_indices, metadata_path=metadata_path)
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print(f"Retrieved Metadata: {metadata}")
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recipes = []
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for item in metadata
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recipes.append({
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"title": item
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"url": item
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})
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except ValueError as ve:
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raise HTTPException(status_code=400, detail=str(ve))
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except Exception as e:
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import os
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import re
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import numpy as np
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import torchvision
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import nltk
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import torch
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nltk.download('punkt_tab')
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app = FastAPI()
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app.add_middleware(
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CORSMiddleware,
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allow_origins=["*"],
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async def root():
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return {"message": "Welcome to the FastAPI application! Use the /health endpoint to check health, and /api/query for processing queries."}
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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for i, resource in enumerate(resources):
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resource["score"] = scores[i] if i < len(scores) else 0.0
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resources.sort(key=lambda x: x["score"], reverse=True)
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output = [{"title": resource["title"], "url": resource["url"]} for resource in resources]
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return output
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except ValueError as ve:
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raise HTTPException(status_code=400, detail=str(ve))
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print("Initial results (document indices and similarities):")
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print(initial_results)
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document_indices = [doc_id for doc_id, _ in initial_results]
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print("Document indices:", document_indices)
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metadata_path = 'recipes_metadata.xlsx'
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metadata = retrieve_metadata(document_indices, metadata_path=metadata_path)
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print(f"Retrieved Metadata: {metadata}")
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recipes = []
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for item in metadata:
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recipes.append({
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"title": item.get("original_file_name", "Unknown Title"),
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"url": item.get("url", "")
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})
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response = {
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"recipes": recipes
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}
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return response
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except ValueError as ve:
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raise HTTPException(status_code=400, detail=str(ve))
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except Exception as e:
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