Prathamesh Sable commited on
Commit
f746ed1
·
1 Parent(s): cb44dfc

little twicks

Browse files
main.py CHANGED
@@ -44,8 +44,8 @@ async def log_requests(request: Request, call_next):
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  request._body = body_content
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  response = await call_next(request)
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  print(f"Request: {request.method} {request.url}")
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- print(f"Data: {body_content}"[:100])
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- print(f"Headers: {request.headers}")
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  return response
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  @app.get("/api", response_class=HTMLResponse)
 
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  request._body = body_content
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  response = await call_next(request)
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  print(f"Request: {request.method} {request.url}")
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+ # print(f"Data: {body_content}"[:100])
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+ # print(f"Headers: {request.headers}")
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  return response
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  @app.get("/api", response_class=HTMLResponse)
routers/product.py CHANGED
@@ -136,7 +136,7 @@ async def create_product(
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  # Check if the analysis results are valid
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  analysis_results = results.get("overall_analysis", {})
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- overall_safety_score = analysis_results.get("overall_safety_score", 0)
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  suitable_diet_types = analysis_results.get("suitable_diet_types", [])
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  allergy_warnings = analysis_results.get("allergy_warnings", [])
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  usage_recommendations = analysis_results.get("usage_recommendations", "")
 
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  # Check if the analysis results are valid
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  analysis_results = results.get("overall_analysis", {})
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+ overall_safety_score = analysis_results.get("overall_safety_score", 5)
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  suitable_diet_types = analysis_results.get("suitable_diet_types", [])
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  allergy_warnings = analysis_results.get("allergy_warnings", [])
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  usage_recommendations = analysis_results.get("usage_recommendations", "")
services/productAnalyzerAgent.py CHANGED
@@ -59,7 +59,7 @@ User has the following preferences:
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  You are an expert food scientist and nutritionist analyzing a product's ingredients.
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  Based on the detailed information about each ingredient below, provide a comprehensive
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- analysis that would be helpful for a consumer viewing this in an AR application.
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  ## INGREDIENTS INFORMATION:
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  {''.join(ingredients_summary)}
@@ -67,7 +67,7 @@ analysis that would be helpful for a consumer viewing this in an AR application.
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  {user_context}
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  ## REQUIRED ANALYSIS:
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- 1. Overall Safety Score (1-10): Calculate this based on individual ingredient safety scores
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  2. Suitable Diet Types: Determine if this product is for vegan, vegetarian, or Non-Vegetarian
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  3. Allergy Warnings: Flag any potential allergens present related to food not more than 5 combine if needed
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  4. Usage Recommendations: Provide safe consumption limits or usage guidance
 
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  You are an expert food scientist and nutritionist analyzing a product's ingredients.
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  Based on the detailed information about each ingredient below, provide a comprehensive
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+ analysis that would be helpful for a consumer viewing this while shopping and using that product.
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  ## INGREDIENTS INFORMATION:
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  {''.join(ingredients_summary)}
 
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  {user_context}
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  ## REQUIRED ANALYSIS:
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+ 1. Overall Safety Score (1-10): Calculate this based on individual ingredient safety scores 1 means product is not safe at all (like a toxin) and 10 means product is completely safe
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  2. Suitable Diet Types: Determine if this product is for vegan, vegetarian, or Non-Vegetarian
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  3. Allergy Warnings: Flag any potential allergens present related to food not more than 5 combine if needed
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  4. Usage Recommendations: Provide safe consumption limits or usage guidance
utils/vuforia_utils.py CHANGED
@@ -33,7 +33,7 @@ async def add_target_to_vuforia(image_name: str, image_path: str) -> str:
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  # Create payload
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  payload = {
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  "name": image_name,
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- "width": 1.0, # Default width in scene units
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  "image": image_base64,
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  "active_flag": True,
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  }
 
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  # Create payload
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  payload = {
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  "name": image_name,
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+ "width": 150.0, # Default width in scene units
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  "image": image_base64,
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  "active_flag": True,
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  }