khansaami942
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from typing import Optional, List, Dict, Any from services.llm_service import LLMService class RecommendationService: """Generate recommendations with clear, professional prompts""" def __init__(self): self.llm = LLMService() def generate_haircuts( self, hair_type: str, face_shape: str, gender: str, preference: str, hair_length: str, age: int, ) -> Optional[str]: """Generate haircut recommendations with clear, detailed guidance""" prompt = f"""You are an experienced professional hair stylist. Provide 3 specific haircut recommendations for this client. CLIENT INFORMATION: - Hair Type: {hair_type} - Face Shape: {face_shape} - Gender: {gender} - Age: {age} years - Style Preference: {preference} - Desired Length: {hair_length} REQUIREMENTS: Recommend 3 DIFFERENT haircuts that: 1. Complement the {face_shape} face shape 2. Work well with {hair_type} hair 3. Match the {preference} style 4. Are appropriate for {age} years old 5. Achieve the {hair_length} length For each haircut, provide: - Specific haircut name (e.g., "Textured Layered Bob" not just "Bob") - Clear 2-3 sentence description of the cut - Explanation of why it works for this face shape and hair type - Styling difficulty: Easy/Medium/Advanced - Maintenance level: Low/Medium/High FACE SHAPE GUIDELINES: - Oval: Most versatile, suits almost any style - Round: Add height and angles, avoid width at cheeks - Square: Soften jawline with layers and texture - Heart: Balance wide forehead with volume at chin - Oblong: Add width at sides, avoid too much height - Diamond: Add volume at crown and chin area HAIR TYPE CONSIDERATIONS: - Straight: Needs texture and layers for movement - Wavy: Embrace natural texture, avoid excessive layers - Curly: Account for shrinkage, needs length and moisture - Fine: Avoid over-layering, create illusion of thickness - Thick: Needs thinning and internal layers FORMAT: 1. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 2. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 3. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] Answer: 1.""" response = self.llm.query(prompt, timeout=40) return "1." + response.strip() if response else None def generate_products(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations with care tips and home remedies""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and solutions for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Dove Intensive Repair Shampoo") 2. Include brand name 3. Specify size (e.g., 250ml, 400g, 16 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 3 practical care tips specifically for {hair_problem} with {hair_type} hair. Focus on: - Daily habits and techniques - Washing and styling methods - Protection and prevention - NOT product recommendations TASK 3 - HOME REMEDIES: Provide 3 home remedies for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements - Have clear step-by-step instructions - Explain benefits - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Home Remedies for {hair_problem}: Remedy 1: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 2: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 3: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_products_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations and care tips only""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and care tips for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Pantene Pro-V Daily Moisture Renewal Shampoo") 2. Include brand name 3. Specify size (e.g., 355ml, 16.9 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 5 practical, actionable care tips specifically for {hair_problem} with {hair_type} hair. Tips should: - Be specific daily habits or techniques (NOT product recommendations) - Be evidence-based for {hair_problem} - Be appropriate for {hair_type} hair - Cover different areas: washing, styling, diet, protection, etc. FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_remedies_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate home remedies only""" prompt = f"""You are a natural hair care expert. Provide home remedies for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK: Provide 3 home remedies specifically for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements (tablespoons, cups, etc.) - Have clear step-by-step instructions - Explain benefits and why it works - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) - Be safe for {age} years old - Consider {hair_type} hair characteristics FORMAT: Remedy 1: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 2: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 3: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Answer: Remedy 1:""" response = self.llm.query(prompt, timeout=40) return "Remedy 1:" + response.strip() if response else None def parse_haircuts(self, response: Optional[str]) -> List[Dict]: """Parse haircut response""" haircuts: List[Dict] = [] if not response: return haircuts lines = response.split("\n") current: Dict[str, str] = {} allowed_difficulty = {"easy", "medium", "advanced"} allowed_maintenance = {"low", "medium", "high"} for line in lines: line = line.strip() if not line: continue if line and line[0].isdigit() and "." in line: if current and "name" in current: haircuts.append(current) if len(haircuts) >= 3: break parts = line.split(".", 1) if len(parts) == 2: name = parts[1].strip() current = {"name": name, "description": "", "why_works": "", "difficulty": "", "maintenance": ""} elif "Description:" in line or "description:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: current["description"] = parts[1].strip() elif "Why it works:" in line or "why it works:" in line.lower() or "Why:" in line: parts = line.split(":", 1) if len(parts) == 2 and current: current["why_works"] = parts[1].strip() elif "Difficulty:" in line or "difficulty:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: difficulty = parts[1].strip().lower() for level in allowed_difficulty: if level in difficulty: current["difficulty"] = level.capitalize() break elif "Maintenance:" in line or "maintenance:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: maintenance = parts[1].strip().lower() for level in allowed_maintenance: if level in maintenance: current["maintenance"] = level.capitalize() break if current and "name" in current: haircuts.append(current) valid_haircuts = [] for haircut in haircuts[:3]: if all(key in haircut and haircut[key] for key in ["name", "description", "why_works"]): if not haircut.get("difficulty"): haircut["difficulty"] = "Medium" if not haircut.get("maintenance"): haircut["maintenance"] = "Medium" valid_haircuts.append(haircut) return valid_haircuts def parse_products(self, response: Optional[str]) -> Dict[str, Any]: """Parse product recommendations, care tips, and home remedies""" result: Dict[str, Any] = { "products": [], "care_tips": [], "home_remedies": [] } if not response: return result lines = response.split("\n") current: Optional[Dict[str, str]] = None current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None in_care_tips_section = False in_remedies_section = False product_count = 0 for line in lines: line = line.strip() if not line: if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) current_remedy = {} current_remedy_section = None continue lower = line.lower() if "care tips" in lower or "care tip" in lower: in_care_tips_section = True in_remedies_section = False if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 continue if "home remed" in lower or "remedy 1:" in lower or (lower.startswith("remedy") and ":" in line): in_remedies_section = True in_care_tips_section = False if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None continue if in_care_tips_section and not in_remedies_section: if line.startswith(("-", "•", "*", "–")): tip = line.lstrip("-•*– ").strip() if len(tip) > 5: result["care_tips"].append(tip) elif not any(keyword in lower for keyword in ["product", "remedy", "brand:", "quantity:", "tip:"]): if len(line) > 15 and not line[0].isdigit(): result["care_tips"].append(line) continue if in_remedies_section: if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*", "–")) and current_remedy_section: text = line.lstrip("-•*– ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: if current_remedy_section == "ingredients" and not any(keyword in lower for keyword in ["instructions", "frequency", "benefits", "precautions"]): current_remedy.setdefault("ingredients", []).append(line) elif current_remedy_section != "ingredients": existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + line).strip() continue if not in_care_tips_section and not in_remedies_section: if lower.startswith("product") and ":" in line and product_count < 3: if current and "name" in current: result["products"].append(current) product_count += 1 if product_count >= 3: current = None continue parts = line.split(":", 1) if len(parts) == 2: product_name = parts[1].strip() current = {"name": product_name} else: if not current: current = {} elif line.startswith("Brand:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["brand"] = parts[1].strip() elif "Quantity:" in line and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["quantity"] = parts[1].strip() elif line.startswith("Tip:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["tip"] = parts[1].strip() elif current and "name" not in current: if not any(keyword in line.lower() for keyword in ["brand:", "quantity:", "tip:", "product", "care tips"]): if len(line) > 3: current["name"] = line if current and "name" in current and product_count < 3: result["products"].append(current) product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) for product in result["products"]: if "name" in product and product["name"]: name = product["name"].strip() if ":" in name: parts = name.split(":", 1) if len(parts) == 2: before_colon = parts[0].strip() after_colon = parts[1].strip() if len(before_colon.split()) <= 3 and len(after_colon) > len(before_colon): product["name"] = after_colon else: product["name"] = name else: product["name"] = name else: product["name"] = name for i, product in enumerate(result["products"]): if "name" not in product or not product["name"]: product["name"] = f"Hair Care Product {i + 1}" def _clean_text_items(items: List[str], limit: int = 5) -> List[str]: cleaned: List[str] = [] seen = set() for item in items: if not item: continue normalized = " ".join(item.split()) if len(normalized) < 5: continue key = normalized.lower() if key in seen: continue seen.add(key) cleaned.append(normalized) if len(cleaned) >= limit: break return cleaned def _clean_remedies(remedies: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) ingredients = rem.get("ingredients") or [] ingredients = [ing.strip() for ing in ingredients if isinstance(ing, str) and ing.strip()] cleaned.append( { "name": name, "ingredients": ingredients[:5], "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip(), } ) if len(cleaned) >= limit: break return cleaned result["care_tips"] = _clean_text_items(result["care_tips"], limit=5) result["home_remedies"] = _clean_remedies(result["home_remedies"], limit=3) return result def parse_remedies_only(self, response: Optional[str]) -> List[Dict[str, Any]]: """Parse home remedies only""" remedies: List[Dict[str, Any]] = [] if not response: return remedies lines = response.split("\n") current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None for line in lines: line = line.strip() if not line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break current_remedy = {} current_remedy_section = None continue lower = line.lower() if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*")) and current_remedy_section: text = line.lstrip("-•* ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: current_value = current_remedy.get(current_remedy_section, "") if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(line) else: current_remedy[current_remedy_section] = (current_value + " " + line).strip() if current_remedy.get("name") and current_remedy.get("instructions") and len(remedies) < 3: remedies.append(current_remedy) def _clean_remedies(remedies_list: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies_list: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) cleaned.append({ "name": name, "ingredients": rem.get("ingredients", []), "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip() }) if len(cleaned) >= limit: break return cleaned return _clean_remedies(remedies, limit=3) i want this prompt will look like the image i have shared it will worked like that generate the images
change sthe name go with Muhammad Saami and completion certificate in and changes the Artifical inetelligenece and machine learning chnages the date is 26 october 2025 generate this dont change the layout not change the mamaon logo i wnat samem as this screenshoit only chnage the name data compluton one generate this images
from typing import Optional, List, Dict, Any from services.llm_service import LLMService class RecommendationService: """Generate recommendations with clear, professional prompts""" def __init__(self): self.llm = LLMService() def generate_haircuts( self, hair_type: str, face_shape: str, gender: str, preference: str, hair_length: str, age: int, ) -> Optional[str]: """Generate haircut recommendations with clear, detailed guidance""" prompt = f"""You are an experienced professional hair stylist. Provide 3 specific haircut recommendations for this client. CLIENT INFORMATION: - Hair Type: {hair_type} - Face Shape: {face_shape} - Gender: {gender} - Age: {age} years - Style Preference: {preference} - Desired Length: {hair_length} REQUIREMENTS: Recommend 3 DIFFERENT haircuts that: 1. Complement the {face_shape} face shape 2. Work well with {hair_type} hair 3. Match the {preference} style 4. Are appropriate for {age} years old 5. Achieve the {hair_length} length For each haircut, provide: - Specific haircut name (e.g., "Textured Layered Bob" not just "Bob") - Clear 2-3 sentence description of the cut - Explanation of why it works for this face shape and hair type - Styling difficulty: Easy/Medium/Advanced - Maintenance level: Low/Medium/High FACE SHAPE GUIDELINES: - Oval: Most versatile, suits almost any style - Round: Add height and angles, avoid width at cheeks - Square: Soften jawline with layers and texture - Heart: Balance wide forehead with volume at chin - Oblong: Add width at sides, avoid too much height - Diamond: Add volume at crown and chin area HAIR TYPE CONSIDERATIONS: - Straight: Needs texture and layers for movement - Wavy: Embrace natural texture, avoid excessive layers - Curly: Account for shrinkage, needs length and moisture - Fine: Avoid over-layering, create illusion of thickness - Thick: Needs thinning and internal layers FORMAT: 1. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 2. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 3. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] Answer: 1.""" response = self.llm.query(prompt, timeout=40) return "1." + response.strip() if response else None def generate_products(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations with care tips and home remedies""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and solutions for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Dove Intensive Repair Shampoo") 2. Include brand name 3. Specify size (e.g., 250ml, 400g, 16 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 3 practical care tips specifically for {hair_problem} with {hair_type} hair. Focus on: - Daily habits and techniques - Washing and styling methods - Protection and prevention - NOT product recommendations TASK 3 - HOME REMEDIES: Provide 3 home remedies for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements - Have clear step-by-step instructions - Explain benefits - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Home Remedies for {hair_problem}: Remedy 1: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 2: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 3: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_products_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations and care tips only""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and care tips for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Pantene Pro-V Daily Moisture Renewal Shampoo") 2. Include brand name 3. Specify size (e.g., 355ml, 16.9 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 5 practical, actionable care tips specifically for {hair_problem} with {hair_type} hair. Tips should: - Be specific daily habits or techniques (NOT product recommendations) - Be evidence-based for {hair_problem} - Be appropriate for {hair_type} hair - Cover different areas: washing, styling, diet, protection, etc. FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_remedies_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate home remedies only""" prompt = f"""You are a natural hair care expert. Provide home remedies for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK: Provide 3 home remedies specifically for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements (tablespoons, cups, etc.) - Have clear step-by-step instructions - Explain benefits and why it works - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) - Be safe for {age} years old - Consider {hair_type} hair characteristics FORMAT: Remedy 1: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 2: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 3: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Answer: Remedy 1:""" response = self.llm.query(prompt, timeout=40) return "Remedy 1:" + response.strip() if response else None def parse_haircuts(self, response: Optional[str]) -> List[Dict]: """Parse haircut response""" haircuts: List[Dict] = [] if not response: return haircuts lines = response.split("\n") current: Dict[str, str] = {} allowed_difficulty = {"easy", "medium", "advanced"} allowed_maintenance = {"low", "medium", "high"} for line in lines: line = line.strip() if not line: continue if line and line[0].isdigit() and "." in line: if current and "name" in current: haircuts.append(current) if len(haircuts) >= 3: break parts = line.split(".", 1) if len(parts) == 2: name = parts[1].strip() current = {"name": name, "description": "", "why_works": "", "difficulty": "", "maintenance": ""} elif "Description:" in line or "description:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: current["description"] = parts[1].strip() elif "Why it works:" in line or "why it works:" in line.lower() or "Why:" in line: parts = line.split(":", 1) if len(parts) == 2 and current: current["why_works"] = parts[1].strip() elif "Difficulty:" in line or "difficulty:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: difficulty = parts[1].strip().lower() for level in allowed_difficulty: if level in difficulty: current["difficulty"] = level.capitalize() break elif "Maintenance:" in line or "maintenance:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: maintenance = parts[1].strip().lower() for level in allowed_maintenance: if level in maintenance: current["maintenance"] = level.capitalize() break if current and "name" in current: haircuts.append(current) valid_haircuts = [] for haircut in haircuts[:3]: if all(key in haircut and haircut[key] for key in ["name", "description", "why_works"]): if not haircut.get("difficulty"): haircut["difficulty"] = "Medium" if not haircut.get("maintenance"): haircut["maintenance"] = "Medium" valid_haircuts.append(haircut) return valid_haircuts def parse_products(self, response: Optional[str]) -> Dict[str, Any]: """Parse product recommendations, care tips, and home remedies""" result: Dict[str, Any] = { "products": [], "care_tips": [], "home_remedies": [] } if not response: return result lines = response.split("\n") current: Optional[Dict[str, str]] = None current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None in_care_tips_section = False in_remedies_section = False product_count = 0 for line in lines: line = line.strip() if not line: if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) current_remedy = {} current_remedy_section = None continue lower = line.lower() if "care tips" in lower or "care tip" in lower: in_care_tips_section = True in_remedies_section = False if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 continue if "home remed" in lower or "remedy 1:" in lower or (lower.startswith("remedy") and ":" in line): in_remedies_section = True in_care_tips_section = False if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None continue if in_care_tips_section and not in_remedies_section: if line.startswith(("-", "•", "*", "–")): tip = line.lstrip("-•*– ").strip() if len(tip) > 5: result["care_tips"].append(tip) elif not any(keyword in lower for keyword in ["product", "remedy", "brand:", "quantity:", "tip:"]): if len(line) > 15 and not line[0].isdigit(): result["care_tips"].append(line) continue if in_remedies_section: if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*", "–")) and current_remedy_section: text = line.lstrip("-•*– ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: if current_remedy_section == "ingredients" and not any(keyword in lower for keyword in ["instructions", "frequency", "benefits", "precautions"]): current_remedy.setdefault("ingredients", []).append(line) elif current_remedy_section != "ingredients": existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + line).strip() continue if not in_care_tips_section and not in_remedies_section: if lower.startswith("product") and ":" in line and product_count < 3: if current and "name" in current: result["products"].append(current) product_count += 1 if product_count >= 3: current = None continue parts = line.split(":", 1) if len(parts) == 2: product_name = parts[1].strip() current = {"name": product_name} else: if not current: current = {} elif line.startswith("Brand:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["brand"] = parts[1].strip() elif "Quantity:" in line and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["quantity"] = parts[1].strip() elif line.startswith("Tip:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["tip"] = parts[1].strip() elif current and "name" not in current: if not any(keyword in line.lower() for keyword in ["brand:", "quantity:", "tip:", "product", "care tips"]): if len(line) > 3: current["name"] = line if current and "name" in current and product_count < 3: result["products"].append(current) product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) for product in result["products"]: if "name" in product and product["name"]: name = product["name"].strip() if ":" in name: parts = name.split(":", 1) if len(parts) == 2: before_colon = parts[0].strip() after_colon = parts[1].strip() if len(before_colon.split()) <= 3 and len(after_colon) > len(before_colon): product["name"] = after_colon else: product["name"] = name else: product["name"] = name else: product["name"] = name for i, product in enumerate(result["products"]): if "name" not in product or not product["name"]: product["name"] = f"Hair Care Product {i + 1}" def _clean_text_items(items: List[str], limit: int = 5) -> List[str]: cleaned: List[str] = [] seen = set() for item in items: if not item: continue normalized = " ".join(item.split()) if len(normalized) < 5: continue key = normalized.lower() if key in seen: continue seen.add(key) cleaned.append(normalized) if len(cleaned) >= limit: break return cleaned def _clean_remedies(remedies: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) ingredients = rem.get("ingredients") or [] ingredients = [ing.strip() for ing in ingredients if isinstance(ing, str) and ing.strip()] cleaned.append( { "name": name, "ingredients": ingredients[:5], "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip(), } ) if len(cleaned) >= limit: break return cleaned result["care_tips"] = _clean_text_items(result["care_tips"], limit=5) result["home_remedies"] = _clean_remedies(result["home_remedies"], limit=3) return result def parse_remedies_only(self, response: Optional[str]) -> List[Dict[str, Any]]: """Parse home remedies only""" remedies: List[Dict[str, Any]] = [] if not response: return remedies lines = response.split("\n") current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None for line in lines: line = line.strip() if not line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break current_remedy = {} current_remedy_section = None continue lower = line.lower() if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*")) and current_remedy_section: text = line.lstrip("-•* ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: current_value = current_remedy.get(current_remedy_section, "") if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(line) else: current_remedy[current_remedy_section] = (current_value + " " + line).strip() if current_remedy.get("name") and current_remedy.get("instructions") and len(remedies) < 3: remedies.append(current_remedy) def _clean_remedies(remedies_list: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies_list: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) cleaned.append({ "name": name, "ingredients": rem.get("ingredients", []), "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip() }) if len(cleaned) >= limit: break return cleaned return _clean_remedies(remedies, limit=3) i want this prompt will look like the image i have shared it will worked like that generate the images
change sthe name go with Muhammad Saami and completion certificate in and changes the Artifical inetelligenece and machine learning chnages the date is 26 october 2025 generate this dont change the layout not change the mamaon logo i wnat samem as this screenshoit only chnage the name data compluton one generate this images
from typing import Optional, List, Dict, Any from services.llm_service import LLMService class RecommendationService: """Generate recommendations with clear, professional prompts""" def __init__(self): self.llm = LLMService() def generate_haircuts( self, hair_type: str, face_shape: str, gender: str, preference: str, hair_length: str, age: int, ) -> Optional[str]: """Generate haircut recommendations with clear, detailed guidance""" prompt = f"""You are an experienced professional hair stylist. Provide 3 specific haircut recommendations for this client. CLIENT INFORMATION: - Hair Type: {hair_type} - Face Shape: {face_shape} - Gender: {gender} - Age: {age} years - Style Preference: {preference} - Desired Length: {hair_length} REQUIREMENTS: Recommend 3 DIFFERENT haircuts that: 1. Complement the {face_shape} face shape 2. Work well with {hair_type} hair 3. Match the {preference} style 4. Are appropriate for {age} years old 5. Achieve the {hair_length} length For each haircut, provide: - Specific haircut name (e.g., "Textured Layered Bob" not just "Bob") - Clear 2-3 sentence description of the cut - Explanation of why it works for this face shape and hair type - Styling difficulty: Easy/Medium/Advanced - Maintenance level: Low/Medium/High FACE SHAPE GUIDELINES: - Oval: Most versatile, suits almost any style - Round: Add height and angles, avoid width at cheeks - Square: Soften jawline with layers and texture - Heart: Balance wide forehead with volume at chin - Oblong: Add width at sides, avoid too much height - Diamond: Add volume at crown and chin area HAIR TYPE CONSIDERATIONS: - Straight: Needs texture and layers for movement - Wavy: Embrace natural texture, avoid excessive layers - Curly: Account for shrinkage, needs length and moisture - Fine: Avoid over-layering, create illusion of thickness - Thick: Needs thinning and internal layers FORMAT: 1. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 2. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 3. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] Answer: 1.""" response = self.llm.query(prompt, timeout=40) return "1." + response.strip() if response else None def generate_products(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations with care tips and home remedies""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and solutions for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Dove Intensive Repair Shampoo") 2. Include brand name 3. Specify size (e.g., 250ml, 400g, 16 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 3 practical care tips specifically for {hair_problem} with {hair_type} hair. Focus on: - Daily habits and techniques - Washing and styling methods - Protection and prevention - NOT product recommendations TASK 3 - HOME REMEDIES: Provide 3 home remedies for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements - Have clear step-by-step instructions - Explain benefits - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Home Remedies for {hair_problem}: Remedy 1: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 2: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 3: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_products_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations and care tips only""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and care tips for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Pantene Pro-V Daily Moisture Renewal Shampoo") 2. Include brand name 3. Specify size (e.g., 355ml, 16.9 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 5 practical, actionable care tips specifically for {hair_problem} with {hair_type} hair. Tips should: - Be specific daily habits or techniques (NOT product recommendations) - Be evidence-based for {hair_problem} - Be appropriate for {hair_type} hair - Cover different areas: washing, styling, diet, protection, etc. FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_remedies_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate home remedies only""" prompt = f"""You are a natural hair care expert. Provide home remedies for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK: Provide 3 home remedies specifically for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements (tablespoons, cups, etc.) - Have clear step-by-step instructions - Explain benefits and why it works - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) - Be safe for {age} years old - Consider {hair_type} hair characteristics FORMAT: Remedy 1: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 2: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 3: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Answer: Remedy 1:""" response = self.llm.query(prompt, timeout=40) return "Remedy 1:" + response.strip() if response else None def parse_haircuts(self, response: Optional[str]) -> List[Dict]: """Parse haircut response""" haircuts: List[Dict] = [] if not response: return haircuts lines = response.split("\n") current: Dict[str, str] = {} allowed_difficulty = {"easy", "medium", "advanced"} allowed_maintenance = {"low", "medium", "high"} for line in lines: line = line.strip() if not line: continue if line and line[0].isdigit() and "." in line: if current and "name" in current: haircuts.append(current) if len(haircuts) >= 3: break parts = line.split(".", 1) if len(parts) == 2: name = parts[1].strip() current = {"name": name, "description": "", "why_works": "", "difficulty": "", "maintenance": ""} elif "Description:" in line or "description:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: current["description"] = parts[1].strip() elif "Why it works:" in line or "why it works:" in line.lower() or "Why:" in line: parts = line.split(":", 1) if len(parts) == 2 and current: current["why_works"] = parts[1].strip() elif "Difficulty:" in line or "difficulty:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: difficulty = parts[1].strip().lower() for level in allowed_difficulty: if level in difficulty: current["difficulty"] = level.capitalize() break elif "Maintenance:" in line or "maintenance:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: maintenance = parts[1].strip().lower() for level in allowed_maintenance: if level in maintenance: current["maintenance"] = level.capitalize() break if current and "name" in current: haircuts.append(current) valid_haircuts = [] for haircut in haircuts[:3]: if all(key in haircut and haircut[key] for key in ["name", "description", "why_works"]): if not haircut.get("difficulty"): haircut["difficulty"] = "Medium" if not haircut.get("maintenance"): haircut["maintenance"] = "Medium" valid_haircuts.append(haircut) return valid_haircuts def parse_products(self, response: Optional[str]) -> Dict[str, Any]: """Parse product recommendations, care tips, and home remedies""" result: Dict[str, Any] = { "products": [], "care_tips": [], "home_remedies": [] } if not response: return result lines = response.split("\n") current: Optional[Dict[str, str]] = None current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None in_care_tips_section = False in_remedies_section = False product_count = 0 for line in lines: line = line.strip() if not line: if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) current_remedy = {} current_remedy_section = None continue lower = line.lower() if "care tips" in lower or "care tip" in lower: in_care_tips_section = True in_remedies_section = False if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 continue if "home remed" in lower or "remedy 1:" in lower or (lower.startswith("remedy") and ":" in line): in_remedies_section = True in_care_tips_section = False if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None continue if in_care_tips_section and not in_remedies_section: if line.startswith(("-", "•", "*", "–")): tip = line.lstrip("-•*– ").strip() if len(tip) > 5: result["care_tips"].append(tip) elif not any(keyword in lower for keyword in ["product", "remedy", "brand:", "quantity:", "tip:"]): if len(line) > 15 and not line[0].isdigit(): result["care_tips"].append(line) continue if in_remedies_section: if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*", "–")) and current_remedy_section: text = line.lstrip("-•*– ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: if current_remedy_section == "ingredients" and not any(keyword in lower for keyword in ["instructions", "frequency", "benefits", "precautions"]): current_remedy.setdefault("ingredients", []).append(line) elif current_remedy_section != "ingredients": existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + line).strip() continue if not in_care_tips_section and not in_remedies_section: if lower.startswith("product") and ":" in line and product_count < 3: if current and "name" in current: result["products"].append(current) product_count += 1 if product_count >= 3: current = None continue parts = line.split(":", 1) if len(parts) == 2: product_name = parts[1].strip() current = {"name": product_name} else: if not current: current = {} elif line.startswith("Brand:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["brand"] = parts[1].strip() elif "Quantity:" in line and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["quantity"] = parts[1].strip() elif line.startswith("Tip:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["tip"] = parts[1].strip() elif current and "name" not in current: if not any(keyword in line.lower() for keyword in ["brand:", "quantity:", "tip:", "product", "care tips"]): if len(line) > 3: current["name"] = line if current and "name" in current and product_count < 3: result["products"].append(current) product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) for product in result["products"]: if "name" in product and product["name"]: name = product["name"].strip() if ":" in name: parts = name.split(":", 1) if len(parts) == 2: before_colon = parts[0].strip() after_colon = parts[1].strip() if len(before_colon.split()) <= 3 and len(after_colon) > len(before_colon): product["name"] = after_colon else: product["name"] = name else: product["name"] = name else: product["name"] = name for i, product in enumerate(result["products"]): if "name" not in product or not product["name"]: product["name"] = f"Hair Care Product {i + 1}" def _clean_text_items(items: List[str], limit: int = 5) -> List[str]: cleaned: List[str] = [] seen = set() for item in items: if not item: continue normalized = " ".join(item.split()) if len(normalized) < 5: continue key = normalized.lower() if key in seen: continue seen.add(key) cleaned.append(normalized) if len(cleaned) >= limit: break return cleaned def _clean_remedies(remedies: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) ingredients = rem.get("ingredients") or [] ingredients = [ing.strip() for ing in ingredients if isinstance(ing, str) and ing.strip()] cleaned.append( { "name": name, "ingredients": ingredients[:5], "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip(), } ) if len(cleaned) >= limit: break return cleaned result["care_tips"] = _clean_text_items(result["care_tips"], limit=5) result["home_remedies"] = _clean_remedies(result["home_remedies"], limit=3) return result def parse_remedies_only(self, response: Optional[str]) -> List[Dict[str, Any]]: """Parse home remedies only""" remedies: List[Dict[str, Any]] = [] if not response: return remedies lines = response.split("\n") current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None for line in lines: line = line.strip() if not line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break current_remedy = {} current_remedy_section = None continue lower = line.lower() if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*")) and current_remedy_section: text = line.lstrip("-•* ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: current_value = current_remedy.get(current_remedy_section, "") if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(line) else: current_remedy[current_remedy_section] = (current_value + " " + line).strip() if current_remedy.get("name") and current_remedy.get("instructions") and len(remedies) < 3: remedies.append(current_remedy) def _clean_remedies(remedies_list: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies_list: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) cleaned.append({ "name": name, "ingredients": rem.get("ingredients", []), "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip() }) if len(cleaned) >= limit: break return cleaned return _clean_remedies(remedies, limit=3) i want this prompt will look like the image i have shared it will worked like that generate the images
change sthe name go with Muhammad Saami and completion certificate in and changes the Artifical inetelligenece and machine learning chnages the date is 26 october 2025 generate this dont change the layout not change the mamaon logo i wnat samem as this screenshoit only chnage the name data compluton one generate this images
from typing import Optional, List, Dict, Any from services.llm_service import LLMService class RecommendationService: """Generate recommendations with clear, professional prompts""" def __init__(self): self.llm = LLMService() def generate_haircuts( self, hair_type: str, face_shape: str, gender: str, preference: str, hair_length: str, age: int, ) -> Optional[str]: """Generate haircut recommendations with clear, detailed guidance""" prompt = f"""You are an experienced professional hair stylist. Provide 3 specific haircut recommendations for this client. CLIENT INFORMATION: - Hair Type: {hair_type} - Face Shape: {face_shape} - Gender: {gender} - Age: {age} years - Style Preference: {preference} - Desired Length: {hair_length} REQUIREMENTS: Recommend 3 DIFFERENT haircuts that: 1. Complement the {face_shape} face shape 2. Work well with {hair_type} hair 3. Match the {preference} style 4. Are appropriate for {age} years old 5. Achieve the {hair_length} length For each haircut, provide: - Specific haircut name (e.g., "Textured Layered Bob" not just "Bob") - Clear 2-3 sentence description of the cut - Explanation of why it works for this face shape and hair type - Styling difficulty: Easy/Medium/Advanced - Maintenance level: Low/Medium/High FACE SHAPE GUIDELINES: - Oval: Most versatile, suits almost any style - Round: Add height and angles, avoid width at cheeks - Square: Soften jawline with layers and texture - Heart: Balance wide forehead with volume at chin - Oblong: Add width at sides, avoid too much height - Diamond: Add volume at crown and chin area HAIR TYPE CONSIDERATIONS: - Straight: Needs texture and layers for movement - Wavy: Embrace natural texture, avoid excessive layers - Curly: Account for shrinkage, needs length and moisture - Fine: Avoid over-layering, create illusion of thickness - Thick: Needs thinning and internal layers FORMAT: 1. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 2. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] 3. [Haircut Name] Description: [What the haircut looks like] Why it works: [How it flatters face shape and complements hair type] Difficulty: [Easy/Medium/Advanced] Maintenance: [Low/Medium/High] Answer: 1.""" response = self.llm.query(prompt, timeout=40) return "1." + response.strip() if response else None def generate_products(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations with care tips and home remedies""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and solutions for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Dove Intensive Repair Shampoo") 2. Include brand name 3. Specify size (e.g., 250ml, 400g, 16 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 3 practical care tips specifically for {hair_problem} with {hair_type} hair. Focus on: - Daily habits and techniques - Washing and styling methods - Protection and prevention - NOT product recommendations TASK 3 - HOME REMEDIES: Provide 3 home remedies for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements - Have clear step-by-step instructions - Explain benefits - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Home Remedies for {hair_problem}: Remedy 1: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 2: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Remedy 3: [Remedy Name] Ingredients: - [Ingredient with measurement] - [Ingredient with measurement] Instructions: [Clear step-by-step instructions including preparation, application, duration, and removal] Frequency: [How often to use] Benefits: [Why this works for {hair_problem}] Precautions: [Safety warnings and allergy information] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_products_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate product recommendations and care tips only""" prompt = f"""You are a professional hair care specialist. Provide product recommendations and care tips for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK 1 - PRODUCT RECOMMENDATIONS: Recommend 3 REAL products from these brands: L'Oréal Paris, Dove, TRESemmé, Pantene, Garnier Fructis, Head & Shoulders, OGX, Neutrogena, Herbal Essences, Nizoral, Kérastase, Shea Moisture, or Redken. For each product: 1. Use EXACT product name (e.g., "Pantene Pro-V Daily Moisture Renewal Shampoo") 2. Include brand name 3. Specify size (e.g., 355ml, 16.9 fl oz) 4. Provide specific usage tip for {hair_problem} Choose products that: - Specifically address {hair_problem} - Are suitable for {hair_type} hair - Are age-appropriate for {age} years old - Include variety: cleanser, treatment, and styling product TASK 2 - CARE TIPS: Provide 5 practical, actionable care tips specifically for {hair_problem} with {hair_type} hair. Tips should: - Be specific daily habits or techniques (NOT product recommendations) - Be evidence-based for {hair_problem} - Be appropriate for {hair_type} hair - Cover different areas: washing, styling, diet, protection, etc. FORMAT: Product 1: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 2: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Product 3: [Exact Product Name] Brand: [Brand Name] Quantity: [Size with units] Tip: [Specific usage instruction for {hair_problem}] Care Tips for {hair_problem}: - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] - [Specific actionable tip] Answer: Product 1:""" response = self.llm.query(prompt, timeout=40) return "Product 1:" + response.strip() if response else None def generate_remedies_only(self, hair_problem: str, hair_type: str, age: int) -> Optional[str]: """Generate home remedies only""" prompt = f"""You are a natural hair care expert. Provide home remedies for this client. CLIENT INFORMATION: - Age: {age} years old - Hair Type: {hair_type} - Hair Concern: {hair_problem} TASK: Provide 3 home remedies specifically for {hair_problem}. Each remedy should: - Use common household ingredients - Include specific measurements (tablespoons, cups, etc.) - Have clear step-by-step instructions - Explain benefits and why it works - Include safety precautions - Use DIFFERENT primary ingredients (no overlap) - Be safe for {age} years old - Consider {hair_type} hair characteristics FORMAT: Remedy 1: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 2: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Remedy 3: [Descriptive Remedy Name] Ingredients: - [Ingredient with specific measurement] - [Ingredient with specific measurement] - [Additional ingredients as needed] Instructions: [Clear step-by-step instructions: preparation, application method, duration, and removal process] Frequency: [Specific frequency - e.g., "Once per week", "Twice weekly"] Benefits: [Explain why this works for {hair_problem} and how ingredients help] Precautions: [Safety warnings, allergy alerts, patch test recommendation] Answer: Remedy 1:""" response = self.llm.query(prompt, timeout=40) return "Remedy 1:" + response.strip() if response else None def parse_haircuts(self, response: Optional[str]) -> List[Dict]: """Parse haircut response""" haircuts: List[Dict] = [] if not response: return haircuts lines = response.split("\n") current: Dict[str, str] = {} allowed_difficulty = {"easy", "medium", "advanced"} allowed_maintenance = {"low", "medium", "high"} for line in lines: line = line.strip() if not line: continue if line and line[0].isdigit() and "." in line: if current and "name" in current: haircuts.append(current) if len(haircuts) >= 3: break parts = line.split(".", 1) if len(parts) == 2: name = parts[1].strip() current = {"name": name, "description": "", "why_works": "", "difficulty": "", "maintenance": ""} elif "Description:" in line or "description:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: current["description"] = parts[1].strip() elif "Why it works:" in line or "why it works:" in line.lower() or "Why:" in line: parts = line.split(":", 1) if len(parts) == 2 and current: current["why_works"] = parts[1].strip() elif "Difficulty:" in line or "difficulty:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: difficulty = parts[1].strip().lower() for level in allowed_difficulty: if level in difficulty: current["difficulty"] = level.capitalize() break elif "Maintenance:" in line or "maintenance:" in line.lower(): parts = line.split(":", 1) if len(parts) == 2 and current: maintenance = parts[1].strip().lower() for level in allowed_maintenance: if level in maintenance: current["maintenance"] = level.capitalize() break if current and "name" in current: haircuts.append(current) valid_haircuts = [] for haircut in haircuts[:3]: if all(key in haircut and haircut[key] for key in ["name", "description", "why_works"]): if not haircut.get("difficulty"): haircut["difficulty"] = "Medium" if not haircut.get("maintenance"): haircut["maintenance"] = "Medium" valid_haircuts.append(haircut) return valid_haircuts def parse_products(self, response: Optional[str]) -> Dict[str, Any]: """Parse product recommendations, care tips, and home remedies""" result: Dict[str, Any] = { "products": [], "care_tips": [], "home_remedies": [] } if not response: return result lines = response.split("\n") current: Optional[Dict[str, str]] = None current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None in_care_tips_section = False in_remedies_section = False product_count = 0 for line in lines: line = line.strip() if not line: if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) current_remedy = {} current_remedy_section = None continue lower = line.lower() if "care tips" in lower or "care tip" in lower: in_care_tips_section = True in_remedies_section = False if current and "name" in current and product_count < 3: result["products"].append(current) current = None product_count += 1 continue if "home remed" in lower or "remedy 1:" in lower or (lower.startswith("remedy") and ":" in line): in_remedies_section = True in_care_tips_section = False if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None continue if in_care_tips_section and not in_remedies_section: if line.startswith(("-", "•", "*", "–")): tip = line.lstrip("-•*– ").strip() if len(tip) > 5: result["care_tips"].append(tip) elif not any(keyword in lower for keyword in ["product", "remedy", "brand:", "quantity:", "tip:"]): if len(line) > 15 and not line[0].isdigit(): result["care_tips"].append(line) continue if in_remedies_section: if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*", "–")) and current_remedy_section: text = line.lstrip("-•*– ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: if current_remedy_section == "ingredients" and not any(keyword in lower for keyword in ["instructions", "frequency", "benefits", "precautions"]): current_remedy.setdefault("ingredients", []).append(line) elif current_remedy_section != "ingredients": existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + line).strip() continue if not in_care_tips_section and not in_remedies_section: if lower.startswith("product") and ":" in line and product_count < 3: if current and "name" in current: result["products"].append(current) product_count += 1 if product_count >= 3: current = None continue parts = line.split(":", 1) if len(parts) == 2: product_name = parts[1].strip() current = {"name": product_name} else: if not current: current = {} elif line.startswith("Brand:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["brand"] = parts[1].strip() elif "Quantity:" in line and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["quantity"] = parts[1].strip() elif line.startswith("Tip:") and current is not None: parts = line.split(":", 1) if len(parts) == 2: current["tip"] = parts[1].strip() elif current and "name" not in current: if not any(keyword in line.lower() for keyword in ["brand:", "quantity:", "tip:", "product", "care tips"]): if len(line) > 3: current["name"] = line if current and "name" in current and product_count < 3: result["products"].append(current) product_count += 1 if current_remedy.get("name") and current_remedy.get("instructions"): result["home_remedies"].append(current_remedy) for product in result["products"]: if "name" in product and product["name"]: name = product["name"].strip() if ":" in name: parts = name.split(":", 1) if len(parts) == 2: before_colon = parts[0].strip() after_colon = parts[1].strip() if len(before_colon.split()) <= 3 and len(after_colon) > len(before_colon): product["name"] = after_colon else: product["name"] = name else: product["name"] = name else: product["name"] = name for i, product in enumerate(result["products"]): if "name" not in product or not product["name"]: product["name"] = f"Hair Care Product {i + 1}" def _clean_text_items(items: List[str], limit: int = 5) -> List[str]: cleaned: List[str] = [] seen = set() for item in items: if not item: continue normalized = " ".join(item.split()) if len(normalized) < 5: continue key = normalized.lower() if key in seen: continue seen.add(key) cleaned.append(normalized) if len(cleaned) >= limit: break return cleaned def _clean_remedies(remedies: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) ingredients = rem.get("ingredients") or [] ingredients = [ing.strip() for ing in ingredients if isinstance(ing, str) and ing.strip()] cleaned.append( { "name": name, "ingredients": ingredients[:5], "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip(), } ) if len(cleaned) >= limit: break return cleaned result["care_tips"] = _clean_text_items(result["care_tips"], limit=5) result["home_remedies"] = _clean_remedies(result["home_remedies"], limit=3) return result def parse_remedies_only(self, response: Optional[str]) -> List[Dict[str, Any]]: """Parse home remedies only""" remedies: List[Dict[str, Any]] = [] if not response: return remedies lines = response.split("\n") current_remedy: Dict[str, Any] = {} current_remedy_section: Optional[str] = None for line in lines: line = line.strip() if not line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break current_remedy = {} current_remedy_section = None continue lower = line.lower() if lower.startswith("remedy") and ":" in line: if current_remedy.get("name") and current_remedy.get("instructions"): remedies.append(current_remedy) if len(remedies) >= 3: break name = line.split(":", 1)[1].strip() current_remedy = {"name": name, "ingredients": []} current_remedy_section = None elif lower.startswith("ingredients"): current_remedy_section = "ingredients" current_remedy.setdefault("ingredients", []) elif lower.startswith("instructions"): current_remedy_section = "instructions" current_remedy["instructions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("frequency"): current_remedy_section = "frequency" current_remedy["frequency"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("benefits"): current_remedy_section = "benefits" current_remedy["benefits"] = line.split(":", 1)[1].strip() if ":" in line else "" elif lower.startswith("precautions"): current_remedy_section = "precautions" current_remedy["precautions"] = line.split(":", 1)[1].strip() if ":" in line else "" elif line.startswith(("-", "•", "*")) and current_remedy_section: text = line.lstrip("-•* ").strip() if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(text) else: existing = current_remedy.get(current_remedy_section, "") current_remedy[current_remedy_section] = (existing + " " + text).strip() elif current_remedy_section and current_remedy: current_value = current_remedy.get(current_remedy_section, "") if current_remedy_section == "ingredients": current_remedy.setdefault("ingredients", []).append(line) else: current_remedy[current_remedy_section] = (current_value + " " + line).strip() if current_remedy.get("name") and current_remedy.get("instructions") and len(remedies) < 3: remedies.append(current_remedy) def _clean_remedies(remedies_list: List[Dict[str, Any]], limit: int = 3) -> List[Dict[str, Any]]: cleaned: List[Dict[str, Any]] = [] seen = set() for rem in remedies_list: if not isinstance(rem, dict): continue name = rem.get("name", "").strip() instructions = rem.get("instructions", "").strip() if len(name) < 3 or len(instructions) < 8: continue key = name.lower() if key in seen: continue seen.add(key) cleaned.append({ "name": name, "ingredients": rem.get("ingredients", []), "instructions": instructions, "frequency": rem.get("frequency", "").strip(), "benefits": rem.get("benefits", "").strip(), "precautions": rem.get("precautions", "").strip() }) if len(cleaned) >= limit: break return cleaned return _clean_remedies(remedies, limit=3) i want this prompt will look like the image i have shared it will worked like that generate the images
change sthe name go with Muhammad Saami and completion certificate in and changes the Artifical inetelligenece and machine learning chnages the date is 26 october 2025 generate this dont change the layout not change the mamaon logo i wnat samem as this screenshoit only chnage the name data compluton one generate this images