Create app.py

app.py

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+import random
+import uuid
+import json
+from transformers import AutoTokenizer, AutoModelForCausalLM
+
+
+# Load the tokenizer and model without FlashAttention2
+tokenizer = AutoTokenizer.from_pretrained("microsoft/Phi-3.5-vision-instruct")
+
+# Disable FlashAttention2 by forcing default attention
+config = {
+    'attn_implementation': 'default'
+}
+
+model = AutoModelForCausalLM.from_pretrained(
+    "microsoft/Phi-3.5-vision-instruct",
+    trust_remote_code=True,
+    **config
+)
+
+
+
+
+# Function to generate text using the model
+def generate_text(prompt):
+    inputs = tokenizer(prompt, return_tensors="pt")
+    outputs = model.generate(inputs['input_ids'], max_length=150)
+    return tokenizer.decode(outputs[0], skip_special_tokens=True)
+
+# Lists for random selection
+interest_list = ["networking", "dealMaking"]
+personal_interest_list = [
+    "Drawing", "Cooking", "Foodie", "Board Gaming", "Card games", "Checkers", "Chess", 
+    "PC gaming", "Puzzle solving", "Video gaming", "Reading", "Science experiments", 
+    "Magic and illusion", "Stand-up comedy", "Walking", "Beer brewing", "Gourmet food exploration", 
+    "Mixology", "Wine tasting"
+]
+professional_interest_list = [
+    "Building a customer-centric culture", "Community Building", "Community Management", 
+    "Delivering exceptional customer service", "Ensuring product/service quality", 
+    "Handling customer complaints and feedback"
+]
+
+# Function to generate random profile with intelligent education/professional details
+def generate_intelligent_profile():
+    # Randomly select interests and location
+    profile = {
+        "_id": str(uuid.uuid4()),  # Generate random ID
+        "latitude": random.uniform(-90, 90),  # Random latitude
+        "longitude": random.uniform(-180, 180),  # Random longitude
+        "interest": random.sample(interest_list, random.randint(1, len(interest_list))),  # Random interests
+        "personalInterest": random.sample(personal_interest_list, random.randint(3, 7)),  # Random personal interests
+        "professionalInterest": random.sample(professional_interest_list, random.randint(3, 5))  # Random professional interests
+    }
+    
+    # Generate intelligent educational details using the model
+    education_prompt = "Generate an educational background for a professional profile with relevant qualifications."
+    profile["educationalDetails"] = [generate_text(education_prompt)]
+    
+    # Generate intelligent professional details using the model
+    professional_prompt = "Generate a professional career summary for a profile with achievements and roles."
+    profile["professionalDetails"] = [generate_text(professional_prompt)]
+    
+    return profile
+
+# Function to generate multiple profiles
+def generate_profiles(num_profiles=5):
+    profiles = [generate_intelligent_profile() for _ in range(num_profiles)]
+    return {"data": profiles}
+
+# Generate and print random intelligent profiles
+generated_profiles = generate_profiles(3)
+print(json.dumps(generated_profiles, indent=4))