Final Commit

LICENSE

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2024 PSYCHEPLOT
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

@@ -1,14 +1,28 @@
----
-title: PSYCHEPLOT
-emoji: 🏢
-colorFrom: pink
-colorTo: blue
-sdk: streamlit
-sdk_version: 1.44.1
-app_file: app.py
-pinned: false
-license: mit
-short_description: Personality Detection through Interactive Narrative Gen
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+# PSYCHEPLOT
+
+[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
+
+Interactive storytelling application with personality analysis.
+
+## Setup
+1. Clone the repository
+2. Install dependencies: `pip install -r requirements.txt`
+3. Add GROQ API key to Hugging Face Spaces secrets
+
+## Files
+- `app.py`: Main Streamlit application
+- `story_engine.py`: Story generation logic
+- `model.py`: Personality prediction model
+- `personality_profiles.json`: Personality type definitions
+
+## Models
+Make sure these files are included in the repository:
+- personality_rf_model.joblib
+- tfidf_vectorizer.joblib
+- label_encoder.joblib
+
+## Features
+- Multiple story genres
+- Dynamic story generation
+- Personality analysis
+- Real-time trait tracking

app.py

@@ -0,0 +1,211 @@
+import streamlit as st
+import os
+from dotenv import load_dotenv
+from story_engine import generate_story, continue_story
+from model import predict_personality
+
+# Load environment variables and set up API key first
+load_dotenv()
+
+# Get API key - handle both local development and Hugging Face Spaces
+try:
+    GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
+except:
+    GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+if not GROQ_API_KEY:
+    st.error("GROQ API Key not found. Please check your environment configuration.")
+    st.stop()
+
+os.environ["GROQ_API_KEY"] = GROQ_API_KEY
+os.environ["STREAMLIT_WATCHER_TYPE"] = "none"
+
+# Initialize session state variables
+if "selected_genre" not in st.session_state:
+    st.session_state.selected_genre = None
+if "story_history" not in st.session_state:
+    st.session_state.story_history = []
+if "story_options" not in st.session_state:
+    st.session_state.story_options = []
+if "choice_history" not in st.session_state:
+    st.session_state.choice_history = []
+    
+# Track trait counts across choices
+if "trait_counts" not in st.session_state:
+    st.session_state.trait_counts = {
+        "O": 0,  # Openness
+        "C": 0,  # Conscientiousness
+        "E": 0,  # Extraversion
+        "A": 0,  # Agreeableness
+        "N": 0   # Neuroticism
+    }
+    
+# Track personality predictions for each step
+if "personality_history" not in st.session_state:
+    st.session_state.personality_history = []
+
+st.set_page_config(layout="wide", page_title="PSYCHEPLOT", page_icon="👾")
+
+st.title("👾 PSYCHEPLOT")
+st.header("Select your genre")
+
+if st.session_state.selected_genre is None:
+    col1, col2, col3, col4 = st.columns(4)
+    with col1:
+        if st.button("Crime"):
+            st.session_state.selected_genre = "Crime"
+            story_segment, options = generate_story("Crime", st.session_state.story_history)
+            st.session_state.story_options = options
+    with col2:
+        if st.button("Comedy"):
+            st.session_state.selected_genre = "Comedy"
+            story_segment, options = generate_story("Comedy", st.session_state.story_history)
+            st.session_state.story_options = options
+    with col3:
+        if st.button("Dark"):
+            st.session_state.selected_genre = "Dark"
+            story_segment, options = generate_story("Dark", st.session_state.story_history)
+            st.session_state.story_options = options
+    with col4:
+        if st.button("Educational"):
+            st.session_state.selected_genre = "Educational"
+            story_segment, options = generate_story("Educational", st.session_state.story_history)
+            st.session_state.story_options = options
+
+if "step_count" not in st.session_state:
+    st.session_state.step_count = 0
+if "chosen_options" not in st.session_state:
+    st.session_state.chosen_options = []
+
+def update_personality_traits(choice_text):
+    """Update trait counts based on the current choice"""
+    result = predict_personality(choice_text)
+    st.session_state.personality_history.append(result)
+    
+    # Custom thresholds for each trait
+    thresholds = {
+        "O": 0.20,  # Openness
+        "C": 0.20,  # Conscientiousness
+        "E": 0.15,  # Extraversion
+        "A": 0.15,  # Agreeableness
+        "N": 0.30   # Higher threshold for Neuroticism
+    }
+    
+    # Update trait counts with custom thresholds
+    for trait, score in result["traits"].items():
+        if score >= thresholds[trait]:
+            st.session_state.trait_counts[trait] += 1
+    
+    return result
+
+def get_final_personality():
+    """Calculate final personality based on accumulated trait counts"""
+    from model import PERSONALITY_MAP, DOMINANT_TYPES
+    traits = ["O", "C", "E", "A", "N"]
+    trait_scores = {}
+    
+    # Calculate scores
+    for trait in traits:
+        count = st.session_state.trait_counts[trait]
+        score = count / st.session_state.step_count
+        trait_scores[trait] = score
+    
+    # Find potential dominant traits
+    max_score = max(trait_scores.values())
+    dominant_candidates = [
+        trait for trait, score in trait_scores.items()
+        if abs(score - max_score) < 0.01
+    ]
+    
+    # Check if there's a clear dominant trait
+    if len(dominant_candidates) == 1:
+        dominant_trait = dominant_candidates[0]
+        other_scores = [score for trait, score in trait_scores.items() 
+                       if trait != dominant_trait]
+        max_other = max(other_scores)
+        
+        if max_score >= 0.5 and (max_score - max_other) >= 0.2:
+            profile = DOMINANT_TYPES[dominant_trait]
+            return {
+                "type": dominant_trait,
+                "category": "Dominant Trait",
+                "label": profile["label"],
+                "description": profile["description"],
+                "traits": trait_scores
+            }
+    
+    # If no clear dominant trait, create binary code and use personality map
+    binary_code = "".join(["H" if trait_scores[trait] > 0.3 else "L" 
+                          for trait in traits])
+    
+    profile = PERSONALITY_MAP.get(binary_code, {
+        "label": "Unique Profile",
+        "description": "A distinctive combination of personality traits that creates a unique character profile."
+    })
+    
+    return {
+        "type": binary_code,
+        "category": "Mixed Profile",
+        "label": profile["label"],
+        "description": profile["description"],
+        "traits": trait_scores
+    }
+
+if st.session_state.selected_genre:
+    st.subheader(f"📖 Story Begins ({st.session_state.selected_genre} story):")
+    for i, segment in enumerate(st.session_state.story_history):
+        cleaned_segment = "\n".join([line for line in segment.split("\n") if not line.startswith(("1.", "2.", "3.", "4."))])
+        st.write(cleaned_segment)
+        if i < len(st.session_state.story_history) - 1:
+            st.divider()
+    
+    if st.session_state.step_count < 6:
+        st.subheader("🔮 Choose the next step:")
+        for option in st.session_state.story_options:
+            if st.button(option):
+                story_segment, options = continue_story(st.session_state.story_history, option)
+                st.session_state.story_options = options
+                
+                # Store the choice
+                st.session_state.choice_history.append({
+                    "step": st.session_state.step_count + 1,
+                    "chosen_option": option
+                })
+                st.session_state.chosen_options.append(option)
+                
+                # Update personality prediction after this choice
+                choice_text = f"Step {st.session_state.step_count + 1}: {option}"
+                update_personality_traits(choice_text)
+                
+                st.session_state.step_count += 1
+                st.rerun()
+    else:
+        # Final personality calculation based on accumulated trait counts
+        result = get_final_personality()
+
+        st.subheader("🧠 Final Personality Assessment:")
+        st.markdown(f"**Type:** `{result['type']}` ({result['category']})")
+        st.markdown(f"**Label:** {result['label']}")
+        st.markdown("**Description:**")
+        st.write(result['description'])
+
+        st.divider()
+        st.markdown("### 📊 Trait Breakdown")
+        for trait, score in result["traits"].items():
+            count = st.session_state.trait_counts[trait]
+            st.progress(score, text=f"{trait}: {score:.2f} ({count}/{st.session_state.step_count} choices)")
+
+        # Show choices
+        st.divider()
+        with st.expander("📜 Your Story Choices"):
+            choices_text = "\n".join([f"Step {choice['step']}: {choice['chosen_option']}" for choice in st.session_state.choice_history])
+            st.text(choices_text)
+        
+        # Show personality evolution
+        with st.expander("📈 Personality Evolution"):
+            for i, personality in enumerate(st.session_state.personality_history):
+                st.markdown(f"**Step {i+1}**: {personality['type']} - {personality['label']}")
+                cols = st.columns(5)
+                for j, (trait, score) in enumerate(personality['traits'].items()):
+                    with cols[j]:
+                        st.progress(score, text=f"{trait}: {score:.2f}")

label_encoder.joblib

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+version https://git-lfs.github.com/spec/v1
+oid sha256:55e7a831ac825d0ba41c0e985ab58cb8127232091c76d229de76d1197398e5ae
+size 615

model.py

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+import joblib
+import json
+import re
+
+# Load the models
+rf_model = joblib.load("personality_rf_model.joblib")
+vectorizer = joblib.load("tfidf_vectorizer.joblib")
+label_encoder = joblib.load("label_encoder.joblib")
+
+# Load personality profiles
+with open("personality_profiles.json", "r") as f:
+    PERSONALITY_MAP = json.load(f)
+
+# Define dominant types
+DOMINANT_TYPES = {
+    "O": {
+        "label": "High Openness",
+        "description": "Curious, imaginative, and open to new experiences. Thrives in creative and unconventional environments."
+    },
+    "C": {
+        "label": "High Conscientiousness",
+        "description": "Organized, dependable, and goal-oriented. Strong sense of duty and self-discipline."
+    },
+    "E": {
+        "label": "High Extraversion",
+        "description": "Energetic, outgoing, and thrives on social interaction. Feeds off external stimulation."
+    },
+    "A": {
+        "label": "High Agreeableness",
+        "description": "Kind-hearted, empathetic, and cooperative. Seeks harmony and avoids conflict."
+    },
+    "N": {
+        "label": "High Neuroticism",
+        "description": "Emotionally sensitive, reactive, and prone to mood swings. Deeply introspective."
+    }
+}
+
+def preprocess_text(text):
+    """Preprocess text for prediction"""
+    text = text.lower()
+    text = re.sub(r'[^a-zA-Z\s]', '', text)
+    text = re.sub(r'\s+', ' ', text)
+    return text.strip()
+
+def predict_personality(choices_text):
+    """Predict personality based on choices text"""
+    try:
+        # Extract choice numbers from the text
+        choices = re.findall(r'Step \d+: (\d+)\.', choices_text)
+        
+        # Define trait mapping for each option number
+        trait_mapping = {
+            "1": "O",  # Openness
+            "2": "C",  # Conscientiousness
+            "3": "E",  # Extraversion/Agreeableness
+            "4": "N"   # Neuroticism
+        }
+        
+        # Initialize trait counts
+        trait_counts = {"O": 0, "C": 0, "E": 0, "A": 0, "N": 0}
+        total_choices = len(choices)
+        
+        # Count traits based on choices
+        for choice in choices:
+            if choice in trait_mapping:
+                trait = trait_mapping[choice]
+                trait_counts[trait] += 1
+                # Special case: option 3 contributes to both E and A
+                if choice == "3":
+                    trait_counts["A"] += 0.5  # Reduced weight for secondary trait
+        
+        # Calculate trait scores as percentages
+        trait_scores = {
+            trait: count/total_choices 
+            for trait, count in trait_counts.items()
+        } if total_choices > 0 else trait_counts
+        
+        # Find dominant trait(s) with stricter criteria
+        max_score = max(trait_scores.values())
+        
+        # Count traits that share the max score
+        max_score_traits = [
+            trait for trait, score in trait_scores.items() 
+            if abs(score - max_score) < 0.01  # Account for floating point comparison
+        ]
+        
+        # Only consider dominant if:
+        # 1. Single trait has highest score
+        # 2. Score is significantly higher than others (>= 0.5)
+        # 3. No other trait is close to the max score
+        if len(max_score_traits) == 1 and max_score >= 0.5:
+            dominant_trait = max_score_traits[0]
+            other_scores = [score for trait, score in trait_scores.items() 
+                          if trait != dominant_trait]
+            max_other = max(other_scores) if other_scores else 0
+            
+            if max_score - max_other >= 0.2:  # Must be significantly higher
+                profile = DOMINANT_TYPES[dominant_trait]
+                return {
+                    "type": dominant_trait,
+                    "category": "Dominant Trait",
+                    "label": profile["label"],
+                    "description": profile["description"],
+                    "traits": trait_scores
+                }
+
+        # If no clear dominant trait, use binary code
+        binary_code = "".join(["H" if trait_scores[trait] > 0.3 else "L" 
+                              for trait in ["O", "C", "E", "A", "N"]])  # Fixed order
+        
+        # Get profile from personality map
+        profile = PERSONALITY_MAP.get(binary_code, {
+            "label": "Mixed Profile",
+            "description": "A balanced combination of different personality traits."
+        })
+        
+        return {
+            "type": binary_code,
+            "category": "Mixed Profile",
+            "label": profile["label"],
+            "description": profile["description"],
+            "traits": trait_scores
+        }
+        
+    except Exception as e:
+        print(f"Error during prediction: {e}")
+        return {
+            "type": "ERROR",
+            "category": "Error",
+            "label": "Prediction Error",
+            "description": str(e),
+            "traits": {}
+        }
+
+# if __name__ == "__main__":
+#     example_text = "I enjoy meeting new people and trying new experiences"
+#     result = predict_personality(example_text)
+#     print(json.dumps(result, indent=2))

personality_profiles.json

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+{
+        "HHHHH": {
+          "label": "The Enlightened Leader",
+          "description": "Curious, disciplined, outgoing, kind, and emotionally aware. A natural leader with high emotional intelligence."
+        },
+        "HHHHL": {
+          "label": "The Visionary Diplomat",
+          "description": "Inventive, reliable, socially skilled, cooperative, and emotionally stable. Great at guiding others and building bridges."
+        },
+        "HHHLH": {
+          "label": "The Passionate Performer",
+          "description": "Creative, organized, charismatic, assertive, and emotionally expressive. Thrives in dynamic, public environments."
+        },
+        "HHHLL": {
+          "label": "The Independent Idealist",
+          "description": "Imaginative and structured, yet introverted and blunt. Strives for truth over harmony."
+        },
+        "HHLHH": {
+          "label": "The Charismatic Reactor",
+          "description": "Thoughtful and unconventional, struggles with emotional turbulence but excels at inspiring others."
+        },
+        "HHLHL": {
+          "label": "The Unpredictable Artist",
+          "description": "Highly creative and principled, but emotionally steady and often distant. Expresses through abstract forms."
+        },
+        "HHLLH": {
+          "label": "The Analytical Rebel",
+          "description": "Innovative and introverted, resistant to rules but deeply sensitive inside."
+        },
+        "HHLLL": {
+          "label": "The Detached Visionary",
+          "description": "Independent, logical, and emotionally distant. Values thought over connection."
+        },
+        "HLHHH": {
+          "label": "The Fiery Advocate",
+          "description": "Empathetic yet impulsive. Low on structure but high on social drive and emotional intensity."
+        },
+        "HLHHL": {
+          "label": "The Vibrant Connector",
+          "description": "Warm, spontaneous, and full of life. Prefers chaos over routine but deeply values harmony."
+        },
+        "HLHLH": {
+          "label": "The Empathetic Strategist",
+          "description": "Creative and emotionally insightful, yet assertive and unafraid of conflict. Balances heart and head."
+        },
+        "HLHLL": {
+          "label": "The Expressive Maverick",
+          "description": "Energetic and persuasive, but emotionally stable and unapologetically individualistic."
+        },
+        "HLLHH": {
+          "label": "The Sensitive Idealist",
+          "description": "Kind-hearted and emotionally intense, yet often disorganized and introspective."
+        },
+        "HLLHL": {
+          "label": "The Intuitive Wanderer",
+          "description": "Unconventional and curious with a soft demeanor. Dislikes routine and avoids conflict."
+        },
+        "HLLLH": {
+          "label": "The Lone Visionary",
+          "description": "Quiet, original, sensitive, and slightly chaotic. Expresses through solitude and deep thought."
+        },
+        "HLLLL": {
+          "label": "The Elusive Thinker",
+          "description": "Detached from structure and low in sociability, yet highly imaginative and philosophical."
+        },
+        "LHHHH": {
+          "label": "The Loyal Realist",
+          "description": "Grounded, dependable, and sensitive. Seeks harmony and stability in a chaotic world."
+        },
+        "LHHHL": {
+          "label": "The Social Strategist",
+          "description": "Disciplined, sociable, and emotionally grounded. Excels in managing group dynamics."
+        },
+        "LHHLH": {
+          "label": "The Compassionate Achiever",
+          "description": "Structured, ambitious, and sensitive to others’ needs. Driven by purpose and empathy."
+        },
+        "LHHLL": {
+          "label": "The Grounded Realist",
+          "description": "Practical and persistent. Values results, avoids drama, and prefers predictability."
+        },
+        "LHLHH": {
+          "label": "The Expressive Sentinel",
+          "description": "Emotionally in tune and supportive, but avoids chaos and prefers routine."
+        },
+        "LHLHL": {
+          "label": "The Warm Minimalist",
+          "description": "Reserved and steady, but deeply caring. Keeps things simple and values deep connections."
+        },
+        "LHLLH": {
+          "label": "The Pragmatic Thinker",
+          "description": "Introverted but deeply rational. Balanced emotionality and a strong moral compass."
+        },
+        "LHLLL": {
+          "label": "The Structured Observer",
+          "description": "Detail-oriented and organized, with a tendency toward solitude."
+        },
+        "LLHHH": {
+          "label": "The Tender Explorer",
+          "description": "Emotionally rich and adventurous, but often lacks follow-through. Guided by heart and curiosity."
+        },
+        "LLHHL": {
+          "label": "The Relational Drifter",
+          "description": "Compassionate and engaging, but scattered. Thrives in the moment, avoids hard rules."
+        },
+        "LLHLH": {
+          "label": "The Emotional Realist",
+          "description": "Feels deeply and sees clearly. Honest and loyal, but struggles with emotional regulation."
+        },
+        "LLHLL": {
+          "label": "The Gentle Disruptor",
+          "description": "Quietly rebellious, kind, and skeptical of systems. Doesn’t like to be boxed in."
+        },
+        "LLLHH": {
+          "label": "The Chaotic Thinker",
+          "description": "Unstructured, sensitive, and highly perceptive. Often lost in thought or feeling."
+        },
+        "LLLHL": {
+          "label": "The Quiet Helper",
+          "description": "Introverted and steady, avoids confrontation. Gentle and observant, a calming presence."
+        },
+        "LLLLH": {
+          "label": "The Internal Storm",
+          "description": "Low in structure and sociability, but emotionally intense. Often misunderstood but deeply insightful."
+        },
+        "LLLLL": {
+          "label": "The Detached Observer",
+          "description": "Low across the board. Independent and rational, but emotionally distant and withdrawn."
+        }
+  }
+  

personality_rf_model.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:e1a8e8bca637b5fbf193ed70ca19b5deb38aa2248a98c426b3cc095d69f81fc3
+size 11635057

requirements.txt

@@ -0,0 +1,6 @@
+streamlit
+groq
+python-dotenv
+joblib
+scikit-learn
+watchdog

story_engine.py

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+
+import os
+from groq import Groq
+from dotenv import load_dotenv
+import streamlit as st
+
+# Load environment variables
+load_dotenv()
+
+# Get API key - handle both local development and Hugging Face Spaces
+try:
+    # Try to get from Streamlit secrets (Hugging Face Spaces)
+    GROQ_API_KEY = st.secrets["GROQ_API_KEY"]
+except:
+    # Fallback to local .env file
+    GROQ_API_KEY = os.getenv("GROQ_API_KEY")
+
+if not GROQ_API_KEY:
+    raise Exception("GROQ API Key not found. Please check your environment configuration.")
+
+# Initialize Groq client
+client = Groq(api_key=GROQ_API_KEY)
+
+# Different story starts for each genre
+GENRE_STARTS = {
+    "Crime": "It's 11:00 pm on a winter night, you are standing next to a phone booth, you are witnessing a murder scene, and then the murderers see you standing behind the booth and watching the scene.",
+    "Comedy": "You accidentally walk into a top-secret government meeting, but instead of being arrested, they mistake you for their new intern. Now, you must pretend to know what you're doing.",
+    "Dark": "The last thing you remember is falling asleep in your bed, but now you wake up in an abandoned hospital with flickering lights and a note in your hand that says 'RUN'.",
+    "Educational": "A renowned scientist just discovered a way to time travel, and you're the first volunteer to test the machine. However, something goes wrong, and you end up in the year 3024."
+}
+
+def generate_story(genre, story_history):
+    try:
+        start_story = GENRE_STARTS.get(genre, "A new adventure begins...")
+        prompt = f"""
+        Write a story continuation and provide 4 options that map to specific personality traits:
+        Story start: {start_story}
+
+        Format:
+        [STORY]
+        Write the story continuation here (max 150 words)
+
+        [OPTIONS]
+        1. An option showing openness (creative, exploratory approach)
+        2. An option showing conscientiousness (methodical, careful approach)
+        3. An option showing extraversion and agreeableness (social, cooperative approach)
+        4. An option showing neuroticism (emotional, cautious approach)
+
+        Important: Present the options naturally without mentioning these traits explicitly.
+        Each option should be a natural story choice while subtly reflecting its trait.
+        """
+        
+        response = client.chat.completions.create(
+            messages=[{"role": "user", "content": prompt}],
+            model="meta-llama/llama-4-scout-17b-16e-instruct",
+            temperature=0.7,
+            max_tokens=800
+        )
+        
+        content = response.choices[0].message.content
+        
+        # Split content into story and options
+        parts = content.split("[OPTIONS]")
+        if len(parts) == 2:
+            story = parts[0].replace("[STORY]", "").strip()
+            options_text = parts[1].strip()
+            options = [line.strip() for line in options_text.split("\n") if line.strip().startswith(("1.", "2.", "3.", "4."))]
+        else:
+            story = content
+            options = ["Continue the story", "Ask for help", "Take a different path", "Wait and observe"]
+        
+        story_history.append(story)
+        return story, options
+        
+    except Exception as e:
+        print(f"Error generating story: {e}")
+        return "An error occurred while generating the story. Please try again.", ["Retry", "Choose different genre", "Start over", "Get help"]
+
+def continue_story(story_history, selected_option):
+    try:
+        full_story = "\n".join(story_history)
+        prompt = f"""
+        Previous story: {full_story}
+        Chosen action: {selected_option}
+
+        Continue the story based on the chosen action.
+        Provide 4 new options that map to:
+        - Option 1: Openness (innovative, creative solutions)
+        - Option 2: Conscientiousness (careful planning, responsibility)
+        - Option 3: Extraversion/Agreeableness (social interaction, cooperation)
+        - Option 4: Neuroticism (emotional awareness, caution)
+
+        Format:
+        [STORY]
+        Write the continuation here (max 150 words)
+
+        [OPTIONS]
+        Present 4 natural story options that subtly reflect these traits without explicitly mentioning them.
+        Make each option feel like a natural choice in the story.
+        """
+        
+        response = client.chat.completions.create(
+            model="meta-llama/llama-4-scout-17b-16e-instruct",
+            messages=[{"role": "user", "content": prompt}],
+            temperature=0.7,
+            max_tokens=800
+        )
+        
+        content = response.choices[0].message.content
+        
+        # Split content into story and options
+        parts = content.split("[OPTIONS]")
+        if len(parts) == 2:
+            story = parts[0].replace("[STORY]", "").strip()
+            options_text = parts[1].strip()
+            options = [line.strip() for line in options_text.split("\n") if line.strip().startswith(("1.", "2.", "3.", "4."))]
+        else:
+            story = content
+            options = ["Continue forward", "Take a different approach", "Reconsider the situation", "Try something new"]
+        
+        story_history.append(story)
+        return story, options
+        
+    except Exception as e:
+        print(f"Error continuing story: {e}")
+        return "An error occurred while continuing the story. Please try again.", ["Retry", "Go back", "Choose different option", "Start over"]
+
+# def predict_personality(choices_text):
+#     prompt = f"""
+#     Analyze the following choices made by the user and determine their personality type:
+    
+#     Choices:
+#     {choices_text}
+    
+#     The choices are labeled as follows:
+#     1. Emotional
+#     2. Rational
+#     3. Diplomatic
+#     4. Angry
+    
+#     Based on the frequency and pattern of choices, predict the user's personality type.
+#     Give a short summary of their personality traits.
+    
+#     ### Give me only output
+#     """
+    
+#     response = client.chat.completions.create(
+#         model="llama3-70b-8192",
+#         messages=[{"role": "user", "content": prompt}],
+#         temperature=0.3,
+#         max_tokens=300
+#     )
+    
+#    return response.choices[0].message.content
+
+

tfidf_vectorizer.joblib

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:bdcdf34dc746af15d6a03516ab5e655e7a3a9b4b05508d1fe3bf7b7bc11cb1d3
+size 196257