initial commit

.idea/Haiku.iml

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+<?xml version="1.0" encoding="UTF-8"?>
+<module type="PYTHON_MODULE" version="4">
+  <component name="NewModuleRootManager">
+    <content url="file://$MODULE_DIR$" />
+    <orderEntry type="inheritedJdk" />
+    <orderEntry type="sourceFolder" forTests="false" />
+  </component>
+</module>

.idea/inspectionProfiles/Project_Default.xml

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+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="2">
+            <item index="0" class="java.lang.String" itemvalue="streamlit" />
+            <item index="1" class="java.lang.String" itemvalue="plotly" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>

.idea/inspectionProfiles/profiles_settings.xml

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+<component name="InspectionProjectProfileManager">
+  <settings>
+    <option name="USE_PROJECT_PROFILE" value="false" />
+    <version value="1.0" />
+  </settings>
+</component>

.idea/modules.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project version="4">
+  <component name="ProjectModuleManager">
+    <modules>
+      <module fileurl="file://$PROJECT_DIR$/.idea/Haiku.iml" filepath="$PROJECT_DIR$/.idea/Haiku.iml" />
+    </modules>
+  </component>
+</project>

app.py

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+import streamlit as st
+from transformers import pipeline
+import nltk
+from nltk.corpus import cmudict
+import random
+import torch
+
+# Download required NLTK data
+nltk.download('cmudict')
+d = cmudict.dict()
+
+
+class HaikuGenerator:
+    def __init__(self):
+        # Initialize different language models
+        self.models = {
+            "BERT": pipeline('fill-mask', model='bert-base-uncased'),
+            "RoBERTa": pipeline('fill-mask', model='roberta-base'),
+            "GPT2": pipeline('text-generation', model='gpt2'),
+            "DistilBERT": pipeline('fill-mask', model='distilbert-base-uncased')
+        }
+
+    def count_syllables(self, word):
+        """Count syllables in a word using CMU dictionary."""
+        try:
+            return len([x for x in d[word.lower()][0] if x[-1].isdigit()])
+        except KeyError:
+            return len(''.join(c for c in word if c in 'aeiouAEIOU'))
+
+    def get_related_words(self, word, model_name):
+        """Get related words using different models."""
+        if model_name in ["BERT", "RoBERTa", "DistilBERT"]:
+            if model_name == "RoBERTa":
+                masked_text = f"The {word} is <mask>."
+            else:
+                masked_text = f"The {word} is [MASK]."
+            predictions = self.models[model_name](masked_text)
+            return [pred['token_str'].strip() for pred in predictions]
+        else:  # GPT2
+            prompt = f"The word {word} reminds me of"
+            predictions = self.models[model_name](prompt, max_length=20, num_return_sequences=5)
+            words = []
+            for pred in predictions:
+                text = pred['generated_text'].split()
+                if len(text) > 6:  # Get the first new word after the prompt
+                    words.append(text[6])
+            return words
+
+    def create_themed_haiku(self, character_name, traits, model_name):
+        """Generate a themed haiku about a character using specified model."""
+        syllable_targets = [5, 7, 5]
+        lines = []
+
+        # Create word pool from character traits and related words
+        word_pool = set(traits)
+        word_pool.add(character_name)
+
+        for word in traits:
+            related = self.get_related_words(word, model_name)
+            word_pool.update(related)
+
+        # Add character-specific words based on traits
+        for trait in traits:
+            themed_words = self.get_related_words(trait, model_name)
+            word_pool.update(themed_words)
+
+        # Generate each line ensuring character name appears
+        for i, target in enumerate(syllable_targets):
+            current_line = []
+            current_syllables = 0
+
+            # Ensure character name appears in one of the lines (preferably first)
+            if i == 0 and self.count_syllables(character_name) <= target:
+                current_line.append(character_name)
+                current_syllables += self.count_syllables(character_name)
+
+            while current_syllables < target:
+                available_words = [w for w in word_pool
+                                   if current_syllables + self.count_syllables(w) <= target]
+                if not available_words:
+                    break
+
+                word = random.choice(available_words)
+                current_line.append(word)
+                current_syllables += self.count_syllables(word)
+
+            lines.append(' '.join(current_line))
+
+        return lines
+
+
+def main():
+    st.title("🎋 Character Haiku Generator")
+    st.write("Generate unique haikus about a character using different AI models!")
+
+    # Initialize generator
+    generator = HaikuGenerator()
+
+    # Input fields
+    character_name = st.text_input("Character Name:")
+
+    # Four traits/characteristics
+    cols = st.columns(4)
+    traits = []
+    for i, col in enumerate(cols):
+        trait = col.text_input(f"Trait/Characteristic {i + 1}")
+        if trait:
+            traits.append(trait)
+
+    # Model selection
+    model_options = ["BERT", "RoBERTa", "DistilBERT", "GPT2"]
+    selected_models = st.multiselect(
+        "Select AI Models to Generate Haikus",
+        model_options,
+        default=["BERT"]
+    )
+
+    if character_name and len(traits) == 4 and st.button("Generate Haikus"):
+        st.subheader("Your Generated Haikus:")
+
+        for model in selected_models:
+            with st.expander(f"🎯 {model} Generated Haiku"):
+                with st.spinner(f"Crafting haiku using {model}..."):
+                    haiku_lines = generator.create_themed_haiku(character_name, traits, model)
+
+                    # Display haiku with styling
+                    for line in haiku_lines:
+                        st.write(line)
+
+                    # Display syllable count
+                    st.caption("Syllable count verification:")
+                    for i, line in enumerate(haiku_lines):
+                        syllables = sum(generator.count_syllables(word)
+                                        for word in line.split())
+                        st.caption(f"Line {i + 1}: {syllables} syllables")
+
+
+if __name__ == "__main__":
+    main()

requirements.txt

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+streamlit==1.31.0
+transformers==4.36.0
+torch==2.1.0
+nltk==3.8.1