Upload app.py

app.py

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+import gradio as gr
+import ftfy
+import language_tool_python
+import re
+from sentence_transformers import SentenceTransformer, util
+from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer
+
+# Load fine-tuned GPT-2 model
+model_path = "/content/drive/MyDrive/gpt2_tinystories_finetuned"  # Update if needed
+model = AutoModelForCausalLM.from_pretrained(model_path)
+tokenizer = AutoTokenizer.from_pretrained(model_path)
+
+# Create a text-generation pipeline
+story_generator = pipeline("text-generation", model=model, tokenizer=tokenizer)
+
+# Load NLP tools
+tool = language_tool_python.LanguageTool('en-UK')
+sentence_model = SentenceTransformer('all-MiniLM-L6-v2')
+
+def refine_story(text):
+    """Refines the generated story by fixing encoding, grammar, and redundancy."""
+    text = ftfy.fix_text(text)  # Fix encoding
+    matches = tool.check(text)  # Check grammar
+    text = language_tool_python.utils.correct(text, matches)  # Apply fixes
+
+    # Remove redundant words/phrases
+    text = re.sub(r'(\b\w+\b) \1', r'\1', text)  # Remove duplicate words
+    text = re.sub(r'(\b\w+ and \w+\b)(,? \1)+', r'\1', text)  # Remove phrase repetitions
+
+    return text
+
+def detect_inconsistencies(text):
+    """Checks for logical inconsistencies by comparing sentence similarities."""
+    sentences = text.split(". ")
+    inconsistencies = []
+
+    # Compare each sentence with the next one
+    for i in range(len(sentences) - 1):
+        similarity_score = util.pytorch_cos_sim(sentence_model.encode(sentences[i]), sentence_model.encode(sentences[i+1]))
+
+        if similarity_score.item() < 0.3:  # If similarity is low, flag as inconsistent
+            inconsistencies.append(f"⚠️ **Possible inconsistency detected:**\n➡ {sentences[i]} \n➡ {sentences[i+1]}")
+
+    return "\n\n".join(inconsistencies) if inconsistencies else "✅ No major inconsistencies detected."
+
+def story_pipeline(prompt):
+    """Generates a story, refines it, and checks inconsistencies."""
+    # Generate the story
+    generated = story_generator(prompt, max_length=200, do_sample=True, temperature=1.0, top_p=0.9, top_k=50)
+    raw_story = generated[0]['generated_text']
+
+    # Refine the generated story
+    refined_story = refine_story(raw_story)
+
+    # Detect logical inconsistencies
+    inconsistencies = detect_inconsistencies(refined_story)
+
+    return raw_story, refined_story, inconsistencies
+
+# ✅ Gradio Interface with Proper Logical Inconsistency Detection
+interface = gr.Interface(
+    fn=story_pipeline,
+    inputs=gr.Textbox(label="Enter Story Prompt", placeholder="Once upon a time..."),
+    outputs=[
+        gr.Textbox(label="📖 Generated Story", interactive=True),  # Interactive textbox
+        gr.Textbox(label="✅ Refined Story", interactive=True),  # Refined output
+        gr.Textbox(label="⚠️ Logical Inconsistencies", interactive=False),  # Shows inconsistencies correctly
+    ],
+    title="📖 FableWeaver AI",
+    description="Generates AI-powered TinyStories using GPT-2 fine-tuned on TinyStories. Automatically refines the story and detects logical inconsistencies."
+)
+
+# Launch Gradio app
+interface.launch(share="True")