Create app.py

app.py

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+import streamlit as st
+from unsloth import FastLanguageModel
+import torch
+
+# Load the model and tokenizer
+max_seq_length = 2048
+dtype = None  # None for auto detection. Float16 for Tesla T4, V100, Bfloat16 for Ampere+
+load_in_4bit = True  # Use 4bit quantization to reduce memory usage. Can be False.
+
+# Initialize the model
+model, tokenizer = FastLanguageModel.from_pretrained(
+    model_name="suhaifLLM/unsloth-llama3-8b-instruct-4bit",
+    max_seq_length=max_seq_length,
+    dtype=dtype,
+    load_in_4bit=load_in_4bit
+)
+
+# Default instruction
+default_instruction = "You are a creative writer. Based on the given input, generate a well-structured story with an engaging plot, well-developed characters, and immersive details. Ensure the story has a clear beginning, middle, and end. Include dialogue and descriptions to bring the story to life. You can add a twist to the story also."
+
+def format_prompt(input_text, instruction=default_instruction):
+    return f"{instruction}\n\nInput:\n{input_text}\n\nResponse:\n"
+
+# Streamlit App
+st.title("Interactive Storytelling Assistant")
+st.write("Create your story prompt and receive story suggestions!")
+
+# User input for story prompt
+user_input = st.text_area("Enter your story idea:", "A young adventurer embarks on a journey to find a lost treasure.")
+generate_story = st.button("Generate Story")
+
+if generate_story and user_input:
+    # Prepare inputs for the model
+    inputs = tokenizer(
+        [format_prompt(user_input)],
+        return_tensors="pt"
+    ).to("cuda")
+    
+    # Generate story
+    outputs = model.generate(**inputs, max_new_tokens=500, use_cache=True)
+    generated_story = tokenizer.decode(outputs[0], skip_special_tokens=True)
+    
+    # Display generated story
+    st.subheader("Generated Story:")
+    st.write(generated_story)
+
+# Feedback mechanism
+st.subheader("Rate the Story")
+story_rating = st.slider("How would you rate this story?", 1, 5)
+user_feedback = st.text_area("Additional Feedback/Suggestions:")
+
+if st.button("Submit Feedback"):
+    st.write("Thank you for your feedback!")
+    # Process feedback (In a real scenario, this would be saved to a database)
+
+# Community engagement
+st.subheader("Share Your Story")
+user_story = st.text_area("Write or paste your own story here:")
+if st.button("Share Story"):
+    st.write("Thank you for sharing your story!")
+    # Save the story (In a real scenario, this would be saved to a shared community platform)
+
+# Display shared stories (Placeholder example)
+st.subheader("Community Stories")
+st.write("Story 1: An epic tale of adventure...")  # Placeholder for actual stories
+
+# Critique section
+st.text_area("Leave a critique for Story 1:")
+if st.button("Submit Critique"):
+    st.write("Thank you for your critique!")