Spaces:
Sleeping
Sleeping
Create app.py
Browse files
app.py
ADDED
|
@@ -0,0 +1,25 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
import streamlit as st
|
| 2 |
+
from transformers import pipeline
|
| 3 |
+
|
| 4 |
+
# Load the gated model
|
| 5 |
+
model_name = "RickyDeSkywalker/TheoremLlama"
|
| 6 |
+
generator = pipeline('text-generation', model=model_name)
|
| 7 |
+
|
| 8 |
+
# Streamlit app
|
| 9 |
+
st.title("Lean 4 Code Generation with TheoremLlama")
|
| 10 |
+
st.write("Enter a natural language prompt to generate Lean 4 code.")
|
| 11 |
+
|
| 12 |
+
# Text input for user prompt
|
| 13 |
+
prompt = st.text_area("Prompt", value="Prove that the sum of two even numbers is even.")
|
| 14 |
+
|
| 15 |
+
# Generate button
|
| 16 |
+
if st.button("Generate Lean 4 Code"):
|
| 17 |
+
with st.spinner("Generating Lean 4 code..."):
|
| 18 |
+
# Generate code based on the prompt
|
| 19 |
+
result = generator(prompt, max_length=1000, num_return_sequences=1)
|
| 20 |
+
generated_code = result[0]['generated_text']
|
| 21 |
+
|
| 22 |
+
# Display the generated code
|
| 23 |
+
st.code(generated_code, language='lean')
|
| 24 |
+
|
| 25 |
+
st.markdown("Developed by [Your Name]")
|