Refactor app.py to transition from Gradio to Streamlit for the job application email generator interface. Update UI components including text areas, file upload, and sliders for user input. Modify requirements.txt to remove Gradio and include necessary dependencies for Streamlit and Hugging Face. This change enhances user experience and streamlines the email generation process.

app.py

@@ -1,4 +1,4 @@
-import gradio as gr
+import streamlit as st
 from huggingface_hub import InferenceClient
 from transformers import AutoTokenizer, AutoModelForCausalLM
 import torch
@@ -48,7 +48,7 @@ client = InferenceClient(token=access_token)
 def conversation_predict(input_text):
     """Generate a response for single-turn input using the model."""
     # Tokenize the input text
-    input_ids = tokenizer("""Job Description:
+    input_ids = tokenizer(f"""Job Description:
 {input_text}
 
 Instructions: Write a concise and professional email expressing interest in the position. 
@@ -106,24 +106,30 @@ CV Summary:
         response += token
         yield response
 
-# Create a Gradio ChatInterface demo
-demo = gr.ChatInterface(
-    fn=respond,
-    additional_inputs=[
-        gr.Textbox(value="Instructions: Write a concise and professional email expressing interest in the position.", 
-                   label="System message"),
-        gr.File(label="Upload CV (PDF or DOCX)", file_types=[".pdf", ".docx"]),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
+# Streamlit UI
+st.title("Job Application Email Generator")
+
+# Instructions text area
+system_message = st.text_area("System message", 
+                              "Instructions: Write a concise and professional email expressing interest in the position.", 
+                              height=150)
+
+# CV file upload
+cv_file = st.file_uploader("Upload CV (PDF or DOCX)", type=["pdf", "docx"])
 
-if __name__ == "__main__":
-    demo.launch()
+# Sliders for max tokens, temperature, and top-p
+max_tokens = st.slider("Max new tokens", min_value=1, max_value=2048, value=512, step=1)
+temperature = st.slider("Temperature", min_value=0.1, max_value=4.0, value=0.7, step=0.1)
+top_p = st.slider("Top-p (nucleus sampling)", min_value=0.1, max_value=1.0, value=0.95, step=0.05)
+
+# Input message field
+message = st.text_input("Job Description", "")
+
+# Button to generate response
+if st.button("Generate Email"):
+    if message:
+        response = conversation_predict(message)
+        st.write("Generated Email:")
+        st.write(response)
+    else:
+        st.warning("Please enter a job description.")

requirements.txt

@@ -1,11 +1,9 @@
 # add requirements
 streamlit
-python-dotenv
-langchain
 transformers
 torch
-PyPDF2
-gradio
-huggingface_hub
 python-docx
+PyPDF2
+huggingface-hub
+python-dotenv