Create app.py

app.py

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+import streamlit as st
+from openai import OpenAI
+import os
+
+# AIML API settings
+aiml_api_key = os.getenv("AIML_API_KEY")  # Fetch the API key from environment variables
+client = OpenAI(api_key=aiml_api_key)
+
+# Function to generate sentiment analysis
+def generate_response(feedback, feedback_source):
+    prompt = f"Analyze the following {feedback_source} feedback and provide the sentiment (positive, negative, neutral) and key phrases: {feedback}"
+    chat_completion = client.chat.completions.create(
+        model="o1-mini",
+        messages=[
+            {"role": "user", "content": prompt},
+        ],
+        max_tokens=1000,
+    )
+    return chat_completion.choices[0].message.content
+
+# Streamlit app layout
+st.title("Sentiment Analysis Tool")
+
+# Category selection (for feedback context)
+category = st.selectbox("Select your feedback source", ("Product Reviews", "Social Media", "Post-purchase Surveys"))
+
+# Input for customer's feedback
+query = st.text_area("Enter customer feedback for analysis", placeholder="Paste product review or social media comment here...")
+
+# Button to trigger sentiment analysis
+if st.button("Analyze Feedback"):
+    if query:
+        # Generate sentiment and key phrases
+        response = generate_response(query, category)
+        st.write(response)
+    else:
+        st.write("Please enter customer feedback.")