Update app.py

app.py

@@ -1,31 +1,53 @@
 import streamlit as st
-from utils import query_agent
+import pandas as pd
+import anthropic
 
-# Basic UI
-st.title("CSV Analyst with Claude")
-st.header("Upload your CSV file for analysis")
+st.title("CSV Analyzer with Claude")
 
-# Input Anthropic API key
-anthropic_api_key = st.text_input("Enter your Anthropic API Key:", type="password")
+# API Key input
+api_key = st.text_input("Enter your Anthropic API Key (starts with 'sk-'):", type="password")
 
-# Capture the CSV file
-data = st.file_uploader("Upload CSV file", type="csv")
-query = st.text_area("What would you like to know about your data?")
+# File upload
+uploaded_file = st.file_uploader("Choose a CSV file", type="csv")
 
-# Check if Anthropic API key is available
-if anthropic_api_key:
-    # If Anthropic API key is available, show submit button
-    button = st.button("Analyze")
-
-    if button and data is not None:
-        try:
-            with st.spinner("Claude is analyzing your data..."):
-                # Get Response
-                answer = query_agent(data, query, api_key=anthropic_api_key)
-                st.write(answer)
-        except Exception as e:
-            st.error(f"An error occurred: {str(e)}")
-    elif button and data is None:
-        st.warning("Please upload a CSV file first.")
-else:
-    st.warning("Please input your Anthropic API key to continue.")
+if uploaded_file is not None and api_key:
+    try:
+        # Read CSV
+        df = pd.read_csv(uploaded_file)
+        st.write("Data Preview:")
+        st.dataframe(df.head())
+        
+        # Question input
+        question = st.text_input("What would you like to know about this data?")
+        
+        if question and st.button("Analyze"):
+            try:
+                # Create base Anthropic client
+                client = anthropic.Client(api_key=api_key)
+                
+                # Prepare content
+                data_info = {
+                    "columns": list(df.columns),
+                    "sample": df.head(3).to_dict('records')
+                }
+                
+                # Create message
+                completion = client.messages.create(
+                    max_tokens=1024,
+                    messages=[{
+                        "role": "user",
+                        "content": f"Analyze this CSV data: {data_info}\n\nQuestion: {question}"
+                    }],
+                    model="claude-3.5-sonnet-20241022"
+                )
+                
+                # Display response
+                st.write("Analysis:")
+                st.write(completion.content)
+                
+            except Exception as e:
+                st.error(f"Analysis error: {str(e)}")
+                st.write("Error details:", e.__dict__)
+                
+    except Exception as e:
+        st.error(f"File error: {str(e)}")