Update app.py

app.py

@@ -8,6 +8,12 @@ data = pd.read_csv("RR.csv")
 # Set your OpenAI API key
 openai.api_key = "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"
 
+# Create four graphs using plotly express
+graph1 = px.line(data, x="Month", y="Sales Forecast")
+graph2 = px.line(data, x="Month", y="Sales Actual")
+graph3 = px.line(data, x="Month", y="Marketing Budget")
+graph4 = px.line(data, x="Month", y="Support Chats and Calls")
+
 def query_gpt(prompt):
     model_engine = "text-davinci-002"  # Use any available GPT model here
     max_tokens = 50
@@ -26,12 +32,12 @@ def query_gpt(prompt):
 
 
 def get_insights(question):
-    prompt = f"Using ONLY the information in the following dataset:\n\n{data.to_string(index=False)}\n\nPlease answer the question: {question}\n\nRemember, base your answer solely on the data provided in the dataset."
+    prompt = f"Please answer the question: {question}\n\nRemember, base your answer solely on the data provided in the dataset."
     answer = query_gpt(prompt)
     return answer
 
 
-markdown_data = f"Mock Dataset Sales & Marketing Budget :\n```\n{data.head(10).to_string(index=False)}\n```\n"
+markdown_data = "Mock Dataset Sales & Marketing Budget"
 
 iface = gr.Interface(
     fn=get_insights,
@@ -50,8 +56,14 @@ iface = gr.Interface(
     allow_screenshot=False,
     theme="compact",
     layout="vertical",
+    article="",
+    # Add four plot outputs
+    outputs=[
+        gr.outputs.Plot(plot=graph1),
+        gr.outputs.Plot(plot=graph2),
+        gr.outputs.Plot(plot=graph3),
+        gr.outputs.Plot(plot=graph4),
+    ],
 )
 
-
-
-iface.launch(inbrowser=True)
+iface.launch(inbrowser=True)