Update app.py

app.py

@@ -177,21 +177,18 @@ def openai_response(PROMPT):
 st.title("Welcome to :red[AlexaPiro]!!🤖")
 st.title("How can I help?")
 
-Usage = st.radio(
-    "I want to ask:",
-    ('Random Questions', 'Questions based on custom CSV data')
-)
-
+option_ = ['Random Questions','Questions based on custom CSV data']
+Usage = st.selectbox('Select an option:', option_)
 if Usage == 'Questions based on custom CSV data':
     st.text('''Upload any CSV file and ask questions based on the contents of the file.
-    
     Example:
     If I have a CSV file having data on cars, I could ask:
-    - How many cars were manufactured each year between 2000 to 2008?
-    
-    The feature returns a SQL query based on your question and if the returned data has atleast 2 columns then a graph will also be returned''')
+        - How many cars were manufactured each year between 2000 to 2008?
+        
+    The feature returns a SQL query based on your question and if the returned 
+    data has atleast 2 columns then a graph will also be returned.''')
     
-    option = ['Reset','Upload_csv']
+    option = ['Sample_Cars_csv','Upload_csv']
     res = st.selectbox('Select the Upload_csv option:',option)
     if res == 'Upload_csv':
         uploaded_file = st.file_uploader("Add dataset (csv) ",type=['csv'])
@@ -268,6 +265,74 @@ if Usage == 'Questions based on custom CSV data':
             except:
                 pass
 
+    elif res == "Sample_Cars_csv":
+        df = pd.read_csv('cars.csv')
+        col= df.columns
+        try:
+            columns = str((df.columns).tolist())
+            column = clean(columns)
+            st.write('Columns:' )
+            st.text(col)
+        except:
+            pass
+    
+        temp = st.slider('Temperature: ', 0.0, 1.0, 0.0)
+        
+        
+        with st.form(key='columns_in_form2'):
+            col3, col4 = st.columns(2)
+        with col3:
+            userPrompt = st.text_area("Input Prompt",'Enter Natural Language Query')
+            submitButton = st.form_submit_button(label = 'Submit')
+            if submitButton:
+                try:
+                    col_p ="Create SQL statement from instruction.  "+ext+" " " (" + column +")." +" Request:" + userPrompt  + "SQL statement:" 
+                    result = gpt3(col_p)
+                except:    
+                    results = gpt3(userPrompt)
+                st.success('loaded')
+        with col4:
+            try:
+                sqlOutput = st.text_area('SQL Query', value=gpt3(col_p))
+                warning(sqlOutput) 
+                cars=pd.read_csv('cars.csv')
+                result_tab2=ps.sqldf(sqlOutput)
+                st.write(result_tab2)
+                with open("fewshot_matplot.txt", "r") as file:
+                            text_plot = file.read()
+
+                result_tab = result_tab2.reset_index(drop=True)
+                result_tab_string = result_tab.to_string()
+                gr_prompt = text_plot + userPrompt + result_tab_string + "Plot graph for: " 
+                
+                if len(gr_prompt) > 4097:
+                    st.write('OVERWHELMING DATA!!! You have given me more than 4097 tokens! ^_^')
+                    st.write('As of today, the NLP model text-davinci-003 that I run on takes in inputs that have less than 4097 tokens. Kindly retry ^_^')
+                
+                elif len(result_tab2.columns) < 2:
+                    st.write("I need more data to conduct analysis and provide visualizations for you... ^_^") 
+
+                else:
+                    st.success("Plotting...")
+                    response_graph = openai.Completion.create(
+                            engine="text-davinci-003",
+                            prompt = gr_prompt,
+                            max_tokens=1024,
+                            n=1,
+                            stop=None,
+                            temperature=0.5,
+                        )
+                    
+                    if response_graph['choices'][0]['text'] != "":    
+                        print(response_graph['choices'][0]['text'])
+                        exec(response_graph['choices'][0]['text'])
+                    
+                    else:
+                        print('Retry! Graph could not be plotted *_*')
+
+            except:
+                pass
+        
 
 elif Usage == 'Random Questions':
     st.text('''You can ask me for: