Update app.py

app.py

@@ -368,29 +368,93 @@ if Usage == 'Ask me anything (CSV file data)!📊':
                     try:
                         col_p ="Create SQL statement from instruction.  "+ext+" " " (" + column +")." +" Request:" + userPrompt  + "SQL statement:" 
                         result = gpt3(col_p)
+                        with col2:
+                            sqlOutput = gpt3(col_p) #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/gpt-3.5-turbo 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:    
                         results = gpt3(userPrompt)
-                    st.success('loaded')
+                        st.success('loaded')
+                    
+    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_form'):
+            col1, col2 = st.columns(2)
+        with col1:
+            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)
+                    
                     with col2:
-                        sqlOutput = gpt3(col_p) #st.text_area('SQL Query', value=gpt3(col_p))
+                        sqlOutput = result #st.text_area('SQL Query', value=gpt3(col_p))
                         warning(sqlOutput) 
-                        # cars=pd.read_csv('cars.csv')
+                        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/gpt-3.5-turbo that I run on takes in inputs that have less than 4097 tokens. Kindly retry ^_^')
+                            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(
@@ -408,72 +472,10 @@ if Usage == 'Ask me anything (CSV file data)!📊':
                             
                             else:
                                 print('Retry! Graph could not be plotted *_*')
-
-    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_form'):
-            col1, col2 = st.columns(2)
-        with col1:
-            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')
+                    st.success('loaded')
                 
-                with col2:
-                    sqlOutput = gpt3(col_p) #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 *_*')
 
 elif Usage == 'Ask me anything!😊':
     st.text('''You can ask me: