Update app.py

app.py

@@ -357,53 +357,53 @@ if Usage == 'Ask me anything (CSV file data)!📊':
                 pass
     
         temp = st.slider('Temperature: ', 0.0, 1.0, 0.0)
-        
-        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)
-                sqlOutput = result #st.text_area('SQL Query', value=gpt3(col_p))
-                warning(sqlOutput) 
-                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 st.form("Form Layout Upload_csv"):
+            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)
+                    sqlOutput = result #st.text_area('SQL Query', value=gpt3(col_p))
+                    warning(sqlOutput) 
+                    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 response_graph['choices'][0]['text'] != "":    
-                        print(response_graph['choices'][0]['text'])
-                        exec(response_graph['choices'][0]['text'])
+                    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:
-                        print('Retry! Graph could not be plotted *_*')
-
-            except:    
-                results = gpt3(userPrompt)
-                st.success('loaded')
+                        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')
                     
     elif res == "Sample_Cars_csv":
         df = pd.read_csv('cars.csv')
@@ -417,53 +417,54 @@ if Usage == 'Ask me anything (CSV file data)!📊':
             pass
     
         temp = st.slider('Temperature: ', 0.0, 1.0, 0.0)
+
+        if st.form("Form Layout Custom_csv"):
+            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)
+                    sqlOutput = result #st.text_area('SQL Query', value=gpt3(col_p))
+                    warning(sqlOutput)
+                    result_tab2=ps.sqldf(sqlOutput)
+                    st.write(result_tab2)
+                    
+                    with open("fewshot_matplot.txt", "r") as file:
+                        text_plot = file.read()
         
-        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)
-                sqlOutput = result #st.text_area('SQL Query', value=gpt3(col_p))
-                warning(sqlOutput)
-                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,
-                        )
+                    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 response_graph['choices'][0]['text'] != "":    
-                        print(response_graph['choices'][0]['text'])
-                        exec(response_graph['choices'][0]['text'])
+                    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:
-                        print('Retry! Graph could not be plotted *_*')
-            except:    
-                results = gpt3(userPrompt)
-                st.success('loaded')
+                        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')
                 
 
 elif Usage == 'Ask me anything!😊':