Update app.py

app.py

@@ -203,7 +203,7 @@ def search_internet(question):
             # snippets
         
             response = openai.Completion.create(
-                model="text-davinci-002",
+                model="text-davinci-003",
                 prompt=f'''following are snippets from google search with these as knowledge base only answer questions and print  reference link as well followed by answer. \n\n {snippets}\n\n question-{question}\n\nAnswer-''',
                 temperature=0.49,
                 max_tokens=256,
@@ -324,7 +324,7 @@ drawings, abstract art 🎨, play music 🎵 or videos, create tweets 🐦 and p
 all with the help of HyperBot! 🤖 ✨
 ''')
 
-option_ = ['Random Questions','Questions based on custom CSV data']
+option_ = ['Ask me anything!😊','Ask me anything (CSV file data)!📊']
 Usage = st.selectbox('Select an option:', option_)
 
 if Usage == 'Questions based on custom CSV data':
@@ -359,23 +359,22 @@ if Usage == 'Questions based on custom CSV data':
         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:
+        with st.form(key='columns_in_form'):
+            col1, col2 = 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:
                 sqlOutput = gpt3(col_p) #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:
@@ -410,9 +409,6 @@ if Usage == 'Questions based on custom CSV data':
                     else:
                         print('Retry! Graph could not be plotted *_*')
 
-            except:
-                pass
-
     elif res == "Sample_Cars_csv":
         df = pd.read_csv('cars.csv')
         col= df.columns
@@ -427,63 +423,59 @@ if Usage == 'Questions based on custom CSV data':
         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:
+        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:
-                    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 *_*')
-    
-                except:
-                    pass
-        
+                    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 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 == 'Random Questions':
+elif Usage == 'Ask me anything!😊':
     st.text('''You can ask me: 
     1. All the things you ask ChatGPT.
     2. Generating paintings, drawings, abstract art.