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Update app.py
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app.py
CHANGED
@@ -361,7 +361,7 @@ if Usage == 'Ask me anything (CSV file data)!📊':
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with st.form(key='columns_in_form'):
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col1, col2 = st.columns(2)
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with
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userPrompt = st.text_area("Input Prompt",'Enter Natural Language Query')
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submitButton = st.form_submit_button(label = 'Submit')
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if submitButton:
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@@ -371,43 +371,43 @@ if Usage == 'Ask me anything (CSV file data)!📊':
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except:
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results = gpt3(userPrompt)
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st.success('loaded')
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elif res == "Sample_Cars_csv":
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df = pd.read_csv('cars.csv')
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@@ -436,44 +436,44 @@ if Usage == 'Ask me anything (CSV file data)!📊':
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results = gpt3(userPrompt)
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st.success('loaded')
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elif Usage == 'Ask me anything!😊':
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st.text('''You can ask me:
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with st.form(key='columns_in_form'):
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col1, col2 = st.columns(2)
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with col1:
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userPrompt = st.text_area("Input Prompt",'Enter Natural Language Query')
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submitButton = st.form_submit_button(label = 'Submit')
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if submitButton:
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except:
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results = gpt3(userPrompt)
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st.success('loaded')
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with col2:
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sqlOutput = gpt3(col_p) #st.text_area('SQL Query', value=gpt3(col_p))
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warning(sqlOutput)
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# cars=pd.read_csv('cars.csv')
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result_tab2=ps.sqldf(sqlOutput)
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st.write(result_tab2)
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with open("fewshot_matplot.txt", "r") as file:
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text_plot = file.read()
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result_tab = result_tab2.reset_index(drop=True)
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result_tab_string = result_tab.to_string()
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gr_prompt = text_plot + userPrompt + result_tab_string + "Plot graph for: "
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if len(gr_prompt) > 4097:
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st.write('OVERWHELMING DATA!!! You have given me more than 4097 tokens! ^_^')
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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 ^_^')
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elif len(result_tab2.columns) < 2:
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st.write("I need more data to conduct analysis and provide visualizations for you... ^_^")
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else:
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st.success("Plotting...")
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response_graph = openai.Completion.create(
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engine="text-davinci-003",
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prompt = gr_prompt,
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max_tokens=1024,
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n=1,
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stop=None,
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temperature=0.5,
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)
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if response_graph['choices'][0]['text'] != "":
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print(response_graph['choices'][0]['text'])
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exec(response_graph['choices'][0]['text'])
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else:
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print('Retry! Graph could not be plotted *_*')
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elif res == "Sample_Cars_csv":
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df = pd.read_csv('cars.csv')
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results = gpt3(userPrompt)
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st.success('loaded')
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with col2:
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sqlOutput = gpt3(col_p) #st.text_area('SQL Query', value=gpt3(col_p))
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warning(sqlOutput)
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cars=pd.read_csv('cars.csv')
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result_tab2=ps.sqldf(sqlOutput)
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st.write(result_tab2)
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with open("fewshot_matplot.txt", "r") as file:
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text_plot = file.read()
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result_tab = result_tab2.reset_index(drop=True)
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result_tab_string = result_tab.to_string()
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gr_prompt = text_plot + userPrompt + result_tab_string + "Plot graph for: "
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if len(gr_prompt) > 4097:
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st.write('OVERWHELMING DATA!!! You have given me more than 4097 tokens! ^_^')
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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 ^_^')
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elif len(result_tab2.columns) < 2:
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st.write("I need more data to conduct analysis and provide visualizations for you... ^_^")
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else:
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st.success("Plotting...")
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response_graph = openai.Completion.create(
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engine="text-davinci-003",
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prompt = gr_prompt,
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max_tokens=1024,
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n=1,
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stop=None,
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temperature=0.5,
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)
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if response_graph['choices'][0]['text'] != "":
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print(response_graph['choices'][0]['text'])
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exec(response_graph['choices'][0]['text'])
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else:
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print('Retry! Graph could not be plotted *_*')
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elif Usage == 'Ask me anything!😊':
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st.text('''You can ask me:
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