Update app.py

app.py

@@ -1,45 +1,54 @@
+from pandasai.llm import GoogleGemini
 import streamlit as st
-from pandasai.llm.openai import OpenAI
-import pandas as pd
-from pandasai import SmartDataframe, Agent
-import io
 import os
-
-st.title("Brave Retail Insights")
-
-openai_api_key = os.environ['openai_api_key']
-
-
-llm = OpenAI(api_token=openai_api_key)
-
-#uploader_file = st.file_uploader("Upload a CSV file", type=["csv"])
-
-    
-data = pd.read_csv("")
-st.write(data.head(3))
-
-df = SmartDataframe(data, config={"llm": llm})
-agent = Agent(data, config={"llm": llm, "open_charts": "False"})
-
-prompt = st.text_area("Enter your prompt:")
-system_prompt = "Decide whether this needs a graph. If it does determine what type of graph (i.e. line/scatter/bar/pie etc). then generate the graph according to the requirements. we may not always need you to generate a graph. if a graph is not required just generate a written output. If you are generating a graph also include a brief description."
-full_prompt = "Main query: " + prompt + " Instructions: " + system_prompt
-
-if st.button("Generate"):
-    if prompt:
-        with st.spinner("Generating response..."):
-            try:
-                graph = df.chat(full_prompt)
-                if "temp_chart" in str(graph):
-                    st.image(graph)
-
-                response = agent.chat(prompt + " Instructions: we don't generate graphs even if it is asked for")
-                if "temp_chart" not in str(response):
-                    st.write(response)
-
-                with st.expander("See Explanation:"):
-                    st.write(agent.explain())
-            except Exception as e:
-                    st.error(f"An error occurred: {e}")
-    else:
-        st.warning("Please enter a prompt!")
+import pandas as pd
+from pandasai import SmartDataframe
+from pandasai.responses.response_parser import  ResponseParser
+
+class StreamLitResponse(ResponseParser):
+        def __init__(self,context) -> None:
+              super().__init__(context)
+        def format_dataframe(self,result):
+               st.dataframe(result['value'])
+               return
+        def format_plot(self,result):
+               st.image(result['value'])
+               return
+        def format_other(self, result):
+               st.write(result['value'])
+               return
+
+gemini_api_key = os.environ['Gemini']
+
+def generateResponse(dataFrame,prompt):
+        llm = GoogleGemini(api_key=gemini_api_key)
+        pandas_agent = SmartDataframe(dataFrame,config={"llm":llm, "response_parser":StreamLitResponse})
+        answer = pandas_agent.chat(prompt)
+        return answer
+
+st.write("# Brave Retail Insights")
+st.write("##### Engage in insightful conversations with your data through powerful visualizations")
+with st.sidebar:
+        st.title("Brave Retail Insights")
+        
+        # Added a divider
+        st.divider()
+        # Add content to the sidebar/drawer
+        with st.expander("Data Visualization"):
+        st.write("<div>Developed by - <span style=\"color: cyan; font-size: 24px; font-weight: 600;\">Rairo</span></div>",unsafe_allow_html=True)
+
+
+uploaded_file = "alaba.csv"
+if uploaded_file is not None:
+        # Read the CSV file
+        df = pd.read_csv(uploaded_file)
+
+        # Display the data
+        with st.expander("Preview"):
+            st.write(df.head())
+
+        # Plot the data
+        user_input = st.text_input("Type your message here",placeholder="Ask me about your data")
+        if user_input:
+                answer = generateResponse(dataFrame=df,prompt=user_input)
+                st.write(answer)