Update app.py

app.py

@@ -1,134 +1,3 @@
-# import streamlit as st
-# import pandas as pd
-# import plotly.express as px
-# import os
-# from langchain_google_genai import GoogleGenerativeAI
-# from langchain_core.prompts import ChatPromptTemplate
-# from langchain_core.output_parsers import StrOutputParser
-
-# # Streamlit App
-# st.set_page_config(page_title="Cricket Player Stats Dashboard", layout="wide")
-
-# # Create a folder to save CSVs if not exists
-# data_folder = "data"
-# os.makedirs(data_folder, exist_ok=True)
-
-# # File paths
-# batting_path = "Batting_10_Teams_Final.csv"
-# bowling_path = "Bowling_10_Teams_Final.csv"
-
-# # Load saved CSVs
-# batting_df = pd.read_csv(batting_path)
-# bowling_df = pd.read_csv(bowling_path)
-
-# # Extract unique teams and players
-# teams = sorted(set(batting_df['Country'].unique()).union(bowling_df['Country'].unique()))
-# team = st.sidebar.selectbox("Select Team", teams)
-
-# # Filter players by team
-# batting_players = batting_df[batting_df['Country'] == team]['player_name'].unique()
-# bowling_players = bowling_df[bowling_df['Country'] == team]['player_name'].unique()
-# players = sorted(set(batting_players).union(bowling_players))
-# player = st.sidebar.selectbox("Select Player", players)
-
-# # Filter data for the selected player
-# player_batting = batting_df[(batting_df['player_name'] == player) & (batting_df['Country'] == team)]
-# player_bowling = bowling_df[(bowling_df['player_name'] == player) & (bowling_df['Country'] == team)]
-
-# st.title(f"{player}")
-
-# # ✅ Integrating LLMs using Gen-AI
-
-# # Loading API key and creating model
-# api_key = st.secrets.get('genai_key')
-# model = GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=api_key)
-
-# # Creating output parser to generate output
-# out_par = StrOutputParser()
-
-# # Creating prompt template
-# prompt = ChatPromptTemplate.from_messages([
-#     ("system", '''You are an AI cricket player information provider. Display the player's complete bio data in a 
-#                   detailed table format with rows and columns, including personal information. Below the table, 
-#                   include debut details for all formats. Additionally, provide a brief description of the player 
-#                   underneath. Only include player information, not their performance statistics.'''),
-#     ("human", "{player_name}")
-# ])
-
-# # Creating chain
-# chain = prompt | model | out_par
-
-# # Query GenAI with the player's name
-# response = chain.invoke({"player_name": player})
-# st.write(response)
-
-# # Buttons for Batting and Bowling Cards with Toggle Feature
-# col_card1, col_card2 = st.columns(2)
-# if "batting_card" not in st.session_state:
-#     st.session_state["batting_card"] = False
-# if "bowling_card" not in st.session_state:
-#     st.session_state["bowling_card"] = False
-
-# with col_card1:
-#     if st.button("Batting Card"):
-#         st.session_state["batting_card"] = not st.session_state["batting_card"]
-
-# if st.session_state["batting_card"]:
-#     if len(player_batting) > 0:
-#         st.write("### Batting Data")
-#         st.dataframe(player_batting.iloc[:, :16])  # Display first 16 columns
-#     else:
-#         st.write("No batting data available.")
-
-# with col_card2:
-#     if st.button("Bowling Card"):
-#         st.session_state["bowling_card"] = not st.session_state["bowling_card"]
-
-# if st.session_state["bowling_card"]:
-#     if len(player_bowling) > 0:
-#         st.write("### Bowling Data")
-#         st.dataframe(player_bowling.iloc[:, :15])  # Display first 15 columns
-#     else:
-#         st.write("No bowling data available.")
-
-
-    
-    
-# # Batting Visualization
-# if not player_batting.empty:
-#     st.subheader("Batting Stats")
-#     col1, col2 = st.columns(2)
-#     with col1:
-#         fig_bat_runs = px.bar(player_batting, x='Format', y='Runs', color='Format', title='Runs by Format')
-#         st.plotly_chart(fig_bat_runs, use_container_width=True)
-#     with col2:
-#         fig_bat_sr = px.line(player_batting, x='Format', y='SR', title='Strike Rate by Format')
-#         st.plotly_chart(fig_bat_sr, use_container_width=True)
-
-#      # Batting Pie Chart
-#     fig_bat_pie = px.pie(player_batting, values='Runs', names='Format', 
-#                          title='Runs Distribution Across Formats', 
-#                          color_discrete_map={"ODI": "red", "T20": "green", "Test": "blue"})
-#     st.plotly_chart(fig_bat_pie, use_container_width=True)
-
-# # Bowling Visualization
-# if not player_bowling.empty:
-#     st.subheader("Bowling Stats")
-#     col3, col4 = st.columns(2)
-#     with col3:
-#         fig_bowl_wickets = px.bar(player_bowling, x='Format', y='Wickets', color='Format', title='Wickets by Format')
-#         st.plotly_chart(fig_bowl_wickets, use_container_width=True)
-#     with col4:
-#         fig_bowl_eco = px.line(player_bowling, x='Format', y='Eco', title='Economy Rate by Format')
-#         st.plotly_chart(fig_bowl_eco, use_container_width=True)
-
-#       # Bowling Pie Chart
-#     fig_bowl_pie = px.pie(player_bowling, values='Wickets', names='Format', 
-#                           title='Wickets Distribution Across Formats', 
-#                           color_discrete_map={"ODI": "yellow", "T20": "purple", "Test": "brown"})
-#     st.plotly_chart(fig_bowl_pie, use_container_width=True)
-    
-
 import streamlit as st
 import pandas as pd
 import plotly.express as px
@@ -138,13 +7,12 @@ from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.output_parsers import StrOutputParser
 
 # Set page config
-st.set_page_config(page_title="🏏 Ultimate Cricket Analytics", layout="wide")
+st.set_page_config(page_title="\ud83c\udfcf Ultimate Cricket Analytics", layout="wide")
 
 # Create a folder to save CSVs if not exists
 data_folder = "data"
 os.makedirs(data_folder, exist_ok=True)
 
-
 # Load all three formats
 odi_df = pd.read_csv("odi.xls")
 t20_df = pd.read_csv("t20.xls")
@@ -154,30 +22,97 @@ test_df = pd.read_csv("test.xls")
 batting_df = pd.read_csv("Batting_10_Teams_Final.csv")
 bowling_df = pd.read_csv("Bowling_10_Teams_Final.csv")
 
+# Sidebar Navigation
+st.sidebar.title("\ud83c\udfcf Navigation Panel")
+option = st.sidebar.selectbox("Choose Option", [
+    "Team Info",
+    "Team Stats Comparison",
+    "Player Stats",
+    "Player Comparison"
+])
+
+# Sidebar UI based on selection
+team_info = selected_teams_stats = selected_format = None
+selected_team = selected_player = None
+player1 = player2 = None
+
+if option == "Team Info":
+    team_info = st.sidebar.selectbox("Select Team", sorted(batting_df['Country'].unique()))
+
+elif option == "Team Stats Comparison":
+    num_teams = st.sidebar.selectbox("Select Number of Teams", [2, 3])
+    selected_teams_stats = st.sidebar.multiselect("Select Teams", sorted(batting_df['Country'].unique()), max_selections=num_teams)
+    selected_format = st.sidebar.selectbox("Select Format", ["ODI", "T20", "Test"])
+
+elif option == "Player Stats":
+    selected_team = st.sidebar.selectbox("Select Team", sorted(batting_df['Country'].unique()))
+    players_list = sorted(set(batting_df[batting_df['Country'] == selected_team]['player_name']).union(
+        bowling_df[bowling_df['Country'] == selected_team]['player_name']
+    ))
+    selected_player = st.sidebar.selectbox("Select Player", players_list)
+
+elif option == "Player Comparison":
+    selected_team_for_players = st.sidebar.selectbox("Select Team", sorted(batting_df['Country'].unique()))
+    players_team = sorted(set(batting_df[batting_df['Country'] == selected_team_for_players]['player_name']).union(
+        bowling_df[bowling_df['Country'] == selected_team_for_players]['player_name']
+    ))
+    player1 = st.sidebar.selectbox("Select Player 1", players_team)
+    player2 = st.sidebar.selectbox("Select Player 2", [p for p in players_team if p != player1])
+
+# Load GenAI
+api_key = st.secrets.get('genai_key')
+model = GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=api_key)
+out_par = StrOutputParser()
+
+# ---- Main Content ----
+if option == "Team Info" and team_info:
+    st.title(f"\ud83d\udcc3 Team Bio - {team_info}")
+    team_prompt = ChatPromptTemplate.from_messages([
+        ("system", "You are an AI cricket historian. Provide a brief yet detailed overview of the team."),
+        ("human", "{team_name}")
+    ])
+    team_chain = team_prompt | model | out_par
+    st.write(team_chain.invoke({"team_name": team_info}))
+
+elif option == "Team Stats Comparison" and selected_teams_stats:
+    st.title("\ud83d\udcca Team Stats Comparison")
+    odi_df['Format'] = 'ODI'
+    t20_df['Format'] = 'T20'
+    test_df['Format'] = 'Test'
+    combined_df = pd.concat([odi_df, t20_df, test_df], ignore_index=True)
+
+    selected_data = combined_df[(combined_df['Team'].isin(selected_teams_stats)) & (combined_df['Format'] == selected_format)]
+
+    stat_options = {
+        'Mat': 'Matches',
+        'Won': 'Wins',
+        'Lost': 'Losses',
+        'Draw': 'Draws',
+        'Tied': 'Ties',
+        'W/L': 'Win/Loss Ratio',
+        '%W': 'Win %',
+        '%L': 'Loss %',
+        '%D': 'Draw %'
+    }
+    stat_choice = st.selectbox("Select Stat to Compare", list(stat_options.keys()), format_func=lambda x: stat_options[x])
+
+    fig = px.bar(
+        selected_data,
+        x='Team',
+        y=stat_choice,
+        color='Format',
+        barmode='group',
+        title=f"{stat_options[stat_choice]} by Team in {selected_format}"
+    )
+    st.plotly_chart(fig, use_container_width=True)
+    st.dataframe(selected_data.reset_index(drop=True))
+
+elif option == "Player Stats" and selected_player:
+    st.title(f"\ud83c\udfcf Player Dashboard - {selected_player}")
+
+    player_batting = batting_df[(batting_df['player_name'] == selected_player) & (batting_df['Country'] == selected_team)]
+    player_bowling = bowling_df[(bowling_df['player_name'] == selected_player) & (bowling_df['Country'] == selected_team)]
 
-# Tabs for navigation
-tab1, tab2, tab3 = st.tabs(["🏏 Player Dashboard", "📊 Team Comparison", "📚 GenAI Team Bio"])
-
-# ---------------- TAB 1: Player Dashboard ----------------
-with tab1:
-    st.title("🏏 Player Dashboard")
-    teams = sorted(set(batting_df['Country'].unique()).union(bowling_df['Country'].unique()))
-    team = st.sidebar.selectbox("Select Team", teams)
-
-    batting_players = batting_df[batting_df['Country'] == team]['player_name'].unique()
-    bowling_players = bowling_df[bowling_df['Country'] == team]['player_name'].unique()
-    players = sorted(set(batting_players).union(bowling_players))
-    player = st.sidebar.selectbox("Select Player", players)
-
-    player_batting = batting_df[(batting_df['player_name'] == player) & (batting_df['Country'] == team)]
-    player_bowling = bowling_df[(bowling_df['player_name'] == player) & (bowling_df['Country'] == team)]
-
-    st.header(player)
-
-    # GenAI Player Info
-    api_key = st.secrets.get('genai_key')
-    model = GoogleGenerativeAI(model="gemini-1.5-pro", google_api_key=api_key)
-    out_par = StrOutputParser()
     prompt = ChatPromptTemplate.from_messages([
         ("system", '''You are an AI cricket player information provider. Display the player's complete bio data in a 
                       detailed table format with rows and columns, including personal information. Below the table, 
@@ -186,15 +121,13 @@ with tab1:
         ("human", "{player_name}")
     ])
     chain = prompt | model | out_par
-    st.write(chain.invoke({"player_name": player}))
+    st.write(chain.invoke({"player_name": selected_player}))
 
-    # Toggle Cards
     if st.button("Show Batting Card"):
         st.dataframe(player_batting.iloc[:, :16])
     if st.button("Show Bowling Card"):
         st.dataframe(player_bowling.iloc[:, :15])
 
-    # Visuals
     if not player_batting.empty:
         st.subheader("Batting Visualizations")
         col1, col2 = st.columns(2)
@@ -213,85 +146,20 @@ with tab1:
             st.plotly_chart(px.line(player_bowling, x='Format', y='Eco'))
         st.plotly_chart(px.pie(player_bowling, values='Wickets', names='Format'))
 
-# ---------------- TAB 2: Team Comparison ----------------
-# ---------------- TAB 2: Team Comparison ----------------
-# ---------------- TAB 2: Team Comparison ----------------
-with tab2:
-    st.title("📊 Team Comparison")
-
-    try:
-        # Tag the format for clarity
-        odi_df['Format'] = 'ODI'
-        t20_df['Format'] = 'T20'
-        test_df['Format'] = 'Test'
-
-        # Combine all formats
-        combined_df = pd.concat([odi_df, t20_df, test_df], ignore_index=True)
-
-        # Columns as per your data
-        team_column = 'Team'
-
-        # Team selection
-        selected_teams = st.multiselect("Select Teams to Compare (up to 3)", combined_df[team_column].unique(), max_selections=3)
-
-        if selected_teams:
-            selected_data = combined_df[combined_df[team_column].isin(selected_teams)]
-
-            # Map column names to user-friendly labels
-            stat_options = {
-                'Mat': 'Matches',
-                'Won': 'Wins',
-                'Lost': 'Losses',
-                'Draw': 'Draws',
-                'Tied': 'Ties',
-                'W/L': 'Win/Loss Ratio',
-                '%W': 'Win %',
-                '%L': 'Loss %',
-                '%D': 'Draw %'
-            }
-
-            stat_choice = st.selectbox("Select Stat to Compare", list(stat_options.keys()), format_func=lambda x: stat_options[x])
-
-            st.subheader(f"{stat_options[stat_choice]} Comparison")
-
-            fig = px.bar(
-                selected_data,
-                x='Team',
-                y=stat_choice,
-                color='Format',
-                barmode='group',
-                title=f"{stat_options[stat_choice]} by Team and Format"
-            )
-            st.plotly_chart(fig, use_container_width=True)
+elif option == "Player Comparison" and player1 and player2:
+    st.title(f"\ud83d\udcc8 Player Comparison: {player1} vs {player2}")
 
-            if st.checkbox("Show Raw Team Data Table"):
-                st.dataframe(selected_data.reset_index(drop=True))
+    def get_player_data(name):
+        return (
+            batting_df[batting_df['player_name'] == name],
+            bowling_df[bowling_df['player_name'] == name]
+        )
 
-            # GenAI Team Summary
-            st.subheader("📘 GenAI Team Summary")
-            for team in selected_teams:
-                st.markdown(f"#### {team}")
-                team_prompt = ChatPromptTemplate.from_messages([
-                    ("system", "You are an AI cricket historian. Provide a brief yet detailed overview of the team."),
-                    ("human", "{team_name}")
-                ])
-                team_chain = team_prompt | model | out_par
-                bio = team_chain.invoke({"team_name": team})
-                st.write(bio)
-        else:
-            st.info("Please select at least one team to compare.")
+    bat1, bowl1 = get_player_data(player1)
+    bat2, bowl2 = get_player_data(player2)
 
-    except Exception as e:
-        st.error(f"Error loading team data: {e}")
+    st.subheader("Batting Comparison")
+    st.plotly_chart(px.bar(pd.concat([bat1, bat2]), x='Format', y='Runs', color='player_name', barmode='group'))
 
-# ---------------- TAB 3: Team GenAI Bio ----------------
-with tab3:
-    st.title("📚 Team GenAI Bio")
-    team_input = st.text_input("Enter Team Name (e.g., India, Australia)")
-    if team_input:
-        team_prompt = ChatPromptTemplate.from_messages([
-            ("system", "You are an AI cricket historian. Provide a brief yet detailed overview of the team."),
-            ("human", "{team_name}")
-        ])
-        team_chain = team_prompt | model | out_par
-        st.write(team_chain.invoke({"team_name": team_input}))
+    st.subheader("Bowling Comparison")
+    st.plotly_chart(px.bar(pd.concat([bowl1, bowl2]), x='Format', y='Wickets', color='player_name', barmode='group'))