(feat) add credentials page

frontend/pages/orchestration/credentials/README.md

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+### Description
+
+This page helps you deploy and manage Hummingbot instances:
+
+- Starting and stopping Hummingbot Broker
+- Creating, starting and stopping bot instances
+- Managing strategy and script files that instances run
+- Fetching status of running instances
+
+### Maintainers
+
+This page is maintained by Hummingbot Foundation as a template other pages:
+
+* [cardosfede](https://github.com/cardosfede)
+* [fengtality](https://github.com/fengtality)
+
+### Wiki
+
+See the [wiki](https://github.com/hummingbot/dashboard/wiki/%F0%9F%90%99-Bot-Orchestration) for more information.

frontend/pages/orchestration/credentials/app.py

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+from CONFIG import BACKEND_API_HOST, BACKEND_API_PORT
+from backend.services.backend_api_client import BackendAPIClient
+from frontend.st_utils import initialize_st_page
+import streamlit as st
+import pandas as pd
+import plotly.express as px
+
+initialize_st_page(title="Account Balances", icon="💰")
+
+# Page content
+client = BackendAPIClient.get_instance(host=BACKEND_API_HOST, port=BACKEND_API_PORT)
+
+@st.cache_data(ttl=60)
+def get_all_balances():
+    return client.get_all_balances()
+
+# Fetch all balances
+balances = get_all_balances()
+
+# Convert balances to a DataFrame for easier manipulation
+def balances_to_df(balances):
+    data = []
+    for account, exchanges in balances.items():
+        for exchange, tokens in exchanges.items():
+            for token, amount in tokens.items():
+                data.append({"Account": account, "Exchange": exchange, "Token": token, "Amount": amount})
+    return pd.DataFrame(data)
+
+df_balances = balances_to_df(balances)
+
+# Aggregation at different levels
+account_agg = df_balances.groupby(["Account", "Token"])["Amount"].sum().reset_index()
+exchange_agg = df_balances.groupby(["Exchange", "Token"])["Amount"].sum().reset_index()
+overall_agg = df_balances.groupby("Token")["Amount"].sum().reset_index()
+
+# Display balances
+st.header("Current Balances")
+st.write(df_balances)
+
+# Aggregated Balances
+st.header("Aggregated Balances")
+st.write(account_agg)
+
+# Displaying account level balances
+st.subheader("Account Level")
+for account in account_agg["Account"].unique():
+    st.write(f"**{account}**")
+    df = account_agg[account_agg["Account"] == account]
+    st.write(df)
+
+# Displaying exchange level balances
+st.subheader("Exchange Level")
+for exchange in exchange_agg["Exchange"].unique():
+    st.write(f"**{exchange}**")
+    df = exchange_agg[exchange_agg["Exchange"] == exchange]
+    st.write(df)
+
+# Overall holdings
+st.subheader("Overall Holdings")
+st.write(overall_agg)
+
+# Visualizations
+st.header("Visualizations")
+
+# Account level pie chart
+st.subheader("Account Level Balances")
+for account in account_agg["Account"].unique():
+    df = account_agg[account_agg["Account"] == account]
+    fig = px.pie(df, names='Token', values='Amount', title=f"Account: {account}")
+    st.plotly_chart(fig)
+
+# Exchange level bar chart
+st.subheader("Exchange Level Balances")
+for exchange in exchange_agg["Exchange"].unique():
+    df = exchange_agg[exchange_agg["Exchange"] == exchange]
+    fig = px.bar(df, x='Token', y='Amount', title=f"Exchange: {exchange}")
+    st.plotly_chart(fig)
+
+# Overall holdings pie chart
+st.subheader("Overall Holdings by Token")
+fig = px.pie(overall_agg, names='Token', values='Amount', title="Overall Holdings by Token")
+st.plotly_chart(fig)
+