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import json
import re
from typing import Any, Dict, List, Tuple, Optional
from datetime import datetime
from pathlib import Path
import gradio as gr
import pandas as pd
from second_brain_online.config import settings
class CustomerProfileUI:
"""Gradio UI for displaying customer profile analyses with search functionality."""
def __init__(self, data_dir: str = None):
# Default to the offline data directory
if data_dir is None:
# Go up from second-brain-online to second-brain-offline/data/customer_analyses
data_dir = Path(__file__).parent.parent.parent.parent.parent.parent / "second-brain-offline" / "data" / "customer_analyses"
self.data_dir = Path(data_dir)
self.analyses_cache = None
self.load_analyses_from_disk()
self.setup_ui()
def load_analyses_from_disk(self):
"""Load all customer analyses from JSON files on disk."""
try:
# Check if the all-in-one file exists
all_file = self.data_dir / "customer_analyses_all.json"
if all_file.exists():
print(f"π Loading analyses from: {all_file}")
with open(all_file, 'r') as f:
self.analyses_cache = json.load(f)
print(f"β
Loaded {len(self.analyses_cache)} analyses from disk")
else:
# Load individual files
print(f"π Loading analyses from directory: {self.data_dir}")
self.analyses_cache = []
for json_file in self.data_dir.glob("customer_analysis_*.json"):
try:
with open(json_file, 'r') as f:
analysis = json.load(f)
self.analyses_cache.append(analysis)
except Exception as e:
print(f"β οΈ Failed to load {json_file}: {e}")
print(f"β
Loaded {len(self.analyses_cache)} analyses from {len(list(self.data_dir.glob('customer_analysis_*.json')))} files")
except Exception as e:
print(f"β Failed to load analyses from disk: {e}")
self.analyses_cache = []
def format_text_for_table(self, text_list, max_items=3):
"""Format a list of text items for better table display with proper bullet point spacing."""
if not text_list:
return "No items"
if isinstance(text_list, str):
return text_list
if len(text_list) == 0:
return "No items"
elif len(text_list) == 1:
return f"β’ {text_list[0]}"
else:
# Format bullet points with proper spacing
formatted_items = []
items_to_show = min(len(text_list), max_items)
for i in range(items_to_show):
formatted_items.append(f"β’ {text_list[i]}")
# Add indicator for remaining items if any
if len(text_list) > max_items:
remaining = len(text_list) - max_items
formatted_items.append(f"β’ ... and {remaining} more")
return "\n".join(formatted_items)
def setup_ui(self):
"""Setup the Gradio interface for customer profile analyses."""
with gr.Blocks(
title="Customer Profile Analysis Dashboard",
theme=gr.themes.Soft(),
css="""
.customer-card {
border: 1px solid #e0e0e0;
border-radius: 8px;
padding: 16px;
margin: 8px 0;
background-color: #f8f9fa;
}
.customer-title {
font-weight: bold;
color: #2c3e50;
margin-bottom: 8px;
font-size: 1.1em;
}
.customer-meta {
font-size: 0.9em;
color: #6c757d;
margin-bottom: 12px;
}
.key-changes {
background-color: #fff3cd;
border-left: 4px solid #ffc107;
padding: 8px 12px;
margin: 8px 0;
border-radius: 4px;
font-size: 0.9em;
}
.recommendations {
background-color: #d1ecf1;
border-left: 4px solid #17a2b8;
padding: 8px 12px;
margin: 8px 0;
border-radius: 4px;
font-size: 0.9em;
}
.email-strategy {
background-color: #d4edda;
border-left: 4px solid #28a745;
padding: 8px 12px;
margin: 8px 0;
border-radius: 4px;
font-size: 0.9em;
}
.follow-up-email {
background-color: #e2e3e5;
border-left: 4px solid #6c757d;
padding: 8px 12px;
margin: 8px 0;
border-radius: 4px;
font-size: 0.9em;
}
.search-highlight {
background-color: #fff3cd;
padding: 2px 4px;
border-radius: 3px;
}
.dataframe {
font-size: 0.9em;
line-height: 1.4;
}
.dataframe td {
padding: 8px 6px;
vertical-align: top;
word-wrap: break-word;
white-space: pre-wrap;
}
.dataframe th {
padding: 8px 6px;
font-weight: bold;
background-color: #f8f9fa;
}
"""
) as self.interface:
gr.Markdown("# π Customer Profile Analysis Dashboard")
gr.Markdown("View and search through customer profile analyses with AI-generated insights and follow-up emails.")
# Statistics section at the top
with gr.Row():
with gr.Column(scale=1):
gr.Markdown("### π Dashboard Statistics")
self.stats_view = gr.HTML(
value=self.generate_statistics(),
label="Analysis Statistics",
show_label=False
)
# Filter buttons
with gr.Row():
gr.Markdown("### π Quick Filters")
with gr.Row():
self.strategy_dropdown = gr.Dropdown(
choices=self.get_strategy_choices(),
label="Email Strategy",
value=None,
multiselect=False,
scale=2
)
self.priority_dropdown = gr.Dropdown(
choices=self.get_priority_choices(),
label="Priority Level",
value=None,
multiselect=False,
scale=2
)
self.clear_filters_btn = gr.Button("π Clear All Filters", scale=1, variant="secondary")
gr.Markdown("---") # Separator line
# Search functionality
with gr.Row():
self.search_input = gr.Textbox(
label="Search Customer Analyses",
placeholder="Search by company name, customer ID, key changes, recommendations, or email content...",
scale=4
)
self.clear_search_btn = gr.Button("Clear Search", scale=1)
self.refresh_btn = gr.Button("Refresh Data", scale=1, variant="secondary")
# Main data table
self.customer_table = gr.Dataframe(
headers=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"],
datatype=["str", "str", "str", "str", "str", "str"],
interactive=False,
label="Customer Profile Analyses",
wrap=True,
max_height=600,
column_widths=["10%", "20%", "12%", "25%", "25%", "8%"],
value=self.load_customer_analyses()
)
# Detailed view accordion
with gr.Accordion("π Detailed Analysis View", open=False):
self.detailed_view = gr.HTML(
value="Select a row from the table above to view detailed analysis",
label="Detailed Analysis"
)
# Event handlers
self.search_input.change(
fn=self.filter_customer_analyses,
inputs=[self.search_input],
outputs=[self.customer_table]
)
self.clear_search_btn.click(
fn=self.clear_search,
inputs=[],
outputs=[self.search_input, self.customer_table]
)
self.refresh_btn.click(
fn=self.refresh_data,
inputs=[],
outputs=[self.customer_table, self.stats_view]
)
self.strategy_dropdown.change(
fn=self.filter_by_strategy,
inputs=[self.strategy_dropdown],
outputs=[self.customer_table]
)
self.priority_dropdown.change(
fn=self.filter_by_priority,
inputs=[self.priority_dropdown],
outputs=[self.customer_table]
)
self.clear_filters_btn.click(
fn=self.clear_filters,
inputs=[],
outputs=[self.strategy_dropdown, self.priority_dropdown, self.customer_table]
)
self.customer_table.select(
fn=self.show_detailed_analysis,
inputs=[self.customer_table],
outputs=[self.detailed_view]
)
def get_strategy_choices(self):
"""Get unique email strategy choices for dropdown."""
if not self.analyses_cache:
return []
strategies = set()
for doc in self.analyses_cache:
strategy = doc.get("email_strategy", {}).get("email_type", "Unknown")
strategies.add(strategy)
return sorted(list(strategies))
def get_priority_choices(self):
"""Get unique priority choices for dropdown."""
if not self.analyses_cache:
return []
priorities = set()
for doc in self.analyses_cache:
priority = doc.get("email_strategy", {}).get("priority", "Unknown")
priorities.add(priority)
return sorted(list(priorities))
def filter_by_strategy(self, strategy):
"""Filter analyses by email strategy."""
if not strategy:
return self.load_customer_analyses()
if not self.analyses_cache:
return pd.DataFrame(columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
try:
filtered_docs = []
for doc in self.analyses_cache:
doc_strategy = doc.get("email_strategy", {}).get("email_type", "Unknown")
if doc_strategy == strategy:
filtered_docs.append(doc)
return self.format_analyses_for_table(filtered_docs)
except Exception as e:
print(f"β Error filtering by strategy: {e}")
return self.load_customer_analyses()
def filter_by_priority(self, priority):
"""Filter analyses by priority level."""
if not priority:
return self.load_customer_analyses()
if not self.analyses_cache:
return pd.DataFrame(columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
try:
filtered_docs = []
for doc in self.analyses_cache:
doc_priority = doc.get("email_strategy", {}).get("priority", "Unknown")
if doc_priority == priority:
filtered_docs.append(doc)
return self.format_analyses_for_table(filtered_docs)
except Exception as e:
print(f"β Error filtering by priority: {e}")
return self.load_customer_analyses()
def clear_filters(self):
"""Clear all filters and reload data."""
return None, None, self.load_customer_analyses()
def format_analyses_for_table(self, docs):
"""Format a list of documents for table display."""
data = []
for doc in docs:
customer_id = str(doc.get("customer_id", "Unknown"))
company_name = doc.get("company_name", "Unknown Company")
analysis_date = doc.get("analysis_date", "Unknown Date")
# Format key changes with proper bullet points
key_changes = doc.get("key_changes", [])
key_changes_text = self.format_text_for_table(key_changes, max_items=3)
# Format recommendations with proper bullet points
recommendations = doc.get("recommendations", [])
recommendations_text = self.format_text_for_table(recommendations, max_items=3)
# Format email strategy
email_strategy = doc.get("email_strategy", {})
if isinstance(email_strategy, dict):
strategy_type = email_strategy.get("email_type", "Unknown")
priority = email_strategy.get("priority", "Unknown")
email_strategy_text = f"{strategy_type.replace('_', ' ').title()}\n({priority.title()})"
else:
email_strategy_text = str(email_strategy)[:60] + "..." if len(str(email_strategy)) > 60 else str(email_strategy)
data.append([
customer_id,
company_name,
analysis_date,
key_changes_text,
recommendations_text,
email_strategy_text
])
return pd.DataFrame(data, columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
def load_customer_analyses(self, limit: int = 100) -> pd.DataFrame:
"""Load customer analyses from disk and format for display."""
if not self.analyses_cache:
return pd.DataFrame(columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
try:
return self.format_analyses_for_table(self.analyses_cache[:limit])
except Exception as e:
print(f"β Error loading customer analyses: {e}")
return pd.DataFrame(columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
def filter_customer_analyses(self, search_term: str) -> pd.DataFrame:
"""Filter customer analyses based on search term."""
if not search_term.strip():
return self.load_customer_analyses()
if not self.analyses_cache:
return pd.DataFrame(columns=["Customer ID", "Company Name", "Analysis Date", "Key Changes", "Recommendations", "Email Strategy"])
try:
# Filter analyses based on search term (case-insensitive)
search_lower = search_term.lower()
filtered_docs = []
for doc in self.analyses_cache:
# Search in various fields
if (search_lower in str(doc.get("customer_id", "")).lower() or
search_lower in doc.get("company_name", "").lower() or
any(search_lower in change.lower() for change in doc.get("key_changes", [])) or
any(search_lower in rec.lower() for rec in doc.get("recommendations", [])) or
search_lower in str(doc.get("email_strategy", {}).get("key_messaging", "")).lower() or
search_lower in str(doc.get("follow_up_email", {}).get("subject", "")).lower() or
search_lower in str(doc.get("follow_up_email", {}).get("body", "")).lower()):
filtered_docs.append(doc)
return self.format_analyses_for_table(filtered_docs[:100]) # Limit to 100 results
except Exception as e:
print(f"β Error filtering customer analyses: {e}")
return self.load_customer_analyses()
def clear_search(self):
"""Clear search input and reload all data."""
return "", self.load_customer_analyses()
def refresh_data(self):
"""Refresh the data from disk."""
self.load_analyses_from_disk()
return self.load_customer_analyses(), self.generate_statistics()
def show_detailed_analysis(self, table_data, evt: gr.SelectData):
"""Show detailed analysis for selected row."""
try:
if evt.index[0] >= len(table_data):
return "Please select a valid row from the table."
# Get the row data using iloc for proper pandas indexing
row_data = table_data.iloc[evt.index[0]]
customer_id = str(row_data.iloc[0]) # Customer ID is the first column
# Find document in cache by customer_id
if not self.analyses_cache:
return "No analyses loaded from disk."
doc = None
for analysis in self.analyses_cache:
if str(analysis.get("customer_id")) == customer_id:
doc = analysis
break
if not doc:
return f"No detailed data found for customer {customer_id}"
# Format detailed analysis
html = self.format_detailed_analysis(doc)
return html
except Exception as e:
return f"Error loading detailed analysis: {str(e)}"
def format_detailed_analysis(self, doc: dict) -> str:
"""Format detailed analysis as HTML."""
customer_id = doc.get("customer_id", "Unknown")
company_name = doc.get("company_name", "Unknown Company")
analysis_date = doc.get("analysis_date", "Unknown Date")
# Format key changes
key_changes = doc.get("key_changes", [])
key_changes_html = ""
if isinstance(key_changes, list):
for i, change in enumerate(key_changes, 1):
key_changes_html += f"<li>{change}</li>"
else:
key_changes_html = f"<li>{key_changes}</li>"
# Format recommendations
recommendations = doc.get("recommendations", [])
recommendations_html = ""
if isinstance(recommendations, list):
for i, rec in enumerate(recommendations, 1):
recommendations_html += f"<li>{rec}</li>"
else:
recommendations_html = f"<li>{recommendations}</li>"
# Format email strategy
email_strategy = doc.get("email_strategy", {})
strategy_html = ""
if isinstance(email_strategy, dict):
strategy_type = email_strategy.get("email_type", "Unknown")
priority = email_strategy.get("priority", "Unknown")
key_messaging = email_strategy.get("key_messaging", "No messaging provided")
call_to_action = email_strategy.get("call_to_action", "No call to action")
strategy_html = f"""
<div class="email-strategy">
<strong>Type:</strong> {strategy_type.title()}<br>
<strong>Priority:</strong> {priority.title()}<br>
<strong>Key Messaging:</strong> {key_messaging}<br>
<strong>Call to Action:</strong> {call_to_action}
</div>
"""
else:
strategy_html = f"<div class='email-strategy'>{email_strategy}</div>"
# Format conversation insights
conversation_insights = doc.get("conversation_insights", [])
insights_html = ""
if conversation_insights:
insights_html = """
<div style="background-color: #f0f4f8; border-left: 4px solid #3b82f6; padding: 12px 16px; margin: 8px 0; border-radius: 4px;">
<h4 style="margin: 0 0 12px 0; color: #1e40af;">π¬ Recent Conversation Insights</h4>
"""
for i, conv in enumerate(conversation_insights[:5], 1): # Show up to 5 conversations
title = conv.get('title', 'Unknown')
source = conv.get('source', 'Unknown')
datetime_str = conv.get('datetime', 'Unknown')
summary = conv.get('summary', 'No summary available')
key_findings = conv.get('key_findings', [])
insights_html += f"""
<div style="background-color: white; padding: 12px; margin: 8px 0; border-radius: 4px; border: 1px solid #e0e7ff;">
<div style="font-weight: bold; color: #1e40af; margin-bottom: 4px;">
{i}. {title}
</div>
<div style="font-size: 0.85em; color: #6b7280; margin-bottom: 8px;">
{source} | {datetime_str}
</div>
<div style="margin-bottom: 8px;">
<strong>Summary:</strong> {summary}
</div>
"""
if key_findings:
insights_html += '<div style="margin-top: 8px;"><strong>Key Findings:</strong><ul style="margin: 4px 0; padding-left: 20px;">'
for finding in key_findings[:3]: # Show top 3 findings
finding_text = finding.get('finding', '')
impact = finding.get('impact', '')
insight_type = finding.get('insight_type', '')
# Color code by impact
impact_color = "#dc2626" if impact.lower() == "high" else "#f59e0b" if impact.lower() == "medium" else "#10b981"
insights_html += f"""
<li style="margin: 4px 0;">
<span style="background-color: {impact_color}; color: white; padding: 2px 6px; border-radius: 3px; font-size: 0.75em; font-weight: bold;">
{insight_type}/{impact}
</span>
{finding_text}
</li>
"""
insights_html += '</ul></div>'
insights_html += '</div>'
insights_html += '</div>'
else:
insights_html = """
<div style="background-color: #fef3c7; border-left: 4px solid #f59e0b; padding: 12px 16px; margin: 8px 0; border-radius: 4px;">
<strong>βΉοΈ No conversation insights available for this customer</strong>
</div>
"""
# Format follow-up email
follow_up_email = doc.get("follow_up_email", {})
email_html = ""
if isinstance(follow_up_email, dict):
subject = follow_up_email.get("subject", "No Subject")
body = follow_up_email.get("body", "No body content")
call_to_action = follow_up_email.get("call_to_action", "No call to action")
priority = follow_up_email.get("priority", "Unknown")
# Color code priority
priority_color = "#dc2626" if priority.lower() == "high" else "#f59e0b" if priority.lower() == "medium" else "#10b981"
email_html = f"""
<div class="follow-up-email">
<strong>Subject:</strong> {subject}<br>
<strong>Priority:</strong> <span style="background-color: {priority_color}; color: white; padding: 2px 8px; border-radius: 3px; font-weight: bold;">{priority.upper()}</span><br>
<strong>Body:</strong><br>
<div style="margin-left: 20px; margin-top: 8px; white-space: pre-wrap;">{body}</div>
<br><strong>Call to Action:</strong> {call_to_action}
</div>
"""
else:
email_html = f"<div class='follow-up-email'>{follow_up_email}</div>"
html = f"""
<div class="customer-card">
<div class="customer-title">{company_name} (ID: {customer_id})</div>
<div class="customer-meta">
<strong>Analysis Date:</strong> {analysis_date}
</div>
<h4>π Key Changes</h4>
<div class="key-changes">
<ul>{key_changes_html}</ul>
</div>
<h4>π‘ Recommendations</h4>
<div class="recommendations">
<ul>{recommendations_html}</ul>
</div>
<h4>π¬ Conversation Insights</h4>
{insights_html}
<h4>π§ Email Strategy</h4>
{strategy_html}
<h4>π¨ Follow-up Email</h4>
{email_html}
</div>
"""
return html
def generate_statistics(self) -> str:
"""Generate statistics about the customer analyses."""
if not self.analyses_cache:
return "No analyses loaded from disk."
try:
# Get total count
total_count = len(self.analyses_cache)
# Get email strategy distribution
strategy_counts = {}
for doc in self.analyses_cache:
strategy_type = doc.get("email_strategy", {}).get("email_type", "Unknown")
strategy_counts[strategy_type] = strategy_counts.get(strategy_type, 0) + 1
strategy_stats = [{"_id": k, "count": v} for k, v in sorted(strategy_counts.items(), key=lambda x: x[1], reverse=True)]
# Get priority distribution
priority_counts = {}
for doc in self.analyses_cache:
priority = doc.get("email_strategy", {}).get("priority", "Unknown")
priority_counts[priority] = priority_counts.get(priority, 0) + 1
priority_stats = [{"_id": k, "count": v} for k, v in sorted(priority_counts.items(), key=lambda x: x[1], reverse=True)]
# Count recent analyses (just show total for now since we don't have created_at timestamps)
recent_count = total_count
# Format statistics with enhanced visual design and clickable filters
stats_html = f"""
<div style="background: linear-gradient(135deg, #667eea 0%, #764ba2 100%); color: white; padding: 20px; border-radius: 12px; margin: 10px 0; box-shadow: 0 4px 6px rgba(0,0,0,0.1);">
<div style="display: grid; grid-template-columns: repeat(auto-fit, minmax(200px, 1fr)); gap: 20px;">
<!-- Total Counts Card -->
<div style="background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; backdrop-filter: blur(10px);">
<h4 style="margin: 0 0 10px 0; color: #fff; font-size: 1.1em;">π Total Accounts</h4>
<div style="font-size: 2em; font-weight: bold; color: #fff;">{total_count}</div>
</div>
<!-- Email Strategies Card -->
<div style="background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; backdrop-filter: blur(10px);">
<h4 style="margin: 0 0 10px 0; color: #fff; font-size: 1.1em;">π§ Email Strategies</h4>
<div style="font-size: 0.9em;">
"""
for stat in strategy_stats:
strategy_type = stat["_id"] or "Unknown"
count = stat["count"]
percentage = (count / total_count * 100) if total_count > 0 else 0
stats_html += f"""
<div style="display: flex; justify-content: space-between; margin: 5px 0; padding: 3px 0; border-bottom: 1px solid rgba(255,255,255,0.2);">
<span style="cursor: pointer; padding: 2px 6px; border-radius: 3px; transition: background-color 0.2s;"
onmouseover="this.style.backgroundColor='rgba(255,255,255,0.2)'"
onmouseout="this.style.backgroundColor='transparent'"
onclick="filterByStrategy('{strategy_type}')">{strategy_type.title()}</span>
<span style="font-weight: bold;">{count} ({percentage:.1f}%)</span>
</div>
"""
stats_html += """
</div>
</div>
<!-- Priority Distribution Card -->
<div style="background: rgba(255,255,255,0.1); padding: 15px; border-radius: 8px; backdrop-filter: blur(10px);">
<h4 style="margin: 0 0 10px 0; color: #fff; font-size: 1.1em;">β‘ Priority Levels</h4>
<div style="font-size: 0.9em;">
"""
for stat in priority_stats:
priority = stat["_id"] or "Unknown"
count = stat["count"]
percentage = (count / total_count * 100) if total_count > 0 else 0
# Color code based on priority
color = "#ff6b6b" if priority.lower() == "high" else "#feca57" if priority.lower() == "medium" else "#48dbfb"
stats_html += f"""
<div style="display: flex; justify-content: space-between; margin: 5px 0; padding: 3px 0; border-bottom: 1px solid rgba(255,255,255,0.2);">
<span style="color: {color}; font-weight: bold; cursor: pointer; padding: 2px 6px; border-radius: 3px; transition: background-color 0.2s;"
onmouseover="this.style.backgroundColor='rgba(255,255,255,0.2)'"
onmouseout="this.style.backgroundColor='transparent'"
onclick="filterByPriority('{priority}')">{priority.title()}</span>
<span style="font-weight: bold;">{count} ({percentage:.1f}%)</span>
</div>
"""
stats_html += """
</div>
</div>
</div>
</div>
<script>
function filterByStrategy(strategy) {
// This will be handled by Gradio's JavaScript interface
console.log('Filtering by strategy:', strategy);
// We'll implement this with Gradio's interface
}
function filterByPriority(priority) {
// This will be handled by Gradio's JavaScript interface
console.log('Filtering by priority:', priority);
// We'll implement this with Gradio's interface
}
</script>
"""
return stats_html
except Exception as e:
return f"Error generating statistics: {str(e)}"
def launch(self, **kwargs):
"""Launch the Gradio interface."""
return self.interface.launch(**kwargs)
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