app.py

import streamlit as st
import tempfile
import os
import re
import json
import subprocess
import requests
from pathlib import Path
from datetime import datetime, timezone, timedelta

from datetime import datetime, timezone, timedelta

def is_valid_email(email: str) -> bool:
    pattern = r'^[a-zA-Z0-9._%+-]+@[a-zA-Z0-9.-]+\.[a-zA-Z]{2,}$'
    return bool(re.match(pattern, email))

def to_rfc3339(dt_obj):
    """Convert datetime to UTC RFC3339 format: YYYY-MM-DDTHH:MM:SS.sssZ"""
    if dt_obj.tzinfo is None:
        dt_obj = dt_obj.replace(tzinfo=timezone.utc)
    else:
        dt_obj = dt_obj.astimezone(timezone.utc)
    return dt_obj.strftime('%Y-%m-%dT%H:%M:%S.') + f'{dt_obj.microsecond // 1000:03d}Z'


def render_teach_mode_page():
    """Render the Teach Mode page for INTERNAL users - Self-Healing & Maintenance"""
    st.title("🧠 Teach Mode")
    st.caption("Add and manage manual knowledge fixes for the AI assistant")
    
    tab1, tab2 = st.tabs(["Add Knowledge", "Manage Fixes"])
    
    with tab1:
        st.subheader("🧠 Teach the Bot")
        st.write("Add a new Q&A pair to fix knowledge gaps in the assistant.")
        
        with st.form("add_knowledge_form"):
            question = st.text_input(
                "Question",
                placeholder="What question should the bot be able to answer?",
                help="Enter the question that users might ask"
            )
            
            answer = st.text_area(
                "Answer",
                placeholder="What is the correct answer to this question?",
                height=150,
                help="Enter the accurate answer that the bot should provide"
            )
            
            col1, col2 = st.columns(2)
            
            with col1:
                product_options = ["RazorpayX", "POS", "Payroll", "SmartCollect", "Miscellaneous"]
                product = st.selectbox("Product", product_options)
            
            with col2:
                access_level = st.radio(
                    "Access Level",
                    ["INTERNAL", "EXTERNAL"],
                    horizontal=True,
                    help="INTERNAL = Staff only, EXTERNAL = Visible to all users"
                )
            
            submitted = st.form_submit_button("Add to Brain", type="primary", use_container_width=True)
            
            if submitted:
                if not question or not answer:
                    st.error("Please fill in both Question and Answer fields.")
                else:
                    try:
                        res = requests.post(
                            "http://127.0.0.1:8000/api/v1/knowledge/teach", 
                            json={
                                "question": question, 
                                "answer": answer, 
                                "product": product, 
                                "access_level": access_level
                            }
                        )
                        res.raise_for_status()
                        st.success("Knowledge Added! The bot will now use this information.")
                    except requests.exceptions.ConnectionError:
                        st.error("Cannot connect to backend API.")
                    except requests.exceptions.HTTPError as e:
                        st.error(f"Failed to add knowledge: {e.response.text}")
                    except Exception as e:
                        st.error(f"Unexpected error: {str(e)}")
    
    with tab2:
        st.subheader("🗑️ Maintain Knowledge Base")
        st.write("View and delete previously added manual fixes.")
        
        df = vector_db.get_all_manual_fixes()
        
        if df.empty:
            st.info("No manual fixes found. Use the 'Add Knowledge' tab to add new Q&A pairs.")
        else:
            st.dataframe(df, use_container_width=True, hide_index=True)
            
            st.divider()
            
            col1, col2 = st.columns([2, 1])
            
            with col1:
                selected_id = st.selectbox(
                    "Select ID to Remove",
                    options=df["ID"].tolist(),
                    help="Select the manual fix you want to delete"
                )
            
            with col2:
                st.write("")
                st.write("")
                if st.button("Delete Selected Fix", type="primary", use_container_width=True):
                    if selected_id:
                        try:
                            res = requests.delete(f"http://127.0.0.1:8000/api/v1/knowledge/teach/{selected_id}")
                            res.raise_for_status()
                            st.success(f"Deleted: {selected_id}")
                            st.rerun()
                        except requests.exceptions.ConnectionError:
                            st.error("Cannot connect to backend API.")
                        except requests.exceptions.HTTPError as e:
                            st.error(f"Failed to delete: {e.response.text}")
                        except Exception as e:
                            st.error(f"Unexpected error: {str(e)}")

def render_system_logs_page():
    """Render the System Logs page for INTERNAL users"""
    st.title("📊 System Logs")
    st.caption("Query and analyze Coralogix production logs")
    
    if not os.path.exists("./coralogix-mcp"):
        st.warning("⚠️ 'coralogix-mcp' binary not found. Running in MOCK mode.")
    
    if not os.environ.get("CORA_AUTH_TOKEN"):
        st.error("⚠️ CORA_AUTH_TOKEN not configured. Please add it to secrets to connect to Coralogix.")
    
    st.divider()
    
    st.subheader("⏰ Time Range")
    time_mode = st.radio("Select Time Range Mode", ["Quick Filters", "Custom Range"], horizontal=True)
    
    relative_hours = None
    start_dt = None
    end_dt = None
    
    if time_mode == "Quick Filters":
        col1, col2, col3, col4 = st.columns(4)
        
        if "selected_hours" not in st.session_state:
            st.session_state.selected_hours = 1
        
        with col1:
            if st.button("Last 1 Hour", use_container_width=True, type="primary" if st.session_state.selected_hours == 1 else "secondary"):
                st.session_state.selected_hours = 1
        with col2:
            if st.button("Last 6 Hours", use_container_width=True, type="primary" if st.session_state.selected_hours == 6 else "secondary"):
                st.session_state.selected_hours = 6
        with col3:
            if st.button("Last 24 Hours", use_container_width=True, type="primary" if st.session_state.selected_hours == 24 else "secondary"):
                st.session_state.selected_hours = 24
        with col4:
            if st.button("Last 4 Days", use_container_width=True, type="primary" if st.session_state.selected_hours == 96 else "secondary"):
                st.session_state.selected_hours = 96
        
        relative_hours = st.session_state.selected_hours
        st.info(f"📅 Selected: Last {relative_hours} hour(s)")
        
    else:
        from datetime import time as dt_time
        
        now = datetime.now()
        yesterday = now - timedelta(days=1)
        
        def get_default_hour_12(dt_obj):
            hour_24 = dt_obj.hour
            if hour_24 == 0:
                return 12
            elif hour_24 > 12:
                return hour_24 - 12
            else:
                return hour_24 if hour_24 != 0 else 12
        
        def get_default_meridian(dt_obj):
            return 1 if dt_obj.hour >= 12 else 0
        
        def convert_to_24_hour(hour_12, meridian):
            hour = int(hour_12)
            if meridian == "AM":
                return 0 if hour == 12 else hour
            else:
                return 12 if hour == 12 else hour + 12
        
        col1, col2 = st.columns(2)
        
        with col1:
            st.write("**Start Date & Time**")
            start_date = st.date_input("Start Date", value=yesterday.date(), key="start_date", label_visibility="collapsed")
            
            t1_c1, t1_c2, t1_c3, t1_c4, t1_c5 = st.columns([1.2, 1.2, 1.2, 0.3, 1.2])
            
            with t1_c1:
                start_hour = st.number_input("HH", min_value=1, max_value=12, value=get_default_hour_12(yesterday), key="start_hour", format="%02d")
            
            with t1_c2:
                start_minute = st.number_input("MM", min_value=0, max_value=59, value=yesterday.minute, key="start_minute", format="%02d")
            
            with t1_c3:
                start_second = st.number_input("SS", min_value=0, max_value=59, value=yesterday.second, key="start_second", format="%02d")
            
            with t1_c4:
                st.write("")
            
            with t1_c5:
                start_meridian = st.selectbox("", options=["AM", "PM"], index=get_default_meridian(yesterday), key="start_meridian", label_visibility="collapsed")
            
            start_hour_24 = convert_to_24_hour(start_hour, start_meridian)
            start_time_obj = dt_time(start_hour_24, int(start_minute), int(start_second))
            start_dt = datetime.combine(start_date, start_time_obj)
        
        with col2:
            st.write("**End Date & Time** *(defaults to now if unchanged)*")
            end_date = st.date_input("End Date", value=now.date(), key="end_date", label_visibility="collapsed")
            
            t2_c1, t2_c2, t2_c3, t2_c4, t2_c5 = st.columns([1.2, 1.2, 1.2, 0.3, 1.2])
            
            with t2_c1:
                end_hour = st.number_input("HH", min_value=1, max_value=12, value=get_default_hour_12(now), key="end_hour", format="%02d")
            
            with t2_c2:
                end_minute = st.number_input("MM", min_value=0, max_value=59, value=now.minute, key="end_minute", format="%02d")
            
            with t2_c3:
                end_second = st.number_input("SS", min_value=0, max_value=59, value=now.second, key="end_second", format="%02d")
            
            with t2_c4:
                st.write("")
            
            with t2_c5:
                end_meridian = st.selectbox("", options=["AM", "PM"], index=get_default_meridian(now), key="end_meridian", label_visibility="collapsed")
            
            end_hour_24 = convert_to_24_hour(end_hour, end_meridian)
            end_time_obj = dt_time(end_hour_24, int(end_minute), int(end_second))
            end_dt = datetime.combine(end_date, end_time_obj)
        
        if start_dt >= end_dt:
            st.error("Start Time must be earlier than End Time.")
    
    st.divider()
    
    st.subheader("🔍 Query Parameters")
    query_string = st.text_input(
        "Search Query",
        placeholder="Enter Payout ID, Error Code, IP, or Lucene syntax...",
        help="Use Lucene query syntax for advanced searches"
    )
    
    st.divider()
    
    if st.button("🚀 Fetch Logs", type="primary", use_container_width=True):
        if not query_string:
            st.warning("Please enter a search query.")
        elif time_mode == "Custom Range" and (start_dt is None or end_dt is None):
            st.warning("Please fix the time format errors before fetching logs.")
        elif time_mode == "Custom Range" and start_dt >= end_dt:
            st.warning("Start Time must be earlier than End Time. Please adjust your selection.")
        else:
            with st.spinner("Fetching logs from Coralogix..."):
                if time_mode == "Quick Filters":
                    logs_result = fetch_coralogix_logs(query_string, relative_hours=relative_hours)
                else:
                    logs_result = fetch_coralogix_logs(query_string, start_time=start_dt, end_time=end_dt)
            
            st.session_state.logs_result = logs_result
            st.session_state.logs_query = query_string
    
    if "logs_result" in st.session_state and st.session_state.logs_result:
        logs_result = st.session_state.logs_result
        query_string = st.session_state.get("logs_query", "")
        
        st.divider()
        
        if logs_result.get("mock_mode"):
            st.warning("⚠️ Displaying MOCK data - Coralogix binary not available")
        
        if logs_result.get("error"):
            st.error(f"Error: {logs_result.get('message', 'Unknown error')}")
        else:
            st.subheader("🤖 AI Analysis")
            with st.spinner("Analyzing logs with AI..."):
                analysis = analyze_logs_with_ai(logs_result, query_string)
            st.info(analysis)
            
            st.divider()
            
            st.subheader("📄 Raw Logs")
            with st.expander("View Raw JSON Logs", expanded=False):
                st.json(logs_result)

st.set_page_config(
    page_title="RazorpayX AI",
    page_icon="🤖",
    layout="wide"
)

if "messages" not in st.session_state:
    st.session_state.messages = []

if "user_info" not in st.session_state:
    col1, col2, col3 = st.columns([1, 2, 1])
    
    with col2:
        st.markdown("---")
        st.markdown("<h1 style='text-align: center;'>RazorpayX AI Support</h1>", unsafe_allow_html=True)
        st.markdown("<p style='text-align: center; color: gray;'>Your intelligent support assistant</p>", unsafe_allow_html=True)
        st.markdown("---")
        
        with st.container():
            st.subheader("Login")
            email = st.text_input("Enter your work email", placeholder="you@company.com")
            
            if st.button("Login", type="primary", use_container_width=True):
                if not email or not email.strip():
                    st.warning("Please enter an email.")
                elif not is_valid_email(email.strip()):
                    st.error("Please enter a valid email address (e.g., user@company.com)")
                else:
                    email = email.strip().lower()
                    
                    if email.endswith("@razorpay.com"):
                        role = "INTERNAL"
                    else:
                        role = "EXTERNAL"
                    
                    st.session_state["user_info"] = {
                        "email": email,
                        "role": role
                    }
                    st.rerun()
            
            st.markdown("---")
            st.markdown("<p style='text-align: center; font-size: 12px; color: gray;'>Staff members use @razorpay.com email for internal access</p>", unsafe_allow_html=True)

else:
    user_info = st.session_state["user_info"]
    user_email = user_info["email"]
    user_role = user_info["role"]
    
    if user_role == "EXTERNAL":
        current_view = "Assistant"
    else:
        if "current_view" not in st.session_state:
            st.session_state["current_view"] = "Assistant"
    
    with st.sidebar:
        st.markdown(f"👤 **{user_email}**")
        
        if user_role == "INTERNAL":
            st.error("🔴 Staff Access")
        else:
            st.success("🟢 Guest Access")
        
        if st.button("Logout", use_container_width=True):
            del st.session_state["user_info"]
            st.session_state.messages = []
            if "current_view" in st.session_state:
                del st.session_state["current_view"]
            st.rerun()
        
        st.divider()
        
        if user_role == "INTERNAL":
            current_view = st.radio(
                "Navigation",
                ["Assistant", "Knowledge Base Admin", "System Logs", "Teach Mode"],
                key="nav_radio"
            )
            st.session_state["current_view"] = current_view
        else:
            current_view = "Assistant"
        
        if current_view == "Assistant":
            st.header("📋 Session Context")
            
            product_options = ["All Products", "RazorpayX", "POS", "Payroll", "SmartCollect", "Miscellaneous"]
            selected_product = st.selectbox(
                "Product Filter",
                product_options,
                help="Filter knowledge base by product"
            )
            
            if st.button("Clear Chat History", use_container_width=True):
                st.session_state.messages = []
                st.rerun()
        
        elif current_view == "Knowledge Base Admin":
            st.header("🔧 Knowledge Admin")
            
            admin_tab = st.radio(
                "Select Action",
                ["Add Knowledge", "Manage Knowledge"],
                horizontal=True
            )
            
            st.divider()
            
            if admin_tab == "Add Knowledge":
                st.subheader("📋 Configure Metadata")
                
                product_options_admin = ["RazorpayX", "Payroll", "SmartCollect", "Other"]
                selected_product_admin = st.selectbox("Product", product_options_admin)
                
                if selected_product_admin == "Other":
                    custom_product = st.text_input("Enter Custom Product Name")
                    product = custom_product if custom_product else "Other"
                else:
                    product = selected_product_admin
                
                feature_options = ["General", "Payouts", "Webhooks", "API Errors", "Other"]
                selected_feature = st.selectbox("Feature", feature_options)
                
                if selected_feature == "Other":
                    custom_feature = st.text_input("Enter Custom Feature Name")
                    feature = custom_feature if custom_feature else "Other"
                else:
                    feature = selected_feature
                
                access_level = st.radio(
                    "Access Level",
                    ["EXTERNAL", "INTERNAL"],
                    format_func=lambda x: f"{x} (Public)" if x == "EXTERNAL" else f"{x} (Private)",
                    horizontal=True
                )
                
                st.divider()
                st.subheader("📁 Data Source")
                
                source_type = st.radio(
                    "Select Source Type",
                    ["Upload Files", "Add Web URL"],
                    horizontal=True
                )
                
                uploaded_file = None
                url_input = None
                
                if source_type == "Upload Files":
                    uploaded_file = st.file_uploader(
                        "Upload Document",
                        type=["pdf", "docx", "csv", "txt"],
                        help="Supported formats: PDF, DOCX, CSV, TXT"
                    )
                    if uploaded_file:
                        st.info(f"Selected: {uploaded_file.name}")
                else:
                    url_input = st.text_area(
                        "Enter URLs (one per line)",
                        placeholder="https://example.com/page1\nhttps://example.com/page2",
                        height=100
                    )
                
                st.divider()
                
                if st.button("🚀 Ingest into Knowledge Base", type="primary", use_container_width=True):
                    if source_type == "Upload Files" and uploaded_file:
                        with st.spinner("Processing document via backend API..."):
                            try:
                                files = {"file": (uploaded_file.name, uploaded_file.getvalue(), uploaded_file.type)}
                                data = {"product": product, "feature": feature, "access_level": access_level}
                                
                                res = requests.post("http://127.0.0.1:8000/api/v1/knowledge/upload/file", files=files, data=data)
                                res.raise_for_status()
                                response_data = res.json()
                                chunk_count = response_data.get("chunks", 0)
                                st.success(f"Successfully ingested {chunk_count} chunks from '{uploaded_file.name}'")
                            except requests.exceptions.ConnectionError:
                                st.error("Cannot connect to backend API uploading file.")
                            except Exception as e:
                                st.error(f"Error processing file via API: {str(e)}")
                    
                    elif source_type == "Add Web URL" and url_input:
                        urls = [url.strip() for url in url_input.strip().split("\n") if url.strip()]
                        
                        if not urls:
                            st.warning("Please enter at least one URL")
                        else:
                            with st.spinner(f"Processing {len(urls)} URL(s) via backend API..."):
                                try:
                                    payload = {
                                        "urls": urls,
                                        "product": product,
                                        "feature": feature,
                                        "access_level": access_level
                                    }
                                    res = requests.post("http://127.0.0.1:8000/api/v1/knowledge/upload/urls", json=payload)
                                    res.raise_for_status()
                                    result = res.json()
                                    
                                    total_chunks = result.get("total_chunks", 0)
                                    for detail in result.get("details", []):
                                        if detail["status"] == "success":
                                            st.success(f"Ingested {detail['chunks']} chunks from: {detail['url']}")
                                        else:
                                            st.error(f"Failed to process: {detail['url']}")
                                            
                                    if total_chunks > 0:
                                        st.success(f"Total: {total_chunks} chunks added to knowledge base")
                                except requests.exceptions.ConnectionError:
                                    st.error("Cannot connect to backend API processing URLs.")
                                except Exception as e:
                                    st.error(f"Error processing URLs via API: {str(e)}")
                    else:
                        st.warning("Please upload a file or enter URLs first")
            
            else:
                st.subheader("📊 Manage Knowledge Base")
                
                try:
                    res = requests.get("http://127.0.0.1:8000/api/v1/knowledge/sources")
                    if res.status_code == 200:
                        kb_data = res.json()
                        source_ids = kb_data.get("source_ids", [])
                        total_chunks = kb_data.get("total_chunks", 0)
                        source_metadata = kb_data.get("metadata", {})
                    else:
                        source_ids = []
                        total_chunks = 0
                        source_metadata = {}
                except Exception:
                    source_ids = []
                    total_chunks = 0
                    source_metadata = {}
                    st.error("Could not fetch knowledge base stats from backend API.")
                
                st.metric("Total Documents", len(source_ids))
                st.metric("Total Chunks", total_chunks)
                
                st.divider()
                
                if source_ids:
                    st.subheader("📑 Indexed Sources")
                    
                    for source_id in source_ids:
                        metadata = source_metadata.get(source_id, {})
                        
                        with st.expander(f"📄 {source_id}", expanded=False):
                            col1, col2 = st.columns(2)
                            with col1:
                                st.write(f"**Product:** {metadata.get('product', 'N/A')}")
                                st.write(f"**Feature:** {metadata.get('feature', 'N/A')}")
                            with col2:
                                st.write(f"**Access:** {metadata.get('access_level', 'N/A')}")
                                st.write(f"**Chunks:** {metadata.get('chunk_count', 0)}")
                            
                            if st.button(f"🗑️ Delete", key=f"del_{source_id}", type="secondary"):
                                try:
                                    delete_res = requests.delete(f"http://127.0.0.1:8000/api/v1/knowledge/source/{source_id}")
                                    delete_res.raise_for_status()
                                    deleted = delete_res.json().get("chunks_deleted", 0)
                                    st.success(f"Deleted {deleted} chunks for '{source_id}'")
                                    st.rerun()
                                except Exception as e:
                                    st.error(f"Failed to delete source from API: {e}")
                else:
                    st.info("No documents in the knowledge base yet. Add some using the 'Add Knowledge' tab.")
    
    if current_view == "Assistant":
        st.title("🤖 RazorpayX AI Assistant")
        
        if user_role == "INTERNAL":
            st.caption(f"🔴 Staff Access | Product: **{selected_product}**")
        else:
            st.caption(f"🟢 Guest Access | Product: **{selected_product}**")
        
        st.divider()
        
        for message in st.session_state.messages:
            with st.chat_message(message["role"]):
                st.markdown(message["content"])
        
        if prompt := st.chat_input("Ask a question about RazorpayX..."):
            st.session_state.messages.append({"role": "user", "content": prompt})
            
            with st.chat_message("user"):
                st.markdown(prompt)
            
            with st.chat_message("assistant"):
                with st.spinner("Thinking..."):
                    try:
                        api_payload = {
                            "query_text": prompt,
                            "role": user_role,
                            "product": selected_product,
                            "chat_history": st.session_state.messages[:-1]
                        }
                        
                        endpoint = "http://127.0.0.1:8000/api/v1/chat"
                        res = requests.post(endpoint, json=api_payload)
                        res.raise_for_status()
                        
                        response_data = res.json()
                        response = response_data.get("answer", "No answer provided from the API.")
                        
                    except requests.exceptions.ConnectionError:
                        st.error("The RazorpayX AI backend API is currently offline or unreachable.")
                        response = "I cannot connect to my knowledge base right now. Please try again later."
                    except Exception as e:
                        st.error(f"API Error: {str(e)}")
                        response = "There was an unexpected error talking to the backend API."
                    
                    st.markdown(response)
                    st.session_state.messages.append({"role": "assistant", "content": response})
    
    elif current_view == "Knowledge Base Admin" and user_role == "INTERNAL":
        st.title("Knowledge Base Admin")
        st.subheader("🔴 Staff Access - Full knowledge base visibility")
        
        st.divider()
        
        col1, col2 = st.columns([2, 1])
        
        with col1:
            st.subheader("📈 Knowledge Base Overview")
            
            try:
                res = requests.get("http://127.0.0.1:8000/api/v1/knowledge/sources")
                if res.status_code == 200:
                    kb_data = res.json()
                    source_ids = kb_data.get("source_ids", [])
                    total_chunks = kb_data.get("total_chunks", 0)
                    source_metadata = kb_data.get("metadata", {})
                else:
                    source_ids = []
                    total_chunks = 0
                    source_metadata = {}
            except Exception:
                source_ids = []
                total_chunks = 0
                source_metadata = {}
            
            if source_ids:
                import pandas as pd
                
                data = []
                for source_id in source_ids:
                    metadata = source_metadata.get(source_id, {})
                    data.append({
                        "Source": source_id,
                        "Product": metadata.get("product", "N/A"),
                        "Feature": metadata.get("feature", "N/A"),
                        "Access Level": metadata.get("access_level", "N/A"),
                        "Chunks": metadata.get("chunk_count", 0)
                    })
                
                df = pd.DataFrame(data)
                st.dataframe(df, use_container_width=True, hide_index=True)
            else:
                st.info("No documents in the knowledge base. Use the sidebar to add documents or URLs.")
        
        with col2:
            st.subheader("📊 Statistics")
            st.metric("Total Sources", len(source_ids))
            st.metric("Total Chunks", total_chunks)
            
            if source_ids:
                products = {}
                access_levels = {"EXTERNAL": 0, "INTERNAL": 0}
                
                for source_id in source_ids:
                    metadata = source_metadata.get(source_id, {})
                    prod = metadata.get("product", "Unknown")
                    products[prod] = products.get(prod, 0) + 1
                    
                    access = metadata.get("access_level", "Unknown")
                    if access in access_levels:
                        access_levels[access] += 1
                
                st.write("**By Product:**")
                for prod, count in products.items():
                    st.write(f"- {prod}: {count}")
                
                st.write("**By Access Level:**")
                for access, count in access_levels.items():
                    label = "Public" if access == "EXTERNAL" else "Private"
                    st.write(f"- {label}: {count}")
    
    elif current_view == "System Logs" and user_role == "INTERNAL":
        render_system_logs_page()
    
    elif current_view == "Teach Mode" and user_role == "INTERNAL":
        render_teach_mode_page()