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Gradio chat interface for end users
Uses Gradio 5.49 ChatInterface API
"""
import gradio as gr
import os
import time
from collections import defaultdict
from dotenv import load_dotenv
from src.chatbot import create_rag_chain, ask_question
from src.config import load_settings
import re
import uuid
load_dotenv()
# Rate limiting: max requests per window (per IP)
RATE_LIMIT_REQUESTS = int(os.getenv("RATE_LIMIT_REQUESTS", "10"))
RATE_LIMIT_WINDOW_SEC = int(os.getenv("RATE_LIMIT_WINDOW_SEC", "60"))
_rate_limit_store = defaultdict(list) # {client_key: [timestamp, ...]}
_rate_limit_last_cleanup = 0.0
def _check_rate_limit(client_key: str) -> bool:
"""
Sliding window rate limit. Returns True if allowed, False if exceeded.
Periodically purges stale keys to prevent unbounded memory growth.
"""
global _rate_limit_last_cleanup
now = time.time()
window_start = now - RATE_LIMIT_WINDOW_SEC
# Purge stale keys every 5 minutes
if now - _rate_limit_last_cleanup > 300:
stale = [k for k, ts in _rate_limit_store.items() if not ts or ts[-1] <= window_start]
for k in stale:
del _rate_limit_store[k]
_rate_limit_last_cleanup = now
timestamps = _rate_limit_store[client_key]
timestamps[:] = [t for t in timestamps if t > window_start]
if len(timestamps) >= RATE_LIMIT_REQUESTS:
return False
timestamps.append(now)
return True
# Initialize chatbot
print("🤖 Initializing chatbot...")
rag_chain, retriever, llm = create_rag_chain()
print("✅ Chatbot ready!")
def check_pii(text: str) -> bool:
"""
Simple PII detection - checks for potential names
Args:
text: Input text to check
Returns:
True if PII detected
"""
# Check for capitalized words that might be names
name_pattern = r'\b[A-Z][a-z]+ [A-Z][a-z]+\b'
if re.search(name_pattern, text):
return True
return False
def chat_response(message: str, history: list, session_id: str, request: gr.Request) -> str:
"""
Handle chat messages (Gradio 5.x format)
Args:
message: User's message
history: Conversation history
session_id: Unique session ID per user (from gr.State)
request: Injected by Gradio for IP/session access
Returns:
Bot's response
"""
# Rate limit by IP (fallback to session_id if no client info)
client_key = "unknown"
if request and hasattr(request, "client") and request.client:
client_key = getattr(request.client, "host", session_id) or session_id
else:
client_key = session_id
if not _check_rate_limit(client_key):
return "⏳ **Rate limit reached.** Please wait a minute before sending more messages. This helps us keep the service available for everyone."
# Check for PII
warning = ""
if check_pii(message):
warning = "⚠️ **Warning**: Please avoid sharing personal information about specific individuals.\n\n"
# Get answer from chatbot
try:
answer, sources = ask_question(rag_chain, retriever, llm, message, session_id)
# Format response with sources
response = warning + answer
if sources:
response += "\n\n📚 **Sources:**\n"
for i, doc in enumerate(sources[:3], 1):
source = doc.metadata.get("source", "Unknown")
response += f"{i}. {source}\n"
return response
except Exception as e:
return f"❌ Error: {str(e)}\n\nPlease make sure documents have been uploaded to the system."
# Load configurable texts from config/chatbot_settings.json
_settings = load_settings()
DISCLAIMER_TEXT = _settings["disclaimer"]
WELCOME_MESSAGE = _settings["welcome_message"]
BOT_AVATAR_URL = _settings["bot_avatar_url"]
PRIMARY_COLOR = _settings["primary_color"]
SECONDARY_COLOR = _settings["secondary_color"]
FONT_FAMILY = _settings["font_family"]
_custom_css = f"""
* {{ font-family: {FONT_FAMILY} !important; }}
.gradio-container button.primary {{ background-color: {PRIMARY_COLOR} !important; border-color: {PRIMARY_COLOR} !important; }}
.gradio-container {{ background-color: {SECONDARY_COLOR} !important; }}
"""
# Create Gradio interface (Gradio 5.49 API)
with gr.Blocks(
title="HR Intervals AI Assistant",
theme=gr.themes.Soft(),
css=_custom_css
) as demo:
gr.Markdown("""
# 💼 HR Intervals AI Assistant
Get instant answers to your HR questions based on our knowledge base.
""")
# Disclaimer (text loaded from config)
with gr.Accordion("⚠️ Important Disclaimer - Please Read", open=False):
gr.Markdown(DISCLAIMER_TEXT)
# Per-user session ID (each browser tab gets a unique ID)
session_state = gr.State(value=lambda: str(uuid.uuid4()))
# Chat interface (Gradio 5.x ChatInterface)
chat_interface = gr.ChatInterface(
fn=chat_response,
additional_inputs=[session_state],
chatbot=gr.Chatbot(
height=500,
show_label=False,
type='messages',
avatar_images=(None, BOT_AVATAR_URL),
value=[{"role": "assistant", "content": WELCOME_MESSAGE}]
),
textbox=gr.Textbox(
placeholder="Ask your HR question here...",
container=False,
scale=7
),
title="",
description="",
theme=gr.themes.Soft()
)
# Footer
gr.Markdown("""
---
💡 **Tip**: Be specific in your questions for better answers. Remember to consult professionals for legal matters.
""")
if __name__ == "__main__":
demo.launch(
server_name="0.0.0.0",
server_port=7860,
share=False
)
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