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import streamlit as st
from main import ask_agent_sync
from pdf_generator import pdf_receipt_generator
st.set_page_config(page_title="Intelligent Booking Agent", page_icon=":robot:")
st.title("Velora AI Agent")
st.write("Chat with Velora about Bookings and Receipts")
# Initialize chat session
if "messages" not in st.session_state:
st.session_state.messages = []
if "history" not in st.session_state:
st.session_state.history = None
if "tool_data" not in st.session_state:
st.session_state.tool_data = []
if "pdfs" not in st.session_state:
st.session_state.pdfs = []
# Display chat history
for msg in st.session_state.messages:
role = msg["role"]
content = msg["content"]
with st.chat_message(role):
st.markdown(content)
# User input
if prompt := st.chat_input("Type your message..."):
# Append user message
st.session_state.messages.append({"role": "user", "content": prompt})
with st.chat_message("user"):
st.markdown(prompt)
with st.chat_message("assistant"):
message_placeholder = st.empty()
message_placeholder.markdown("Typing...")
st.session_state.tool_data = []
st.session_state.pdfs = []
# Call agent
response = ask_agent_sync(prompt, st.session_state.history)
st.session_state.history = response["history"]
# Append agent response
st.session_state.messages.append({"role": "assistant", "content": response["output"]})
# Replace placeholder with actual response
message_placeholder.markdown(response["output"])
# message_placeholder.markdown(response)
# response
# st.session_state.tool_data = []
for entry in response["history"]:
if entry.__class__.__name__ == "ModelRequest":
for parts in entry.parts:
if parts.__class__.__name__ == "ToolReturnPart":
if parts.tool_name == "fetch_records":
st.session_state.tool_data.extend(parts.content)
# print(parts.content)
#
# for entry in response.get("history", []):
# model_response = getattr(entry, "model_response", None)
# if model_response:
# for part in getattr(model_response, "parts", []):
# if part.__class__.__name__ == "ToolReturnPart":
# tool_data.extend(part.content) # This is your Airtable records
if st.session_state.tool_data and not st.session_state.pdfs:
for item in st.session_state.tool_data:
pdf_buffer = pdf_receipt_generator(item)
st.session_state.pdfs.append(pdf_buffer) # Only if the tool returned data
if st.session_state.pdfs:
st.markdown("### 📄 Available Receipts")
for idx, item in enumerate(st.session_state.pdfs, start=1):
# pdf_buffer = pdf_receipt_generator(item)
st.download_button(
label=f"📄 Download Receipt {idx}",
data=item,
file_name=f"trip_receipt_{idx}.pdf",
mime="application/pdf",
key=f"download_{idx}"
)
# Test the pdf_generator separately
# if st.button("Test PDF Generation"):
# test_data = {
# "trip_id": "12345",
# "passenger_name": "John Doe",
# "pickup": "123 Main St",
# "dropoff": "456 Oak Ave",
# "fare": "$25.00",
# "date": "2025-01-01"
# }
# try:
# pdf_buffer = pdf_receipt_generator(test_data)
# st.download_button(
# label="📄 Download Test Receipt",
# data=pdf_buffer,
# file_name="test_receipt.pdf",
# mime="application/pdf"
# )
# except Exception as e:
# st.error(f"PDF generation error: {str(e)}")
# st.experimental_rerun()
# -----------------------
# Footer / credits
# -----------------------
st.markdown("---")
# st.markdown(
# "Created with :heart: using **Streamlit** and **Airbyte**."
# )
import logging
logging.basicConfig(level=logging.INFO)
logging.info(f"Tool records found: {len(st.session_state.tool_data)}") |