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import streamlit as st
import os
import time
import re
import requests
import tempfile
import wave
import numpy as np
from openai import OpenAI
from streamlit_audio_recorder import audio_recorder
# ------------------ Page Config ------------------
st.set_page_config(page_title="Document AI Assistant", layout="wide")
st.title("π Document AI Assistant")
st.caption("Chat with an AI Assistant on your medical/pathology documents")
# ------------------ Load Secrets ------------------
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
ASSISTANT_ID = os.environ.get("ASSISTANT_ID")
if not OPENAI_API_KEY or not ASSISTANT_ID:
st.error("β Missing secrets. Please set both OPENAI_API_KEY and ASSISTANT_ID in Hugging Face Space settings.")
st.stop()
client = OpenAI(api_key=OPENAI_API_KEY)
# ------------------ Session State Init ------------------
for key in ["messages", "thread_id", "image_url", "transcript"]:
if key not in st.session_state:
st.session_state[key] = [] if key == "messages" else None
# ------------------ Whisper Transcription ------------------
def transcribe_audio(file_path, api_key):
with open(file_path, "rb") as f:
response = requests.post(
"https://api.openai.com/v1/audio/transcriptions",
headers={"Authorization": f"Bearer {api_key}"},
files={"file": f},
data={"model": "whisper-1"}
)
return response.json().get("text", None)
# ------------------ Sidebar & Layout ------------------
st.sidebar.header("π§ Settings")
if st.sidebar.button("π Clear Chat"):
st.session_state.messages = []
st.session_state.thread_id = None
st.session_state.image_url = None
st.session_state.transcript = None
st.rerun()
show_image = st.sidebar.checkbox("π Show Document Image", value=True)
col1, col2 = st.columns([1, 2])
# ------------------ Image Panel ------------------
with col1:
if show_image and st.session_state.image_url:
st.image(st.session_state.image_url, caption="π Extracted Page", use_container_width=True)
# ------------------ Chat + Mic Panel ------------------
with col2:
for message in st.session_state.messages:
st.chat_message(message["role"]).write(message["content"])
st.subheader("ποΈ Ask with Your Voice")
audio_bytes = audio_recorder(pause_threshold=3.0, energy_threshold=-1.0, sample_rate=44100)
if audio_bytes:
# Save temporary WAV file
with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmpfile:
tmpfile.write(audio_bytes)
tmp_path = tmpfile.name
st.audio(tmp_path, format="audio/wav")
with st.spinner("π§ Transcribing..."):
transcript = transcribe_audio(tmp_path, OPENAI_API_KEY)
if transcript:
st.success("π Transcript: " + transcript)
st.session_state.transcript = transcript
# Submit Transcript to Assistant
if st.session_state.transcript:
if st.button("β
Send Transcript to Assistant"):
user_input = st.session_state.transcript
st.session_state.transcript = None # reset
st.session_state.messages.append({"role": "user", "content": user_input})
st.chat_message("user").write(user_input)
try:
if st.session_state.thread_id is None:
thread = client.beta.threads.create()
st.session_state.thread_id = thread.id
thread_id = st.session_state.thread_id
client.beta.threads.messages.create(thread_id=thread_id, role="user", content=user_input)
run = client.beta.threads.runs.create(thread_id=thread_id, assistant_id=ASSISTANT_ID)
with st.spinner("π€ Assistant is thinking..."):
while True:
run_status = client.beta.threads.runs.retrieve(thread_id=thread_id, run_id=run.id)
if run_status.status == "completed":
break
time.sleep(1)
messages = client.beta.threads.messages.list(thread_id=thread_id)
assistant_message = next(
(m.content[0].text.value for m in reversed(messages.data) if m.role == "assistant"), None
)
st.chat_message("assistant").write(assistant_message)
st.session_state.messages.append({"role": "assistant", "content": assistant_message})
# Extract GitHub image if available
image_match = re.search(
r'https://raw\.githubusercontent\.com/AndrewLORTech/surgical-pathology-manual/main/[\w\-/]*\.png',
assistant_message
)
if image_match:
st.session_state.image_url = image_match.group(0)
except Exception as e:
st.error(f"β Error: {str(e)}")
# Fallback text input
if prompt := st.chat_input("π¬ Or type your question..."):
st.session_state.messages.append({"role": "user", "content": prompt})
st.chat_message("user").write(prompt)
st.session_state.transcript = prompt # Treat like voice input for now
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