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import streamlit as st
import os
import time
import re
import requests
from PIL import Image
from io import BytesIO
from openai import OpenAI
# ------------------ Page Config ------------------
st.set_page_config(page_title="AI Pathology Assistant", layout="wide", initial_sidebar_state="collapsed")
# ------------------ Authentication ------------------
VALID_USERS = {
"[email protected]": "Pass.123",
"[email protected]": "Pass.123",
"[email protected]": "Pass.123",
"[email protected]": "Pass.123",
}
def login():
st.title("π Login Required")
email = st.text_input("Email")
password = st.text_input("Password", type="password")
if st.button("Login"):
if VALID_USERS.get(email) == password:
st.session_state.authenticated = True
st.rerun()
else:
st.error("β Incorrect email or password.")
if "authenticated" not in st.session_state:
st.session_state.authenticated = False
if not st.session_state.authenticated:
login()
st.stop()
# ------------------ Load OpenAI ------------------
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
if not OPENAI_API_KEY:
st.error("β Missing OPENAI_API_KEY environment variable.")
st.stop()
client = OpenAI(api_key=OPENAI_API_KEY)
# ------------------ Assistant Setup ------------------
ASSISTANT_ID = "asst_jXDSjCG8LI4HEaFEcjFVq8KB"
# ------------------ State Initialization ------------------
for key in ["messages", "thread_id", "image_urls", "pending_prompt"]:
if key not in st.session_state:
st.session_state[key] = [] if key.endswith("s") else None
# ------------------ UI Tabs ------------------
tab1, tab2 = st.tabs(["π¬ Chat Assistant", "πΌοΈ Visual Reference Search"])
# ------------------ Tab 1: Chat Assistant ------------------
with tab1:
with st.sidebar:
st.header("π§ͺ Pathology Tools")
if st.button("π§Ή Clear Chat"):
for k in ["messages", "thread_id", "image_urls", "pending_prompt"]:
st.session_state[k] = [] if k.endswith("s") else None
st.rerun()
show_image = st.toggle("πΈ Show Images", value=True)
keyword = st.text_input("Keyword Search", placeholder="e.g. mitosis, carcinoma")
if st.button("π Search") and keyword:
st.session_state.pending_prompt = f"Find clauses or references related to: {keyword}"
section = st.text_input("Section Lookup", placeholder="e.g. Connective Tissue")
if section:
st.session_state.pending_prompt = f"Summarize or list key points from section: {section}"
action = st.selectbox("Common Pathology Queries", [
"Select an action...",
"List histological features of inflammation",
"Summarize features of carcinoma",
"List muscle types and features",
"Extract diagnostic markers",
"Summarize embryology stages"
])
if action != "Select an action...":
st.session_state.pending_prompt = action
chat_col, image_col = st.columns([2, 1])
with chat_col:
st.markdown("### π¬ Ask a Pathology-Specific Question")
user_input = st.chat_input("Example: What are features of squamous cell carcinoma?")
if user_input:
st.session_state.messages.append({"role": "user", "content": user_input})
elif st.session_state.pending_prompt:
st.session_state.messages.append({"role": "user", "content": st.session_state.pending_prompt})
st.session_state.pending_prompt = None
if st.session_state.messages and st.session_state.messages[-1]["role"] == "user":
try:
if not st.session_state.thread_id:
st.session_state.thread_id = client.beta.threads.create().id
client.beta.threads.messages.create(
thread_id=st.session_state.thread_id,
role="user",
content=st.session_state.messages[-1]["content"]
)
run = client.beta.threads.runs.create(
thread_id=st.session_state.thread_id,
assistant_id=ASSISTANT_ID
)
with st.spinner("π¬ Analyzing..."):
while True:
status = client.beta.threads.runs.retrieve(
thread_id=st.session_state.thread_id, run_id=run.id
)
if status.status in ("completed", "failed", "cancelled"):
break
time.sleep(1)
if status.status == "completed":
responses = client.beta.threads.messages.list(
thread_id=st.session_state.thread_id
).data
for m in reversed(responses):
if m.role == "assistant":
reply = m.content[0].text.value.strip()
if not any(reply in msg["content"] or msg["content"] in reply
for msg in st.session_state.messages if msg["role"] == "assistant"):
st.session_state.messages.append({"role": "assistant", "content": reply})
# Extract image URLs from response
images = re.findall(
r'https://raw\.githubusercontent\.com/AndrewLORTech/witspathologai/main/[^\s\n"]+\.png',
reply
)
st.session_state.image_urls = images
break
else:
st.error("β Assistant failed to complete.")
st.rerun()
except Exception as e:
st.error(f"β Error: {e}")
# Display messages
for msg in st.session_state.messages:
with st.chat_message(msg["role"]):
st.markdown(msg["content"], unsafe_allow_html=True)
# Display follow-up questions
if st.session_state.messages and st.session_state.messages[-1]["role"] == "assistant":
last = st.session_state.messages[-1]["content"]
if "Some Possible Questions:" in last:
# Filter only lines that are actual questions
all_lines = re.findall(r"[-β’]\s*(.*)", last)
questions = [line for line in all_lines if line.strip().endswith("?")]
if questions:
st.markdown("#### π‘ Follow-Up Suggestions")
for q in questions:
if st.button(f"π {q}"):
st.session_state.pending_prompt = q
st.rerun()
else:
st.markdown("#### π‘ No follow-up questions detected in the assistant's response.")
with image_col:
if show_image and st.session_state.image_urls:
st.markdown("### πΌοΈ Images")
for url in st.session_state.image_urls:
try:
img = Image.open(BytesIO(requests.get(url, timeout=5).content))
st.image(img, caption=url.split("/")[-1], use_container_width=True)
except Exception:
st.warning(f"β οΈ Failed to load image: {url}")
# ------------------ Tab 2: Visual Reference Search ------------------
with tab2:
ASSISTANT_ID = "asst_9v09zgizdcuuhNdcFQpRo9RO"
if "image_thread_id" not in st.session_state:
st.session_state.image_thread_id = None
if "image_response" not in st.session_state:
st.session_state.image_response = None
if "image_results" not in st.session_state:
st.session_state.image_results = []
if "image_lightbox" not in st.session_state:
st.session_state.image_lightbox = None
image_input = st.chat_input("Ask for histology visual references (e.g. ovary histology, mitosis)")
if image_input:
st.session_state.image_response = None
st.session_state.image_results = []
st.session_state.image_lightbox = None
try:
if st.session_state.image_thread_id is None:
thread = client.beta.threads.create()
st.session_state.image_thread_id = thread.id
client.beta.threads.messages.create(
thread_id=st.session_state.image_thread_id,
role="user",
content=image_input
)
run = client.beta.threads.runs.create(
thread_id=st.session_state.image_thread_id,
assistant_id=ASSISTANT_ID
)
with st.spinner("π¬ Searching for histology references..."):
while True:
run_status = client.beta.threads.runs.retrieve(
thread_id=st.session_state.image_thread_id,
run_id=run.id
)
if run_status.status in ("completed", "failed", "cancelled"):
break
time.sleep(1)
if run_status.status == "completed":
messages = client.beta.threads.messages.list(thread_id=st.session_state.image_thread_id)
for msg in reversed(messages.data):
if msg.role == "assistant":
response_text = msg.content[0].text.value
st.session_state.image_response = response_text
# β
FINAL FIXED PARSER: Handles Image URL on next line
lines = response_text.splitlines()
image_urls = []
expecting_url = False
for line in lines:
line_clean = line.strip().replace("**", "")
if "Image URL:" in line_clean:
parts = line_clean.split("Image URL:")
if len(parts) > 1 and parts[1].strip().startswith("http"):
image_urls.append(parts[1].strip())
else:
expecting_url = True # Flag next line
elif expecting_url:
if line_clean.startswith("http"):
image_urls.append(line_clean)
expecting_url = False
st.session_state.image_results = [{"image": url} for url in image_urls]
if image_urls and not st.session_state.image_lightbox:
st.session_state.image_lightbox = image_urls[0]
break
except Exception as e:
st.error(f"β Visual Assistant Error: {e}")
text_col, image_col = st.columns([2, 1])
with text_col:
if st.session_state.image_response:
st.markdown("### π§ Assistant Response")
st.markdown(st.session_state.image_response, unsafe_allow_html=True)
# Optional: Debug
# st.code(st.session_state.image_response, language="markdown")
with image_col:
if st.session_state.image_results:
st.markdown("### πΌοΈ Image Preview(s)")
for i, item in enumerate(st.session_state.image_results):
image_url = item.get("image")
if image_url:
try:
encoded_url = requests.utils.requote_uri(image_url)
r = requests.get(encoded_url, timeout=10)
r.raise_for_status()
img = Image.open(BytesIO(r.content))
st.image(img, caption=encoded_url.split("/")[-1], use_container_width=True)
if st.button("π View Full Image", key=f"full_img_{i}"):
st.session_state.image_lightbox = encoded_url
except Exception as e:
st.warning(f"β οΈ Could not load: {image_url}")
st.error(f"{e}")
else:
st.info("βΉοΈ No image references found yet.")
if st.session_state.image_lightbox:
st.markdown("### π¬ Full Image View")
try:
img_url = st.session_state.image_lightbox
r = requests.get(img_url, timeout=10)
r.raise_for_status()
full_img = Image.open(BytesIO(r.content))
st.image(full_img, caption=img_url.split("/")[-1], use_container_width=True)
except Exception as e:
st.warning("β οΈ Could not load full image.")
st.error(str(e))
if st.button("β Close Preview"):
st.session_state.image_lightbox = None
st.rerun()
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