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import streamlit as st
import os
import time
import json
import re
from openai import OpenAI
# Basic config
st.set_page_config(page_title="Forrestdale Drawing Viewer", layout="wide")
st.title("📐 Forrestdale Technical Drawing Assistant")
OPENAI_API_KEY = os.environ.get("OPENAI_API_KEY")
ASSISTANT_ID = "asst_DjvuWBc7tCvMbAhY7n1em4BZ"
if not OPENAI_API_KEY:
st.error("❌ Missing OPENAI_API_KEY.")
st.stop()
client = OpenAI(api_key=OPENAI_API_KEY)
if "tech_thread_id" not in st.session_state:
thread = client.beta.threads.create()
st.session_state.tech_thread_id = thread.id
if "tech_messages" not in st.session_state:
st.session_state.tech_messages = []
prompt = st.chat_input("Ask about plans, drawings or components (e.g. Show me all electrical plans)")
if prompt:
st.session_state.tech_messages.append({"role": "user", "content": prompt})
for msg in st.session_state.tech_messages:
with st.chat_message(msg["role"]):
st.markdown(msg["content"])
# Fetch assistant reply
if st.session_state.tech_messages and st.session_state.tech_messages[-1]["role"] == "user":
with st.spinner("⏳ Fetching results from assistant..."):
try:
client.beta.threads.messages.create(
thread_id=st.session_state.tech_thread_id,
role="user",
content=st.session_state.tech_messages[-1]["content"]
)
run = client.beta.threads.runs.create(
thread_id=st.session_state.tech_thread_id,
assistant_id=ASSISTANT_ID
)
while True:
run_status = client.beta.threads.runs.retrieve(
thread_id=st.session_state.tech_thread_id,
run_id=run.id
)
if run_status.status in ["completed", "failed", "cancelled"]:
break
time.sleep(1)
if run_status.status != "completed":
st.error("⚠️ Assistant run failed.")
else:
messages = client.beta.threads.messages.list(thread_id=st.session_state.tech_thread_id)
for message in reversed(messages.data):
if message.role == "assistant":
reply_content = message.content[0].text.value.strip()
st.session_state.tech_messages.append({"role": "assistant", "content": reply_content})
try:
match = re.search(r"```json\s*(.*?)```", reply_content, re.DOTALL)
json_str = match.group(1) if match else reply_content
results = json.loads(json_str)
if isinstance(results, list):
cols = st.columns(4)
for idx, item in enumerate(results):
with cols[idx % 4]:
with st.container(border=True):
st.markdown(f"### 📁 {item.get('drawing_number')} ({item.get('discipline')})", help=item.get("summary"))
st.caption(item.get("summary"))
with st.expander("📂 View Drawing Details"):
if item.get("question"):
st.markdown(f"**Question Match:** {item.get('question')}")
if item.get("image"):
st.image(item.get("image"), caption=item.get("drawing_number"))
elif item.get("images"):
for i, img in enumerate(item["images"]):
if img.startswith("http"):
st.image(img, caption=f"{item['drawing_number']} – Page {i+1}")
except Exception as parse_error:
st.warning("🟡 Could not parse assistant response as JSON.")
break
except Exception as e:
st.error(f"❌ Error occurred: {e}")
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