Create app.py

app.py

@@ -0,0 +1,143 @@
+import streamlit as st
+import os
+import re
+from openai import AzureOpenAI
+from streamlit_pills import pills
+
+st.set_page_config(layout="wide")
+
+# Initialize the Azure OpenAI client
+client = AzureOpenAI(
+  azure_endpoint = os.getenv("AZURE_OPENAI_ENDPOINT"),
+  api_key= os.getenv("AZURE_OPENAI_API_KEY"),
+  api_version="2024-05-01-preview"
+)
+
+# Retrieve the assistant
+assistant = client.beta.assistants.retrieve("asst_Tbjd3ckxAfOjj29TeP6KaZ0v")
+
+# Streamlit app
+st.title("MultiCare AI Summary Demo")
+
+# Initialize session state
+if "thread_id" not in st.session_state:
+    thread = client.beta.threads.create()
+    st.session_state.thread_id = thread.id
+
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+if "selected_pill" not in st.session_state:
+    st.session_state.selected_pill = None
+
+
+def clean_content(content):
+    # Remove 【18:18†source】and 【5†source】style citations
+    content = re.sub(r'【\d+(?::\d+)?†source】', '', content)
+    # Prettify [1][2] style citations to [1, 2]
+    content = re.sub(r'\[(\d+)\](?:\[(\d+)\])+', lambda m: f"[{', '.join(sorted(set(m.groups())))}]", content)
+    return content.strip()
+
+def process_message_content(message):
+    message_content = message.content[0].text
+    annotations = message_content.annotations
+    citations = []
+    citation_map = {}
+
+    for index, annotation in enumerate(annotations):
+        if file_citation := getattr(annotation, "file_citation", None):
+            cited_file = client.files.retrieve(file_citation.file_id)
+            citation = f"{cited_file.filename}"
+            if citation not in citation_map:
+                citation_map[citation] = len(citation_map) + 1
+            citations.append(f"[{citation_map[citation]}] {citation}")
+            message_content.value = message_content.value.replace(annotation.text, f"[{citation_map[citation]}]")
+        elif file_path := getattr(annotation, "file_path", None):
+            cited_file = client.files.retrieve(file_path.file_id)
+            citation = f"{cited_file.filename}"
+            if citation not in citation_map:
+                citation_map[citation] = len(citation_map) + 1
+            citations.append(f"[{citation_map[citation]}] {citation}")
+            message_content.value = message_content.value.replace(annotation.text, f"[{citation_map[citation]}]")
+
+    cleaned_content = clean_content(message_content.value)
+    return cleaned_content, list(set(citations))
+
+# Function to handle message submission
+def submit_message(message):
+    st.session_state.messages.append({"role": "user", "content": message})
+    with st.chat_message("user", avatar="⚕️"):
+        st.markdown(message)
+
+    client.beta.threads.messages.create(
+        thread_id=st.session_state.thread_id,
+        role="user",
+        content=message
+    )
+
+    with st.spinner("Assistant is thinking..."):
+        run = client.beta.threads.runs.create_and_poll(
+            thread_id=st.session_state.thread_id,
+            assistant_id=assistant.id
+        )
+
+    if run.status == 'completed':
+        messages = client.beta.threads.messages.list(
+            thread_id=st.session_state.thread_id
+        )
+        assistant_message = messages.data[0]
+        
+        processed_content, citations = process_message_content(assistant_message)
+        
+        st.session_state.messages.append({
+            "role": "assistant", 
+            "content": processed_content,
+            "citations": citations
+        })
+        
+        with st.chat_message("assistant", avatar="https://encrypted-tbn0.gstatic.com/images?q=tbn:ANd9GcTETAUBM4r3hXmQ3eC31vWws8A9VbPvOxQNZQ&s"):
+            st.markdown(processed_content)
+            if citations:
+                st.markdown("---")
+                st.markdown("**Citations:**")
+                for citation in citations:
+                    st.markdown(citation)
+    else:
+        st.error(f"Error: {run.status}")
+
+# Display chat messages
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+        if "citations" in message and message["citations"]:
+            st.markdown("---")
+            st.markdown("**Citations:**")
+            for citation in message["citations"]:
+                st.markdown(citation)
+
+suggested_messages = [
+    "I'm a physician working at a primary care clinic, what Epic update changes will affect me?",
+    "Summarize Epic update changes that will impact a Med Surg Registered Nurse.",
+    "What Epic update changes need to be reviewed by ED registration staff?",
+    "Which Epic update changes impact surgeons?",
+    "Are there any Epic update changes that will affect X-ray technicians?",
+    "Create a summary of all Epic update changes that are relevant for referral coordinators?"
+]
+
+selected_pill = pills(
+    "Quick Questions by Role",
+    suggested_messages,
+    icons=['👨‍⚕️', '👩‍⚕️', '🏥', '🥽', '📷', '📞'],
+    index=None,
+    label_visibility="visible",
+    key="suggested_messages"
+)
+
+if selected_pill:
+    submit_message(selected_pill)
+
+# Chat input
+user_input = st.chat_input("What would you like to ask?")
+
+if user_input:
+    submit_message(user_input)