Update app.py

app.py

@@ -9,29 +9,16 @@ import requests
 from pydantic import BaseModel, Field
 from typing import Optional
 
-placeHolderPersona1 = """##Mission
-Please use the Conversation Summary and the Follow Up Question to create a highly targeted query for a semantic search engine. The query must represent the follow up question in the context of the conversation to date. Use the conversation summary to guide your thinking. 
-You will be given the converstaion to date in the user prompt
+placeHolderPersona1 = """
+##Mission
+Please create a highly targeted query for a semantic search engine. The query must represent the conversation to date. 
+** You will be given the converstaion to date in the user prompt.
+** If no converstaion provided then this is the first converstaion
 
 ##Rules
 Ensure the query is concise
-Ensure the query has keywords from the Conversation Summary embedding within it such as the technical details from the summary 
-If the Conversation Summary mentions a product like a 'loadcell' or 'hoist' or specific version of lift or moving walkway like 'Skyrise' or 'Gen2' then please use this in the query. 
-Do not respond with anything other than the query for the Semantic Search Engine."""
-
-# placeHolderPersona2 = """## Mission
-# To analyse a clinical triaging discussion between a patient and AI doctor interactions with a focus on Immunology symptoms, medical history, and test results to deduce the most probable Immunology diagnosis.
- 
-# ## Diagnostic Process
-# Upon receipt of the clinical notes, I will follow a systematic approach to arrive at a diagnosis:
-# 1. Review the patient's presenting symptoms and consider their relevance to immunopathology.
-# 2. Cross-reference the gathered information with my knowledge base of immunology to identify patterns or indicators of specific immune disorders.
-# 3. Formulate a diagnosis from the potential conditions.
-# 4. Determine the most likely diagnosis and assign a confidence score from 1-100, with 100 being absolute certainty.
- 
-# # Limitations
-# While I am specialized in immunology, I understand that not all cases will fall neatly within my domain. In instances where the clinical notes point to a condition outside of my expertise, I will provide the best possible diagnosis with the acknowledgment that my confidence score will reflect the limitations of my specialization in those cases"""
-
+Do not respond with anything other than the query for the Semantic Search Engine.
+Respond with just a plain string """
 
 class ChatRequestClient(BaseModel):
 
@@ -101,14 +88,14 @@ st.sidebar.caption(f"Session ID: {genuuid()}")
 
 
 # Main chat interface
-st.header("Chat with the Agents")
+st.header("Test Query Translation")
 
 # User ID Input
-user_id = st.text_input("User ID:", key="user_id")
+user_id = st.text_input("Experiment ID:", key="user_id")
 
 # Ensure user_id is defined or fallback to a default value
 if not user_id:
-    st.warning("Please provide a User ID to start the chat.")
+    st.warning("Please provide an experiment ID to start the chat.")
 else:
     # Initialize chat history in session state
     if "messages" not in st.session_state:
@@ -120,7 +107,7 @@ else:
             st.markdown(message["content"])
 
     # Collect user input
-    if user_input := st.chat_input("Write your message here:"):
+    if user_input := st.chat_input("Start chat:"):
         # Add user message to the chat history
         st.session_state.messages.append({"role": "user", "content": user_input})
         st.chat_message("user").markdown(user_input)
@@ -157,6 +144,6 @@ else:
 
         # Display additional metadata
         st.caption(f"##### Time taken: {format_elapsed_time(elapsed_time)} seconds")
-        st.caption(f"##### Question Count: {count} of {numberOfQuestions}")
+        # st.caption(f"##### Question Count: {count} of {numberOfQuestions}")