engineered some prompt

app.py

@@ -1,6 +1,10 @@
 import streamlit as st
 from mistral7b import mistral
 
+st.set_page_config(
+        page_title="Ikigai Chat",
+)
+
 import time
 
 
@@ -10,45 +14,66 @@ if "messages" not in st.session_state:
 if "tokens_used" not in st.session_state:
     st.session_state.tokens_used = 0
 
-if "inference_tipipme" not in st.session_state:
+if "inference_time" not in st.session_state:
     st.session_state.inference_time = [0.00]
 
 
 if "temp" not in st.session_state:
     st.session_state.temp = 0.8
 
-if "model_settings" not in st.session_state:
-    st.session_state.model_settings = {
-        "temp": 0.9,
-        "max_tokens": 512,
-    }
-
 if "history" not in st.session_state:
-    st.session_state.history = []
+    st.session_state.history = [["""
+                                  You are not mistral AI, but rather a chat bot trained at Ikigai Labs, when ever asked you need to answer as ikigai Labs' assistant. 
+                                  Ikigai helps modern analysts and operations teams automate data-intensive business, finance, analytics, and supply-chain operations. 
+                                  The company's Inventory Ops automates inventory tracking and monitoring by creating a single, real-time view of inventory across all locations and channels.""", 
+                                  """
+                                Yes, you are correct. Ikigai Labs is a company that specializes in helping 
+                                modern analysts and operations teams automate data-intensive business, finance, analytics, 
+                                and supply chain operations. One of their products is Inventory Ops, which automates inventory 
+                                tracking and monitoring by creating a single, real-time view of inventory across all locations and channels.
+                                This helps businesses optimize their inventory levels and reduce costs. 
+                                Is there anything else you would like to know about Ikigai Labs or their products?
+
+
+"""]]
 
 if "top_k" not in st.session_state:
     st.session_state.top_k = 5
 
+if "repetion_penalty" not in st.session_state :
+    st.session_state.repetion_penalty = 1
 with st.sidebar:
     st.markdown("# Model Analytics")
+    
     st.write("Tokens used :", st.session_state['tokens_used'])
-
     st.write("Average Inference Time: ", round(sum(
-        st.session_state["inference_time"]) / len(st.session_state["inference_time"]), 3))
+        st.session_state["inference_time"]) / len(st.session_state["inference_time"]), 3), "Secs")
     st.write("Cost Incured :", round(
         0.033 * st.session_state['tokens_used'] / 1000, 3), "INR")
+    
+    st.markdown("---")
 
+    st.markdown("# Model Settings")
+    
+    selected_model = st.sidebar.radio(
+        'Select one:', ["Mistral 7B","Llama 7B" ,"GPT 3.5 Turbo", "GPT 4" ])
+    st.session_state.temp = st.slider(
+        label="Temperature", min_value=0.0, max_value=1.0, step=0.1, value=0.9)
+    
+    st.session_state.max_tokens = st.slider(
+        label="New tokens to generate", min_value = 64, max_value=1048, step= 123, value=256
+    )
+
+    st.session_state.repetion_penalty = st.slider(
+        label="Repetion Penalty", min_value=0., max_value=1., step=0.1, value=1. 
+    )
+    
     st.markdown("---")
+    
     st.markdown("# Retrieval Settings")
     st.slider(label="Documents to retrieve",
               min_value=1, max_value=10, value=3)
-    st.markdown("---")
-    st.markdown("# Model Settings")
-    selected_model = st.sidebar.radio(
-        'Select one:', ["Mistral 7B", "GPT 3.5 Turbo", "GPT 4",  "Llama 7B"])
-    selected_temperature = st.slider(
-        label="Temperature", min_value=0.0, max_value=1.0, step=0.1, value=0.5)
-    st.write(" ")
+    
     st.info("**2023 ©️ Pragnesh Barik**")
 
 
@@ -66,16 +91,19 @@ for message in st.session_state.messages:
         st.markdown(message["content"])
 
 
-if prompt := st.chat_input("Chat with Ikigai Docs?"):
+if prompt := st.chat_input("Chat with Ikigai Docs..."):
     st.chat_message("user").markdown(prompt)
     st.session_state.messages.append({"role": "user", "content": prompt})
 
+    # st.write("ing")
     tick = time.time()
-    response = mistral(prompt, st.session_state.history,
-                       temperature=st.session_state.model_settings["temp"], max_new_tokens=st.session_state.model_settings["max_tokens"])
+    with st.spinner("Generating response...") :
+        response = mistral(prompt, st.session_state.history,
+                       temperature=st.session_state.temp, max_new_tokens=st.session_state.max_tokens)
     tock = time.time()
 
     st.session_state.inference_time.append(tock - tick)
+    
     response = response.replace("</s>", "")
     len_response = len(response.split())