Add demo_ui.py to project (#68)

* Add demo_ui.py to project

Uploaded demo_ui.py file to project example folder. 

Signed-off-by: Zuhayer C <[email protected]>

* Replace "Customary xxxxxx: chatbot" with project name

Signed-off-by: Zuhayer C <[email protected]>

---------

Signed-off-by: Zuhayer C <[email protected]>

example/demo_ui.py

@@ -0,0 +1,153 @@
+import streamlit as st
+import random
+import string
+import datetime
+import tiktoken
+from openai import OpenAI
+
+RMIT="RMIT"
+
+encoding = tiktoken.get_encoding("r50k_base") 
+
+client = OpenAI(base_url="http://localhost:8080/v1", api_key="not-needed", organization='SelectedModel')
+
+def writehistory(filename,text):
+    with open(filename, 'a', encoding='utf-8') as f:
+        f.write(text)
+        f.write('\n')
+    f.close()
+
+#AVATARS  👷🐦  🥶🌀
+av_us = '🦖'  #"🦖"  #A single emoji, e.g. "🧑‍💻", "🤖", "🦖".
+av_ass = '👷'
+
+# Set the webpage title
+st.set_page_config(
+    page_title=f"Your LocalGPT with 🌟 {RMIT}",
+    page_icon="🌟",
+    layout="wide")
+
+# Create a header element
+mytitle = '# Local AI Solutions and LLM-based Chatbot development 🌟'
+st.markdown(mytitle, unsafe_allow_html=True)
+st.markdown('### Conversation tokens context window')
+# function to generate random alphanumeric sequence for the filename
+def genRANstring(n):
+    """
+    n = int number of char to randomize
+    """
+    N = n
+    res = ''.join(random.choices(string.ascii_uppercase +
+                                string.digits, k=N))
+    return res
+
+# create THE SESSIoN STATES
+if "logfilename" not in st.session_state:
+## Logger file
+    logfile = f'{genRANstring(5)}_log.txt'
+    st.session_state.logfilename = logfile
+    #Write in the history the first 2 sessions
+    writehistory(st.session_state.logfilename,f'{str(datetime.datetime.now())}\n\nYour own LocalGPT with 🌀 {RMIT}\n---\n🧠🫡: You are a helpful assistant.')    
+    writehistory(st.session_state.logfilename,f'🌀: How may I help you today?')
+
+if "repeat" not in st.session_state:
+    st.session_state.repeat = 1.35
+
+if "temperature" not in st.session_state:
+    st.session_state.temperature = 0.1
+
+if "maxlength" not in st.session_state:
+    st.session_state.maxlength = 500
+
+
+# CREATE THE SIDEBAR
+with st.sidebar:
+    st.image('img/RMIT_POS3.png', use_column_width=True)
+    st.session_state.temperature = st.slider('Temperature:', min_value=0.0, max_value=1.0, value=0.1, step=0.02)
+    st.session_state.maxlength = st.slider('Length reply:', min_value=150, max_value=1000, 
+                                           value=500, step=50)
+    st.session_state.repeat = st.slider('Repeat Penalty:', min_value=0.0, max_value=2.0, value=1.35, step=0.01)
+    st.markdown(f"**Logfile**: {st.session_state.logfilename}")
+    btnClear = st.button("Clear History",type="primary", use_container_width=True)
+
+
+# We store the conversation in the session state.
+# This will be used to render the chat conversation.
+# We initialize it with the first message we want to be greeted with. 
+#Note that the first 3 messages will never be used for the genration, they are only for the Chat interface
+if "messages" not in st.session_state:
+    st.session_state.messages = [
+        {"role": "system", "content": "You are assistant, a helpful assistant. You reply only to the user questions. You always reply in the language of the instructions.",},
+        {"role": "user", "content": "Hi, I am P000252SE."},
+        {"role": "assistant", "content": "Hi there, I am assistant, how may I help you today?"}
+    ]
+# we define the function to clear from the screen the conversation history
+def clearHistory():
+    st.session_state.messages = [
+        {"role": "system", "content": "You are assistant, a helpful assistant. You reply only to the user questions. You always reply in the language of the instructions.",},
+        {"role": "user", "content": "Hi, I am P000252SE."},
+        {"role": "assistant", "content": "Hi there, I am assistant, how may I help you today?"}
+    ]
+if btnClear:
+      clearHistory()  
+
+
+# We loop through each message in the session state and render it as # a chat message.
+for message in st.session_state.messages[1:]:
+    if message["role"] == "user":
+        with st.chat_message(message["role"],avatar=av_us):
+            st.markdown(message["content"])
+    else:
+        with st.chat_message(message["role"],avatar=av_ass):
+            st.markdown(message["content"])
+
+# We take questions/instructions from the chat input to pass to the LLM
+if user_prompt := st.chat_input("Your message here. Shift+Enter to add a new line", key="user_input"):
+
+    # Add our input to the session state
+    st.session_state.messages.append(
+        {"role": "user", "content": user_prompt}
+    )
+
+    # Add our input to the chat window
+    with st.chat_message("user", avatar=av_us):
+        st.markdown(user_prompt)
+        writehistory(st.session_state.logfilename,f'👷: {user_prompt}')
+
+
+    with st.chat_message("assistant",avatar=av_ass):
+        message_placeholder = st.empty()
+        with st.spinner("Inferencing..."):
+            response = ''
+            conv_messages = []
+            conv_messages.append(st.session_state.messages[-1])
+            full_response = ""
+
+            completion = client.chat.completions.create(
+                model="local-model",
+                messages=conv_messages,  #st.session_state.messages if you want to keep previous messages,
+                temperature=st.session_state.temperature,
+                frequency_penalty  = st.session_state.repeat,
+                stop=['<|im_end|>','</s>'],
+                max_tokens=st.session_state.maxlength,
+                stream=True,
+            )
+            for chunk in completion:
+                if chunk.choices[0].delta.content:
+                    full_response += chunk.choices[0].delta.content
+                    message_placeholder.markdown(full_response + "🌟")
+
+            toregister = full_response + f"""
+```
+
+prompt tokens: {len(encoding.encode(st.session_state.messages[-1]['content']))}
+generated tokens: {len(encoding.encode(full_response))}
+```"""
+            message_placeholder.markdown(toregister)
+            writehistory(st.session_state.logfilename,f'🌟: {toregister}\n\n---\n\n') 
+
+
+    # Add the response to the session state
+    st.session_state.messages.append(
+        {"role": "assistant", "content": toregister}
+    )