Simple conversation implementation

.streamlit/config.toml

@@ -0,0 +1,4 @@
+[server]
+runOnSave = true
+headless = true
+maxUploadSize = 2000

README.md

@@ -10,3 +10,5 @@ pinned: false
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+To use this project, you will need to get an API key from OpenAI.

app.py

@@ -1,4 +1,83 @@
 import streamlit as st
+from openai import OpenAI
+
+
+model = "gpt-3.5-turbo"
+
+
+st.sidebar.title('OpenAI Simple Conversation')
+st.sidebar.write('Please provide your OpenAI key to be used for this conversation.')
+
+def onchange_openai_key():
+    print(st.session_state.openai_key) 
+
+openai_key = st.sidebar.text_input('OpenAI key', on_change=onchange_openai_key, key='openai_key')
+
+st.title('OpenAI Simple Conversation')
+st.write(f'Ask any question that can be answer by the LLM {model}.')
+
+def submit_openai_key(model=model):
+    if(openai_key == None or openai_key==''):
+        st.sidebar.write('Please provide the key before')
+        return
+    else:
+        client = OpenAI(api_key=openai_key)
+        model = model
+        completion = client.chat.completions.create(
+            model=model,  
+            messages=[
+                {"role": "system", "content": "You are an assistant giving simple and short answer for question of child"},
+                {"role": "user", "content": "count from 0 to 10"}
+            ]
+        )        
+        st.sidebar.write(f'Simple count : {completion.choices[0].message.content}')
+
+
+def askQuestion(model=model, question=''):
+    if(openai_key == None or openai_key==''):
+        print('Please provide the key before')
+        return 'LLM API is not defined. Please provide the key before'
+    else:
+        client = OpenAI(api_key=openai_key)
+        model = model
+        completion = client.chat.completions.create(
+            model=model,  
+            messages=[
+                {"role": "system", "content": "You are an assistant giving simple and short answer for question of child"},
+                {"role": "user", "content": f'{question}'}
+            ]
+        )        
+        return completion.choices[0].message.content
+
+
+
+# Initialize chat history
+if "messages" not in st.session_state:
+    st.session_state.messages = []
+
+# Display chat messages from history on app rerun
+for message in st.session_state.messages:
+    with st.chat_message(message["role"]):
+        st.markdown(message["content"])
+
+# React to user input
+if prompt := st.chat_input("What is up?"):
+    with st.status('Running', expanded=True) as status:
+        # Display user message in chat message container
+        st.chat_message("user").markdown(prompt)
+        # Add user message to chat history
+        st.session_state.messages.append({"role": "user", "content": prompt})
+
+        response = askQuestion(question=prompt)
+        # Display assistant response in chat message container
+        with st.chat_message("assistant"):
+            st.markdown(response)
+            
+        # Add assistant response to chat history
+        st.session_state.messages.append({"role": "assistant", "content": response})
+        status.update(label='Reponse of last question', state="complete", expanded=True)
+
+
+submit_key = st.sidebar.button(label='Submit', on_click=submit_openai_key)
+
 
-x = st.slider('Select a value')
-st.write(x, 'squared is', x * x)

requirements.txt

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+streamlit
+openai
+watchdog