building the bot

src/genai/sandbox/signals/signals_app.py

@@ -1,11 +1,45 @@
+import json
+import os
+
+import openai
 import streamlit as st
 
+from dotenv import load_dotenv
+
 from genai import MessageTemplate
 from genai.eyfs import TextGenerator
 from genai.streamlit_pages.utils import reset_state
 
 
-def eli3(sidebar: bool = True) -> None:
+load_dotenv()
+
+data_path = "src/genai/sandbox/signals/data/"
+signals_data = json.load(open(data_path + "signals_2023.json", "r"))
+
+
+def auth_openai() -> None:
+    """Authenticate with OpenAI."""
+    try:
+        openai.api_key = os.environ["OPENAI_API_KEY"]
+    except Exception:
+        openai.api_key = st.secrets["OPENAI_API_KEY"]
+
+
+def generate_signals_texts(signals_data: dict):
+    signals_titles = [signal["title"] for signal in signals_data]
+    signals_summaries = [signal["summary"] for signal in signals_data]
+
+    # Combine titles and summaries into a single string
+    signals_description = ""
+    no = 0
+    for title, summary in zip(signals_titles, signals_summaries):
+        no += 1
+        signals_description += f"Signal {no}: {title}\n{summary}\n\n"
+
+    return signals_description
+
+
+def signals_bot(sidebar: bool = True) -> None:
     """Explain me a concept like I'm 3."""
 
     # Define your custom CSS
@@ -26,51 +60,48 @@ def eli3(sidebar: bool = True) -> None:
     # # Apply the custom CSS
     # st.markdown(custom_css, unsafe_allow_html=True)
 
-    st.title("Explain-Like-I'm-3")
-
-    # Create the generator
-    if sidebar:
-        with st.sidebar:
-            selected_model = st.radio(
-                label="**OpenAI model**",
-                options=["gpt-3.5-turbo", "gpt-4"],
-                on_change=reset_state,
-            )
-            temperature = st.slider(
-                label="**Temperature**",
-                min_value=0.0,
-                max_value=2.0,
-                value=0.6,
-                step=0.1,
-                on_change=reset_state,
-            )
+    signals_descriptions = generate_signals_texts(signals_data)
 
-            st.button("Reset chat", on_click=reset_state, type="primary", help="Reset the chat history")
-    else:
-        selected_model = "gpt-4"
-        temperature = 0.6
+    selected_model = "gpt-3.5-turbo"
+    temperature = 0.6
 
-    prompt_template = MessageTemplate.load("src/genai/eli3/prompts/eli3_chat_2.json")
+    st.title("Signals chatbot")
+    st.write("Some text here")
 
-    # Initialize chat history
     if "messages" not in st.session_state:
-        st.session_state.messages = [{"role": prompt_template.role, "content": prompt_template.content}]
+        st.session_state.messages = []
+        st.session_state.state = "start"
+        # Write first message
+        with st.chat_message("assistant"):
+            opening_message = "Hi! I'm the Signals chatbot. I'm here to help you find out more about the Signals project. Tell me about yourself"
+            st.session_state.messages.append(
+                {
+                    "role": "user",
+                    "content": "###Instructions###\nYou are a helpful, kind, intelligent and polite futurist. Your task is to engage the user about future signals by helping the user imagine and appreciate how the signals will impact their life. You will personalise the user experience by taking the information provided by the user and tailoring your explanation to the user background.",
+                }
+            )
+            st.session_state.messages.append({"role": "assistant", "content": opening_message})
+
+    # # add input form
+    # input_name = st.text_input("What's your name", value="")
+    # input_interest = st.text_input("What are you interested in?", placeholder="For example: education, sustainability or health?")
+    # input_job = st.text_input("What's your job", value="")
 
     # Display chat messages from history on app rerun.
-    # The first message is the prompt, so we skip it.
     for message in st.session_state.messages[1:]:
         with st.chat_message(message["role"]):
             st.markdown(message["content"])
 
-    # Accept user input
-    prompt = st.chat_input("How do whales breathe?")
-    if prompt:
-        # Display user message in chat message container
+    user_message = st.chat_input("My name is Mark, I'm interested in education and I'm a teacher")
+    if user_message:
+        # Write user message
         with st.chat_message("user"):
-            st.markdown(prompt)
-        # Add user message to chat history
-        st.session_state.messages.append({"role": "user", "content": prompt})
-
+            st.markdown(user_message)
+        # Add user message to history
+        prompt = prompt2()
+        st.session_state.messages.append({"role": "user", "content": prompt.to_prompt()})
+        print(user_message)
+        # Generate AI response
         with st.chat_message("assistant"):
             message_placeholder = st.empty()
             full_response = ""
@@ -84,4 +115,41 @@ def eli3(sidebar: bool = True) -> None:
                 full_response += response.choices[0].delta.get("content", "")
                 message_placeholder.markdown(full_response + "▌")
             message_placeholder.markdown(full_response)
+        # Add AI response to history
         st.session_state.messages.append({"role": "assistant", "content": full_response})
+
+
+def llm_call(selected_model: str, temperature: float, message: MessageTemplate, messages_placeholders: dict) -> str:
+    """Call the LLM"""
+    message_placeholder = st.empty()
+    full_response = ""
+    for response in TextGenerator.generate(
+        model=selected_model,
+        temperature=temperature,
+        messages=[message],
+        message_kwargs=messages_placeholders,
+        stream=True,
+    ):
+        full_response += response.choices[0].delta.get("content", "")
+        message_placeholder.markdown(full_response + "▌")
+
+    message_placeholder.markdown(full_response)
+
+    return full_response
+
+
+def prompt2():
+    """
+    Generate a prompt for an overview of the impact of signals on the user
+    """
+    prompt = MessageTemplate.load(data_path + "prompt2.json")
+    return prompt
+
+
+def main() -> None:
+    """Run the app."""
+    auth_openai()
+    signals_bot(sidebar=False)
+
+
+main()