AI Mad Libs

madlibs/.env.example

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+# Rename this file to .env once you have filled in the below environment variables!
+
+# Get your Open AI API Key by following these instructions -
+# https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key
+# You only need this environment variable set if you set LLM_MODEL to a GPT model
+OPENAI_API_KEY=
+
+# See all Open AI models you can use here -
+# https://platform.openai.com/docs/models
+# A good default to go with here is gpt-4o
+LLM_MODEL=gpt-4o

madlibs/madlibs.py

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+from dotenv import load_dotenv
+from datetime import datetime
+from typing import List
+import streamlit as st
+import time
+import json
+import os
+
+from langchain_core.messages import AIMessage, SystemMessage, HumanMessage, ToolMessage
+from langchain_core.output_parsers import JsonOutputParser
+from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_core.prompts import PromptTemplate
+from langchain_openai import ChatOpenAI
+
+load_dotenv()
+
+model = os.getenv('LLM_MODEL', 'gpt-4o')
+
+mad_libs_prompt = """
+You are an expert at creating funny and interesting Mad Libs. All of the Mad Libs you create have between 20 and 25 fill-in-the-blanks. 
+Each fill-in-the-blank can be one of the following:
+
+Noun
+Verb
+Adjective
+Adverb 
+Plural Noun 
+Proper Noun 
+Place 
+Exclamation 
+Part of the Body 
+Occupation 
+Emotion 
+Verb Ending in -ing
+
+Create a Mad Lib with the theme of {theme}. Output JSON in the format:
+
+{{
+    “text”: “Mad Lib text with exactly three underscores (like ___) to represent each fill-in-the-blank. Only include exactly 3 underscores for each blank. Don’t include the type of blank in this part of the JSON”,
+    “blanks”: [Array of blanks where each element is the type of fill-in-the-blank such as Noun or Verb. List them in the order they are used in the Mad Lib text]
+}}
+"""
+
+class MadLib(BaseModel):
+    text: str = Field(description="Mad Lib text with three underscores (___) for each fill-in-the-blank")
+    blanks: List[str] = Field(description="Array of blanks where each element is the type of fill-in-the-blank such as Noun or Verb listed in the order they are used in the Mad Lib text")
+
+def stream_text(text):
+    for word in text.split(" "):
+        yield word + " "
+        time.sleep(0.05)
+
+def main():
+    st.title("AI Mad Libs!")
+
+    # Initialize the chat history with the initial system message
+    if "messages" not in st.session_state:
+        st.session_state.messages = [
+            AIMessage(content=f"Give me a theme and I'll make a Mad Lib for you!")
+        ]
+
+        # State will either be choosing-theme, choosing-words
+        st.session_state.state = "choosing-theme"
+
+    # Display chat messages from history each time the script is rerun when the UI state changes
+    for message in st.session_state.messages:
+        message_json = json.loads(message.json())
+        message_type = message_json["type"]
+        if message_type in ["human", "ai"]:
+            with st.chat_message(message_json["type"]):
+                st.markdown(message_json["content"])        
+
+    # Assign prompt to the user input if any is given, otherwise skip everything in this if statement
+    if user_input := st.chat_input("Enter theme and fill-in-the-blanks here"):
+        # Display user message in chat message container
+        st.chat_message("user").markdown(user_input)
+
+        # Add the user message to chat history
+        st.session_state.messages.append(HumanMessage(content=user_input))
+
+        # Get the current state of the chat which is either choosing-theme or choosing-words
+        curr_state = st.session_state.state
+
+        # If the user just selected a theme, generate the Madlib
+        if curr_state == "choosing-theme":
+            parser = JsonOutputParser(pydantic_object=MadLib)
+            chatbot = ChatOpenAI(model=model)
+            prompt = PromptTemplate(
+                template=mad_libs_prompt,
+                input_variables=["theme"]
+            )
+
+            # Create the chain with the prompt, model (GPT or Local), and MadLib output parser
+            mad_lib_chain = prompt | chatbot | parser
+
+            # Invoke the chain with the theme the user selected to generate the Madlib
+            mad_lib_json = mad_lib_chain.invoke({"theme": user_input})    
+
+            st.session_state.text = mad_lib_json["text"]
+            st.session_state.blanks = mad_lib_json["blanks"]
+            num_blanks = len(mad_lib_json["blanks"])
+            st.session_state.count = num_blanks
+            first_blank = mad_lib_json["blanks"][0]
+
+            with st.chat_message("assistant"):
+                response = st.write_stream(stream_text(f"Alright, let's get started!\n\n1 / {num_blanks}: {first_blank}"))
+                st.session_state.messages.append(AIMessage(content=response))        
+
+            st.session_state.state = "choosing-words"
+
+        # If the user is picking words for a Madlib, add these message as a word and move to the next
+        elif curr_state == "choosing-words":
+            st.session_state.text = st.session_state.text.replace("___", f"**{user_input}**", 1)
+            st.session_state.blanks = st.session_state.blanks[1:]
+            blanks = st.session_state.blanks
+            num_blanks = st.session_state.count
+
+            # Still more blanks to fill in
+            if len(blanks):
+                next_blank = blanks[0]
+                with st.chat_message("assistant"):
+                    response = st.write_stream(stream_text(f"{num_blanks - len(blanks) + 1} / {num_blanks}: {next_blank}"))
+                    st.session_state.messages.append(AIMessage(content=response))                     
+            # No more blanks to fill in
+            else:
+                with st.chat_message("assistant"):
+                    response = st.write_stream(stream_text(st.session_state.text))
+                    st.session_state.messages.append(AIMessage(content=response))    
+
+                st.session_state.state = "choosing-theme"
+
+
+if __name__ == "__main__":
+    main()