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| # ========================== | |
| # Imports | |
| # ========================== | |
| import os, sys, random | |
| import gradio as gr | |
| from langchain_openai import ChatOpenAI | |
| from langchain.schema import AIMessage, HumanMessage | |
| from langchain.prompts import ChatPromptTemplate | |
| from langchain.schema.output_parser import StrOutputParser | |
| from langchain_core.runnables import RunnableLambda | |
| from langchain_core.messages import AIMessage, AIMessageChunk, HumanMessage, HumanMessageChunk | |
| from game_info import * | |
| # ========================== | |
| # Constants / Globals | |
| # ========================== | |
| NVIDIA_API_KEY = os.environ["API_KEY"] # API Key for the LLM - Using NVIDIA's NIM to access an 8 Billion parameter Llama3 model | |
| CHATBOT_HEIGHT = 700 # Height of Gradio Chatbot | |
| LINES_PER_BOX = 20 # Number of text lines in a gradio text box | |
| SUSPECTS_PER_PAGE = 10 # Number of suspects shown per page | |
| game = cMystery() # New mystery game imported from game_info | |
| # ========================== | |
| # LLM Functions | |
| # ========================== | |
| # Using NVIDIA's NIM (NVIDIA Inference Microservices) to access an 8 Billion parameter Llama3 model | |
| llm = ChatOpenAI(model = "meta/llama3-8b-instruct",temperature=0.5,max_tokens=1024,timeout=None,max_retries=2, | |
| base_url = "https://integrate.api.nvidia.com/v1", | |
| api_key = NVIDIA_API_KEY) | |
| # ================================ | |
| # Custom LangChain Tools and Pipes | |
| # ================================ | |
| def output_parser(ai_message: AIMessage) -> str: | |
| global game | |
| current_suspect = game.get_current_suspect() | |
| game.add_note_to_recap(ai_message.content, current_suspect) # Save a record of the conversation with the suspect name in the recap | |
| return ai_message.content | |
| # ========================== | |
| # UI Functions | |
| # ========================== | |
| # ============================================ | |
| # Feed the chat message to the LLM | |
| # ============================================ | |
| def predict(message, history): | |
| global game | |
| global llm | |
| current_suspect = game.get_current_suspect() | |
| if current_suspect is None: | |
| return "Please select a suspect." | |
| AI_Instructions = f"You are a suspect in an art theft." + \ | |
| f"Your name is {game.get_suspect_proper_name(current_suspect)} " + \ | |
| f"and your background is {game.get_suspect_background(current_suspect)}. " + \ | |
| f"Your motive for stealing the painting is {game.get_suspect_motive(current_suspect)}. " + \ | |
| f"If you stole the painting do not admit it. " + \ | |
| f"Base all conversations on the following JSON text:{game.create_interview(current_suspect)}" | |
| prompt = ChatPromptTemplate.from_messages([ | |
| ("system", f"{AI_Instructions}"), | |
| ("human", f"{message}"), | |
| ]) | |
| history_langchain_format = [] | |
| history_langchain_format.append(AIMessage(content=AI_Instructions)) | |
| history_langchain_format.append(HumanMessage(content=message)) | |
| gpt_response = llm(history_langchain_format) | |
| output_parser(gpt_response) | |
| response = gpt_response.content | |
| # LCEL configuration for future game expansion / options | |
| # lcel_chain = prompt | llm | output_parser | |
| # response = lcel_chain.invoke(message) | |
| return response | |
| # ========================== | |
| # Generate recap of game | |
| # ========================== | |
| def get_recap(): | |
| global game | |
| recap = "" | |
| recap += "💡 Hints 💡 \n\n" + game.get_hints_recap() + "\n" # Add revealed hints | |
| recap += "🕵 Suspect Interview Notes 🕵 \n\n" # Add notes from interviews | |
| recap += game.get_crime_recap() | |
| return gr.Textbox(lines=LINES_PER_BOX, label="Recap of the Mystery", value=recap) | |
| # ========================== | |
| # Question suspect | |
| # ========================== | |
| def question_suspect(image, name): | |
| global game | |
| game.set_current_suspect(name) | |
| current_suspect = game.get_current_suspect() | |
| return gr.Textbox(lines = LINES_PER_BOX, | |
| label = "About the Suspect", | |
| value = game.get_suspect_profile(current_suspect)) | |
| # ========================== | |
| # Generate game hint | |
| # ========================== | |
| def get_hint(): | |
| global game | |
| return gr.Textbox(lines = LINES_PER_BOX, | |
| label = "Hint About the Mystery", | |
| value = game.give_hint()) | |
| # =============================== | |
| # Reset game for a new mystery | |
| # =============================== | |
| def new_crime(): | |
| global game | |
| game = cMystery() | |
| game.print_game() | |
| return [gr.Image (value = game.get_stolen_painting(), height=500, width=500, label = game.get_stolen_painting_name(), interactive=False), | |
| gr.Textbox(lines = LINES_PER_BOX, label="A Crime has been Committed", value = game.get_crime_text()), | |
| gr.Image (value = "Question_Mark.jpg", height=500, width=500, label = "Suspect", interactive=False), | |
| gr.Textbox(lines = LINES_PER_BOX, label="About the Suspect", value = ""),] | |
| # ============================================ | |
| # Arrest attempt - Are you correct ? | |
| # ============================================ | |
| def arrest(): | |
| global game | |
| current_suspect = game.get_current_suspect() | |
| guilty_suspect = game.get_guilty_suspect_name() | |
| if current_suspect is None: | |
| arrest_results = "Please select a suspect on the right to arrest." | |
| elif current_suspect == guilty_suspect: | |
| arrest_results = "👍👍 Congratulations 👍👍 \n\nYou caught " + guilty_suspect + " and recovered the painting.\n\n" + \ | |
| guilty_suspect + " confessed why: \n\n'" + game.get_suspect_motive(guilty_suspect) + "'" + \ | |
| "and said 'I would have gotten away with it too if it weren't for you meddling detectives'" | |
| else: | |
| arrest_results = "❌❌❌ You Failed Detective ❌❌❌\n\n" + guilty_suspect + " stole the painting and snuck away while you were arresting the wrong person" | |
| return gr.Textbox(lines = LINES_PER_BOX, | |
| label = "Results of Your Arrest", | |
| value = arrest_results) | |
| # ================================ | |
| # Main Code - Draw Gradio UI | |
| # ================================ | |
| game.print_game() # DEBUG - Print out the game settings | |
| with gr.Blocks() as demo: | |
| image_manor = gr.Image(value = "mystery_manor.jpg", width=2400, interactive=False) | |
| with gr.Row(): | |
| with gr.Column(): | |
| painting = gr.Image (value = game.get_stolen_painting(), height=500, width=500, label = game.get_stolen_painting_name(), interactive=False) | |
| crime_desc = gr.Textbox(lines = LINES_PER_BOX, label="A Crime has been Committed", value = game.get_crime_text() ) | |
| with gr.Row(): | |
| btn_new_crime = gr.Button("⚡ New Crime ⚡") | |
| btn_recap = gr.Button("💡 Recap 💡") | |
| with gr.Column(): | |
| suspect_image = gr.Image (value = "Question_Mark.jpg", height=500,width=500, label="Suspect", interactive=False) | |
| suspect_desc = gr.Textbox(lines = LINES_PER_BOX, label = "About the Suspect", value="") | |
| with gr.Row(): | |
| btn_arrest= gr.Button("👮 Arrest 👮") | |
| btn_hint = gr.Button("🕵 Clue 🕵") | |
| with gr.Column(): | |
| suspect_list = gr.Examples(examples = game.get_suspect_images(), inputs = [suspect_image,suspect_desc], outputs=[suspect_desc], examples_per_page=SUSPECTS_PER_PAGE, fn=question_suspect, run_on_click=True, label="Suspect List", cache_examples=False) | |
| with gr.Column(): | |
| QnA = gr.ChatInterface(fn=predict, examples=game.get_sample_questions(), title="❓"+" Question the Suspect "+"❓", fill_height=False, retry_btn=None, undo_btn=None, cache_examples=False) | |
| btn_new_crime.click(new_crime, inputs=None, outputs=[painting, crime_desc, suspect_image, suspect_desc]) # Resets game to new one | |
| btn_recap.click (get_recap, inputs=None, outputs=[crime_desc]) # Prints out summary of notes | |
| btn_arrest.click (arrest, inputs=None, outputs=[suspect_desc]) # Arrest selected subject | |
| btn_hint.click (get_hint, inputs=None, outputs=[suspect_desc]) # Ask for hint/clue | |
| if __name__ == "__main__": | |
| demo.launch() | |