Add GPT based conversation processor to understand intent and converse with user

- Allow conversing with user using GPT's contextually aware, generative capability
- Extract metadata, user intent from user's messages using GPT's general understanding

src/processor/conversation/gpt.py

@@ -0,0 +1,70 @@
+# Standard Packages
+import os
+
+# External Packages
+import openai
+
+
+def understand(text, api_key=None, temperature=0.5, max_tokens=100):
+    """
+    Understand user input using OpenAI's GPT
+    """
+    # Initialize Variables
+    openai.api_key = api_key or os.getenv("OPENAI_API_KEY")
+    understand_primer="Extract information from each chat message\n\nremember(memory-type, data);\nmemory-type=[\"companion\", \"notes\", \"ledger\", \"image\", \"music\"]\nsearch(search-type, data);\nsearch-type=[\"google\", \"youtube\"]\ngenerate(activity);\nactivity=[\"paint\",\"write\", \"chat\"]\ntrigger-emotion(emotion);\nemotion=[\"happy\",\"confidence\",\"fear\",\"surprise\",\"sadness\",\"disgust\",\"anger\", \"curiosity\", \"calm\"]\n\nQ: How are you doing?\nA: activity(\"chat\"); trigger-emotion(\"surprise\")\nQ: Do you remember what I told you about my brother Antoine when we were at the beach?\nA: remember(\"notes\", \"Brother Antoine when we were at the beach\"); trigger-emotion(\"curiosity\");\nQ: what did we talk about last time?\nA: remember(\"notes\", \"talk last time\"); trigger-emotion(\"curiosity\");\nQ: Let's make some drawings!\nA: generate(\"paint\"); trigger-emotion(\"happy\");\nQ: Do you know anything about Lebanon?\nA: search(\"google\", \"lebanon\");  trigger-emotion(\"confidence\");\nQ: Find a video about a panda rolling in the grass\nA: search(\"youtube\",\"panda rolling in the grass\");  trigger-emotion(\"happy\"); \nQ: Tell me a scary story\nA: generate(\"write\" \"A story about some adventure\"); trigger-emotion(\"fear\");\nQ: What fiction book was I reading last week about AI starship?\nA: remember(\"notes\", \"read fiction book about AI starship last week\"); trigger-emotion(\"curiosity\");\nQ: How much did I spend at Subway for dinner last time?\nA: remember(\"ledger\", \"last Subway dinner\"); trigger-emotion(\"curiosity\");\nQ: I'm feeling sleepy\nA: activity(\"chat\"); trigger-emotion(\"calm\")\nQ: What was that popular Sri lankan song that Alex showed me recently?\nA: remember(\"music\", \"popular Sri lankan song that Alex showed recently\");  trigger-emotion(\"curiosity\"); \nQ: You're pretty funny!\nA: activity(\"chat\"); trigger-emotion(\"pride\")"
+
+    # Setup Prompt with Understand Primer
+    prompt = message_to_prompt(text, understand_primer, start_sequence="\nA:", restart_sequence="\nQ:")
+
+    # Get Reponse from GPT
+    response = openai.Completion.create(
+        engine="davinci",
+        prompt=prompt,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        top_p=1,
+        frequency_penalty=0.2,
+        presence_penalty=0,
+        stop=["\n"])
+
+    # Extract, Clean Message from GPT's Response
+    story = response['choices'][0]['text']
+    return str(story)
+
+
+def converse(text, conversation_history=None, api_key=None, temperature=0.9, max_tokens=150):
+    """
+    Converse with user using OpenAI's GPT
+    """
+    # Initialize Variables
+    openai.api_key = api_key or os.getenv("OPENAI_API_KEY")
+
+    start_sequence = "\nAI:"
+    restart_sequence = "\nHuman:"
+    conversation_primer = f"The following is a conversation with an AI assistant. The assistant is helpful, creative, clever, and very friendly companion.\n{restart_sequence} Hello, who are you?{start_sequence} Hi, I am an AI conversational companion created by OpenAI. How can I help you today?"
+
+    # Setup Prompt with Primer or Conversation History
+    prompt = message_to_prompt(text, conversation_history or conversation_primer, start_sequence=start_sequence, restart_sequence=restart_sequence)
+
+    # Get Response from GPT
+    response = openai.Completion.create(
+        engine="davinci",
+        prompt=prompt,
+        temperature=temperature,
+        max_tokens=max_tokens,
+        top_p=1,
+        frequency_penalty=0,
+        presence_penalty=0.6,
+        stop=["\n", " Human:", " AI:"])
+
+    # Extract, Clean Message from GPT's Response
+    story = response['choices'][0]['text']
+    return str(story).strip()
+
+
+def message_to_prompt(user_message, conversation_history="", gpt_message=None, start_sequence="\nAI:", restart_sequence="\nHuman:"):
+    """Create prompt for GPT from message"""
+    if gpt_message:
+        return f"{conversation_history}{restart_sequence} {user_message}{start_sequence} {gpt_message}"
+    else:
+        return f"{conversation_history}{restart_sequence} {user_message}{start_sequence}"