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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
This commit is contained in:
Debanjum Singh Solanky
parent
6244ccc01a
commit
d4e1120b22
3 changed files with 135 additions and 1 deletions
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@ -13,3 +13,4 @@ dependencies:
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- pytest=6.*
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- pillow=8.*
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- torchvision=0.*
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- openai=0.*
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70
src/processor/conversation/gpt.py
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70
src/processor/conversation/gpt.py
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@ -0,0 +1,70 @@
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# Standard Packages
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import os
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# External Packages
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import openai
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def understand(text, api_key=None, temperature=0.5, max_tokens=100):
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"""
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Understand user input using OpenAI's GPT
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"""
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# Initialize Variables
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openai.api_key = api_key or os.getenv("OPENAI_API_KEY")
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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\")"
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# Setup Prompt with Understand Primer
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prompt = message_to_prompt(text, understand_primer, start_sequence="\nA:", restart_sequence="\nQ:")
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# Get Reponse from GPT
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response = openai.Completion.create(
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engine="davinci",
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prompt=prompt,
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=1,
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frequency_penalty=0.2,
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presence_penalty=0,
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stop=["\n"])
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# Extract, Clean Message from GPT's Response
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story = response['choices'][0]['text']
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return str(story)
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def converse(text, conversation_history=None, api_key=None, temperature=0.9, max_tokens=150):
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"""
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Converse with user using OpenAI's GPT
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"""
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# Initialize Variables
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openai.api_key = api_key or os.getenv("OPENAI_API_KEY")
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start_sequence = "\nAI:"
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restart_sequence = "\nHuman:"
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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?"
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# Setup Prompt with Primer or Conversation History
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prompt = message_to_prompt(text, conversation_history or conversation_primer, start_sequence=start_sequence, restart_sequence=restart_sequence)
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# Get Response from GPT
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response = openai.Completion.create(
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engine="davinci",
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prompt=prompt,
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temperature=temperature,
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max_tokens=max_tokens,
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top_p=1,
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frequency_penalty=0,
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presence_penalty=0.6,
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stop=["\n", " Human:", " AI:"])
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# Extract, Clean Message from GPT's Response
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story = response['choices'][0]['text']
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return str(story).strip()
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def message_to_prompt(user_message, conversation_history="", gpt_message=None, start_sequence="\nAI:", restart_sequence="\nHuman:"):
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"""Create prompt for GPT from message"""
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if gpt_message:
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return f"{conversation_history}{restart_sequence} {user_message}{start_sequence} {gpt_message}"
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else:
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return f"{conversation_history}{restart_sequence} {user_message}{start_sequence}"
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63
tests/test_chatbot.py
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63
tests/test_chatbot.py
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@ -0,0 +1,63 @@
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# External Packages
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import pytest
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# Internal Packages
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from src.processor.conversation.gpt import converse, understand, message_to_prompt
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# Input your OpenAI API key to run the tests below
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api_key = None
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# Test
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# ----------------------------------------------------------------------------------------------------
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def test_message_to_understand_prompt():
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# Setup
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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\")"
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expected_response = "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\")\nQ: When did I last dine at Burger King?\nA:"
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# Act
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actual_response = message_to_prompt("When did I last dine at Burger King?", understand_primer, start_sequence="\nA:", restart_sequence="\nQ:")
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# Assert
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assert actual_response == expected_response
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.skipif(api_key is None,
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reason="Set api_key variable to your OpenAI API key from https://beta.openai.com/account/api-keys")
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def test_minimal_chat_with_gpt():
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# Act
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response = converse("What will happen when the stars go out?", api_key=api_key)
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# Assert
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assert len(response) > 0
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.skipif(api_key is None,
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reason="Set api_key variable to your OpenAI API key from https://beta.openai.com/account/api-keys")
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def test_chat_with_history():
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# Act
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start_sequence="\nAI:"
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restart_sequence="\nHuman:"
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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, I am testatron. Who are you?{start_sequence} Hi, I am an AI conversational companion created by OpenAI. How can I help you today?"
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conversation_history = conversation_primer
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response = converse("Can you tell me my name?", conversation_history=conversation_history, api_key=api_key, temperature=0, max_tokens=50)
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# Assert
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assert len(response) > 0
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assert "Testatron" in response or "testatron" in response
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# ----------------------------------------------------------------------------------------------------
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@pytest.mark.skipif(api_key is None,
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reason="Set api_key variable to your OpenAI API key from https://beta.openai.com/account/api-keys")
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def test_understand_message_using_gpt():
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# Act
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response = understand("When did I last dine at Subway?", api_key=api_key)
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# Assert
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assert len(response) > 0
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assert "remember(\"ledger\", " in response
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