🔴 LIVE 🔴 MATRIX FACTORIZATION TECHNIQUES FOR RECOMMENDER SYSTEMS

[mdbayazid]

Is there any discord channel available?

[cerealpeer]

am snek..


Certainly! Here's an example that combines the adaptive logic web with a web of thought, creating a more comprehensive system that incorporates both:

```python
import openai

# Set up OpenAI API credentials
openai.api_key = 'YOUR_API_KEY'

# Initialize the logic web
logic_web = {}

# Function to add a logic statement to the web
def add_logic_statement(condition, action):
if condition not in logic_web:
logic_web[condition] = []



# Function to evaluate a condition and perform corresponding actions
def
if condition in logic_web:
actions = logic_web[condition]
for action in actions:
print(f"Performing action: {action}")

# Function to generate response from GPT-3
def generate_response(prompt):
response = openai.Completion.create(
engine='text-davinci-003',
prompt=prompt,
max_tokens=100,
n=1, # Generate a single response
stop=None,
temperature=0.7
)

return

# Function to generate a thought from the web of thought
def generate_thought():
# Generate thought based on the current state of the logic web
thought = "Thought generated based on the web of thought"
return thought

# User interaction loop
while True:
user_input = input("User: ")

# Add user input to the web of thought
add_logic_statement("WebOfThought", user_input)

# Generate a thought from the web of thought
thought = generate_thought()
print(f"Thought: {thought}")

prompt = f"User input: {user_input}\nThought: {thought}\nGPT-3 response:"

# Generate response from GPT-3
gpt_response = generate_response(prompt)

print(f"GPT-3: {gpt_response}")

# Add logic statement based on GPT-3 response
add_logic_statement(gpt_response, "Perform some action")

# Evaluate conditions based on user input, thought, and GPT-3 response

evaluate_condition(thought)


# Add more custom conditions and actions
if user_input == "specific input":
add_logic_statement("specific input", "Perform specific action")

# Additional conditions and actions...
# add_logic_statement(condition, action)
# evaluate_condition(condition)

```

In this updated example, the code incorporates a web of thought alongside the adaptive logic web. Here are the main changes:

- The `generate_thought` function generates a thought based on the current state of the logic web. This function can be customized to generate a thought that combines various elements from the logic web or other sources.

- The user input is added to the web of thought using the `add_logic_statement` function, associating it with the key `"WebOfThought"`. This allows the system to keep track of the user's input and integrate it into the thought generation process.

- The thought, along with the user input and GPT-3 response, is included in the prompt for generating a response from GPT-3. This provides a contextual prompt for GPT-3, incorporating the ongoing conversation and the thought generated from the web of thought.

- The conditions evaluated in the `evaluate_condition` function include the user input, thought, and GPT-3 response, in addition to any custom conditions you add. This allows the system to trigger actions based on various aspects of the conversation and thought process.

Remember to replace `'YOUR_API_KEY'` with your actual OpenAI

API key.

This example demonstrates the integration of the adaptive logic web and the web of thought, allowing the system to adapt its logic based on user input, generate thoughts based on the logic web, and incorporate the generated thoughts in the GPT-3 conversation.

#chatgpt #openai