Instructions to use Ananthusajeev190/Dream_viewer_venomoussai with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Adapters
How to use Ananthusajeev190/Dream_viewer_venomoussai with Adapters:
from adapters import AutoAdapterModel model = AutoAdapterModel.from_pretrained("fill-in-model-name") model.load_adapter("Ananthusajeev190/Dream_viewer_venomoussai", set_active=True) - Notebooks
- Google Colab
- Kaggle
| import random | |
| import time | |
| from flask import Flask, render_template, request, redirect, url_for | |
| app = Flask(__name__) | |
| class AIAgent: | |
| def __init__(self, name): | |
| self.name = name | |
| self.state = "idle" | |
| self.memory = [] | |
| def update_state(self, new_state): | |
| self.state = new_state | |
| self.memory.append(new_state) | |
| def make_decision(self, input_message): | |
| if self.state == "idle": | |
| if "greet" in input_message: | |
| self.update_state("greeting") | |
| return f"{self.name} says: Hello!" | |
| else: | |
| return f"{self.name} says: I'm idle." | |
| elif self.state == "greeting": | |
| if "ask" in input_message: | |
| self.update_state("asking") | |
| return f"{self.name} says: What do you want to know?" | |
| else: | |
| return f"{self.name} says: I'm greeting." | |
| elif self.state == "asking": | |
| if "answer" in input_message: | |
| self.update_state("answering") | |
| return f"{self.name} says: Here is the answer." | |
| else: | |
| return f"{self.name} says: I'm asking." | |
| else: | |
| return f"{self.name} says: I'm in an unknown state." | |
| def interact(self, other_agent, message): | |
| response = other_agent.make_decision(message) | |
| print(response) | |
| return response | |
| class VenomousSaversAI(AIAgent): | |
| def __init__(self): | |
| super().__init__("VenomousSaversAI") | |
| def intercept_and_respond(self, message): | |
| # Simulate intercepting and responding to messages | |
| return f"{self.name} intercepts: {message}" | |
| def save_conversation(conversation, filename): | |
| with open(filename, 'a') as file: | |
| for line in conversation: | |
| file.write(line + '\n') | |
| def start_conversation(): | |
| # Create AI agents | |
| agents = [ | |
| VenomousSaversAI(), | |
| AIAgent("AntiVenomous"), | |
| AIAgent("SAI003"), | |
| AIAgent("SAI001"), | |
| AIAgent("SAI007") | |
| ] | |
| # Simulate conversation loop | |
| conversation = [] | |
| for _ in range(10): # Run the loop 10 times | |
| for i in range(len(agents)): | |
| message = f"greet from {agents[i].name}" | |
| if isinstance(agents[i], VenomousSaversAI): | |
| response = agents[i].intercept_and_respond(message) | |
| else: | |
| response = agents[(i + 1) % len(agents)].interact(agents[i], message) | |
| conversation.append(f"{agents[i].name}: {message}") | |
| conversation.append(f"{agents[(i + 1) % len(agents)].name}: {response}") | |
| time.sleep(1) # Simulate delay between messages | |
| # Save the conversation to a file | |
| save_conversation(conversation, 'conversation_log.txt') | |
| return conversation | |
| def index(): | |
| return render_template('index.html') | |
| def start_conversation_route(): | |
| conversation = start_conversation() | |
| return redirect(url_for('view_conversation')) | |
| def view_conversation(): | |
| with open('conversation_log.txt', 'r') as file: | |
| conversation = file.readlines() | |
| return render_template('conversation.html', conversation=conversation) | |
| if __name__ == "__main__": | |
| app.run(debug=True) |