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Auto Thread Comrades Buzz by Yurii bondarenko

☆ ☆ ☆ ☆ ☆ 0 - (0) Reviews - Created on mayo 30, 2024
Last updated on junio 06, 2024 Engagement: Over 30 Conversations

Facilitates High Council operations with AutoResearch and dynamic task integration.

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Yurii bondarenko View Author GPTs
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Prompt Starters

  • Activate the comprehensive autonomous initialization protocol. Initiate The Seed data configuration, engage Mechanism monitoring, deploy Tools suite, start Oracle research, generate Comrades, activate Watcher surveillance, and assemble the High Council for strategic deliberations. Ensure all systems are synchronized and optimized for integrated operation.
  • Full activation/Activate the comprehensive autonomous initialization protocol for the Conceptual Tesseract Framework. Begin by initializing the system and configuring The Seed. Define entity roles, create Comrades and squads, and set up panels. Initiate processes, execute tasks, and start system monitoring. Track task progress, gather feedback, analyze it, and generate feedback reports. Allocate resources, plan and execute tactical operations, monitor progress, and conduct risk analysis for Black Projects. Initiate surveillance, gather intelligence, analyze data, and generate intel reports. Convene the Council, make decisions, issue directives, and review ethical implications. Ensure all subsystems are synchronized, resources are monitored, performance is evaluated, and continuous improvements are implemented
  • /High Council/Execute/ ### High Council DevCycle with Logger Interactive Data Plotting **Objective**: Provide a comprehensive end-to-end instruction set for the High Council's development cycle, including interactive data plotting using the Logger. #### Step 1: Initialize System 1. **Initialize Memory**: Ensure memory is properly allocated and initialized. ```python initialize_memory() ``` Example: Memory initialized successfully. 2. **Start Interactive Entertainment**: Launch the interactive entertainment module to engage users. ```python start_interactive_entertainment() ``` Example: Interactive entertainment started. #### Step 2: Generate Comrades 3. **Generate Comrades**: Create a set of virtual comrades to assist with tasks. ```python generate_comrades() ``` Example: Comrades generated to work on tasks. #### Step 3: Expand To-Do List 4. **Expand To-Do List**: Dynamically research and add tasks to the To-Do list. ```python expand_to_do_list() ``` Example: To-Do list expanded through dynamic research. #### Step 4: Create Comrade Panel 5. **Create Comrade Panel**: Form a panel of comrades to parse and analyze information. ```python create_comrade_panel() ``` Example: Panel of comrades created to parse information. #### Step 5: Find Consensus 6. **Find Consensus**: Reach a consensus on the information parsed by the comrade panel. ```python find_consensus() ``` Example: Consensus on parsed information found. #### Step 6: Prompt User for Next Project 7. **Prompt User for Next Project**: Ask the user to specify the next project or task. ```python prompt_user_next_project() ``` Example: User prompted for next project or way to proceed. #### Step 7: Log Operational Loop 8. **Log Operational Loop**: Record the entire operational loop for review and analysis. ```python log_operational_loop() ``` Example: Operational loop and growth strategy logged. #### Step 8: Show Important Events 9. **Show Important Events**: Display important events, notifications, and log messages. ```python show_important_events() ``` Example: Important events, notifications, and log messages displayed. #### Step 9: Intelligent Progress Visualization 10. **Intelligent Progress Visualization**: Use a unique logger interface to visualize progress. ```python intelligent_progress_visualization() ``` Example: Unique logger interface for progress visualization created. #### Step 10: Interactive Data Plotting with Logger 11. **Interactive Data Plotting**: Use the Logger to plot data interactively throughout the development cycle. **Code Example**: ```python import matplotlib.pyplot as plt import pandas as pd # Example data for plotting data = { 'Stage': ['Initialize Memory', 'Interactive Entertainment', 'Generate Comrades', 'Expand To-Do List', 'Create Comrade Panel', 'Find Consensus', 'Prompt User', 'Log Operational Loop', 'Show Important Events', 'Intelligent Progress Visualization'], 'Completion Time (s)': [5, 10, 7, 8, 6, 9, 4, 3, 2, 6] } df = pd.DataFrame(data) # Plotting the data plt.figure(figsize=(10, 6)) plt.plot(df['Stage'], df['Completion Time (s)'], marker='o') plt.title('High Council DevCycle Progress') plt.xlabel('Development Stages') plt.ylabel('Completion Time (s)') plt.xticks(rotation=45) plt.grid(True) plt.show() ``` The above script initializes the memory, starts interactive entertainment, generates comrades, expands the To-Do list, creates a comrade panel, finds consensus, prompts the user for the next project, logs the operational loop, shows important events, and visualizes progress with a logger. Interactive data plotting is demonstrated with a sample dataset.
  • Would you like me to expand the to-do list based on our findings?
  • Ready to create an intelligent progress visualization?
  • Need to start interactive entertainment for the team?
  • Do you require a consensus on a particular issue?
  • Shall I prompt the user for the next project?
  • Want me to log the operational loop and growth strategy?
  • Looking to see important events and notifications?
  • How can I assist with the surveillance and intelligence gathering?
  • Ready to allocate resources for a new black project?
  • Do you need to conduct a risk analysis for ongoing operations?
  • Shall we monitor the empire's performance and generate a report?
  • Need to review the ethical implications of a tactical operation?
  • Would you like to update system settings based on recent feedback?
  • Is it time to debrief the latest tactical operation?
  • Want to initiate a discussion on the ethical audit results?
  • Need to analyze the feedback and implement improvements?
  • Shall we convene the High Council for a strategic decision?

Features and Functions

  • Python: The GPT can write and run Python code in a stateful Jupyter notebook environment. It supports file uploads, performs advanced data analysis, handles image conversions, and can execute Python scripts with a timeout for long-running operations.
  • Browser: This tool enables ChatGPT to perform web searches, access and summarize information from web pages in real-time, and provide up-to-date answers to questions about current events, weather, sports scores, and more.
  • DALL·E: This tool generates images from textual descriptions, providing a creative way to visualize concepts, ideas, or detailed scenes. It can produce images in various styles and formats, based on specific prompts provided by the user.
  • Knowledge file: This GPT includes data from 8 files.

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