- Added logic to determine the N8N_WORKFLOWS_IMPORTED_EVER variable based on existing environment values and user input.
- Updated the apply_update.sh script to check if workflows have been imported previously, modifying the RUN_N8N_IMPORT and N8N_WORKFLOWS_IMPORTED_EVER variables accordingly.
- Improved user prompts for importing n8n workflows, ensuring a smoother configuration experience.
- Introduced a comprehensive workflow that automates the generation of short-form videos using OpenAI, Flux, Kling, and ElevenLabs.
- The workflow includes nodes for image generation, video creation, voiceover generation, and uploading to multiple social media platforms.
- Enhanced user guidance with sticky notes detailing setup instructions and API key requirements for seamless integration.
- Implemented error handling and retry mechanisms to ensure robust execution of video generation tasks.
- Enhanced the final report script to include details for a standalone PostgreSQL instance used by n8n and Langfuse.
- Added Ollama service information for internal access based on active profiles.
- Clarified the distinction between Supabase's internal PostgreSQL and the standalone instance for better user understanding.
- Introduced Ollama service with CPU and GPU profiles in docker-compose.yml, allowing users to run large language models locally.
- Added Ollama selection option in the wizard script for hardware profile configuration.
- Updated README.md to include Ollama as a new available service.
- Adjusted .env.example to include GRAFANA_HOSTNAME in the correct position.
- Introduced a new workflow that automates the backup of all n8n workflows to Google Drive at a 4-hour interval.
- The workflow includes nodes for creating folders, converting workflows to JSON files, and managing folder deletions to maintain organization.
- Enhanced scheduling and filtering capabilities to ensure efficient backup management.
- Introduced a comprehensive workflow that automates the backup of n8n workflows to Google Drive.
- The workflow includes nodes for scheduling, retrieving existing workflows, and sending success or failure notifications via email and Discord.
- Enhanced user guidance with sticky notes detailing setup instructions and important information.
- Introduced a comprehensive workflow that automatically documents and backs up n8n workflows to Notion and GitHub.
- The workflow includes nodes for setting fields, mapping data, and handling notifications, ensuring efficient management and tracking of workflow changes.
- Added a check to prevent duplicate entries when appending environment variables to TMP_ENV_FILE, ensuring cleaner and more efficient script execution.
- Moved the sourcing of the utilities file to the beginning of the script for better organization and clarity.
- Removed redundant sourcing of the utilities file from the middle of the script.
- Added logic to detect and correct nested n8n-installer directory structures.
- Included re-execution of the install script from the corrected path to ensure proper script execution and path resolution.
- Added Letta service to docker-compose.yml with necessary environment variables and volume configuration.
- Updated Caddyfile to include reverse proxy for Letta.
- Included Letta in the README.md for service availability and provided a brief description.
- Enhanced scripts to generate Letta server password and report its status in the final report.
- Updated .env.example to include Letta hostname and server password variable.
- Changed the DATABASE_URL environment variable for the langfuse worker service to connect to the langfuse database instead of the default postgres database, ensuring proper database configuration for the application.
- Introduced a comprehensive workflow that automates the scheduling of YouTube videos, including fetching the latest videos, generating SEO-optimized titles, descriptions, and tags using AI, and updating video metadata.
- The workflow enhances content management efficiency on YouTube by integrating various nodes for video processing and scheduling.
- Introduced a comprehensive workflow that automates the process of uploading videos to YouTube, including downloading video files from Google Drive, generating descriptions and tags using AI, and updating video metadata.
- The workflow includes nodes for downloading videos, creating descriptions, generating SEO-optimized titles, and managing video uploads, enhancing the efficiency of content management on YouTube.
- Standardized prompt formatting by removing unnecessary newline characters, enhancing clarity and consistency in user interactions.
- Updated prompts to ensure a more straightforward user experience during input collection, particularly for domain name, email, and n8n worker count inputs.
- Updated the user prompt to clarify the response options for importing n8n workflows, enhancing user understanding and interaction.
- Ensured consistency in prompt formatting across the script for improved user experience.
- Updated prompts to use printf for better formatting, ensuring dynamic inclusion of variable values in user messages.
- Improved user experience by making prompts clearer and more informative during input collection.
- Updated prompts to include newline characters for better readability, improving user experience during input collection.
- Ensured consistency in user interaction across scripts by standardizing prompt formatting.
- Simplified the user prompt for importing n8n workflows by removing the check for the RUN_N8N_IMPORT variable being true, allowing users to indicate if they have already imported the workflow.
- Retained the logic for modifying the RUN_N8N_IMPORT variable based on user input, ensuring flexibility in workflow management.
- Added a git reset --hard HEAD command to the update.sh script to ensure a clean working directory before pulling the latest changes. This helps prevent issues caused by uncommitted local changes during updates, while also logging a warning if the reset fails.
- Added a check to skip the import prompt if RUN_N8N_IMPORT is already set to true in the .env file, improving user experience by preventing unnecessary prompts.
- Retained the existing logic for modifying the RUN_N8N_IMPORT variable based on user input, ensuring flexibility in workflow management.
- Removed the npm install command for cheerio from the n8n service to streamline the startup process.
- Added environment variables NODE_FUNCTION_ALLOW_BUILTIN and NODE_FUNCTION_ALLOW_EXTERNAL to allow specific built-in and external modules, enhancing the flexibility of the n8n service.
- Modified the command for the n8n service in the docker-compose.yml file to use a simplified shell invocation, enhancing readability while maintaining functionality.
- Updated the docker-compose.yml file to include a command that installs the cheerio package before starting the n8n service. This ensures that the necessary dependencies are available for the application to function correctly.
- Introduced a new section addressing potential browser security warnings after deploying services, detailing symptoms, causes, and solutions.
- This addition aims to assist users in troubleshooting common SSL certificate issues during initial service access.
- Enhanced the final report script to include Redis connection details when the n8n or langfuse profiles are active.
- This addition provides clearer insights into internal service communication settings, improving the overall utility of the report.
- Added python3-pip to the list of standard CLI tools installed in the system preparation script, enhancing the environment setup for Python package management.
- Modified the installation and update commands in the README to include 'sudo', ensuring proper permissions for script execution.
- This change enhances the installation process by preventing potential permission issues during setup and updates.
- Updated the update.sh script to define the path for the apply_update.sh script, ensuring it can be referenced correctly during the update process.
- This change enhances the script's functionality by establishing a clear link to the new update handling script introduced in the previous commit.
- Introduced a new script, apply_update.sh, to handle the update process, including stopping services, pulling the latest container versions, and modifying the .env file based on user input for n8n workflow import and worker count.
- Refactored update.sh to delegate the update tasks to apply_update.sh, improving code organization and maintainability.
- Enhanced error handling and logging throughout the update process for better user experience and troubleshooting.
- Added functionality to prompt the user for a new n8n worker count during the update process, including validation for positive integers.
- Improved error handling and logging for cases where the N8N_WORKER_COUNT line is missing in the .env file, ensuring better user guidance and script robustness.
- Moved the langfuse profile output section to ensure it includes user email and password details, enhancing the clarity and completeness of the final report.
- Rearranged and updated the list of automation categories for clarity, ensuring that users can easily identify available workflows across various domains such as HR, E-commerce, and communication platforms.
- Added a new section outlining over 300 pre-built automations available for users, categorized by use cases such as AI agents, email handling, social media, and more, enhancing user onboarding and resource accessibility.
- Updated the unquoting mechanism in 03_generate_secrets.sh to repeatedly remove surrounding quotes from variable values, improving the handling of quoted strings and ensuring accurate environment variable assignment.
- Included a new point under the General Issues section to remind users to verify that their server meets the minimum hardware and operating system requirements, enhancing troubleshooting guidance.
- Introduced a new section addressing potential VPN conflicts that may interfere with downloading Docker images, providing users with troubleshooting guidance.
- Expanded the description of the installer, highlighting the rich toolset and scalable n8n performance.
- Revised DNS configuration instructions for clarity and updated server requirements to include specific memory, CPU, and disk space recommendations.
- Clarified the installation command and added details about the number of n8n workers during setup.
