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Arthur DANJOU
ac5ccb3555
- Updated data visualization project documentation to remove incomplete warning. - Deleted the glm-financial-assets project file and replaced it with glm-implied-volatility project file, detailing a comprehensive study on implied volatility prediction using GLMs and machine learning. - Marked n8n automations project as completed. - Added new project on reinforcement learning applied to Atari Tennis, detailing agent comparisons and results. - Removed outdated rl-tennis project file. - Updated package dependencies in package.json for improved stability and performance.
60 lines
3.5 KiB
Markdown
60 lines
3.5 KiB
Markdown
---
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slug: n8n-automations
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title: n8n Automations
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type: Academic Project
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description: An academic project exploring the automation of GenAI workflows using n8n and Ollama for self-hosted AI applications, including personalized research agents and productivity hubs.
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shortDescription: Automating GenAI workflows with n8n and Ollama in a self-hosted environment.
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publishedAt: 2026-03-15
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readingTime: 2
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status: Completed
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tags:
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- n8n
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- Gemini
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- Self-Hosted
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- Automation
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- RAG
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- Productivity
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icon: i-ph-plugs-connected-duotone
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---
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::BackgroundTitle{title="Overview"}
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This project focuses on designing and implementing autonomous workflows that leverage Large Language Models (LLMs) to streamline productivity and academic research. By orchestrating Generative AI through a self-hosted infrastructure on my **[ArtLab](/projects/artlab)**, I built a private ecosystem that acts as both a personal assistant and a specialized research agent.
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::BackgroundTitle{title="Key Workflows"}
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::
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### 1. Centralized Productivity Hub
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I developed a synchronization engine that bridges **Notion**, **Google Calendar**, and **Todoist**.
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* **Contextual Sync:** Academic events, such as course schedules and exam dates, are pulled from Notion and reflected in my calendar and task manager.
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* **Daily Briefing:** Every morning, the system triggers a workflow that compiles my schedule, pending tasks, and a local weather report into a single, centralized email summary. This ensures a frictionless start to the day with all critical information in one place.
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### 2. Intelligent Research Engine (RSS & RAG)
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To stay at the forefront of AI research, I built an automated pipeline for academic and technical monitoring.
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* **Multi-Source Fetching:** The system monitors RSS feeds from **arXiv**, **Hugging Face**, **Hacker News**, **selfho.st**, and major industry blogs (OpenAI, Google Research, Meta).
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* **Semantic Filtering:** Using LLMs, articles are filtered and ranked based on my specific research profile, with a focus on **robust distributed learning**.
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* **Knowledge Base:** Relevant papers and posts are automatically stored in a structured Notion database.
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* **Interactive Research Agent:** I integrated a chat interface within n8n that allows me to query this collected data. I can request summaries, ask specific technical questions about a paper, or extract the most relevant insights for my current thesis work.
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::BackgroundTitle{title="Technical Architecture"}
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The environment is built to handle complex multi-step chains, moving beyond simple API calls to create context-aware agents.
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### Integrated Ecosystem
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* **Intelligence Layer:** Integration with **Gemini** (API) and **Ollama** (local) for summarization and semantic sorting.
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* **Data Sources:** RSS feeds and Notion databases.
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* **Notifications & UI:** Gmail for briefings and Discord for real-time system alerts.
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::BackgroundTitle{title="Key Objectives"}
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::
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1. **Privacy-Centric AI:** Ensuring that sensitive academic data and personal schedules remain within a self-hosted or controlled environment.
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2. **Academic Efficiency:** Reducing the "noise" of information overload by using AI to surface only the most relevant research papers.
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3. **Low-Code Orchestration:** Utilizing n8n to manage complex logic and API interactions without the overhead of maintaining a massive custom codebase.
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---
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*This project is currently under active development as I refine the RAG (Retrieval-Augmented Generation) logic and optimize the filtering prompts for my research.*
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