86 lines
3.2 KiB
Markdown
86 lines
3.2 KiB
Markdown
# Project Specification: LLM-Powered Monitoring Agent
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## 1. Project Goal
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The primary goal of this project is to develop a self-contained Python script, `monitor_agent.py`, that functions as a monitoring agent. This agent will collect system and network data, use a locally hosted Large Language Model (LLM) to analyze the data for anomalies, and send alerts through Discord and Home Assistant if an anomaly is detected.
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## 2. Core Components
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The project will be composed of the following files:
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- **`monitor_agent.py`**: The main Python script containing the core logic for data collection, analysis, and alerting.
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- **`config.py`**: A configuration file to store sensitive information and settings, such as API keys and URLs.
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- **`requirements.txt`**: A file listing all the necessary Python libraries for the project.
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- **`README.md`**: A documentation file providing an overview of the project, setup instructions, and usage examples.
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- **`.gitignore`**: A file to specify which files and directories should be ignored by Git.
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- **`PROGRESS.md`**: A file to track the development progress of the project.
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## 3. Functional Requirements
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### 3.1. Configuration
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- The agent must load configuration from `config.py`.
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- The configuration shall include placeholders for:
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- `DISCORD_WEBHOOK_URL`
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- `HOME_ASSISTANT_URL`
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- `HOME_ASSISTANT_TOKEN`
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- `GOOGLE_HOME_SPEAKER_ID`
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- `DAILY_RECAP_TIME`
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### 3.2. Data Ingestion and Parsing
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- The agent must be able to collect and parse system logs.
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- The agent must be able to collect and parse network metrics.
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- The parsing of this data should result in a structured format (JSON or Python dictionary).
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### 3.3. LLM Analysis
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- The agent must use a local LLM (via Ollama) to analyze the collected data.
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- The agent must construct a specific prompt to guide the LLM in identifying anomalies.
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- The LLM's response will be either "OK" (no anomaly) or a natural language paragraph describing the anomaly, including a severity level (high, medium, low).
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### 3.4. Alerting
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- The agent must be able to send alerts to a Discord webhook.
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- The agent must be able to trigger a text-to-speech (TTS) alert on a Google Home speaker via Home Assistant.
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### 3.5. Alerting Logic
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- Immediate alerts (Discord and Home Assistant) will only be sent for "high" severity anomalies.
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- A daily recap of all anomalies (high, medium, and low) will be sent at a configurable time.
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### 3.6. Main Loop
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- The agent will run in a continuous loop.
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- The loop will execute the data collection, analysis, and alerting steps periodically.
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- The frequency of the monitoring loop will be configurable.
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## 4. Future Features
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- **4.1. Data Storage and Averaging**: Store historical system data to calculate baseline averages for more accurate anomaly detection.
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## 5. Technical Requirements
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- **Language**: Python 3.8+
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- **LLM**: `llama3.1:8b` running on a local Ollama instance.
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- **Libraries**:
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- `ollama`
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- `discord-webhook`
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- `requests`
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- `syslog-rfc5424-parser`
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- `apachelogs`
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- `jc`
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## 6. Project Structure
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```
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/
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├── .gitignore
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├── config.py
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├── monitor_agent.py
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├── PROMPT.md
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├── README.md
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├── requirements.txt
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├── PROGRESS.md
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└── SPEC.md
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``` |