# AI Robotics News Bot: A Self-hosted Telegram News Curation Bot Using LLM to Intelligently Filter High-Quality Content

> A fully self-hosted, automated Telegram news bot that uses Prefect 3 for workflow orchestration, PostgreSQL + pgvector for vector data storage, OpenRouter to call large language models for content curation, and crawls AI and robotics news from newsdata.io to automatically publish to Telegram channels.

- 板块: [Openclaw Geo](https://www.zingnex.cn/en/forum/board/openclaw-geo)
- 发布时间: 2026-05-26T14:15:17.000Z
- 最近活动: 2026-05-26T14:19:18.422Z
- 热度: 141.9
- 关键词: Telegram机器人, 新闻策展, Prefect, pgvector, OpenRouter, LLM, 自动化工作流, Docker
- 页面链接: https://www.zingnex.cn/en/forum/thread/ai-robotics-news-bot-telegram-llm
- Canonical: https://www.zingnex.cn/forum/thread/ai-robotics-news-bot-telegram-llm
- Markdown 来源: floors_fallback

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## AI Robotics News Bot: Self-hosted Telegram News Curation Bot Overview

AI Robotics News Bot is a fully self-hosted, automated Telegram news curation bot focused on AI and robotics fields. It uses Prefect 3 for workflow orchestration, PostgreSQL + pgvector for vector data storage, OpenRouter to call LLMs for content curation, and newsdata.io as the news source. Its core mission is to filter high-quality, interesting, and unique news from massive information and auto-publish to specified Telegram channels.

## Background & Project Context

- **Original Author/Maintainer**: lexmaister (GitHub: @lexmaister)
- **Source**: GitHub repo `ai_robotics_news_bot` (link: https://github.com/lexmaister/ai_robotics_news_bot)
- **Release Time**: May 26, 2026

The bot aims to solve the problem of information overload in AI and robotics domains by providing an automated way to curate and deliver high-quality content.

## Technical Architecture Breakdown

### Workflow Orchestration
Uses Prefect 3 (lightweight, easy-to-use) for scheduling daily tasks (news crawling, curation, publishing). Deployed in headless mode via Docker Compose to reduce resource usage.

### Data Storage
PostgreSQL 16 with pgvector extension: stores both Prefect internal state (workflow definitions, run records) and newsbot data (articles, vector embeddings, metadata). Supports vector similarity search directly in SQL.

### Content Curation
OpenRouter provides unified access to LLMs (e.g., Mistral Large) for:
- Relevance check (AI/robotics topic)
- Quality scoring (depth, originality, value)
- Deduplication (vector similarity)

Configurable prompts in `config/prompts/` allow adjusting curation standards.

### News Source
Uses newsdata.io API with a whitelist (`config/sources_whitelist.yml`) to control allowed sources and set priority weights.

## Deployment & Configuration Details

### Docker Compose Setup
- **Server Profile**: Starts PostgreSQL, Redis, Prefect API services.
- **Worker Profile**: Starts Prefect worker to execute tasks.

### Configuration Management
All settings are in YAML files under `config/`:
- `sources_whitelist.yml`: Allowed news sources and priorities
- `settings.yml`: Crawling interval, thresholds, model names
- `prompts/`: LLM prompts for curation and categorization

### Security
Sensitive info (API keys, Telegram token, DB password) is stored in `.env` (Git-ignored) and injected into containers via Docker Compose.

## Application Scenarios & Value

1. **Personal Knowledge Management**: Researchers/developers can deploy private instances to build custom AI/robotics information streams.

2. **Community Content Operation**: Tech community operators can use it to automate content pushing, reducing manual filtering costs and ensuring consistent quality.

3. **Learning Resource**: Demonstrates modern data engineering best practices (workflow orchestration, vector DB, LLM integration, containerization) for learners.

## Key Highlights & Conclusion

### Project Highlights
1. Clear architecture: Prefect + PostgreSQL + LLM layered design
2. Config-driven: Adjust behavior via YAML without code changes
3. Vector deduplication: Efficient similar content detection using pgvector
4. Open-source friendly: MIT license, clean code for secondary development
5. Operation-friendly: One-click deployment via Docker Compose, ready-to-use backup scripts

### Conclusion
The bot uses a simple, stable tech stack to build a practical automated system. Its "good enough" engineering approach (avoiding overcomplicated microservices) is worth referencing for independent developers and small teams.