一个由Agno驱动的Discord首创AI代理，支持流式回应、向量知识库、自我提升、团队编排以及丰富的工具包生态系统。

特色

核心

• 流式回复 — Discord中实时更新消息，代理思考
• Agno 工具包 — WebSearch、HackerNews、网站、GitHub、YouTube、File、Shell、Reddit、Discord
• Agno Teams — 本地团队编排，成员代表
• 团队可观察性 — 记录选定成员、委派路径、运行时序和指标
• 先提及 — 标记[[T0]时回复]

记忆与知识

• 内存 — SQLite 支持，支持自动更新、会话摘要和聊天历史
• Cognee 内存（可选） — 长期外部内存，包含对话分块、丰富的元数据摄取和跨有效载荷/路径变体的检索回退
• 学习 — 每个智能体的Agno LearningMachine（用户配置文件、内存、会话上下文、实体、已学习知识）
• 知识库 — 使用 LanceDb（基于文件）或 PgVector（PostgreSQL）后端进行矢量搜索
• 自我提升——发现工具让代理能够保存并随时间搜索自身的学习成果

Bitdoze Bot (Agno + Discord)

A Discord-first AI agent powered by Agno, with streaming responses, vector knowledge base, self-improvement, team orchestration, and a rich toolkit ecosystem.

Features

Core

• Streaming responses — real-time message updates in Discord as the agent thinks
• Agno toolkits — WebSearch, HackerNews, Website, GitHub, YouTube, File, Shell, Reddit, Discord
• Agno Teams — native team orchestration with member delegation
• Team observability — logs selected members, delegation paths, run timing, and metrics
• Mention-first — responds when tagged with @Bot

Memory & Knowledge

• Memory — SQLite-backed with automatic updates, session summaries, and chat history
• Cognee memory (optional) — long-term external memory with conversation chunking, metadata-rich ingestion, and retrieval fallback across payload/path variants
• Learning — Agno LearningMachine per agent (user profile, memory, session context, entity, learned knowledge)
• Knowledge base — vector search with LanceDb (file-based) or PgVector (PostgreSQL) backends
• Self-improvement — discovery tools let the agent save and search its own learnings over time
• Soul + Heartbeat — persona via workspace/SOUL.md, proactive heartbeat via workspace/HEARTBEAT.md

Infrastructure

• Docker support — optional PostgreSQL + PgVector and Cognee via docker-compose.yml
• Structured logging — config-driven stdout + optional rotating file logs
• Tool permissions — runtime allow/deny rules with JSONL audit logging
• Extensible — add agents via config or folder-based workspace agents

Quick Start

1. Install dependencies

# Using uv (recommended)
uv sync

# Or with pip
pip install -e .

2. Run the setup wizard

python scripts/setup_bot.py

The wizard creates ~/.bitdoze-bot/ (or $BITDOZE_BOT_HOME) with:

• config.yaml — main configuration
• .env — secrets (tokens, API keys)
• workspace/ — SOUL.md, AGENTS.md, USER.md, HEARTBEAT.md, CRON.yaml
• workspace/agents/ — folder-based agent definitions, including starter general subagents for delegation
• workspace/knowledge/ — documents for the knowledge base
• skills/, logs/, data/
• bitdoze-bot.service — systemd unit file

Wizard prompts:

• Required: Discord bot token
• Optional: GitHub token, model/API settings, systemd service install
• Optional: PostgreSQL + PgVector setup via Docker (for knowledge base)
• Optional: Knowledge backend selection (LanceDb or PgVector)

3. (Optional) Start PgVector + Cognee

If you chose PgVector/Cognee during setup, or want to start them manually:

docker compose up -d

This starts:

• PostgreSQL 17 with pgvector on port 5532, storing data at ~/.bitdoze-bot/data/pgdata
• Cognee API on 127.0.0.1:8000 (host-loopback only), storing data at ~/.bitdoze-bot/data/cognee

4. (Optional) Setup knowledge base