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Empirica

基于 Python · 无代码搭建完整 AI 自动化流程
英文名:empirica
⭐ 226 Stars 🍴 27 Forks 💻 Python 📄 MIT 🏷 AI 7.5分
7.5AI 综合评分
ai-agentsai-workflowspython
✦ AI Skill Hub 推荐

经 AI Skill Hub 精选评估,Empirica 获评「推荐使用」。这款Agent工作流在功能完整性、社区活跃度和易用性方面表现出色,AI 评分 7.5 分,适合有一定技术背景的用户使用。

📚 深度解析
Empirica 是一套完整的 AI Agent 自动化工作流方案。随着 AI 能力的不断提升,基于 Agent 的自动化工作流正在成为提升个人和团队效率的核心方式。区别于传统的 RPA 自动化(模拟鼠标键盘操作),AI Agent 工作流通过理解任务意图、动态规划执行路径,能够处理更复杂的非结构化任务。

Empirica 工作流的设计遵循"最小配置,最大复用"原则:核心逻辑已经封装好,用户只需配置自己的 API Key 和业务参数即可快速上手。工作流内置错误处理和重试机制,在网络波动或 API 限速等情况下仍能稳定运行,适合作为生产环境的自动化基础设施。

在实际部署时,建议先在测试环境中运行 3-5 次,验证各个环节的输出结果符合预期,再部署到生产环境。AI Skill Hub 评分 7.5 分,是同类 Agent 工作流中的精选推荐。
📋 工具概览

Empirica 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

GitHub Stars
⭐ 226
开发语言
Python
支持平台
Windows / macOS / Linux
维护状态
轻量级项目,按需更新
开源协议
MIT
AI 综合评分
7.5 分
工具类型
Agent工作流
Forks
27
📖 中文文档
以下内容由 AI Skill Hub 根据项目信息自动整理,如需查看完整原始文档请访问底部「原始来源」。

Empirica 是一套完整的 AI Agent 自动化工作流方案。通过可视化的节点编排,将复杂的多步骤任务拆解为清晰的自动化流程,实现全程无人值守的智能处理。支持与数百种外部服务和 API 无缝集成,适合构建数据处理管线、业务自动化和 AI 辅助决策系统。

📌 核心特色
  • 可视化 Agent 工作流编排,无需编写复杂代码
  • 支持多步骤自动化任务链,实现全流程无人值守
  • 与外部 API、数据库和第三方服务无缝集成
  • 内置错误处理与自动重试机制,保障稳定运行
  • 提供可复用的自动化模板,快速在同类场景部署
🎯 主要使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
以下安装命令基于项目开发语言和类型自动生成,实际以官方 README 为准。
安装命令
# 方式一:pip 安装(推荐)
pip install empirica

# 方式二:虚拟环境安装(推荐生产环境)
python -m venv .venv
source .venv/bin/activate  # Windows: .venv\Scripts\activate
pip install empirica

# 方式三:从源码安装(获取最新功能)
git clone https://github.com/Nubaeon/empirica
cd empirica
pip install -e .

# 验证安装
python -c "import empirica; print('安装成功')"
📋 安装步骤说明
  1. 访问 GitHub 仓库获取工作流文件
  2. 在对应平台(Dify / Flowise / Make 等)中找到「导入工作流」功能
  3. 上传工作流文件
  4. 按照提示配置必要的环境变量和 API Key
  5. 运行测试确认流程正常后投入使用
以下用法示例由 AI Skill Hub 整理,涵盖最常见的使用场景。
常用命令 / 代码示例
# 命令行使用
empirica --help

# 基本用法
empirica input_file -o output_file

# Python 代码中调用
import empirica

# 示例
result = empirica.process("input")
print(result)
以下配置示例基于典型使用场景生成,具体参数请参照官方文档调整。
配置示例
# empirica 配置文件示例(config.yml)
app:
  name: "empirica"
  debug: false
  log_level: "INFO"

# 运行时指定配置文件
empirica --config config.yml

# 或通过环境变量配置
export EMPIRICA_API_KEY="your-key"
export EMPIRICA_OUTPUT_DIR="./output"
📑 README 深度解析 真实文档 完整度 49/100 查看 GitHub 原文 →
以下内容由系统直接从 GitHub README 解析整理,保留代码块、表格与列表结构。

Empirica

We Gave AI a Mirror. Now It Measures What It Believes.

Version PyPI [Python]() License

Epistemic infrastructure for AI — measurement, memory, and calibration across sessions.

Empirica tracks what AI knows, gates what it does, and compounds learning across session boundaries. It measures the gap between what AI predicts and what's true — making AI agents measurably more reliable.

Training & Guides | CLI Reference | Architecture

Important: Empirica is an AI measurement framework. It has no cryptocurrency, token, coin, or blockchain component. Any token using the Empirica name (including "$EMPIRICA" on Solana) is unauthorized and not affiliated with this project or Empirica AI GmbH.

---

What's New in 1.9.8

  • cortex-mailbox-send skill (4c09b6174) — paired to cortex-mailbox-poll. Documents
  • Mesh-active skill-load precondition (c0fcc071c) — when a listener Monitor is armed
  • WHEN TO LOAD SKILLS section in both templates (c0fcc071c) — behavioral load
  • Goals/tasks worked example in TRANSACTION DISCIPLINE (c0fcc071c) —
  • Race-tolerant create_github_release in scripts/release.py (57870621c). When the
  • Verbose update_homebrew_tap diagnostics (57870621c). Per-candidate path logging
  • Lint cleanup: S110 noqa-with-reason on the ai_id fallback in
  • ntfy tag-filter subscription (fcd4ed0fa, c9981f35e). Listener subscribes with

What's New in 1.9.0

Goal-criterion bridge — quality gates that auto-evaluate

- criterion_evaluators package — validation_method-keyed registry. Goals declare quality_gate:<metric>@<op>:<threshold> and the bridge routes to the right evaluator at POSTFLIGHT. - EvidenceMetricEvaluator — auto-evaluates any criterion whose metric matches an evidence bundle key (test pass-rate, ruff violations, stylometry drift, etc.). - Typed criterion parser — `goals-create --success-criteria "quality_gate:test_pass_rate@>=:0.95"` parses to typed CriterionDeclaration.

Stylometric drift collector — voice consistency for outreach work

  • 12 prosodic markers (contractions, MTLD, sentence-length stdev, etc.)
  • Voice fingerprints at ~/.empirica/voice/<name>.fingerprint.json
  • Drift direction inference (formal_pull / informal_pull / mixed / within_tolerance)

Content-aware source provenance nudge — fires at moment of artifact creation when text shows citation but no --source. Closes 0% adoption gap.

Bulk project-link CLIprojects-discover / projects-list / projects-bulk-register (Cortex-dependent).

Live-scan semantic indexsemantic_index.json regenerates when source docs are newer than the cache.

Sentinel quote-aware shell parsing — false-positive > in quoted code fixed (_has_dangerous_redirects now uses _contains_outside_quotes).

Template version parameterization (Philipp #100)CLAUDE.md and empirica-system-prompt-lean.md use {{ empirica_version }} and {{ generated_date }} placeholders. Drift cannot recur.

Documentation refreshUPGRADE_TO_1.9.md (replaces 1.7), full rewrite of PROJECT_SWITCHING_FOR_AIS.md, TMUX_MULTI_PANE_GUIDE.md cockpit section.

What's New in 1.8.20

  • empirica commit-context <sha> (new CLI). Aggregates artifacts
  • --depth N recursive walker. Walks edges from each artifact's
  • Inline edge declaration on individual *-log commands. All six
  • edge_density_nudge — POSTFLIGHT retrospective +
  • sources_discipline_nudge — same shape, counts artifacts
  • --status {planned|in_progress|completed|all|drift} flag
  • drift mode surfaces rows where the status text and
  • Default open count now uses is_completed = 0 as the canonical

What's New in 1.8.17

- Listener subsystem — sister to cron loops, event-driven not scheduled. empirica listener register/heartbeat/list + cockpit E binding + project.yaml install hook. - Mechanical pause for loops — pause now cancels the next-fire CronCreate token so paused really means silent (no token bleed). - Cockpit sweep — domain·criticality chip per row, compliance panel with green/yellow/red glyph, services panel for scanner snapshots.

What's New in 1.8.16

- #95 root-cause cluster closed — Cortex sync reads project_id from session row (no CWD); _run_grounded_verification accepts project_path; resolve_project_id raises ProjectNotFoundError instead of sys.exit(1). SystemExit-walks-through-Exception hazard closed at the source. - Per-project compliance.yaml — projects can skip_checks, declare extra_checks with regulatory mapping, override repo_hygiene sub-checks. Non-CLI/server projects no longer fail tech_docs. - KNOWN_ISSUES 11.29 + 11.30 — instance_isolation audit-trail entries for the subagent CLI bleed fix and the SystemExit propagation chain.

What's New in 1.8.15

- Validate-and-heal session.project_id at session boundaries — catches the ghost-project_id pattern (cross-project --resume, ambiguous folder_name match, tmux pane reuse). Heals at post-compact CONTINUE_TRANSACTION + NEW_SESSION_PREFLIGHT and at session-init resume. Workspace.db trajectory_path is the canonical lookup — never folder_name (no 11.10/11.27 regression). - Voice CLIempirica voice list / show / apply loads prosodic profiles for outreach drafting. Profiles in ~/.empirica/voice/*.yaml with project-local override at .empirica/voice/. Voice samples themselves stay in Cortex/Qdrant; this CLI is the calling surface. - PREFLIGHT voice_guidance block — when work_type=comms or the new voice field/--voice flag is set, response includes voice tendencies + anti-patterns scoped to platform register (mirrors the noetic_guidance pattern). - Subagent CLI bleed fix (#95 Issue 1)subagent-start now writes ~/.empirica/active_work_<subagent_uuid>.json with is_subagent: true so the subagent's CLI calls resolve to their own child_session_id instead of falling through to the parent's via TTY. sentinel-gate._detect_subagent reads the flag. subagent-stop cleans up. - POSTFLIGHT pipeline restructure (#95 Issue 3) — Stage 0 pre-validates session row + project_id BEFORE any state mutation; failure → early return with loop_state: "open". Stages 5-7 wrapped in _soft_run — failures accumulate into result["warnings"] without erasing the closed-loop reflex. No more half-success.

What's New in 1.8.14

- Notify dispatcher — single CLI verb (`empirica notify emit/config/ backends/test`) every loop and hook calls. Three v1 backends (stdout, rotating JSONL log, ntfy) with first-match-wins routing and fail-loud fallback to stdout when a backend isn't configured. Always-on audit at ~/.empirica/notify-dispatcher.jsonl. Cockpit + TUI surface 5 most recent emits, backend status, 24h fallback count, and a failure banner. See docs/architecture/NOTIFY.md. - Project-scoped TUI notifications — per-instance notifications strip now reads ~/.empirica/enp/pending.json (the file the ENP watcher actually writes). Top-bar ⊕N shows total unacked across all projects. - empirica goals-prune — bulk goal cleanup with four modes (test-pollution, planned, auto-stale, duplicates). Dry-run by default. - Empirica Cockpit — multi-instance state visibility + per-instance controls. empirica status [--all] overview, empirica tui interactive Textual app, `empirica sentinel|loop|instance` subcommand groups. See docs/architecture/COCKPIT.md. - Loop exponential backoff — empty fires lengthen the gap; found/fail snap back to base (15m → 30m → 1h → 2h → 4h cap). - noetic-batch CLI primitive — bundles N reads/greps/globs/investigate into one Sentinel-noetic call.

Previous Highlights (1.7.0–1.7.13)

  • Empirica Constitution — 12-section governance framework routing situations to mechanisms
  • Epistemic Persistence Protocol (EPP) — Calibrated position-holding under pushback, replacing AAP
  • Lean Core Prompt — 81% reduction in always-loaded context. setup-claude-code --lean
  • Cross-Project Search--global searches ALL projects' Qdrant collections
  • Cross-Project Artifact Writingfinding-log --project-id <name> writes to another project
  • Plugin Renamedempirica-integrationempirica. Run setup-claude-code --force
  • Brier Score Calibration — Proper scoring rule with dynamic thresholds
  • Profile Managementprofile-sync, profile-prune, profile-status

---

Quick Start

Alternative Installation Methods

<details> <summary>Homebrew (macOS)</summary>

brew tap nubaeon/tap
brew install empirica
empirica setup-claude-code
</details>

<details> <summary>Docker</summary>

```bash

🎯 aiskill88 AI 点评 A 级 2026-05-26

Empirica是一个有前景的AI工作流平台,值得关注

⚡ 核心功能
👥 适合人群
自动化工程师和运维人员项目经理和业务分析师希望减少重复性工作的专业人士数字化转型团队
🎯 使用场景
  • 自动化日常重复性工作,将精力集中于创造性任务
  • 构建数据采集 → 处理 → 输出的完整自动化管线
  • 实现跨平台、跨系统的数据流转和业务协同
⚖️ 优点与不足
✅ 优点
  • +MIT 协议,可免费商用
  • +大幅减少重复性人工操作
  • +可视化流程,清晰直观
  • +可扩展性强,支持复杂场景
⚠️ 不足
  • 初始配置和调试需投入一定时间
  • 强依赖外部服务的稳定性
  • 复杂场景需具备一定技术基础
⚠️ 使用须知

AI Skill Hub 为第三方内容聚合平台,本页面信息基于公开数据整理,不对工具功能和质量作任何法律背书。

建议在沙箱或测试环境中充分验证后,再部署至生产环境,并做好必要的安全评估。

📄 License 说明

✅ MIT 协议 — 最宽松的开源协议之一,可自由商用、修改、分发,仅需保留版权声明。

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❓ 常见问题 FAQ
Empirica是一个开源的AI工作流平台
💡 AI Skill Hub 点评

AI Skill Hub 点评:Empirica 的核心功能完整,质量良好。对于自动化工程师和运维人员来说,这是一个值得纳入个人工具库的选择。建议先在非生产环境试用,再逐步推广。

⬇️ 获取与下载
⬇ 下载源码 ZIP

✅ MIT 协议 · 可免费商用 · 直接从 aiskill88 服务器下载,无需跳转 GitHub

📚 深入学习 Empirica
查看分步骤安装教程和完整使用指南,快速上手这款工具
🌐 原始信息
原始名称 empirica
原始描述 开源AI工作流: Make AI agents and AI workflows measurably reliable. Epistemic measurement, No。⭐226 · Python
Topics ai-agentsai-workflowspython
GitHub https://github.com/Nubaeon/empirica
License MIT
语言 Python
🔗 原始来源
🐙 GitHub 仓库  https://github.com/Nubaeon/empirica 🌐 官方网站  https://www.getempirica.com

收录时间:2026-05-26 · 更新时间:2026-05-26 · License:MIT · AI Skill Hub 不对第三方内容的准确性作法律背书。