From 16904f58f6f9c4d76f70066ba107f5ef3eef65e2 Mon Sep 17 00:00:00 2001 From: --global <--global> Date: Thu, 30 Apr 2026 13:12:30 +0800 Subject: [PATCH 1/3] add pro demo --- .specify | 2 +- README.zh.md | 60 +++++++++++++++++++++++++++++----------------------- specs | 2 +- 3 files changed, 35 insertions(+), 29 deletions(-) diff --git a/.specify b/.specify index c1c9bf8..a6a9c72 160000 --- a/.specify +++ b/.specify @@ -1 +1 @@ -Subproject commit c1c9bf8ceb2ceb2d52f6ea27f0e50d2b9eb25eee +Subproject commit a6a9c72ace61158fd58635efbc04162a24b92f67 diff --git a/README.zh.md b/README.zh.md index b8e2307..891fb76 100644 --- a/README.zh.md +++ b/README.zh.md @@ -59,11 +59,13 @@ Omen **不预测**单一未来，它是**为复杂性而生**的推演引擎。 希望快速体验 Omen 而勿须本地安装，请访问我们部署在 Streamlit Cloud 的演示应用。点击下面的链接，直接探索战略推演流程： -👉 [在线体验 Omen](https://omen-demo.streamlit.app) +👉 [开源版本 omen-demo.streamlit.app](https://omen-demo.streamlit.app) + +👉 [商业版本 omen-pro.streamlit.app](https://omen-pro.streamlit.app) --- -## 🚀 快速上手 +## 🚀 快速开始 如果你是： @@ -85,7 +87,7 @@ pip install --upgrade pip setuptools wheel pip install -e . ``` -### 🌰 看例子 +### 🌰 演示 如果你希望快速查看 Omen 的运行效果，`demo` 目录中提供了可视化案例及其结果。运行： @@ -95,17 +97,29 @@ streamlit run demo/app/scenario_planning.py 在浏览器中打开 `http://localhost:8501`，即可查看完整的战略推演流程。 -### 🎵 跑流程 +**战略推演全流程视图** + +![全流程视图](docs/assets/images/streamlit-strategic-reason-flow.png) + +#### 更多细节 + +你可以点击页面上各个面板，查看从源文档到情势工件、情景工件、推演结果，再到解释工件的完整链路产出。 + +![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png) + +--- + +## 🎵 开始运行 如果你希望亲自跑一遍完整的**分析——模拟——解释**流程，请使用我们准备的内置案例，用于模拟 2026 年 3 月 SAP 收购 Reltio 的情境。 案例文档位于 `cases/situations/sap_reltio_acquisition.md`，可以通过以下步骤端到端运行。 -#### 第一步：分析 +### 第一步：分析 Omen 分析模块融合战略方法与数据工程管道，你仅需一行命令，即可从源文档中自动生成战略洞察与机器可消费的工件。 -##### 情势分析 +#### 情势分析 ```bash # 分析内置案例，并打包为 "sap" 别名 omen analyze situation --doc sap_reltio_acquisition --pack-id sap @@ -113,7 +127,7 @@ omen analyze situation --doc sap_reltio_acquisition --pack-id sap 此步骤会生成情势工件（Situation Artifact），并创建别名为 `sap` 的包，供后续步骤一致使用。 -##### 情景规划 +#### 情景规划 Omen 当前版本提供了确定性的 A/B/C 情景规划能力： @@ -129,7 +143,7 @@ omen scenario --situation sap 此步骤会在 `data/scenarios/sap/` 下生成用于模拟的情景包工件（Scenario Pack Artifact）。 -#### 第二步：模拟 +### 第二步：模拟 Omen 提供的模拟引擎可针对不同的情景进行推演。下面使用上一步生成的情景包工件，运行模拟： @@ -139,7 +153,7 @@ omen simulate --scenario data/scenarios/sap/scenario_pack.json 此步骤将生成推演轨迹以及结果文件 `output/sap/result.json`。 -#### 第三步：解释 +### 第三步：解释 Omen 解释模块会对模拟结果进行解读，并回溯情势工件中的关键决策点、风险项（已知的未知），生成面向决策者的洞察与建议： @@ -151,40 +165,32 @@ omen explain --pack-id sap ### 启动 UI 应用 -Omen 还提供了一个基于 Streamlit 的 UI 应用，用于可视化完整的战略推演流程。 +Omen 提供了基于 Streamlit 的应用，用于可视化完整的战略推演流程。 ```bash streamlit run app/scenario_planning.py ``` -**战略推演全流程视图** -![全流程视图](docs/assets/images/streamlit-strategic-reason-flow.png) - -#### 更多细节 - -你可以点击页面上各个面板，查看从源文档到情势工件、情景工件、推演结果，再到解释工件的完整链路产出。 - -![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png) - -## 👥 适用人群 - -Omen 专为以下角色打造： -* 技术战略团队 -* 产品与平台负责人 -* AI 基础设施研究者 -* 开源生态观察者 -* 投资与行业分析师 +然后在浏览器中打开 `http://localhost:8501`，即可探索结果。 ## 🎬 案例展示 ### 战略主体分析 +我们内置了五位战略主体的样本： + * 👤 [Elon Musk](cases/actors/elon-musk.md) * 👤 [Jeff Bezos](cases/actors/jeff-bezos.md) * 👤 [Steve Jobs](cases/actors/steve-jobs.md) * 👤 [Jack Ma](cases/actors/jack-ma.md) * 👤 [Chen Jiaxing (me)](cases/actors/chen-jiaxing.md) +运行以下命令，构建战略主体并洞察其画像、行为模式及影响关系图谱： + +```bash +streamlit run app/strategic_actor.py +``` + ### 战略推演案例 * 🧩 [SAP 收购 Reltio：主数据迷雾](cases/situations/sap_reltio_acquisition.md) diff --git a/specs b/specs index b549c9d..0716f57 160000 --- a/specs +++ b/specs @@ -1 +1 @@ -Subproject commit b549c9d11d40eea9176f4498d3546090c7a34592 +Subproject commit 0716f5741e09f72244e0e40cce96d24a2a624596 From 56d2a768905b3f32cf5760db768e8abdc1731578 Mon Sep 17 00:00:00 2001 From: --global <--global> Date: Thu, 30 Apr 2026 13:13:45 +0800 Subject: [PATCH 2/3] add pro demo --- README.md | 59 ++++++++++++++++++++++++++++++------------------------- 1 file changed, 32 insertions(+), 27 deletions(-) diff --git a/README.md b/README.md index b4f09d9..8d00135 100644 --- a/README.md +++ b/README.md @@ -61,11 +61,13 @@ You can explore the strategic reasoning flow directly online: 👉 [Explore Omen on Streamlit Cloud](https://omen-demo.streamlit.app/) +👉 [Explore Omen Pro on Streamlit Cloud](https://omen-pro.streamlit.app/) + --- ## 🚀 Quick Start -If you are: +If you are a: - Data Scientist - AI Researcher @@ -85,7 +87,7 @@ pip install --upgrade pip setuptools wheel pip install -e . ``` -### 🌰 View Demo +### 🌰 Run Demo If you want to quickly see Omen in action, a visualized sample case and its results are available in the `demo` directory. Run: @@ -95,17 +97,29 @@ streamlit run demo/app/scenario_planning.py Then open `http://localhost:8501` in your browser to explore the full strategic reasoning flow. -### 🎵 Run Built-in Case +#### End-to-End Flow + +![End-to-End Flow](docs/assets/images/streamlit-strategic-reason-flow.png) + +#### More details + +You can click on each panel on the page to inspect the full chain of outputs from source document to situation artifact, scenario artifact, simulation result, and explanation artifact. + +![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png) + +--- + +## 🎵 Run Built-in Case If you want to run a complete **Analyze - Simulate - Explain** workflow, we have prepared a built-in case simulating SAP's acquisition of Reltio in March 2026. The case document is `cases/situations/sap_reltio_acquisition.md`, and it can be run end-to-end with the following commands: -#### Step 1. Analyze +### Step 1. Analyze Omen's Analyze module combines strategy methodology and the data pipeline, allowing you to generate strategic insights and machine input artifacts from the source document with a single command. -##### Situation Analysis +#### Situation Analysis ```bash # analyze the built-in case and pack it as "sap" alias @@ -114,7 +128,7 @@ omen analyze situation --doc sap_reltio_acquisition --pack-id sap This step generates the Situation Artifact and creates a package named `sap` for consistent use in subsequent steps. -##### Scenario Planning +#### Scenario Planning Omen `v0.1.9` provides deterministic A/B/C scenario planning capabilities. @@ -130,7 +144,7 @@ omen scenario --situation sap This step generates the scenario pack artifact under `data/scenarios/sap/` for simulation. -#### Step 2. Simulate +### Step 2. Simulate Omen's simulation engine can reason across different scenarios. Use the scenario pack generated in the previous step to run simulation: @@ -140,7 +154,7 @@ omen simulate --scenario data/scenarios/sap/scenario_pack.json This step generates reasoning traces and writes the deterministic result to `output/sap/result.json`. -#### Step 3. Explain +### Step 3. Explain Omen's explanation module interprets simulation outcomes and traces back key decision points and risk items (known unknowns) from the situation artifact to generate decision-ready insights and recommendations: @@ -152,41 +166,32 @@ This step generates a structured explanation artifact at `output/sap/explanation ### Launch UI -Omen also provides a Streamlit-based UI application for visualizing the full strategic reasoning flow. +The Streamlit application for visualizing the full strategic reasoning flow. ```bash streamlit run app/scenario_planning.py ``` -#### End-to-End Flow - -![End-to-End Flow](docs/assets/images/streamlit-strategic-reason-flow.png) - -#### More details - -You can click on each panel on the page to inspect the full chain of outputs from source document to situation artifact, scenario artifact, simulation result, and explanation artifact. - -![Scenario Planning](docs/assets/images/streamlit-scenario-planning.png) - -## 👥 Target Audience - -Omen is built for the following roles: -* Technology Strategy Teams -* Product & Platform Leads -* AI Infrastructure Researchers -* Open Source Ecosystem Observers -* Investors & Industry Analysts +Then open `http://localhost:8501` in your browser to explore the results. ## 🎬 Showcase ### Strategic Actor Analyze +We have built-in samples of five strategic actors: + * 👤 [Elon Musk](cases/actors/elon-musk.md) * 👤 [Jeff Bezos](cases/actors/jeff-bezos.md) * 👤 [Steve Jobs](cases/actors/steve-jobs.md) * 👤 [Jack Ma](cases/actors/jack-ma.md) * 👤 [Chen Jiaxing (me)](cases/actors/chen-jiaxing.md) +Run the following command to build strategic actors and gain insights into their profiles, behavior patterns, and influence relationship graphs: + +```bash +streamlit run app/strategic_actor.py +``` + ### Strategic Reasoning Cases * 🧩 [Acquisition: SAP vs Reltio](cases/situations/sap_reltio_acquisition.md) From 67d1c9cafe9147366168198bb1166bbd0c52d304 Mon Sep 17 00:00:00 2001 From: --global <--global> Date: Thu, 30 Apr 2026 13:18:44 +0800 Subject: [PATCH 3/3] grammatical clarity --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 8d00135..fb02d9e 100644 --- a/README.md +++ b/README.md @@ -166,7 +166,7 @@ This step generates a structured explanation artifact at `output/sap/explanation ### Launch UI -The Streamlit application for visualizing the full strategic reasoning flow. +Run the Streamlit application for visualizing the full strategic reasoning flow. ```bash streamlit run app/scenario_planning.py