feat: Python Self-Healing Supply Chain Demo (Interactive + Gemini 3)

pr_description.md

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+# feat: Python Self-Healing Supply Chain Demo (Interactive + Gemini 3)
+
+## 📝 Summary
+This PR adds a comprehensive Python sample demonstrating an **Autonomous Supply Chain Agent** capable of "Self-Healing" when a primary supplier fails. It leverages the **Google Agent Development Kit (ADK)** and the latest **Gemini 3 Flash** model to orchestrate a recovery workflow using **UCP** (Commerce) and **AP2** (Governance) protocols.
+
+## ✨ Key Features
+*   **Interactive Simulation**: Includes a CLI-based `InventoryManager` where users simulate sales. The Autonomous Restock triggers automatically when inventory drops below a critical threshold.
+*   **Dynamic Discovery (UCP)**: The agent dynamically resolves backup suppliers via `/.well-known/ucp` instead of hardcoded endpoints, demonstrating true network autonomy.
+*   **Negotiation Capability (UCP)**: Handles multi-step checkout flows, including providing Shipping Address and Discount Codes (`PARTNER_20`) to finalize Tax and Totals.
+*   **Governance & Trust (AP2)**:
+    *   Implements **Detached JWS** signatures for verifiable user intent.
+    *   Enforces a **Variance-Based Spending Policy** (15% threshold).
+    *   **Human-in-the-Loop**: High-variance transactions pause for manual admin sign-off.
+*   **Modern Stack**: Built with `google-genai` (Gemini 3 Flash Preview) and standard `pydantic` models for UCP/AP2 schemas.
+
+## 🏗️ Architecture
+*   **`buyer_agent.py`**: The ADK Agent utilizing a "Brain + Tools" pattern.
+*   **`supplier_server.py`**: A lightweight Mock UCP Server (FastAPI) that handles Discovery, Checkout Negotiation, and Mandate Verification.
+*   **`mock_db.py`**: Simulates a Product Catalog and Corporate Spending Policy.
+
+## 🧪 How to Test
+1.  **Start the Supplier Server**:
+    ```bash
+    python supplier_server.py
+    ```
+2.  **Run the Buyer Agent**:
+    ```bash
+    python buyer_agent.py
+    ```
+3.  **Interactive Loop**:
+    *   Enter sales (e.g., `90` units) to drop inventory below 20.
+    *   Observe the Agent detect the Primary Supplier failure (503).
+    *   Watch the Agent discover the Backup Supplier and request approval for the price variance.
+    *   Approve the purchase to see the Inventory restock.
+
+## ✅ Checklist
+- [x] Code adheres to UCP & AP2 Architectural Best Practices.
+- [x] Includes detailed `README.md` with production architecture diagrams.
+- [x] Secrets managed via `.env.local` (excluded from git).
+- [x] Dependencies listed in `requirements.txt`.

python/self-healing-supply-chain/.gitignore

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+# Python
+__pycache__/
+*.py[cod]
+*$py.class
+
+# Virtual Environment
+.venv/
+venv/
+env/
+
+# Environment Variables (Secrets)
+.env
+.env.local
+
+# IDE
+.vscode/
+.idea/
+
+# OS
+.DS_Store
+
+demo_audit.log
+ucp_samples_fork/

python/self-healing-supply-chain/README.md

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+# Self-Healing Supply Chain Demo (UCP & AP2)
+
+This project demonstrates an **Autonomous Supply Chain Agent** capable of "Self-Healing" when a primary supplier fails. It leverages two key next-generation protocols:
+
+*   **Google ADK (Agent Development Kit)**: For orchestrating the autonomous agent, managing state, and integrating with Gemini 3 Flash.
+*   **UCP (Universal Commerce Protocol)**: For dynamic supplier discovery, checking inventory, and negotiating standardized checkout sessions.
+*   **AP2 (Agent Payments Protocol)**: For secure, policy-driven transaction governance and "Agentic Payments".
+
+## 🚀 Scenario
+
+1.  **Start State**: The demo begins in an **Interactive Mode** with 100 units of inventory. You simulate sales manually.
+2.  **Trigger**: When inventory drops below the critical threshold (20 units), the **Autonomous Agent** wakes up to restock.
+3.  **Discovery (UCP)**: The Agent detects the primary supplier is down (503) and dynamically discovers "Supplier B" via `/.well-known/ucp`.
+4.  **Negotiation (UCP)**:
+    *   **Initial Intent**: Agent requests 100 units.
+    *   **Counter-Offer**: Server returns "Incomplete" status (needs Address).
+    *   **Refinement**: Agent provides Shipping Address + Discount Code (`PARTNER_20`).
+    *   **Final Offer**: Server calculates Tax + Shipping - Discount and returns a **Binding Total**.
+5.  **Governance (AP2)**: The Agent compares the *Final* price against the standard.
+    *   **Variance**: High variance detected (>15%).
+    *   **Policy Check**: The Corporate Spending Policy (`mock_db.py`) pauses for **Human Sign-off**.
+6.  **Execution**: Once approved, the Agent signs a verifiable **AP2 Payment Mandate** for the *exact* final amount and completes the order.
+
+## 🛠️ Setup & Installation
+
+### Prerequisites
+*   Python 3.12+
+*   Google GenAI API Key
+
+### 1. Environment Configuration
+Create a `.env.local` file in the root directory:
+```bash
+GOOGLE_API_KEY=your_api_key_here
+```
+
+### 2. Install Dependencies
+```bash
+pip install fastapi uvicorn requests python-dotenv
+# Note: google-adk, ucp-sdk, ap2-sdk are currently mocked or included in this demo structure.
+```
+
+## 🏃‍♂️ How to Run
+
+You will need **two separate terminal windows**.
+
+### Terminal 1: The Backup Supplier (Server)
+Start the mock supplier server. This represents "Supplier B".
+```bash
+python supplier_server.py
+```
+*Output: `🏭 [SUPPLIER] Server Online at http://0.0.0.0:8000`*
+
+### Terminal 2: The Buyer Agent (Client)
+Run the agent.
+```bash
+python buyer_agent.py
+```
+
+*   **Interactive Loop**: The agent will display current inventory (e.g., `100`).
+
+#### Scenario A: Normal Operation (Safe Zone)
+If Inventory is **> 20 units**:
+1.  Enter a number (e.g., `50`) to simulate sales.
+2.  The Agent will simply update the inventory count.
+3.  *Result:* "Inventory updated to 50." (No autonomous action taken).
+
+#### Scenario B: The Crisis (Critical Zone)
+If Inventory drops **<= 20 units** (e.g., enter `85` when you have 100):
+1.  **Autonomous Trigger**: The "Self-Healing" protocol activates immediately.
+2.  **Visual Feedback**: You will see the Agent:
+    *   Detect Primary Supplier Failure.
+    *   Discover Backup Supplier (Port 8000).
+    *   **Negotiate Price**: Adding Shipping/Tax and applying Discounts.
+3.  **Governance Check**: The Agent detects the price variance is too high.
+4.  **Your Input**: You will be prompted to Approve/Deny the transaction.
+    *   *Input:* Press `Enter` to Approve.
+5.  **Success**: The Agent signs the AP2 Mandate, restocks inventory, and the loop continues.
+
+## 🧠 Agent Architecture (Google ADK)
+
+The Buyer Agent is built using the **Google Agent Development Kit (ADK)**, utilizing a modular "Brain + Tools" pattern:
+
+*   **Model**: Uses `gemini-3-flash-preview` for high-speed reasoning and decision making.
+*   **Tools**: Encapsulates specific capabilities as Python functions (`discover_backup_suppliers`, `execute_ucp_transaction`).
+*   **Runner**: The ADK `Runner` handles the event loop, routing user inputs (sales data) or system triggers (low inventory) to the model, which then decides which Tool to call.
+*   **State**: Uses `InMemorySessionService` to maintain context across the multi-step recovery flow.
+
+## � Best Practices Alignment
+
+This demo adheres to the official **Google Developers UCP & AP2 Architecture**:
+
+1.  **Dynamic Discovery**: Endpoints are never hardcoded. The Agent resolves capabilities dynamically via `/.well-known/ucp`.
+2.  **Service-Based Architecture**: Separation of concerns between UCP (Commerce) and AP2 (Trust).
+3.  **Verifiable Intent**: Utilizes cryptographic **AP2 Mandates** (Detached JWS) to anchor every transaction to a signed user intent.
+4.  **Standardized Schemas**: Uses official `ucp-sdk` Pydantic models generated from the canonical JSON Schemas.
+
+## �🏭 Production Architecture
+
+In a real-world enterprise environment, this architecture scales from local scripts to distributed cloud services.
+
+```mermaid
+graph TD
+    subgraph Buyer_Enterprise ["Enterprise Environment (Buyer)"]
+        Agent["Supply Chain Agent (Cloud Run)"]
+        Orch["Orchestrator (Temporal)"]
+        PolicyDB["Policy Engine (OPA)"]
+
+        subgraph Human ["Human-in-the-Loop"]
+            Approver(("Supply Chain Manager"))
+            Dashboard["Operations Dashboard"]
+        end
+    end
+
+    subgraph External ["External Ecosystem"]
+        Registry["UCP Registry"]
+        SupplierA["Supplier A (Primary - DOWN)"]
+        SupplierB["Supplier B (Backup - FOUND)"]
+    end
+
+    Agent -->|1. Monitor| SupplierA
+    Agent -->|2. Discover| Registry
+    Registry -->|3. Resolve| SupplierB
+    Agent -->|4. Negotiate| SupplierB
+
+    Agent -->|5. Policy Check| PolicyDB
+    PolicyDB -- Fail --> Orch
+    Orch -->|6. Request Approval| Dashboard
+    Approver -->|7. Approve| Dashboard
+    Dashboard -->|8. Sign Mandate| Agent
+
+    Agent -->|9. Execute Payment| SupplierB
+```
+
+### Key Differences in Production
+1.  **Decentralized Discovery**: Instead of a hardcoded `mock_db.py`, the Agent queries a **UCP Registry** or DID Resolver to find verified suppliers dynamically.
+2.  **Cryptographic Trust**: AP2 Mandates are signed with real enterprise Keys (KMS/Vault), providing non-repudiable proof of intent.
+3.  **Governance Dashboard**: The `input()` prompt is replaced by a secure **Operations Dashboard** or Slack/Mobile push notification for one-click approval.