UPGRADE 16-12
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README.md
230
README.md
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* *Spring Boot Version:* `3.2.5` (defined in the parent POM)
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* *Spring Cloud GCP Version:* `5.3.0` (managed via `spring-cloud-gcp-dependencies`)
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* *Spring Cloud Version:* `2023.0.0` (managed via `spring-cloud-dependencies`)
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This project is a **Spring Boot Service Orchestrator** running on **Java 21**.
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Here is step-by-step guide to getting this deployed locally in your IDE.
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-----
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### Step 1: Ensure Prerequisites
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Before we touch the code, we need to make sure your local machine matches the project requirements found in the `pom.xml` and `Dockerfile`.
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1. **Install Java 21 JDK:** The project explicitly requires Java 21.
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* *Check:* Run `java -version` in your terminal. If it doesn't say "21", you need to install it.
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2. **Install Maven:** This is used to build the project dependencies.
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3. **Install the "Extension Pack for Java" in VS Code:** This includes tools for Maven, debugging, and IntelliSense.
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4. **Install Docker (Desktop or Engine):** We will need this to run a local Redis instance.
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-----
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### Step 2: The "Redis Gotcha" (Local Infrastructure)
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If you look at `src/main/resources/application-dev.properties`, you will see this line:
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`spring.data.redis.host=localhost`.
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1. **Start Redis in Docker:**
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Open your terminal and run:
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```bash
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docker run --name local-redis -p 6379:6379 -d redis
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```
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2. **Verify it's running:**
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Run `docker ps`. You should see redis running on port `6379`.
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-----
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### Step 3: Google Cloud Authentication
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This application connects to **Firestore**, **Dialogflow CX**, and **Vertex AI (Gemini)**. It uses the "Application Default Credentials" strategy.
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1. **Install the Google Cloud CLI (`gcloud`)** if you haven't already.
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2. **Login:**
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In your terminal, run:
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```bash
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gcloud auth application-default login
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```
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*This will open a browser window. Log in with your Google account that has access to the `app-jovenes` project.*
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-----
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### Step 4: Configure Local Properties
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We need to tell the application to look at your *local* Redis instead of the cloud one.
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1. Open `src/main/resources/application.properties`.
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2. Ensure the active profile is set to `dev`:
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```properties
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spring.profiles.active=dev
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```
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-----
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### Step 5: Build the Project
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Now let's download all the dependencies defined in the `pom.xml`.
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1. Open the Command Palette (Ctrl+Shift+P or Cmd+Shift+P).
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2. Type **"Maven: Execute Commands"** -\> select the project -\> **"install"**.
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* *Alternative:* Open the built-in terminal and run:
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```bash
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mvn clean install -DskipTests
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```
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* *Why skip tests?* The tests might try to connect to real cloud services or check specific configs that might fail on the first local run. Let's just get it compiling first.
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-----
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### Step 6: Run the Application
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1. Navigate to `src/main/java/com/example/Orchestrator.java`.
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2. You should see a small "Run | Debug" button appear just above the `public static void main` line.
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3. Click **Run**.
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**What to watch for in the Console:**
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* You want to see the Spring Boot logo.
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* Look for `Started Orchestrator in X seconds`.
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* Look for `Netty started on port 8080` (since this is a WebFlux app).
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-----
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### Step 7: Verify it's working
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Since this is an API, let's test the health or a simple endpoint.
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1. The app runs on port **8080** (defined in Dockerfile).
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2. The API has Swagger documentation configured.
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3. Open your browser and go to:
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`http://localhost:8080/webjars/swagger-ui/index.html` .
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* *Note:* If Swagger isn't loading, check the console logs for the exact context path.
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### Summary Checklist for you:
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* [ ] Java 21 Installed?
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* [ ] Docker running Redis on localhost:6379?
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* [ ] `gcloud auth application-default login` run?
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* [ ] `application-dev.properties` updated to use `localhost` for Redis?
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### Examples of endpoint call
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### 1\. The Standard Conversation (Dialogflow)
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This is the most common flow. It simulates a user sending a message like "Hola" to the bot. The orchestrator will route this to Dialogflow CX.
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**Request:**
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```bash
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curl -X POST http://localhost:8080/api/v1/dialogflow/detect-intent \
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-H "Content-Type: application/json" \
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-d '{
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"mensaje": "Hola, ¿quien eres?",
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"usuario": {
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"telefono": "5550001234",
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"nickname": "DiegoLocal"
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},
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"canal": "whatsapp",
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"tipo": "INICIO"
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}'
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```
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**What to expect:**
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* **Status:** `200 OK`
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* **Response:** A JSON object containing `responseText` (the answer from Dialogflow) and `responseId`.
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* **Logs:** Check your VS Code terminal. You should see logs like `Initiating detectIntent for session...`.
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-----
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### 2\. The "Smart" Notification Flow (Gemini Router)
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This is the cool part. We will first "push" a notification to the user, and then simulate the user asking a question about it.
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**Step A: Push the Notification**
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This tells the system: *"Hey, user 5550001234 just received this alert."*
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```bash
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curl -X POST http://localhost:8080/api/v1/dialogflow/notification \
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-H "Content-Type: application/json" \
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-d '{
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"texto": "Tu tarjeta *1234 ha sido bloqueada por seguridad.",
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"telefono": "5550001234",
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"parametrosOcultos": {
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"motivo": "intento_fraude_detectado",
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"ubicacion": "CDMX",
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"fecha": "Hoy"
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}
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}'
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```
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* **Check Logs:** You should see `Notification for phone 5550001234 cached`.
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**Step B: User asks a follow-up (The Test)**
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Now, ask a question that requires context from that notification.
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```bash
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curl -X POST http://localhost:8080/api/v1/dialogflow/detect-intent \
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-H "Content-Type: application/json" \
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-d '{
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"mensaje": "¿Por qué fue bloqueada?",
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"usuario": {
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"telefono": "5550001234"
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},
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"canal": "whatsapp",
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"tipo": "CONVERSACION"
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}'
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```
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* **What happens internally:** The `MessageEntryFilter` (Gemini) will see the previous notification in the history and classify this as a `NOTIFICATION` follow-up, routing it to the LLM instead of standard Dialogflow.
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-----
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### 3\. Quick Replies (Static Content)
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This tests the `QuickRepliesManagerService`. It fetches a JSON screen definition from your local files (e.g., `home.json`).
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**Request:**
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```bash
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curl -X POST http://localhost:8080/api/v1/quick-replies/screen \
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-H "Content-Type: application/json" \
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-d '{
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"usuario": {
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"telefono": "5550001234"
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},
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"canal": "app",
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"tipo": "INICIO",
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"pantallaContexto": "pagos"
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}'
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```
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**What to expect:**
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* **Response:** A JSON object with a `quick_replies` field containing the title "Home" (loaded from `home.json`).
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-----
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### 4\. Reset Everything (Purge)
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If you want to start fresh (clear the cache and history for "Local"), run this:
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```bash
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curl -X DELETE http://localhost:8080/api/v1/data-purge/all
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```
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* **Logs:** You'll see `Starting Redis data purge` and `Starting Firestore data purge`.
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### 5\. Optional testing the llm response with uuid
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```bash
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/api/v1/llm/tune-response
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{
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"sessionInfo": {
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"parameters": {
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"uuid": "21270589-184e-4a1a-922d-fb48464211e8"
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}
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}
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}
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```
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