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Example for Coherence LC4J Provider as well as Metrics Usage (#181)
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‎examples/integrations/langchain4j/coffee-shop-assistant-mp/README.md‎

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@@ -64,3 +64,31 @@ Here are some example queries you can try:
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- **"Can I order a coffee and a cookie?"**
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- *Expected Response:*
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*"Your order for a coffee and a chocolate chip cookie has been saved. The total is $5.00. Would you like anything else?"*
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## Try metrics
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Helidon provides `MetricsChatModelListener` which generates metrics that follow the [OpenTelemetry Semantic Conventions for GenAI Metrics v1.36.0](https://github.com/open-telemetry/semantic-conventions/blob/v1.36.0/docs/gen-ai/gen-ai-metrics.md). This is done out-of-box for Chat API calls. To view the captured metrics use following:
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```shell
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# Prometheus Format
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curl -s -X GET http://localhost:8080/metrics
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...
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# HELP gen_ai_client_token_usage_token Measures number of input and output tokens used
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# TYPE gen_ai_client_token_usage_token histogram
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gen_ai_client_token_usage_token{gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",gen_ai_token_type="output",scope="vendor",quantile="0.5",} 71.0
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...
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gen_ai_client_token_usage_token{gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",gen_ai_token_type="input",scope="vendor",quantile="0.5",} 156.0
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...
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# HELP gen_ai_client_token_usage_token_max Measures number of input and output tokens used
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# TYPE gen_ai_client_token_usage_token_max gauge
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gen_ai_client_token_usage_token_max{gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",gen_ai_token_type="output",scope="vendor",} 71.0
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gen_ai_client_token_usage_token_max{gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",gen_ai_token_type="input",scope="vendor",} 156.0
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....
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# HELP gen_ai_client_operation_duration_seconds_max GenAI operation duration
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# TYPE gen_ai_client_operation_duration_seconds_max gauge
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gen_ai_client_operation_duration_seconds_max{error_type="",gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",scope="vendor",} 2.0
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# HELP gen_ai_client_operation_duration_seconds GenAI operation duration
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# TYPE gen_ai_client_operation_duration_seconds histogram
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gen_ai_client_operation_duration_seconds{error_type="",gen_ai_operation_name="chat",gen_ai_request_model="gpt-4o-mini",gen_ai_response_model="gpt-4o-mini-2024-07-18",scope="vendor",quantile="0.5",} 2.0
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...
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```

‎examples/integrations/langchain4j/coffee-shop-assistant-mp/pom.xml‎

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<mainClass>io.helidon.Main</mainClass>
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</properties>
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<dependencyManagement>
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<dependencies>
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<dependency>
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<groupId>dev.langchain4j</groupId>
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<artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
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<version>${version.lib.langchain4j}</version>
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</dependency>
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</dependencies>
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</dependencyManagement>
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<dependencies>
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<dependency>
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<groupId>io.helidon.integrations.langchain4j</groupId>

‎examples/integrations/langchain4j/coffee-shop-assistant-mp/src/main/resources/META-INF/microprofile-config.properties‎

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langchain4j.rag.embedding-store-content-retriever.enabled=true
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langchain4j.rag.embedding-store-content-retriever.max-results=10
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langchain4j.rag.embedding-store-content-retriever.min-score=0.6
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langchain4j.rag.embedding-store-content-retriever.embedding-store=EmbeddingStore
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langchain4j.rag.embedding-store-content-retriever.embedding-store.service-registry.named=EmbeddingStore
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app.menu-items=data/menu.json

‎examples/integrations/langchain4j/coffee-shop-assistant-se-coherence/README.md‎

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# **Coffee Shop Assistant (Helidon SE Version)**
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This is a **demo application** showcasing the **Helidon SE integration with LangChain4J**. It demonstrates how to build an **AI-powered coffee shop assistant** using **Helidon Inject**, Ollama models, and Coherence LangChain4J integrations.
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NOTE: LangChain4J integration is a preview feature. The APIs shown here are subject to change. These APIs will be finalized in a future release of Helidon.
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## **Features**
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- Integration with **OpenAI chat models**.
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- Utilization of **embedding models**, **embedding store**, **ingestor**, and **content retriever**.
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- **Helidon Inject** for dependency injection.
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- **Embedding store initialization** from a JSON file.
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- Integration with **Coherence Embedding Store**
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- Support for **callback functions** to enhance interactions.
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## **Build the Application**
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To build the application, run:
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```shell
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mvn clean package
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```
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## **Run the Application**
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Execute the following command to start the application:
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```shell
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java -Dcoherence.wka=127.0.0.1 -jar target/helidon-examples-integrations-langchain4j-coffee-shop-assistant-se-coherence.jar
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```
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Once running, you can interact with the assistant via your browser.
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Example:
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```
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http://localhost:8080/chat?question="What can you offer today?"
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```
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## Sample Questions and Expected Responses
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Here are some example queries you can try:
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### Menu and Recommendations
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- **"What hot drinks do you have?"**
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- *Expected Response:* A list of **hot drinks** such as **Latte, Cappuccino, Espresso, and Hot Chocolate**.
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- **"I'm looking for something sweet. What do you recommend?"**
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- *Expected Response:* Suggestions like **Caramel Frappuccino, Blueberry Muffin, Chocolate Chip Cookie, and Hot Chocolate**.
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- **"What drinks can I get with caramel?"**
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- *Expected Response:* Options like **Caramel Frappuccino** and **Latte with caramel syrup add-on**.
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### Dietary Preferences
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- **"Do you have any vegan options?"**
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- *Expected Response:* Items like **Avocado Toast, Iced Matcha Latte (with non-dairy milk), and Blueberry Muffin (if applicable)**.
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### Orders and Availability
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- **"Do you have any breakfast items?"**
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- *Expected Response:* Options such as **Avocado Toast, Blueberry Muffin, and Bagel with Cream Cheese**.
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- **"Can I order a coffee and a cookie?"**
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- *Expected Response:*
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*"Your order for a coffee and a chocolate chip cookie has been saved. The total is $5.00. Would you like anything else?"*

‎examples/integrations/langchain4j/coffee-shop-assistant-se-coherence/data/menu.json‎

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[
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{
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"name": "Latte",
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"description": "A rich espresso drink with steamed milk.",
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"category": "Drink",
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"price": 4.5,
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"tags": [
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"Hot",
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"Customizable",
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"Classic"
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],
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"addOns": [
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"Oat milk",
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"Soy milk",
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"Extra shot",
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"Caramel syrup"
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]
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},
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{
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"name": "Cappuccino",
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"description": "Espresso topped with a thick layer of frothy milk.",
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"category": "Drink",
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"price": 4.0,
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"tags": [
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"Hot",
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"Foamy",
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"Classic"
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],
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"addOns": [
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"Vanilla syrup",
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"Extra shot"
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]
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},
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{
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"name": "Espresso",
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"description": "A strong shot of coffee for a quick energy boost.",
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"category": "Drink",
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"price": 3.0,
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"tags": [
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"Hot",
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"Classic",
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"Bold"
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],
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"addOns": [
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"Extra shot"
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]
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},
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{
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"name": "Iced Matcha Latte",
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"description": "Chilled matcha green tea with milk.",
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"category": "Drink",
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"price": 5.0,
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"tags": [
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"Cold",
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"Vegan",
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"Trendy"
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],
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"addOns": [
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"Oat milk",
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"Almond milk",
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"Extra matcha"
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]
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},
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{
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"name": "Avocado Toast",
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"description": "Toasted bread topped with mashed avocado and seasonings.",
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"category": "Food",
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"price": 6.5,
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"tags": [
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"Healthy",
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"Vegan",
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"Breakfast"
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],
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"addOns": [
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"Egg",
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"Feta cheese",
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"Hot sauce"
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]
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},
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{
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"name": "Blueberry Muffin",
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"description": "A soft muffin bursting with blueberries.",
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"category": "Food",
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"price": 2.75,
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"tags": [
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"Breakfast",
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"Sweet",
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"Vegetarian"
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],
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"addOns": [
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"Warm up"
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]
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},
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{
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"name": "Bagel with Cream Cheese",
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"description": "A freshly baked bagel served with creamy cheese spread.",
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"category": "Food",
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"price": 3.5,
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"tags": [
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"Breakfast",
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"Savory",
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"Vegetarian"
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],
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"addOns": [
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"Butter",
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"Jam"
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]
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},
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{
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"name": "Caramel Frappuccino",
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"description": "A blended coffee drink with caramel drizzle and whipped cream.",
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"category": "Drink",
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"price": 5.5,
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"tags": [
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"Cold",
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"Sweet",
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"Indulgent"
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],
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"addOns": [
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"Extra caramel",
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"Whipped cream"
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]
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},
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{
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"name": "Chocolate Chip Cookie",
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"description": "A large, soft-baked cookie loaded with chocolate chips.",
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"category": "Food",
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"price": 2.0,
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"tags": [
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"Snack",
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"Sweet",
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"Vegetarian"
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],
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"addOns": [
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"Warm up"
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]
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},
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{
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"name": "Hot Chocolate",
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"description": "A creamy hot chocolate drink topped with whipped cream.",
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"category": "Drink",
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"price": 3.75,
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"tags": [
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"Hot",
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"Sweet",
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"Comforting"
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],
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"addOns": [
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"Extra whipped cream",
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"Caramel drizzle"
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]
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}
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]

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