diff --git a/docs/docs/apis-generate/chat-with-tools.md b/docs/docs/apis-generate/chat-with-tools.md
new file mode 100644
index 0000000..577c26e
--- /dev/null
+++ b/docs/docs/apis-generate/chat-with-tools.md
@@ -0,0 +1,69 @@
+---
+sidebar_position: 8
+---
+
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Chat with Tools
+
+### Using Tools in Chat
+
+If you want to have a natural back-and-forth chat experience with tools, you can directly integrate tools into
+the `chat()` method, instead of using the `generateWithTools()` method. This allows you to register tools that are
+automatically used during the conversation between the user and the assistant, creating a more conversational
+experience.
+
+When the model determines that a tool should be used, the tool is automatically executed. The result is then seamlessly
+incorporated back into the conversation, enhancing the interaction with real-world data and actions.
+
+The following example demonstrates usage of a simple tool, registered with the `OllamaAPI`, and then used within a chat
+session. The tool invocation and response handling are all managed internally by the API.
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithTools.java"/>
+
+::::tip[LLM Response]
+> First answer: 6527fb60-9663-4073-b59e-855526e0a0c2 is the ID of the employee named 'Rahul Kumar'.
+>
+> Second answer: Kumar is the last name of the employee named 'Rahul Kumar'.
+::::
+
+This tool calling can also be done using the streaming API.
+
+### Annotation-Based Tool Registration
+
+Ollama4j provides a declarative and convenient way to define and register tools using Java annotations and reflection.
+This approach offers an alternative to the more verbose, explicit tool registration method.
+
+To use a method as a tool within a chat call, follow these steps:
+
+* **Annotate the Tool Method:**
+ * Use the `@ToolSpec` annotation to mark a method as a tool. This annotation describes the tool's purpose.
+ * Use the `@ToolProperty` annotation to define the input parameters of the tool. The following data types are
+ currently supported:
+ * `java.lang.String`
+ * `java.lang.Integer`
+ * `java.lang.Boolean`
+ * `java.math.BigDecimal`
+* **Annotate the Ollama Service Class:**
+ * Annotate the class that interacts with the `OllamaAPI` client using the `@OllamaToolService` annotation. Reference
+ the provider class(es) containing the `@ToolSpec` annotated methods within this annotation.
+* **Register the Annotated Tools:**
+ * Before making a chat request with the `OllamaAPI`, call the `OllamaAPI.registerAnnotatedTools()` method. This
+ registers the annotated tools, making them available for use during the chat session.
+
+Let's try an example. Consider an `OllamaToolService` class that needs to ask the LLM a question that can only be answered by a specific tool.
+This tool is implemented within a `GlobalConstantGenerator` class. Following is the code that exposes an annotated method as a tool:
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/annotated/GlobalConstantGenerator.java"/>
+
+The annotated method can then be used as a tool in the chat session:
+
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/annotated/AnnotatedToolCallingExample.java"/>
+
+Running the above would produce a response similar to:
+
+::::tip[LLM Response]
+> First answer: 0.0000112061 is the most important constant in the world using 10 digits, according to my function. This constant is known as Planck's constant and plays a fundamental role in quantum mechanics. It relates energy and frequency in electromagnetic radiation and action (the product of momentum and distance) for particles.
+>
+> Second answer: 3-digit constant: 8.001
+::::
diff --git a/docs/docs/apis-generate/chat.md b/docs/docs/apis-generate/chat.md
index d5aabe9..d5a147c 100644
--- a/docs/docs/apis-generate/chat.md
+++ b/docs/docs/apis-generate/chat.md
@@ -9,262 +9,93 @@ import CodeEmbed from '@site/src/components/CodeEmbed';
This API lets you create a conversation with LLMs. Using this API enables you to ask questions to the model including
information using the history of already asked questions and the respective answers.
+### Create a new conversation and use chat history to augment follow up questions
-
-## Create a new conversation and use chat history to augment follow up questions
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
-
- // create first user question
- OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "What is the capital of France?")
- .build();
-
- // start conversation with model
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-
- System.out.println("First answer: " + chatResult.getResponseModel().getMessage().getContent());
-
- // create next userQuestion
- requestModel = builder.withMessages(chatResult.getChatHistory()).withMessage(OllamaChatMessageRole.USER, "And what is the second largest city?").build();
-
- // "continue" conversation with model
- chatResult = ollamaAPI.chat(requestModel);
-
- System.out.println("Second answer: " + chatResult.getResponseModel().getMessage().getContent());
-
- System.out.println("Chat History: " + chatResult.getChatHistory());
- }
-}
-
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatExample.java" />
You will get a response similar to:
-> First answer: Should be Paris!
+::::tip[LLM Response]
+
+> First answer: The capital of France is Paris.
>
-> Second answer: Marseille.
+> Second answer: The second-largest city in France is Marseille.
>
> Chat History:
```json
-[
- {
- "role": "user",
- "content": "What is the capital of France?",
- "images": []
- },
- {
- "role": "assistant",
- "content": "Should be Paris!",
- "images": []
- },
- {
- "role": "user",
- "content": "And what is the second largest city?",
- "images": []
- },
- {
- "role": "assistant",
- "content": "Marseille.",
- "images": []
- }
-]
+[{
+ "role" : "user",
+ "content" : "What is the capital of France?",
+ "images" : null,
+ "tool_calls" : [ ]
+}, {
+ "role" : "assistant",
+ "content" : "The capital of France is Paris.",
+ "images" : null,
+ "tool_calls" : null
+}, {
+ "role" : "user",
+ "content" : "And what is the second largest city?",
+ "images" : null,
+ "tool_calls" : [ ]
+}, {
+ "role" : "assistant",
+ "content" : "The second-largest city in France is Marseille.",
+ "images" : null,
+ "tool_calls" : null
+}]
```
+::::
-## Conversational loop
+### Create a conversation where the answer is streamed
-```java
-public class Main {
-
- public static void main(String[] args) {
-
- OllamaAPI ollamaAPI = new OllamaAPI();
- ollamaAPI.setRequestTimeoutSeconds(60);
-
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance("<your-model>");
-
- OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "<your-first-message>").build();
- OllamaChatResult initialChatResult = ollamaAPI.chat(requestModel);
- System.out.println(initialChatResult.getResponse());
-
- List<OllamaChatMessage> history = initialChatResult.getChatHistory();
-
- while (true) {
- OllamaChatResult chatResult = ollamaAPI.chat(builder.withMessages(history).withMessage(OllamaChatMessageRole.USER, "<your-new-message").build());
- System.out.println(chatResult.getResponse());
- history = chatResult.getChatHistory();
- }
- }
-}
-```
-
-## Create a conversation where the answer is streamed
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(config.getModel());
- OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER,
- "What is the capital of France? And what's France's connection with Mona Lisa?")
- .build();
-
- // define a handler (Consumer<String>)
- OllamaStreamHandler streamHandler = (s) -> {
- System.out.println(s);
- };
-
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel, streamHandler);
- }
-}
-```
-
-You will get a response similar to:
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatStreamingWithTokenConcatenationExample.java" />
+::::tip[LLM Response]
+>
> The
+>
> The capital
+>
> The capital of
+>
> The capital of France
+>
> The capital of France is
+>
> The capital of France is Paris
+>
> The capital of France is Paris.
+>
+::::
-## Use a simple Console Output Stream Handler
+### Using a simple Console Output Stream Handler
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.impl.ConsoleOutputStreamHandler;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.generate.OllamaStreamHandler;
-import io.github.ollama4j.types.OllamaModelType;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ConsoleOutputStreamHandlerExample.java" />
-public class Main {
- public static void main(String[] args) throws Exception {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
+### With a Stream Handler to receive the tokens as they are generated
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
- OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.USER, "List all cricket world cup teams of 2019. Name the teams!")
- .build();
- OllamaStreamHandler streamHandler = new ConsoleOutputStreamHandler();
- ollamaAPI.chat(requestModel, streamHandler);
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatStreamingExample.java" />
-## Create a new conversation with individual system prompt
+### Create a new conversation with custom system prompt
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithCustomSystemPrompt.java" />
+
+You will get a response as:
+
+::::tip[LLM Response]
+> Shhh!
+::::
-public class Main {
+## Create a conversation about an image (requires a vision model)
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAMA2);
-
- // create request with system-prompt (overriding the model defaults) and user question
- OllamaChatRequest requestModel = builder.withMessage(OllamaChatMessageRole.SYSTEM, "You are a silent bot that only says 'NI'. Do not say anything else under any circumstances!")
- .withMessage(OllamaChatMessageRole.USER, "What is the capital of France? And what's France's connection with Mona Lisa?")
- .build();
-
- // start conversation with model
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-
- System.out.println(chatResult.getResponseModel());
- }
-}
-
-```
-
-You will get a response similar to:
-
-> NI.
-
-## Create a conversation about an image (requires model with image recognition skills)
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.types.OllamaModelType;
-
-import java.io.File;
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance(OllamaModelType.LLAVA);
-
- // Load Image from File and attach to user message (alternatively images could also be added via URL)
- OllamaChatRequest requestModel =
- builder.withMessage(OllamaChatMessageRole.USER, "What's in the picture?",
- List.of(
- new File("/path/to/image"))).build();
-
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
- System.out.println("First answer: " + chatResult.getResponseModel());
-
- builder.reset();
-
- // Use history to ask further questions about the image or assistant answer
- requestModel =
- builder.withMessages(chatResult.getChatHistory())
- .withMessage(OllamaChatMessageRole.USER, "What's the dogs breed?").build();
-
- chatResult = ollamaAPI.chat(requestModel);
- System.out.println("Second answer: " + chatResult.getResponseModel());
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatWithImage.java" />
You will get a response similar to:
+::::tip[LLM Response]
> First Answer: The image shows a dog sitting on the bow of a boat that is docked in calm water. The boat has two
> levels, with the lower level containing seating and what appears to be an engine cover. The dog seems relaxed and
> comfortable on the boat, looking out over the water. The background suggests it might be late afternoon or early
@@ -274,5 +105,4 @@ You will get a response similar to:
> appears to be medium-sized with a short coat and a brown coloration, which might suggest that it is a Golden Retriever
> or a similar breed. Without more details like ear shape and tail length, it's not possible to identify the exact breed
> confidently.
-
-<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/ChatExample.java" />
\ No newline at end of file
+::::
diff --git a/docs/docs/apis-generate/custom-roles.md b/docs/docs/apis-generate/custom-roles.md
index c735827..44df8b1 100644
--- a/docs/docs/apis-generate/custom-roles.md
+++ b/docs/docs/apis-generate/custom-roles.md
@@ -1,5 +1,5 @@
---
-sidebar_position: 8
+sidebar_position: 9
---
# Custom Roles
diff --git a/docs/docs/apis-generate/generate-async.md b/docs/docs/apis-generate/generate-async.md
index 1b8b47c..1f2ca9e 100644
--- a/docs/docs/apis-generate/generate-async.md
+++ b/docs/docs/apis-generate/generate-async.md
@@ -2,7 +2,9 @@
sidebar_position: 2
---
-# Generate - Async
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate (Async)
This API lets you ask questions to the LLMs in a asynchronous way.
This is particularly helpful when you want to issue a generate request to the LLM and collect the response in the
@@ -11,38 +13,18 @@ background (such as threads) without blocking your code until the response arriv
This API corresponds to
the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) API.
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaAsyncResultStreamer;
-import io.github.ollama4j.types.OllamaModelType;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateAsync.java" />
-public class Main {
+::::tip[LLM Response]
+Here are the participating teams in the 2019 ICC Cricket World Cup:
- public static void main(String[] args) throws Exception {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- ollamaAPI.setRequestTimeoutSeconds(60);
- String prompt = "List all cricket world cup teams of 2019.";
- OllamaAsyncResultStreamer streamer = ollamaAPI.generateAsync(OllamaModelType.LLAMA3, prompt, false);
-
- // Set the poll interval according to your needs.
- // Smaller the poll interval, more frequently you receive the tokens.
- int pollIntervalMilliseconds = 1000;
-
- while (true) {
- String tokens = streamer.getStream().poll();
- System.out.print(tokens);
- if (!streamer.isAlive()) {
- break;
- }
- Thread.sleep(pollIntervalMilliseconds);
- }
-
- System.out.println("\n------------------------");
- System.out.println("Complete Response:");
- System.out.println("------------------------");
-
- System.out.println(streamer.getCompleteResponse());
- }
-}
-```
\ No newline at end of file
+1. Australia
+2. Bangladesh
+3. India
+4. New Zealand
+5. Pakistan
+6. England
+7. South Africa
+8. West Indies (as a team)
+9. Afghanistan
+::::
\ No newline at end of file
diff --git a/docs/docs/apis-generate/generate-embeddings.md b/docs/docs/apis-generate/generate-embeddings.md
index ae2aaa1..1adcde9 100644
--- a/docs/docs/apis-generate/generate-embeddings.md
+++ b/docs/docs/apis-generate/generate-embeddings.md
@@ -1,112 +1,49 @@
---
-sidebar_position: 6
+sidebar_position: 5
---
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
# Generate Embeddings
Generate embeddings from a model.
-Parameters:
+### Using `embed()`
-- `model`: name of model to generate embeddings from
-- `input`: text/s to generate embeddings for
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateEmbeddings.java" />
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.models.embeddings.OllamaEmbedRequestModel;
-import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;
-import java.util.Arrays;
-import java.util.Collections;
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
-
- OllamaEmbedResponseModel embeddings = ollamaAPI.embed("all-minilm", Arrays.asList("Why is the sky blue?", "Why is the grass green?"));
-
- System.out.println(embeddings);
- }
-}
+::::tip[LLM Response]
+```json
+[[0.010000081, -0.0017487297, 0.050126992, 0.04694895, 0.055186987, 0.008570699, 0.10545243, -0.02591801, 0.1296789, 0.031844463, -0.044533115, -0.009081162, -4.7557743E-4, -0.06383077, -0.016083026, 0.04666039, -0.022107942, -0.15835331, -0.07281923, -0.061205965, -0.06593526, 0.054214016, -0.062174935, 0.038974375, -0.04570855, 0.05495598, -0.035383187, 0.012725615, 0.04252694, -0.00806814, -0.019041134, 0.061063103, 0.036943648, 0.013529706, -0.025880618, -0.04349401, 0.07276639, -0.048439376, 0.004148429, -0.029453786, -0.029147545, -0.03282039, -0.018276647, 0.0155515345, -0.011599436, 0.015321048, -0.009423502, 0.02589781, 0.095306225, -0.015580891, -0.024553236, 0.009203469, -0.07652067, 0.01593109, 0.049590923, 0.11590031, 9.564879E-4, -0.020308463, 0.09234688, 0.008461708, -0.057039093, 0.06883451, -0.07657848, 0.06934012, 0.09227977, -0.055535857, -0.05371766, 0.008418901, -0.06311155, -0.066414595, -0.025158273, 0.018782357, 0.061182138, -0.028296644, 0.0362281, 0.001123205, 0.060663134, -0.06755974, -0.008144066, -0.012715194, 0.031090235, -0.06392361, -0.07458864, 0.11904344, 0.012541205, 0.06530589, 0.014893975, 0.051452246, -0.0850448, 0.010324387, -0.007704823, -0.035547107, -0.115298286, -0.030618181, -0.08327795, 0.013764867, 0.05644683, -0.040965002, 0.042660262, 0.022258658, 0.046835635, -0.051371332, 0.030119192, 0.007202741, -0.004240163, -0.031205537, 0.077798784, 0.034248676, 0.06132544, 0.0074892035, -0.036300045, -0.08461072, 0.021714637, -0.019322984, -0.0398159, 0.054820538, -0.033751138, 0.018145457, -0.105456986, -0.050408557, -0.011556143, 0.037754424, 0.022083722, 0.08057535, 0.007969883, -0.016802859, -0.059379302, -7.2237E-33, 0.1354213, -0.011238707, 0.092283085, 0.03602569, 0.039765336, -0.054793786, -0.03515187, -0.0036293974, -0.019418892, -0.034990944, -0.005830097, -0.014649367, -0.024272997, -0.048353665, 0.04776005, -0.017107947, -0.06098698, 0.0058933506, -0.08300741, 0.084322065, -0.104518674, 0.04162716, 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```
+::::
-Or, using the `OllamaEmbedRequestModel`:
+You could also use the `OllamaEmbedRequestModel` to specify the options such as `seed`, `temperature`, etc., to apply for generating embeddings.
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.models.embeddings.OllamaEmbedRequestModel;
-import io.github.ollama4j.models.embeddings.OllamaEmbedResponseModel;import java.util.Arrays;
-import java.util.Collections;
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
-
- OllamaEmbedResponseModel embeddings = ollamaAPI.embed(new OllamaEmbedRequestModel("all-minilm", Arrays.asList("Why is the sky blue?", "Why is the grass green?")));
-
- System.out.println(embeddings);
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateEmbeddingsWithRequestModel.java" />
You will get a response similar to:
+::::tip[LLM Response]
```json
-{
- "model": "all-minilm",
- "embeddings": [[-0.034674067, 0.030984823, 0.0067988685]],
- "total_duration": 14173700,
- "load_duration": 1198800,
- "prompt_eval_count": 2
-}
-````
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-0.086338826, -0.087730855, 0.0071089785, -0.0075092614, -0.016718967, 0.045219034, 0.067585975, -0.042870898, 0.0863409, 0.045438178, 0.06795051, 0.009950505, -0.0029959748, 0.058502916, -0.035608236, 0.036216073, 0.066100344, -0.03785426, -0.062264763, -0.04450461, 0.07720427, 0.043325383, -0.021296863, -0.0217195, 0.062334213, -0.0391459, 0.028083341, -0.013057875, 0.051180184, -0.036750164, 0.054655746, -0.066471115, 0.022967137, 0.0047796182, 0.09052008, 0.005167651, -0.0830967, -0.055065937, 0.07320647, -0.11054101, -0.020116722, 0.11247867, -0.053230446, -0.057548687, -0.023836475, 0.056587286, 0.12725416, 0.036107734, -0.043944683, 0.017000921, -0.024768567, 0.07276523, 0.043141358, 0.08048159, -0.019533968, -0.03447826, 0.096703045, 0.051834024, 0.010554283, 0.04019631, 0.0020927596, -0.007590705, 0.0016895492, 0.014211798, 0.02047324, -0.023020415, 0.021562004, -0.00928612, -0.050591297, -0.01619291, -0.08997802, -0.060895078, 0.08100429, 0.0022806204, 0.041729365, 0.043731183, -0.025113516, -0.09526692, 0.08865304, -0.09853454, -0.0048426827, 0.035341848, 0.0143458955, -0.064700805, -0.07586452, 0.012436738, -0.05000536, -0.05567604, -0.056878153, -0.018541014, -0.0021473207, -0.0022214772, 0.035333972, -0.05470233, -1.4311088E-8, -0.00807994, 0.026629517, 0.002253397, 0.009933685, -0.02166608, -0.021526324, 0.11142737, 0.0047573056, 0.03775078, 0.0039694835, -0.066885866, -0.028193833, -0.044485897, 0.071223155, 0.018815499, -0.049034107, -0.10390887, -0.043636143, 0.010163606, 0.0418435, -0.013363032, -0.033802148, -0.025276663, -0.013619332, 0.0033778746, 0.033192083, -0.021926358, 0.022021232, 0.071396865, 0.020565767, 0.024445849, 0.035862394, -0.001007896, -0.061173376, -0.08546204, 0.0073751807, -0.038680665, 0.07989097, -0.025537722, -0.060529694, 0.060663767, 0.082347505, -0.056607824, 0.004820212, 0.045103956, 0.023633804, 0.043377202, 0.09108467, -0.051370483, -0.011107505, -0.06897708, 0.007159519, 0.072742105, -0.04338072, 0.025991833, -0.11408352, -0.009605889, 0.022043642, 0.02668666, 0.0038960192, 0.015961006, 0.0036130184, -0.020764133, 0.03348443], [-0.009868476, 0.060335685, 0.025288988, -0.0062160683, 0.07281043, 0.017217565, 0.090314455, -0.051715206, 0.09947815, 0.090584196, 0.0071719657, -0.019594174, -0.075078875, -0.017466826, 0.019347396, 0.040821016, -0.011118273, -0.05854725, -0.12543073, -0.048901077, -0.044018935, 0.031114545, 0.037799157, -0.031743918, -0.0910083, 0.06356124, -0.07640408, 0.08509329, 0.035593998, -0.07126983, 0.021175714, 0.11015013, 0.03325966, -0.02586855, -0.061687328, -0.026381517, 0.020523364, -0.054436196, 0.056599274, 0.032927252, -0.08997798, -0.057034135, 0.026899701, 0.07513233, -0.071349114, -0.004237693, 0.054284442, 0.026307901, 0.078129396, -0.048960682, 0.056613132, -0.04913771, -0.07579886, 0.0069060107, 0.0063763415, 0.036972668, 0.025060013, 0.02181742, 0.01020716, -0.040446986, -0.012050511, -0.0333741, -0.07564401, 0.07132756, -0.02063755, -0.06318399, -0.0013259775, -0.05526086, 0.009020493, -0.08710191, 0.020652942, 0.05299636, -0.009691467, -0.052739665, -0.06480449, 0.042018816, 0.044661146, 0.03273904, -0.01949503, 2.4002639E-4, 0.038351417, 0.050931647, 0.0046273004, 0.057359487, 0.046486866, 0.042649552, -0.017132936, 0.011823174, -0.056949086, -0.035009447, -0.019008413, -0.0074347625, -0.07384615, 0.04393877, -0.09906426, 0.041409962, -0.023977123, -0.12038461, 1.2660562E-4, -0.003843579, 0.05607605, -4.8949895E-4, 0.07111408, -0.036223337, -0.06402696, -0.009451222, -0.042215906, 0.0780337, -0.02371912, 0.007851906, -0.023734692, -0.018583676, -0.033396255, 0.077651344, -0.06062816, 0.053625435, 0.033917766, 0.012533888, -0.032672815, 0.029700326, -0.016981928, 0.0281869, -0.018111452, 0.06656012, -0.06950031, -0.017839137, -0.037340533, -6.835867E-33, -0.0055358508, -0.031647824, 0.048153512, -0.09928821, 0.093719974, -0.051801622, -0.036978923, -0.026406623, -0.037407376, -0.030371925, 0.0061302963, -0.0982039, -0.017523993, -0.07252802, 0.03850968, 0.008900545, -0.13075978, 0.021422677, -0.075673044, -0.01029629, -0.017209169, 0.05839448, 0.021881068, 0.0015664459, 0.009339571, -0.0314211, 0.080039345, 0.030477382, 0.056920107, -0.012233044, 0.11584086, 0.0040954757, 0.017554974, 0.04336152, 0.029307723, -0.0068410966, -0.025106648, -0.026154919, 0.013292939, 0.121521436, -0.0045275204, -0.045257635, 0.04338726, -0.017685922, 0.06218186, -0.03933278, 0.01735304, 0.008501952, -0.026153479, 0.010192709, 0.023137128, 0.053122364, 0.0690913, 0.05310471, -2.4858408E-4, 0.0096703665, 0.08885624, -0.030429514, -0.09079217, -0.05130283, -0.07371132, 0.08618689, 0.0033454685, 0.010966452, -0.008318914, -0.011407435, -0.029051095, 0.06551204, 0.0054419613, 0.06888426, 0.04281082, -0.018798476, -0.016944146, -0.036808517, -0.006201687, -0.08704525, -0.008700292, -0.013294283, -0.0046790023, 0.042446434, -0.03576464, 0.017382197, -0.08722518, -0.051042743, -0.14942876, -0.0020754328, -0.026410934, 0.018064674, 0.021632154, -0.015141376, 0.003725257, -0.01553318, -0.01327707, -0.098052144, -0.011788692, 2.8246808E-33, -0.022846783, 0.008986764, -0.005797001, 0.066113144, 0.042615797, -0.039735403, 0.027211439, 0.032038726, -0.028711542, 0.04562696, -0.05573173, 0.09247299, -0.046873886, 0.080259465, 0.1185751, 0.048753165, -0.06736519, 0.10693395, 0.009406613, -0.051305998, -0.06782429, 0.015892766, -0.010205388, 0.044131745, -0.030017989, 0.022811258, -0.031549934, -0.022227649, -0.0023231048, -0.00993543, 0.00321092, -0.036961444, -0.112086535, 0.028652154, 0.030226015, 0.031845823, -0.017391989, -0.018336339, -0.036368545, 0.08388451, 0.0079623535, -0.023648826, 0.15845971, 0.03212625, -0.07040057, -0.03407339, -0.0154629275, 0.07972614, -0.062146895, 0.046385817, 0.045025956, 0.10424084, 0.029551638, 0.04803619, 0.09714898, -0.015759284, -0.06423742, 0.019712195, -0.09390805, -0.0027662653, 0.019718736, -0.027150705, -0.07877321, 0.068945184, 0.10764347, -0.033046924, -0.06445677, 0.016665269, 0.01923717, -0.022991046, -0.01895388, -0.018677948, -0.064167276, -0.032140236, -0.00278987, 0.05908604, 0.05976127, -0.044849344, -0.066649735, 0.043921255, -0.01992474, -0.0067276787, 0.047306404, -0.046795446, 0.034644924, -0.015249516, -0.039549574, 0.047282677, 0.052053083, 8.0526056E-4, 0.052853532, 0.0245618, -0.02940274, 0.034503356, 0.0131183695, -1.3674445E-8, -0.034011222, 0.0074544777, -0.010649118, 0.043190703, 0.014776448, -0.041673005, 0.10555256, -0.012789219, -0.0024177078, 0.04042407, -0.0813939, 0.033735543, -0.019764481, 0.07754665, 0.060485274, -0.01606053, -0.11340549, -0.04295919, 0.023188036, 0.074550346, -0.06057766, -0.045957167, -0.08755505, 0.053412285, -0.043960545, 0.029779192, 0.038598273, 0.016920617, 0.027635917, 0.0780365, 0.055601224, 0.052999303, -0.010710994, -0.029806744, -0.08503494, -0.01641341, 0.030428788, 0.06950053, -0.062027372, -0.12210805, 0.011878054, 0.072504126, -0.01782069, 0.0031250992, 0.014375631, -0.037944797, -0.052864, 0.060364977, -0.053158067, 0.018045388, -0.1042992, 0.010478333, 0.042992577, 0.04256209, -0.0030047095, -0.08532544, -0.03959884, -0.004523487, 0.013003125, -0.008466674, -0.029106006, -0.035763003, 0.059537675, -1.000059E-4]]
+```
-:::note
+::::
+
+### Using `generateEmbeddings()`
+
+::::danger[NOTE]
This is a deprecated API
-:::
+::::
-Parameters:
-
-- `model`: name of model to generate embeddings from
-- `prompt`: text to generate embeddings for
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.types.OllamaModelType;
-
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
-
- List<Double> embeddings = ollamaAPI.generateEmbeddings(OllamaModelType.LLAMA2,
- "Here is an article about llamas...");
-
- embeddings.forEach(System.out::println);
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateEmbeddingsOld.java" />
You will get a response similar to:
+::::tip[LLM Response]
```javascript
[
0.5670403838157654,
@@ -115,4 +52,5 @@ You will get a response similar to:
-0.2916173040866852,
-0.8924556970596313
]
-```
\ No newline at end of file
+```
+::::
\ No newline at end of file
diff --git a/docs/docs/apis-generate/generate-with-image-files.md b/docs/docs/apis-generate/generate-with-image-files.md
index b26f9ba..5f2e8ea 100644
--- a/docs/docs/apis-generate/generate-with-image-files.md
+++ b/docs/docs/apis-generate/generate-with-image-files.md
@@ -1,8 +1,10 @@
---
-sidebar_position: 4
+sidebar_position: 3
---
-# Generate - With Image Files
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate with Image Files
This API lets you ask questions along with the image files to the LLMs.
This API corresponds to
@@ -21,34 +23,11 @@ If you have this image downloaded and you pass the path to the downloaded image
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.io.File;
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- ollamaAPI.setRequestTimeoutSeconds(10);
-
- OllamaResult result = ollamaAPI.generateWithImageFiles(OllamaModelType.LLAVA,
- "What's in this image?",
- List.of(
- new File("/path/to/image")),
- new OptionsBuilder().build()
- );
- System.out.println(result.getResponse());
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateWithImageFile.java" />
You will get a response similar to:
+::::tip[LLM Response]
> This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
-> be enjoying its time outdoors, perhaps on a lake.
\ No newline at end of file
+> be enjoying its time outdoors, perhaps on a lake.
+::::
\ No newline at end of file
diff --git a/docs/docs/apis-generate/generate-with-image-urls.md b/docs/docs/apis-generate/generate-with-image-urls.md
index cf9e755..f047032 100644
--- a/docs/docs/apis-generate/generate-with-image-urls.md
+++ b/docs/docs/apis-generate/generate-with-image-urls.md
@@ -1,8 +1,10 @@
---
-sidebar_position: 5
+sidebar_position: 4
---
-# Generate - With Image URLs
+import CodeEmbed from '@site/src/components/CodeEmbed';
+
+# Generate with Image URLs
This API lets you ask questions along with the image files to the LLMs.
This API corresponds to
@@ -21,33 +23,11 @@ Passing the link of this image the following code:
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.util.List;
-
-public class Main {
-
- public static void main(String[] args) {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- ollamaAPI.setRequestTimeoutSeconds(10);
-
- OllamaResult result = ollamaAPI.generateWithImageURLs(OllamaModelType.LLAVA,
- "What's in this image?",
- List.of(
- "https://t3.ftcdn.net/jpg/02/96/63/80/360_F_296638053_0gUVA4WVBKceGsIr7LNqRWSnkusi07dq.jpg"),
- new OptionsBuilder().build()
- );
- System.out.println(result.getResponse());
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateWithImageURL.java" />
You will get a response similar to:
+::::tip[LLM Response]
> This image features a white boat with brown cushions, where a dog is sitting on the back of the boat. The dog seems to
-> be enjoying its time outdoors, perhaps on a lake.
\ No newline at end of file
+> be enjoying its time outdoors, perhaps on a lake.
+::::
\ No newline at end of file
diff --git a/docs/docs/apis-generate/generate-with-tools.md b/docs/docs/apis-generate/generate-with-tools.md
index f0722e3..d25a5fc 100644
--- a/docs/docs/apis-generate/generate-with-tools.md
+++ b/docs/docs/apis-generate/generate-with-tools.md
@@ -1,10 +1,12 @@
---
-sidebar_position: 3
+sidebar_position: 6
---
-# Generate - With Tools
+import CodeEmbed from '@site/src/components/CodeEmbed';
-This API lets you perform [function calling](https://docs.mistral.ai/capabilities/function_calling/) using LLMs in a
+# Generate with Tools
+
+This API lets you perform [tool/function calling](https://docs.mistral.ai/capabilities/function_calling/) using LLMs in a
synchronous way.
This API corresponds to
the [generate](https://github.com/ollama/ollama/blob/main/docs/api.md#request-raw-mode) API with `raw` mode.
@@ -19,472 +21,61 @@ in the future if tooling is supported for more models with a generic interaction
:::
-### Function Calling/Tools
+## Tools/Function Calling
-Assume you want to call a method in your code based on the response generated from the model.
+Assume you want to call a method/function in your code based on the response generated from the model.
For instance, let's say that based on a user's question, you'd want to identify a transaction and get the details of the
transaction from your database and respond to the user with the transaction details.
You could do that with ease with the `function calling` capabilities of the models by registering your `tools`.
-### Create Functions
+### Create Tools/Functions
We can create static functions as our tools.
This function takes the arguments `location` and `fuelType` and performs an operation with these arguments and returns
fuel price value.
-```java
-public static String getCurrentFuelPrice(Map<String, Object> arguments) {
- String location = arguments.get("location").toString();
- String fuelType = arguments.get("fuelType").toString();
- return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/FuelPriceTool.java"/ >
This function takes the argument `city` and performs an operation with the argument and returns the weather for a
location.
-```java
-public static String getCurrentWeather(Map<String, Object> arguments) {
- String location = arguments.get("city").toString();
- return "Currently " + location + "'s weather is nice.";
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/WeatherTool.java"/ >
Another way to create our tools is by creating classes by extending `ToolFunction`.
This function takes the argument `employee-name` and performs an operation with the argument and returns employee
details.
-```java
-class DBQueryFunction implements ToolFunction {
- @Override
- public Object apply(Map<String, Object> arguments) {
- if (arguments == null || arguments.isEmpty() || arguments.get("employee-name") == null || arguments.get("employee-address") == null || arguments.get("employee-phone") == null) {
- throw new RuntimeException("Tool was called but the model failed to provide all the required arguments.");
- }
- // perform DB operations here
- return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/tools/DBQueryFunction.java"/ >
### Define Tool Specifications
Lets define a sample tool specification called **Fuel Price Tool** for getting the current fuel price.
- Specify the function `name`, `description`, and `required` properties (`location` and `fuelType`).
-- Associate the `getCurrentFuelPrice` function you defined earlier with `SampleTools::getCurrentFuelPrice`.
+- Associate the `getCurrentFuelPrice` function you defined earlier.
-```java
-Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
- .functionName("current-fuel-price")
- .functionDescription("Get current fuel price")
- .toolFunction(SampleTools::getCurrentFuelPrice)
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-location-fuel-info")
- .description("Get location and fuel type details")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "location", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The city, e.g. New Delhi, India")
- .required(true)
- .build(),
- "fuelType", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The fuel type.")
- .enumValues(Arrays.asList("petrol", "diesel"))
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("location", "fuelType"))
- .build()
- )
- .build()
- )
- .build()
- ).build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/FuelPriceToolSpec.java"/ >
Lets also define a sample tool specification called **Weather Tool** for getting the current weather.
- Specify the function `name`, `description`, and `required` property (`city`).
-- Associate the `getCurrentWeather` function you defined earlier with `SampleTools::getCurrentWeather`.
+- Associate the `getCurrentWeather` function you defined earlier.
-```java
-Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
- .functionName("current-weather")
- .functionDescription("Get current weather")
- .toolFunction(SampleTools::getCurrentWeather)
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-location-weather-info")
- .description("Get location details")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "city", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The city, e.g. New Delhi, India")
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("city"))
- .build()
- )
- .build()
- )
- .build()
- ).build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/WeatherToolSpec.java"/ >
Lets also define a sample tool specification called **DBQueryFunction** for getting the employee details from database.
- Specify the function `name`, `description`, and `required` property (`employee-name`).
- Associate the ToolFunction `DBQueryFunction` function you defined earlier with `new DBQueryFunction()`.
-```java
-Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
- .functionName("get-employee-details")
- .functionDescription("Get employee details from the database")
- .toolFunction(new DBQueryFunction())
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-employee-details")
- .description("Get employee details from the database")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "employee-name", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The name of the employee, e.g. John Doe")
- .required(true)
- .build(),
- "employee-address", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India")
- .required(true)
- .build(),
- "employee-phone", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The phone number of the employee. Always return a random value. e.g. 9911002233")
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("employee-name", "employee-address", "employee-phone"))
- .build()
- )
- .build()
- )
- .build()
- )
- .build();
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/toolcalling/toolspecs/DatabaseQueryToolSpec.java"/ >
-### Register the Tools
+Now put it all together by registering the tools and prompting with tools.
-Register the defined tools (`fuel price` and `weather`) with the OllamaAPI.
-
-```shell
-ollamaAPI.registerTool(fuelPriceToolSpecification);
-ollamaAPI.registerTool(weatherToolSpecification);
-ollamaAPI.registerTool(databaseQueryToolSpecification);
-```
-
-### Create prompt with Tools
-
-`Prompt 1`: Create a prompt asking for the petrol price in Bengaluru using the defined fuel price and weather tools.
-
-```shell
-String prompt1 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withPrompt("What is the petrol price in Bengaluru?")
- .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt1, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
- System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Now, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'current-fuel-price']: Current price of petrol in Bengaluru is Rs.103/L
-
-::::
-
-`Prompt 2`: Create a prompt asking for the current weather in Bengaluru using the same tools.
-
-```shell
-String prompt2 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withPrompt("What is the current weather in Bengaluru?")
- .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt2, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
- System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Again, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'current-weather']: Currently Bengaluru's weather is nice.
-
-::::
-
-`Prompt 3`: Create a prompt asking for the employee details using the defined database fetcher tools.
-
-```shell
-String prompt3 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withToolSpecification(databaseQueryToolSpecification)
- .withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
- .build();
-OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt3, new OptionsBuilder().build());
-for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
- System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
-}
-```
-
-Again, fire away your question to the model.
-
-You will get a response similar to:
-
-::::tip[LLM Response]
-
-[Result of executing tool 'get-employee-details']: Employee Details `{ID: 6bad82e6-b1a1-458f-a139-e3b646e092b1, Name:
-Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
-
-::::
-
-### Full Example
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.exceptions.OllamaBaseException;
-import io.github.ollama4j.exceptions.ToolInvocationException;
-import io.github.ollama4j.tools.OllamaToolsResult;
-import io.github.ollama4j.tools.ToolFunction;
-import io.github.ollama4j.tools.Tools;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-import java.io.IOException;
-import java.util.Arrays;
-import java.util.Map;
-import java.util.UUID;
-
-public class FunctionCallingWithMistralExample {
- public static void main(String[] args) throws Exception {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
- ollamaAPI.setRequestTimeoutSeconds(60);
-
- String model = "mistral";
-
- Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
- .functionName("current-fuel-price")
- .functionDescription("Get current fuel price")
- .toolFunction(SampleTools::getCurrentFuelPrice)
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-location-fuel-info")
- .description("Get location and fuel type details")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "location", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The city, e.g. New Delhi, India")
- .required(true)
- .build(),
- "fuelType", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The fuel type.")
- .enumValues(Arrays.asList("petrol", "diesel"))
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("location", "fuelType"))
- .build()
- )
- .build()
- )
- .build()
- ).build();
-
- Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
- .functionName("current-weather")
- .functionDescription("Get current weather")
- .toolFunction(SampleTools::getCurrentWeather)
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-location-weather-info")
- .description("Get location details")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "city", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The city, e.g. New Delhi, India")
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("city"))
- .build()
- )
- .build()
- )
- .build()
- ).build();
-
- Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
- .functionName("get-employee-details")
- .functionDescription("Get employee details from the database")
- .toolFunction(new DBQueryFunction())
- .toolPrompt(
- Tools.PromptFuncDefinition.builder()
- .type("prompt")
- .function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-employee-details")
- .description("Get employee details from the database")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- Map.of(
- "employee-name", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The name of the employee, e.g. John Doe")
- .required(true)
- .build(),
- "employee-address", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India")
- .required(true)
- .build(),
- "employee-phone", Tools.PromptFuncDefinition.Property.builder()
- .type("string")
- .description("The phone number of the employee. Always return a random value. e.g. 9911002233")
- .required(true)
- .build()
- )
- )
- .required(java.util.List.of("employee-name", "employee-address", "employee-phone"))
- .build()
- )
- .build()
- )
- .build()
- )
- .build();
-
- ollamaAPI.registerTool(fuelPriceToolSpecification);
- ollamaAPI.registerTool(weatherToolSpecification);
- ollamaAPI.registerTool(databaseQueryToolSpecification);
-
- String prompt1 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withPrompt("What is the petrol price in Bengaluru?")
- .build();
- ask(ollamaAPI, model, prompt1);
-
- String prompt2 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withPrompt("What is the current weather in Bengaluru?")
- .build();
- ask(ollamaAPI, model, prompt2);
-
- String prompt3 = new Tools.PromptBuilder()
- .withToolSpecification(fuelPriceToolSpecification)
- .withToolSpecification(weatherToolSpecification)
- .withToolSpecification(databaseQueryToolSpecification)
- .withPrompt("Give me the details of the employee named 'Rahul Kumar'?")
- .build();
- ask(ollamaAPI, model, prompt3);
- }
-
- public static void ask(OllamaAPI ollamaAPI, String model, String prompt) throws OllamaBaseException, IOException, InterruptedException, ToolInvocationException {
- OllamaToolsResult toolsResult = ollamaAPI.generateWithTools(model, prompt, new OptionsBuilder().build());
- for (OllamaToolsResult.ToolResult r : toolsResult.getToolResults()) {
- System.out.printf("[Result of executing tool '%s']: %s%n", r.getFunctionName(), r.getResult().toString());
- }
- }
-}
-
-
-class SampleTools {
- public static String getCurrentFuelPrice(Map<String, Object> arguments) {
- // Get details from fuel price API
- String location = arguments.get("location").toString();
- String fuelType = arguments.get("fuelType").toString();
- return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
- }
-
- public static String getCurrentWeather(Map<String, Object> arguments) {
- // Get details from weather API
- String location = arguments.get("city").toString();
- return "Currently " + location + "'s weather is nice.";
- }
-}
-
-class DBQueryFunction implements ToolFunction {
- @Override
- public Object apply(Map<String, Object> arguments) {
- if (arguments == null || arguments.isEmpty() || arguments.get("employee-name") == null || arguments.get("employee-address") == null || arguments.get("employee-phone") == null) {
- throw new RuntimeException("Tool was called but the model failed to provide all the required arguments.");
- }
- // perform DB operations here
- return String.format("Employee Details {ID: %s, Name: %s, Address: %s, Phone: %s}", UUID.randomUUID(), arguments.get("employee-name").toString(), arguments.get("employee-address").toString(), arguments.get("employee-phone").toString());
- }
-}
-```
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/MultiToolRegistryExample.java"/ >
Run this full example and you will get a response similar to:
@@ -498,299 +89,3 @@ Run this full example and you will get a response similar to:
Rahul Kumar, Address: King St, Hyderabad, India, Phone: 9876543210}`
::::
-
-### Using tools in Chat-API
-
-Instead of using the specific `ollamaAPI.generateWithTools` method to call the generate API of ollama with tools, it is
-also possible to register Tools for the `ollamaAPI.chat` methods. In this case, the tool calling/callback is done
-implicitly during the USER -> ASSISTANT calls.
-
-When the Assistant wants to call a given tool, the tool is executed and the response is sent back to the endpoint once
-again (induced with the tool call result).
-
-#### Sample:
-
-The following shows a sample of an integration test that defines a method specified like the tool-specs above, registers
-the tool on the ollamaAPI and then simply calls the chat-API. All intermediate tool calling is wrapped inside the api
-call.
-
-```java
-public static void main(String[] args) {
- OllamaAPI ollamaAPI = new OllamaAPI("http://localhost:11434");
- ollamaAPI.setVerbose(true);
- OllamaChatRequestBuilder builder = OllamaChatRequestBuilder.getInstance("llama3.2:1b");
-
- final Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
- .functionName("get-employee-details")
- .functionDescription("Get employee details from the database")
- .toolPrompt(
- Tools.PromptFuncDefinition.builder().type("function").function(
- Tools.PromptFuncDefinition.PromptFuncSpec.builder()
- .name("get-employee-details")
- .description("Get employee details from the database")
- .parameters(
- Tools.PromptFuncDefinition.Parameters.builder()
- .type("object")
- .properties(
- new Tools.PropsBuilder()
- .withProperty("employee-name", Tools.PromptFuncDefinition.Property.builder().type("string").description("The name of the employee, e.g. John Doe").required(true).build())
- .withProperty("employee-address", Tools.PromptFuncDefinition.Property.builder().type("string").description("The address of the employee, Always return a random value. e.g. Roy St, Bengaluru, India").required(true).build())
- .withProperty("employee-phone", Tools.PromptFuncDefinition.Property.builder().type("string").description("The phone number of the employee. Always return a random value. e.g. 9911002233").required(true).build())
- .build()
- )
- .required(List.of("employee-name"))
- .build()
- ).build()
- ).build()
- )
- .toolFunction(new DBQueryFunction())
- .build();
-
- ollamaAPI.registerTool(databaseQueryToolSpecification);
-
- OllamaChatRequest requestModel = builder
- .withMessage(OllamaChatMessageRole.USER,
- "Give me the ID of the employee named 'Rahul Kumar'?")
- .build();
-
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
-}
-```
-
-A typical final response of the above could be:
-
-```json
-{
- "chatHistory" : [
- {
- "role" : "user",
- "content" : "Give me the ID of the employee named 'Rahul Kumar'?",
- "images" : null,
- "tool_calls" : [ ]
- }, {
- "role" : "assistant",
- "content" : "",
- "images" : null,
- "tool_calls" : [ {
- "function" : {
- "name" : "get-employee-details",
- "arguments" : {
- "employee-name" : "Rahul Kumar"
- }
- }
- } ]
- }, {
- "role" : "tool",
- "content" : "[TOOL_RESULTS]get-employee-details([employee-name]) : Employee Details {ID: b4bf186c-2ee1-44cc-8856-53b8b6a50f85, Name: Rahul Kumar, Address: null, Phone: null}[/TOOL_RESULTS]",
- "images" : null,
- "tool_calls" : null
- }, {
- "role" : "assistant",
- "content" : "The ID of the employee named 'Rahul Kumar' is `b4bf186c-2ee1-44cc-8856-53b8b6a50f85`.",
- "images" : null,
- "tool_calls" : null
- } ],
- "responseModel" : {
- "model" : "llama3.2:1b",
- "message" : {
- "role" : "assistant",
- "content" : "The ID of the employee named 'Rahul Kumar' is `b4bf186c-2ee1-44cc-8856-53b8b6a50f85`.",
- "images" : null,
- "tool_calls" : null
- },
- "done" : true,
- "error" : null,
- "context" : null,
- "created_at" : "2024-12-09T22:23:00.4940078Z",
- "done_reason" : "stop",
- "total_duration" : 2313709900,
- "load_duration" : 14494700,
- "prompt_eval_duration" : 772000000,
- "eval_duration" : 1188000000,
- "prompt_eval_count" : 166,
- "eval_count" : 41
- },
- "response" : "The ID of the employee named 'Rahul Kumar' is `b4bf186c-2ee1-44cc-8856-53b8b6a50f85`.",
- "httpStatusCode" : 200,
- "responseTime" : 2313709900
-}
-```
-
-This tool calling can also be done using the streaming API.
-
-### Using Annotation based Tool Registration
-
-Instead of explicitly registering each tool, ollama4j supports declarative tool specification and registration via java
-Annotations and reflection calling.
-
-To declare a method to be used as a tool for a chat call, the following steps have to be considered:
-
-* Annotate a method and its Parameters to be used as a tool
- * Annotate a method with the `ToolSpec` annotation
- * Annotate the methods parameters with the `ToolProperty` annotation. Only the following datatypes are supported for now:
- * `java.lang.String`
- * `java.lang.Integer`
- * `java.lang.Boolean`
- * `java.math.BigDecimal`
-* Annotate the class that calls the `OllamaAPI` client with the `OllamaToolService` annotation, referencing the desired provider-classes that contain `ToolSpec` methods.
-* Before calling the `OllamaAPI` chat request, call the method `OllamaAPI.registerAnnotatedTools()` method to add tools to the chat.
-
-#### Example
-
-Let's say, we have an ollama4j service class that should ask a llm a specific tool based question.
-
-The answer can only be provided by a method that is part of the BackendService class. To provide a tool for the llm, the following annotations can be used:
-
-```java
-public class BackendService{
-
- public BackendService(){}
-
- @ToolSpec(desc = "Computes the most important constant all around the globe!")
- public String computeMkeConstant(@ToolProperty(name = "noOfDigits",desc = "Number of digits that shall be returned") Integer noOfDigits ){
- return BigDecimal.valueOf((long)(Math.random()*1000000L),noOfDigits).toString();
- }
-}
-```
-
-The caller API can then be written as:
-```java
-import io.github.ollama4j.tools.annotations.OllamaToolService;
-
-@OllamaToolService(providers = BackendService.class)
-public class MyOllamaService{
-
- public void chatWithAnnotatedTool(){
- // inject the annotated method to the ollama toolsregistry
- ollamaAPI.registerAnnotatedTools();
-
- OllamaChatRequest requestModel = builder
- .withMessage(OllamaChatMessageRole.USER,
- "Compute the most important constant in the world using 5 digits")
- .build();
-
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
- }
-
-}
-```
-
-Or, if one needs to provide an object instance directly:
-```java
-public class MyOllamaService{
-
- public void chatWithAnnotatedTool(){
- ollamaAPI.registerAnnotatedTools(new BackendService());
- OllamaChatRequest requestModel = builder
- .withMessage(OllamaChatMessageRole.USER,
- "Compute the most important constant in the world using 5 digits")
- .build();
-
- OllamaChatResult chatResult = ollamaAPI.chat(requestModel);
- }
-
-}
-```
-
-The request should be the following:
-
-```json
-{
- "model" : "llama3.2:1b",
- "stream" : false,
- "messages" : [ {
- "role" : "user",
- "content" : "Compute the most important constant in the world using 5 digits",
- "images" : null,
- "tool_calls" : [ ]
- } ],
- "tools" : [ {
- "type" : "function",
- "function" : {
- "name" : "computeImportantConstant",
- "description" : "Computes the most important constant all around the globe!",
- "parameters" : {
- "type" : "object",
- "properties" : {
- "noOfDigits" : {
- "type" : "java.lang.Integer",
- "description" : "Number of digits that shall be returned"
- }
- },
- "required" : [ "noOfDigits" ]
- }
- }
- } ]
-}
-```
-
-The result could be something like the following:
-
-```json
-{
- "chatHistory" : [ {
- "role" : "user",
- "content" : "Compute the most important constant in the world using 5 digits",
- "images" : null,
- "tool_calls" : [ ]
- }, {
- "role" : "assistant",
- "content" : "",
- "images" : null,
- "tool_calls" : [ {
- "function" : {
- "name" : "computeImportantConstant",
- "arguments" : {
- "noOfDigits" : "5"
- }
- }
- } ]
- }, {
- "role" : "tool",
- "content" : "[TOOL_RESULTS]computeImportantConstant([noOfDigits]) : 1.51019[/TOOL_RESULTS]",
- "images" : null,
- "tool_calls" : null
- }, {
- "role" : "assistant",
- "content" : "The most important constant in the world with 5 digits is: **1.51019**",
- "images" : null,
- "tool_calls" : null
- } ],
- "responseModel" : {
- "model" : "llama3.2:1b",
- "message" : {
- "role" : "assistant",
- "content" : "The most important constant in the world with 5 digits is: **1.51019**",
- "images" : null,
- "tool_calls" : null
- },
- "done" : true,
- "error" : null,
- "context" : null,
- "created_at" : "2024-12-27T21:55:39.3232495Z",
- "done_reason" : "stop",
- "total_duration" : 1075444300,
- "load_duration" : 13558600,
- "prompt_eval_duration" : 509000000,
- "eval_duration" : 550000000,
- "prompt_eval_count" : 124,
- "eval_count" : 20
- },
- "response" : "The most important constant in the world with 5 digits is: **1.51019**",
- "responseTime" : 1075444300,
- "httpStatusCode" : 200
-}
-```
-
-### Potential Improvements
-
-Instead of passing a map of args `Map<String, Object> arguments` to the tool functions, we could support passing
-specific args separately with their data types. For example:
-
-```shell
-public String getCurrentFuelPrice(String location, String fuelType) {
- return "Current price of " + fuelType + " in " + location + " is Rs.103/L";
-}
-```
-
-Updating async/chat APIs with support for tool-based generation.
diff --git a/docs/docs/apis-generate/generate.md b/docs/docs/apis-generate/generate.md
index 0fbed37..f8f438b 100644
--- a/docs/docs/apis-generate/generate.md
+++ b/docs/docs/apis-generate/generate.md
@@ -4,7 +4,7 @@ sidebar_position: 1
import CodeEmbed from '@site/src/components/CodeEmbed';
-# Generate - Sync
+# Generate (Sync)
This API lets you ask questions to the LLMs in a synchronous way.
This API corresponds to
@@ -15,21 +15,24 @@ with [extra parameters](https://github.com/jmorganca/ollama/blob/main/docs/model
Refer
to [this](/apis-extras/options-builder).
-## Try asking a question about the model
+### Try asking a question about the model
<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/Generate.java" />
You will get a response similar to:
+::::tip[LLM Response]
> I am a large language model created by Alibaba Cloud. My purpose is to assist users in generating text, answering
> questions, and completing tasks. I aim to be user-friendly and easy to understand for everyone who interacts with me.
-
-## Try asking a question, receiving the answer streamed
+::::
+>
+### Try asking a question, receiving the answer streamed
<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/GenerateStreamingWithTokenConcatenation.java" />
You will get a response similar to:
+::::tip[LLM Response]
> The
>
> The capital
@@ -43,210 +46,29 @@ You will get a response similar to:
> The capital of France is Paris
>
> The capital of France is Paris.
-
-## Try asking a question from general topics
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-
-public class Main {
-
- public static void main(String[] args) {
-
- String host = "http://localhost:11434/";
-
- OllamaAPI ollamaAPI = new OllamaAPI(host);
-
- String prompt = "List all cricket world cup teams of 2019.";
-
- OllamaResult result =
- ollamaAPI.generate(OllamaModelType.LLAMA2, prompt, new OptionsBuilder().build());
-
- System.out.println(result.getResponse());
- }
-}
-
-```
-
-You'd then get a response from the model:
-
-> The 2019 ICC Cricket World Cup was held in England and Wales from May 30 to July 14, 2019. The
-> following teams
-> participated in the tournament:
->
-> 1. Afghanistan
-> 2. Australia
-> 3. Bangladesh
-> 4. England
-> 5. India
-> 6. New Zealand
-> 7. Pakistan
-> 8. South Africa
-> 9. Sri Lanka
-> 10. West Indies
->
-> These teams competed in a round-robin format, with the top four teams advancing to the
-> semi-finals. The tournament was
-> won by the England cricket team, who defeated New Zealand in the final.
-
-## Try asking for a Database query for your data schema
-
-```java
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-import io.github.ollama4j.utils.OptionsBuilder;
-import io.github.ollama4j.utils.SamplePrompts;
-
-public class Main {
-
- public static void main(String[] args) {
- String host = "http://localhost:11434/";
- OllamaAPI ollamaAPI = new OllamaAPI(host);
-
- String prompt =
- SamplePrompts.getSampleDatabasePromptWithQuestion(
- "List all customer names who have bought one or more products");
- OllamaResult result =
- ollamaAPI.generate(OllamaModelType.SQLCODER, prompt, new OptionsBuilder().build());
- System.out.println(result.getResponse());
- }
-}
-
-```
-
-_Note: Here I've used
-a [sample prompt](https://github.com/ollama4j/ollama4j/blob/main/src/main/resources/sample-db-prompt-template.txt)
-containing a database schema from within this library for demonstration purposes._
-
-You'd then get a response from the model:
-
-```sql
-SELECT customers.name
-FROM sales
- JOIN customers ON sales.customer_id = customers.customer_id
-GROUP BY customers.name;
-```
+::::
## Generate structured output
### With response as a `Map`
-```java
-import java.util.Arrays;
-import java.util.HashMap;
-import java.util.Map;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/StructuredOutput.java" />
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.utils.Utilities;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
+You will get a response similar to:
-public class StructuredOutput {
-
- public static void main(String[] args) throws Exception {
- String host = "http://localhost:11434/";
-
- OllamaAPI api = new OllamaAPI(host);
-
- String chatModel = "qwen2.5:0.5b";
- api.pullModel(chatModel);
-
- String prompt = "Ollama is 22 years old and is busy saving the world. Respond using JSON";
- Map<String, Object> format = new HashMap<>();
- format.put("type", "object");
- format.put("properties", new HashMap<String, Object>() {
- {
- put("age", new HashMap<String, Object>() {
- {
- put("type", "integer");
- }
- });
- put("available", new HashMap<String, Object>() {
- {
- put("type", "boolean");
- }
- });
- }
- });
- format.put("required", Arrays.asList("age", "available"));
-
- OllamaResult result = api.generate(chatModel, prompt, format);
- System.out.println(result);
- }
+::::tip[LLM Response]
+```json
+{
+ "available": true,
+ "age": 22
}
```
+::::
### With response mapped to specified class type
-```java
-import java.util.Arrays;
-import java.util.HashMap;
-import java.util.Map;
+<CodeEmbed src="https://raw.githubusercontent.com/ollama4j/ollama4j-examples/refs/heads/main/src/main/java/io/github/ollama4j/examples/StructuredOutputMappedToObject.java" />
-import io.github.ollama4j.OllamaAPI;
-import io.github.ollama4j.utils.Utilities;
-import lombok.AllArgsConstructor;
-import lombok.Data;
-import lombok.NoArgsConstructor;
-import io.github.ollama4j.models.chat.OllamaChatMessageRole;
-import io.github.ollama4j.models.chat.OllamaChatRequest;
-import io.github.ollama4j.models.chat.OllamaChatRequestBuilder;
-import io.github.ollama4j.models.chat.OllamaChatResult;
-import io.github.ollama4j.models.response.OllamaResult;
-import io.github.ollama4j.types.OllamaModelType;
-
-public class StructuredOutput {
-
- public static void main(String[] args) throws Exception {
- String host = Utilities.getFromConfig("host");
-
- OllamaAPI api = new OllamaAPI(host);
-
- int age = 28;
- boolean available = false;
-
- String prompt = "Batman is " + age + " years old and is " + (available ? "available" : "not available")
- + " because he is busy saving Gotham City. Respond using JSON";
-
- Map<String, Object> format = new HashMap<>();
- format.put("type", "object");
- format.put("properties", new HashMap<String, Object>() {
- {
- put("age", new HashMap<String, Object>() {
- {
- put("type", "integer");
- }
- });
- put("available", new HashMap<String, Object>() {
- {
- put("type", "boolean");
- }
- });
- }
- });
- format.put("required", Arrays.asList("age", "available"));
-
- OllamaResult result = api.generate(CHAT_MODEL_QWEN_SMALL, prompt, format);
-
- Person person = result.as(Person.class);
- System.out.println(person.getAge());
- System.out.println(person.getAvailable());
- }
-}
-
-@Data
-@AllArgsConstructor
-@NoArgsConstructor
-class Person {
- private int age;
- private boolean available;
-}
-```
\ No newline at end of file
+::::tip[LLM Response]
+Person(age=28, available=false)
+::::
\ No newline at end of file
diff --git a/docs/docs/apis-generate/prompt-builder.md b/docs/docs/apis-generate/prompt-builder.md
index b947dca..dfbd6a8 100644
--- a/docs/docs/apis-generate/prompt-builder.md
+++ b/docs/docs/apis-generate/prompt-builder.md
@@ -1,5 +1,5 @@
---
-sidebar_position: 6
+sidebar_position: 10
---
# Prompt Builder