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59 lines
1.8 KiB
Markdown
59 lines
1.8 KiB
Markdown
### Ollama4j
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A Java wrapper for [Ollama](https://github.com/jmorganca/ollama/blob/main/docs/api.md) APIs.
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Start Ollama Container:
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```
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docker run -v ~/ollama:/root/.ollama -p 11434:11434 ollama/ollama
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```
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Pull a model:
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```java
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public class Main {
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public static void main(String[] args) throws Exception {
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String host = "http://localhost:11434/";
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OllamaAPI ollamaAPI = new OllamaAPI(host);
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ollamaAPI.pullModel(OllamaModel.LLAMA2);
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}
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}
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```
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Post a question to Ollama using Ollama4j:
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Using sync API:
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```java
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public class Main {
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public static void main(String[] args) throws Exception {
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String host = "http://localhost:11434/";
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OllamaAPI ollamaAPI = new OllamaAPI(host);
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String response = ollamaAPI.runSync(OllamaModel.LLAMA2, "Who are you?");
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System.out.println(response);
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}
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}
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```
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Using async API:
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```java
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public class Main {
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public static void main(String[] args) throws Exception {
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String host = "http://localhost:11434/";
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OllamaAPI ollamaAPI = new OllamaAPI(host);
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OllamaAsyncResultCallback ollamaAsyncResultCallback = ollamaAPI.runAsync(OllamaModel.LLAMA2, "Who are you?");
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while (true) {
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if (ollamaAsyncResultCallback.isComplete()) {
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System.out.println(ollamaAsyncResultCallback.getResponse());
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break;
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}
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Thread.sleep(1000);
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}
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}
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}
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```
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You'd then get a response from Ollama:
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```
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I am LLaMA, an AI assistant developed by Meta AI that can understand and respond to human input in a conversational manner. I am trained on a massive dataset of text from the internet and can generate human-like responses to a wide range of topics and questions. I can be used to create chatbots, virtual assistants, and other applications that require natural language understanding and generation capabilities.
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```
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