updated docs

docs/docs/apis-ask/ask-async.md

@@ -17,15 +17,16 @@ public class Main {
 
         OllamaAPI ollamaAPI = new OllamaAPI(host);
 
-        OllamaAsyncResultCallback ollamaAsyncResultCallback = ollamaAPI.askAsync(OllamaModelType.LLAMA2,
-                "Who are you?");
+        String prompt = "Who are you?";
 
-        while (true) {
-            if (ollamaAsyncResultCallback.isComplete()) {
-                System.out.println(ollamaAsyncResultCallback.getResponse());
-                break;
+        OllamaAsyncResultCallback callback = ollamaAPI.askAsync(OllamaModelType.LLAMA2, prompt);
+
+        while (!callback.isComplete() || !callback.getStream().isEmpty()) {
+            // poll for data from the response stream
+            String result = callback.getStream().poll();
+            if (response != null) {
+                System.out.print(result.getResponse());
             }
-            // introduce sleep to check for status with a time interval
             Thread.sleep(100);
         }
     }

docs/docs/apis-ask/ask.md

@@ -8,11 +8,13 @@ This API lets you ask questions to the LLMs in a synchronous way.
 These APIs correlate to
 the [completion](https://github.com/jmorganca/ollama/blob/main/docs/api.md#generate-a-completion) APIs.
 
+## Try asking a question about the model.
+
 ```java
 public class Main {
 
     public static void main(String[] args) {
-        
+
         String host = "http://localhost:11434/";
 
         OllamaAPI ollamaAPI = new OllamaAPI(host);
@@ -30,4 +32,75 @@ You will get a response similar to:
 > 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.
+> natural language understanding and generation capabilities.
+
+## Try asking a question from general topics.
+
+```java
+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.ask(OllamaModelType.LLAMA2, prompt);
+
+        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
+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.ask(OllamaModelType.SQLCODER, prompt);
+        System.out.println(result.getResponse());
+    }
+}
+```
+
+_Note: Here I've used
+a [sample prompt](https://github.com/amithkoujalgi/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;
+```

docs/docs/intro.md

@@ -13,7 +13,7 @@ Let's get started with **Ollama4j**.
 - **[Ollama](https://ollama.ai/download)**
 - **[Oracle JDK](https://www.oracle.com/java/technologies/javase/jdk11-archive-downloads.html)** or
   **[Open JDK](https://jdk.java.net/archive/)** 11.0 or above.
-- **[Maven](https://maven.apache.org/download.cgi)** or **[Gradle](https://gradle.org/install/)**
+- **[Maven](https://maven.apache.org/download.cgi)**
 
 ### Start Ollama server
 
@@ -43,9 +43,9 @@ The command runs the Ollama server locally at **http://localhost:11434/**.
 
 ### Setup your project
 
-Get started by **creating a new project** on your favorite IDE.
+Get started by **creating a new Maven project** on your favorite IDE.
 
-If you're on Maven, add the dependency to your project's `pom.xml`.
+Add the dependency to your project's `pom.xml`.
 
 ```xml
 
@@ -58,14 +58,33 @@ If you're on Maven, add the dependency to your project's `pom.xml`.
 
 Find the latest version of the library [here](https://central.sonatype.com/artifact/io.github.amithkoujalgi/ollama4j).
 
-If you're on Gradle, add the following to your `build.gradle`:
+You might want to include an implementation of [SL4J](https://www.slf4j.org/) logger in your `pom.xml` file. For
+example,
 
-```gradle
-dependencies {
-    implementation 'io.github.amithkoujalgi:ollama4j:1.0.27'
-}
+Use `slf4j-jdk14` implementation:
+
+```xml
+
+<dependency>
+    <groupId>org.slf4j</groupId>
+    <artifactId>slf4j-jdk14</artifactId>
+    <version>2.0.9</version> <!--Replace with appropriate version-->
+</dependency>
 ```
 
+or use `logback-classic` implementation:
+
+```xml
+
+<dependency>
+    <groupId>ch.qos.logback</groupId>
+    <artifactId>logback-classic</artifactId>
+    <version>1.3.11</version> <!--Replace with appropriate version-->
+</dependency>
+```
+
+or use other suitable implementations.
+
 Create a new Java class in your project and add this code.
 
 ```java