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Generate - With Tools
This API lets you perform function calling using LLMs in a
synchronous way.
This API corresponds to
the generate API with raw
mode.
:::note
This is an only an experimental implementation and has a very basic design.
Currently, built and tested for Mistral's latest model only. We could redesign this in the future if tooling is supported for more models with a generic interaction standard from Ollama.
:::
Function Calling/Tools
Assume you want to call a method 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
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.
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";
}
This function takes the argument city
and performs an operation with the argument and returns the weather for a
location.
public static String getCurrentWeather(Map<String, Object> arguments) {
String location = arguments.get("city").toString();
return "Currently " + location + "'s weather is nice.";
}
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.
class DBQueryFunction implements ToolFunction {
@Override
public Object apply(Map<String, Object> 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());
}
}
Define Tool Specifications
Lets define a sample tool specification called Fuel Price Tool for getting the current fuel price.
- Specify the function
name
,description
, andrequired
properties (location
andfuelType
). - Associate the
getCurrentFuelPrice
function you defined earlier withSampleTools::getCurrentFuelPrice
.
Tools.ToolSpecification fuelPriceToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-fuel-price")
.functionDescription("Get current fuel price")
.properties(
new Tools.PropsBuilder()
.withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentFuelPrice)
.build();
Lets also define a sample tool specification called Weather Tool for getting the current weather.
- Specify the function
name
,description
, andrequired
property (city
). - Associate the
getCurrentWeather
function you defined earlier withSampleTools::getCurrentWeather
.
Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-weather")
.functionDescription("Get current weather")
.properties(
new Tools.PropsBuilder()
.withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentWeather)
.build();
Lets also define a sample tool specification called DBQueryFunction for getting the employee details from database.
- Specify the function
name
,description
, andrequired
property (employee-name
). - Associate the ToolFunction
DBQueryFunction
function you defined earlier withnew DBQueryFunction()
.
Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
.functionName("get-employee-details")
.functionDescription("Get employee details from the database")
.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()
)
.toolDefinition(new DBQueryFunction())
.build();
Register the Tools
Register the defined tools (fuel price
and weather
) with the OllamaAPI.
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.
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.
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.
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
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")
.properties(
new Tools.PropsBuilder()
.withProperty("location", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.withProperty("fuelType", Tools.PromptFuncDefinition.Property.builder().type("string").description("The fuel type.").enumValues(Arrays.asList("petrol", "diesel")).required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentFuelPrice)
.build();
Tools.ToolSpecification weatherToolSpecification = Tools.ToolSpecification.builder()
.functionName("current-weather")
.functionDescription("Get current weather")
.properties(
new Tools.PropsBuilder()
.withProperty("city", Tools.PromptFuncDefinition.Property.builder().type("string").description("The city, e.g. New Delhi, India").required(true).build())
.build()
)
.toolDefinition(SampleTools::getCurrentWeather)
.build();
Tools.ToolSpecification databaseQueryToolSpecification = Tools.ToolSpecification.builder()
.functionName("get-employee-details")
.functionDescription("Get employee details from the database")
.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()
)
.toolDefinition(new DBQueryFunction())
.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) {
// 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());
}
}
Run this full example and 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
[Result of executing tool 'current-weather']: Currently Bengaluru's weather is nice.
[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}
::::
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.
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:
{
"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.
Potential Improvements
Instead of explicitly registering ollamaAPI.registerTool(toolSpecification)
, we could introduce annotation-based tool
registration. For example:
@ToolSpec(name = "current-fuel-price", desc = "Get current fuel price")
public 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";
}
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:
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.