feat(provider.ollama): add native tool calling support for Ollama API

- Add IOllamaTool and IOllamaToolCall types for native function calling
- Add think parameter to IOllamaModelOptions for reasoning models (GPT-OSS, QwQ)
- Add tools parameter to IOllamaChatOptions
- Add toolCalls to response interfaces (IOllamaStreamChunk, IOllamaChatResponse)
- Update chat(), chatStreamResponse(), collectStreamResponse(), chatWithOptions() to support native tools
- Parse tool_calls from Ollama API responses
- Add support for tool message role in conversation history
This commit is contained in:
2026-01-20 02:39:28 +00:00
parent 7cb9bc24dc
commit 1156320546

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@@ -26,6 +26,39 @@ export interface IOllamaModelOptions {
num_predict?: number; // Max tokens to predict num_predict?: number; // Max tokens to predict
stop?: string[]; // Stop sequences stop?: string[]; // Stop sequences
seed?: number; // Random seed for reproducibility seed?: number; // Random seed for reproducibility
think?: boolean; // Enable thinking/reasoning mode (for GPT-OSS, QwQ, etc.)
}
/**
* JSON Schema tool definition for Ollama native tool calling
* @see https://docs.ollama.com/capabilities/tool-calling
*/
export interface IOllamaTool {
type: 'function';
function: {
name: string;
description: string;
parameters: {
type: 'object';
properties: Record<string, {
type: string;
description?: string;
enum?: string[];
}>;
required?: string[];
};
};
}
/**
* Tool call returned by model in native tool calling mode
*/
export interface IOllamaToolCall {
function: {
name: string;
arguments: Record<string, unknown>;
index?: number;
};
} }
export interface IOllamaProviderOptions { export interface IOllamaProviderOptions {
@@ -43,6 +76,7 @@ export interface IOllamaChatOptions extends ChatOptions {
options?: IOllamaModelOptions; // Per-request model options options?: IOllamaModelOptions; // Per-request model options
timeout?: number; // Per-request timeout in ms timeout?: number; // Per-request timeout in ms
model?: string; // Per-request model override model?: string; // Per-request model override
tools?: IOllamaTool[]; // Available tools for native function calling
// images is inherited from ChatOptions // images is inherited from ChatOptions
} }
@@ -52,6 +86,7 @@ export interface IOllamaChatOptions extends ChatOptions {
export interface IOllamaStreamChunk { export interface IOllamaStreamChunk {
content: string; content: string;
thinking?: string; // For models with extended thinking thinking?: string; // For models with extended thinking
toolCalls?: IOllamaToolCall[]; // Tool calls in streaming mode
done: boolean; done: boolean;
stats?: { stats?: {
totalDuration?: number; totalDuration?: number;
@@ -64,6 +99,7 @@ export interface IOllamaStreamChunk {
*/ */
export interface IOllamaChatResponse extends ChatResponse { export interface IOllamaChatResponse extends ChatResponse {
thinking?: string; thinking?: string;
toolCalls?: IOllamaToolCall[]; // Tool calls from model (native tool calling)
stats?: { stats?: {
totalDuration?: number; totalDuration?: number;
evalCount?: number; evalCount?: number;
@@ -233,18 +269,26 @@ export class OllamaProvider extends MultiModalModel {
userMessage, userMessage,
]; ];
// Build request body - include think parameter if set
const requestBody: Record<string, unknown> = {
model: this.model,
messages: messages,
stream: false,
options: this.defaultOptions,
};
// Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
if (this.defaultOptions.think !== undefined) {
requestBody.think = this.defaultOptions.think;
}
// Make API call to Ollama with defaultOptions and timeout // Make API call to Ollama with defaultOptions and timeout
const response = await fetch(`${this.baseUrl}/api/chat`, { const response = await fetch(`${this.baseUrl}/api/chat`, {
method: 'POST', method: 'POST',
headers: { headers: {
'Content-Type': 'application/json', 'Content-Type': 'application/json',
}, },
body: JSON.stringify({ body: JSON.stringify(requestBody),
model: this.model,
messages: messages,
stream: false,
options: this.defaultOptions,
}),
signal: AbortSignal.timeout(this.defaultTimeout), signal: AbortSignal.timeout(this.defaultTimeout),
}); });
@@ -331,15 +375,28 @@ export class OllamaProvider extends MultiModalModel {
userMessage, userMessage,
]; ];
const response = await fetch(`${this.baseUrl}/api/chat`, { // Build request body with optional tools and think parameters
method: 'POST', const requestBody: Record<string, unknown> = {
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model, model,
messages, messages,
stream: true, stream: true,
options: modelOptions, options: modelOptions,
}), };
// Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
if (modelOptions.think !== undefined) {
requestBody.think = modelOptions.think;
}
// Add tools for native function calling
if (optionsArg.tools && optionsArg.tools.length > 0) {
requestBody.tools = optionsArg.tools;
}
const response = await fetch(`${this.baseUrl}/api/chat`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(requestBody),
signal: AbortSignal.timeout(timeout), signal: AbortSignal.timeout(timeout),
}); });
@@ -364,9 +421,25 @@ export class OllamaProvider extends MultiModalModel {
if (!line.trim()) continue; if (!line.trim()) continue;
try { try {
const json = JSON.parse(line); const json = JSON.parse(line);
// Parse tool_calls from response
let toolCalls: IOllamaToolCall[] | undefined;
if (json.message?.tool_calls && Array.isArray(json.message.tool_calls)) {
toolCalls = json.message.tool_calls.map((tc: any) => ({
function: {
name: tc.function?.name || '',
arguments: typeof tc.function?.arguments === 'string'
? JSON.parse(tc.function.arguments)
: tc.function?.arguments || {},
index: tc.index,
},
}));
}
yield { yield {
content: json.message?.content || '', content: json.message?.content || '',
thinking: json.message?.thinking, thinking: json.message?.thinking,
toolCalls,
done: json.done || false, done: json.done || false,
stats: json.done ? { stats: json.done ? {
totalDuration: json.total_duration, totalDuration: json.total_duration,
@@ -393,11 +466,13 @@ export class OllamaProvider extends MultiModalModel {
const stream = await this.chatStreamResponse(optionsArg); const stream = await this.chatStreamResponse(optionsArg);
let content = ''; let content = '';
let thinking = ''; let thinking = '';
let toolCalls: IOllamaToolCall[] = [];
let stats: IOllamaChatResponse['stats']; let stats: IOllamaChatResponse['stats'];
for await (const chunk of stream) { for await (const chunk of stream) {
if (chunk.content) content += chunk.content; if (chunk.content) content += chunk.content;
if (chunk.thinking) thinking += chunk.thinking; if (chunk.thinking) thinking += chunk.thinking;
if (chunk.toolCalls) toolCalls = toolCalls.concat(chunk.toolCalls);
if (chunk.stats) stats = chunk.stats; if (chunk.stats) stats = chunk.stats;
if (onChunk) onChunk(chunk); if (onChunk) onChunk(chunk);
} }
@@ -406,6 +481,7 @@ export class OllamaProvider extends MultiModalModel {
role: 'assistant' as const, role: 'assistant' as const,
message: content, message: content,
thinking: thinking || undefined, thinking: thinking || undefined,
toolCalls: toolCalls.length > 0 ? toolCalls : undefined,
stats, stats,
}; };
} }
@@ -418,8 +494,17 @@ export class OllamaProvider extends MultiModalModel {
const timeout = optionsArg.timeout || this.defaultTimeout; const timeout = optionsArg.timeout || this.defaultTimeout;
const modelOptions = { ...this.defaultOptions, ...optionsArg.options }; const modelOptions = { ...this.defaultOptions, ...optionsArg.options };
// Format history messages with optional images and reasoning // Format history messages with optional images, reasoning, and tool role
const historyMessages = optionsArg.messageHistory.map((msg) => { const historyMessages = optionsArg.messageHistory.map((msg) => {
// Handle tool result messages
if ((msg as any).role === 'tool') {
return {
role: 'tool',
content: msg.content,
tool_name: (msg as any).toolName,
};
}
const formatted: { role: string; content: string; images?: string[]; reasoning?: string } = { const formatted: { role: string; content: string; images?: string[]; reasoning?: string } = {
role: msg.role, role: msg.role,
content: msg.content, content: msg.content,
@@ -448,15 +533,28 @@ export class OllamaProvider extends MultiModalModel {
userMessage, userMessage,
]; ];
const response = await fetch(`${this.baseUrl}/api/chat`, { // Build request body with optional tools and think parameters
method: 'POST', const requestBody: Record<string, unknown> = {
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
model, model,
messages, messages,
stream: false, stream: false,
options: modelOptions, options: modelOptions,
}), };
// Add think parameter for reasoning models (GPT-OSS, QwQ, etc.)
if (modelOptions.think !== undefined) {
requestBody.think = modelOptions.think;
}
// Add tools for native function calling
if (optionsArg.tools && optionsArg.tools.length > 0) {
requestBody.tools = optionsArg.tools;
}
const response = await fetch(`${this.baseUrl}/api/chat`, {
method: 'POST',
headers: { 'Content-Type': 'application/json' },
body: JSON.stringify(requestBody),
signal: AbortSignal.timeout(timeout), signal: AbortSignal.timeout(timeout),
}); });
@@ -465,10 +563,26 @@ export class OllamaProvider extends MultiModalModel {
} }
const result = await response.json(); const result = await response.json();
// Parse tool_calls from response
let toolCalls: IOllamaToolCall[] | undefined;
if (result.message?.tool_calls && Array.isArray(result.message.tool_calls)) {
toolCalls = result.message.tool_calls.map((tc: any) => ({
function: {
name: tc.function?.name || '',
arguments: typeof tc.function?.arguments === 'string'
? JSON.parse(tc.function.arguments)
: tc.function?.arguments || {},
index: tc.index,
},
}));
}
return { return {
role: 'assistant' as const, role: 'assistant' as const,
message: result.message.content, message: result.message.content || '',
thinking: result.message.thinking, thinking: result.message.thinking,
toolCalls,
stats: { stats: {
totalDuration: result.total_duration, totalDuration: result.total_duration,
evalCount: result.eval_count, evalCount: result.eval_count,