Files
flynn/src/models/local/llamacpp.test.ts
T
William Valentin c01de7d097 feat: native tool calling message normalization for Ollama and llama.cpp
- ollama.ts: add normalizeMessagesForOllama() converting Anthropic-style
  tool_use/tool_result blocks to Ollama's native tool_calls + role:tool format
- llamacpp.ts: add normalizeMessagesForLlamaCpp() with hybrid approach —
  assistant tool_calls in native format, but tool results as structured user
  messages (many GGUF templates silently drop role:tool messages)
- llamacpp.ts: add configurable requestTimeout with AbortController (default 3min)
- Both use fast-path when no tool blocks are present (zero overhead)
- Full test coverage for both normalizers: plain text passthrough, tool_use
  conversion, tool_result mapping, multi-tool round trips, error results
2026-02-11 09:33:21 -08:00

513 lines
14 KiB
TypeScript

import { describe, it, expect, vi, beforeEach, afterEach } from 'vitest';
import { LlamaCppClient, normalizeMessagesForLlamaCpp } from './llamacpp.js';
import type { ChatStreamEvent, Message } from '../types.js';
describe('LlamaCppClient', () => {
const mockFetch = vi.fn();
beforeEach(() => {
mockFetch.mockReset();
vi.stubGlobal('fetch', mockFetch);
});
afterEach(() => {
vi.unstubAllGlobals();
});
it('sends messages and returns response', async () => {
mockFetch.mockResolvedValue({
ok: true,
json: () => Promise.resolve({
choices: [{ message: { content: 'Hello from llama.cpp!' } }],
usage: { prompt_tokens: 10, completion_tokens: 5 },
}),
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
const response = await client.chat({
messages: [{ role: 'user', content: 'Hello' }],
});
expect(response.content).toBe('Hello from llama.cpp!');
expect(response.usage.inputTokens).toBe(10);
expect(response.usage.outputTokens).toBe(5);
});
it('streams responses via SSE', async () => {
const chunks = [
'data: {"choices":[{"delta":{"content":"Hello"}}]}\n\n',
'data: {"choices":[{"delta":{"content":" world"}}]}\n\n',
'data: {"choices":[{}],"usage":{"prompt_tokens":5,"completion_tokens":2}}\n\n',
'data: [DONE]\n\n',
];
const encoder = new TextEncoder();
let chunkIndex = 0;
const mockStream = new ReadableStream({
pull(controller) {
if (chunkIndex < chunks.length) {
controller.enqueue(encoder.encode(chunks[chunkIndex]));
chunkIndex++;
} else {
controller.close();
}
},
});
mockFetch.mockResolvedValue({
ok: true,
body: mockStream,
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
const events: ChatStreamEvent[] = [];
for await (const event of client.chatStream({
messages: [{ role: 'user', content: 'Hi' }],
})) {
events.push(event);
}
expect(events).toHaveLength(3);
expect(events[0]).toEqual({ type: 'content', content: 'Hello' });
expect(events[1]).toEqual({ type: 'content', content: ' world' });
expect(events[2]).toEqual({
type: 'done',
usage: { inputTokens: 5, outputTokens: 2 },
});
});
it('throws clear error when server not running', async () => {
mockFetch.mockRejectedValue(new TypeError('fetch failed'));
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
await expect(client.chat({
messages: [{ role: 'user', content: 'Hello' }],
})).rejects.toThrow('llama-server not running at http://localhost:8080');
});
it('passes tools in request body', async () => {
mockFetch.mockResolvedValue({
ok: true,
json: () => Promise.resolve({
choices: [{ message: { content: 'I can help with that.' } }],
usage: { prompt_tokens: 12, completion_tokens: 6 },
}),
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
await client.chat({
messages: [{ role: 'user', content: 'Run ls' }],
tools: [{
name: 'shell.exec',
description: 'Run shell',
input_schema: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
}],
});
const requestBody = JSON.parse(mockFetch.mock.calls[0][1].body);
expect(requestBody.tools).toEqual([{
type: 'function',
function: {
name: 'shell.exec',
description: 'Run shell',
parameters: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
},
}]);
});
it('parses tool_calls from response', async () => {
mockFetch.mockResolvedValue({
ok: true,
json: () => Promise.resolve({
choices: [{
message: {
content: null,
tool_calls: [{
id: 'call_123',
type: 'function',
function: { name: 'shell.exec', arguments: '{"command":"ls"}' },
}],
},
finish_reason: 'tool_calls',
}],
usage: { prompt_tokens: 15, completion_tokens: 8 },
}),
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
const response = await client.chat({
messages: [{ role: 'user', content: 'List files' }],
tools: [{
name: 'shell.exec',
description: 'Run shell',
input_schema: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
}],
});
expect(response.stopReason).toBe('tool_use');
expect(response.toolCalls).toHaveLength(1);
expect(response.toolCalls![0]).toEqual({
id: 'call_123',
name: 'shell.exec',
args: { command: 'ls' },
});
expect(response.usage.inputTokens).toBe(15);
expect(response.usage.outputTokens).toBe(8);
});
it('does not send tools when none provided', async () => {
mockFetch.mockResolvedValue({
ok: true,
json: () => Promise.resolve({
choices: [{ message: { content: 'Hello!' } }],
usage: { prompt_tokens: 5, completion_tokens: 2 },
}),
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
await client.chat({
messages: [{ role: 'user', content: 'Hello' }],
});
const requestBody = JSON.parse(mockFetch.mock.calls[0][1].body);
expect(requestBody.tools).toBeUndefined();
});
it('streaming: accumulates and yields tool_calls from deltas', async () => {
const chunks = [
'data: {"choices":[{"delta":{"tool_calls":[{"index":0,"id":"call_1","type":"function","function":{"name":"shell.exec"}}]}}]}\n\n',
'data: {"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"{\\"comma"}}]}}]}\n\n',
'data: {"choices":[{"delta":{"tool_calls":[{"index":0,"function":{"arguments":"nd\\":\\"ls\\"}"}}]}}]}\n\n',
'data: {"choices":[{}],"usage":{"prompt_tokens":10,"completion_tokens":5}}\n\n',
'data: [DONE]\n\n',
];
const encoder = new TextEncoder();
let chunkIndex = 0;
const mockStream = new ReadableStream({
pull(controller) {
if (chunkIndex < chunks.length) {
controller.enqueue(encoder.encode(chunks[chunkIndex]));
chunkIndex++;
} else {
controller.close();
}
},
});
mockFetch.mockResolvedValue({
ok: true,
body: mockStream,
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
const events: ChatStreamEvent[] = [];
for await (const event of client.chatStream({
messages: [{ role: 'user', content: 'Run ls' }],
tools: [{
name: 'shell.exec',
description: 'Run shell',
input_schema: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
}],
})) {
events.push(event);
}
// Should have a tool_use event and a done event
const toolUseEvents = events.filter(e => e.type === 'tool_use');
const doneEvents = events.filter(e => e.type === 'done');
expect(toolUseEvents).toHaveLength(1);
expect(toolUseEvents[0].toolCall).toEqual({
id: 'call_1',
name: 'shell.exec',
args: { command: 'ls' },
});
expect(doneEvents).toHaveLength(1);
expect(doneEvents[0].usage).toEqual({
inputTokens: 10,
outputTokens: 5,
});
});
it('streaming: passes tools in request body', async () => {
const chunks = [
'data: {"choices":[{"delta":{"content":"Hi"}}]}\n\n',
'data: {"choices":[{}],"usage":{"prompt_tokens":3,"completion_tokens":1}}\n\n',
'data: [DONE]\n\n',
];
const encoder = new TextEncoder();
let chunkIndex = 0;
const mockStream = new ReadableStream({
pull(controller) {
if (chunkIndex < chunks.length) {
controller.enqueue(encoder.encode(chunks[chunkIndex]));
chunkIndex++;
} else {
controller.close();
}
},
});
mockFetch.mockResolvedValue({
ok: true,
body: mockStream,
});
const client = new LlamaCppClient({
endpoint: 'http://localhost:8080',
model: 'test-model',
});
// Consume the stream to trigger the fetch call
const events: ChatStreamEvent[] = [];
for await (const event of client.chatStream({
messages: [{ role: 'user', content: 'Hi' }],
tools: [{
name: 'shell.exec',
description: 'Run shell',
input_schema: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
}],
})) {
events.push(event);
}
const requestBody = JSON.parse(mockFetch.mock.calls[0][1].body);
expect(requestBody.tools).toEqual([{
type: 'function',
function: {
name: 'shell.exec',
description: 'Run shell',
parameters: {
type: 'object',
properties: { command: { type: 'string' } },
required: ['command'],
},
},
}]);
expect(requestBody.stream).toBe(true);
});
});
describe('normalizeMessagesForLlamaCpp', () => {
it('passes plain text messages through', () => {
const messages: Message[] = [
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
];
const result = normalizeMessagesForLlamaCpp('System prompt', messages);
expect(result).toEqual([
{ role: 'system', content: 'System prompt' },
{ role: 'user', content: 'Hello' },
{ role: 'assistant', content: 'Hi there' },
]);
});
it('converts assistant tool_use blocks to OpenAI tool_calls format', () => {
const messages: Message[] = [
{ role: 'user', content: 'Search for news' },
{
role: 'assistant',
content: [
{ type: 'text', text: 'Searching...' },
{ type: 'tool_use', id: 'call_1', name: 'web.search', input: { query: 'news' } },
] as any,
},
];
const result = normalizeMessagesForLlamaCpp(undefined, messages);
expect(result).toHaveLength(2);
expect(result[1]).toEqual({
role: 'assistant',
content: 'Searching...',
tool_calls: [{
id: 'call_1',
type: 'function',
function: {
name: 'web.search',
arguments: '{"query":"news"}',
},
}],
});
});
it('converts user tool_result blocks to user messages with text formatting', () => {
const messages: Message[] = [
{ role: 'user', content: 'Search' },
{
role: 'assistant',
content: [
{ type: 'tool_use', id: 'call_1', name: 'web.search', input: { query: 'news' } },
] as any,
},
{
role: 'user',
content: [
{ type: 'tool_result', tool_use_id: 'call_1', content: 'Results here', is_error: false },
] as any,
},
];
const result = normalizeMessagesForLlamaCpp(undefined, messages);
expect(result).toHaveLength(3);
expect(result[2]).toEqual({
role: 'user',
content: '[Tool "web.search" result]\nResults here',
});
});
it('handles multiple tool results in a single user message', () => {
const messages: Message[] = [
{ role: 'user', content: 'Do two things' },
{
role: 'assistant',
content: [
{ type: 'tool_use', id: 'call_a', name: 'tool.a', input: {} },
{ type: 'tool_use', id: 'call_b', name: 'tool.b', input: { x: 1 } },
] as any,
},
{
role: 'user',
content: [
{ type: 'tool_result', tool_use_id: 'call_a', content: 'A result' },
{ type: 'tool_result', tool_use_id: 'call_b', content: 'B result' },
] as any,
},
];
const result = normalizeMessagesForLlamaCpp(undefined, messages);
expect(result[1].tool_calls).toHaveLength(2);
expect(result[1].tool_calls![0].id).toBe('call_a');
expect(result[1].tool_calls![1].function.arguments).toBe('{"x":1}');
// Multiple results merged into one user message
expect(result).toHaveLength(3);
expect(result[2]).toEqual({
role: 'user',
content: '[Tool "tool.a" result]\nA result\n\n[Tool "tool.b" result]\nB result',
});
});
it('marks error results in text formatting', () => {
const messages: Message[] = [
{ role: 'user', content: 'Do it' },
{
role: 'assistant',
content: [
{ type: 'tool_use', id: 'call_1', name: 'file.read', input: { path: '/tmp/x' } },
] as any,
},
{
role: 'user',
content: [
{ type: 'tool_result', tool_use_id: 'call_1', content: 'File not found', is_error: true },
] as any,
},
];
const result = normalizeMessagesForLlamaCpp(undefined, messages);
expect(result[2]).toEqual({
role: 'user',
content: '[Tool "file.read" result (error)]\nFile not found',
});
});
it('handles full tool round-trip conversation', () => {
const messages: Message[] = [
{ role: 'user', content: 'What is the weather?' },
{
role: 'assistant',
content: [
{ type: 'text', text: 'Checking...' },
{ type: 'tool_use', id: 'tc_0', name: 'weather.get', input: { city: 'NYC' } },
] as any,
},
{
role: 'user',
content: [
{ type: 'tool_result', tool_use_id: 'tc_0', content: 'Sunny, 72F' },
] as any,
},
{ role: 'assistant', content: 'The weather in NYC is sunny, 72F.' },
];
const result = normalizeMessagesForLlamaCpp('You are helpful.', messages);
expect(result).toHaveLength(5);
expect(result[0]).toEqual({ role: 'system', content: 'You are helpful.' });
expect(result[1]).toEqual({ role: 'user', content: 'What is the weather?' });
expect(result[2]).toEqual({
role: 'assistant',
content: 'Checking...',
tool_calls: [{
id: 'tc_0',
type: 'function',
function: { name: 'weather.get', arguments: '{"city":"NYC"}' },
}],
});
expect(result[3]).toEqual({
role: 'user',
content: '[Tool "weather.get" result]\nSunny, 72F',
});
expect(result[4]).toEqual({ role: 'assistant', content: 'The weather in NYC is sunny, 72F.' });
});
});