Compare commits
17 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
| 5826573d5c | |||
| 797a40a566 | |||
| 7308927a3c | |||
| 04f038ba65 | |||
| d42f58d710 | |||
| 878a8794ee | |||
| 3f1289d993 | |||
| 077f75cdd9 | |||
| 566d84fd7a | |||
| 4230b534fc | |||
| 119f8472f2 | |||
| 9c04e58c63 | |||
| 7fbb42c26a | |||
| be08db8e2c | |||
| 497f051c62 | |||
| 62fbe73b22 | |||
| d53b1c6328 |
@@ -119,7 +119,7 @@ const ai = new Ai({
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system: 'You are a helpful assistant.',
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compress: {max: 90_000, min: 50_000}, // Compress chat history to min tokens when max is reached
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temperature: 0.8,
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max_tokens: 100_000,
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maxTokens: 100_000,
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memoryModel: 'gpt-4o', // Cheap model for managing memories in background, defaults to current model
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models: {
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'claude-3-5-sonnet': {proto: 'anthropic', token: process.env.ANTHROPIC_TOKEN},
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@@ -186,7 +186,7 @@ console.log(chunks);
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// Manually compile history into memories at end of conversation
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// Happens automatically when coverstaions are compressed
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await ai.language.updateMemory(history, memory);
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await ai.language.memorize(history, memory);
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// Summarize text
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const summary = await ai.language.summarize(longText, 200);
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522
package-lock.json
generated
522
package-lock.json
generated
@@ -1,12 +1,12 @@
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{
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"name": "@ztimson/ai-utils",
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"version": "1.2.6",
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"version": "1.5.0",
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"lockfileVersion": 3,
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"requires": true,
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"packages": {
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"": {
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"name": "@ztimson/ai-utils",
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"version": "1.2.6",
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"version": "1.5.0",
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"license": "MIT",
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"dependencies": {
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"@anthropic-ai/sdk": "^0.102.0",
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@@ -16,6 +16,7 @@
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"@ztimson/utils": "^0.29.4",
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"cheerio": "^1.2.0",
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"openai": "^6.42.0",
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"pdf-parse": "^2.4.5",
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"tesseract.js": "^7.0.0"
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@@ -56,39 +57,12 @@
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@@ -577,16 +551,6 @@
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"url": "https://opencollective.com/libvips"
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"integrity": "sha512-DlOzet0HO7OEnmUmB6wWGJrrdvbyJKftI1bhMitK7O2N8W2gc757yyYBbINy9IDafXAV9wmKr9t7xsTaNKRG5Q==",
|
||||
"license": "Apache-2.0",
|
||||
"engines": {
|
||||
"node": ">=20.16.0 || >=22.3.0"
|
||||
},
|
||||
"optionalDependencies": {
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||||
"@napi-rs/canvas": "^0.1.80"
|
||||
}
|
||||
},
|
||||
"node_modules/picocolors": {
|
||||
"version": "1.1.1",
|
||||
"resolved": "https://registry.npmjs.org/picocolors/-/picocolors-1.1.1.tgz",
|
||||
@@ -3272,9 +3381,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/postcss": {
|
||||
"version": "8.5.25",
|
||||
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.25.tgz",
|
||||
"integrity": "sha512-DTPx3RWSSnWyzLxQnlH0rJP+EW5ekl16ZU4/psbIhA0e53kJfdgaN5vKM+xP7yJtXVu+nfdVFmlgFDEKAe4Pyw==",
|
||||
"version": "8.5.26",
|
||||
"resolved": "https://registry.npmjs.org/postcss/-/postcss-8.5.26.tgz",
|
||||
"integrity": "sha512-u82N74LFzG8ca+dD8puPnplTXoGH4fTPpVGuIbt36G3qvNlkvfD0lEAZSxaly3KX8TS/L1A1gsCEmvKmBcVbkQ==",
|
||||
"dev": true,
|
||||
"funding": [
|
||||
{
|
||||
@@ -3292,7 +3401,7 @@
|
||||
],
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"nanoid": "^3.3.16",
|
||||
"nanoid": "^3.3.17",
|
||||
"picocolors": "^1.1.1",
|
||||
"source-map-js": "^1.2.1"
|
||||
},
|
||||
@@ -3434,13 +3543,13 @@
|
||||
"license": "BSD-3-Clause"
|
||||
},
|
||||
"node_modules/rolldown": {
|
||||
"version": "1.1.5",
|
||||
"resolved": "https://registry.npmjs.org/rolldown/-/rolldown-1.1.5.tgz",
|
||||
"integrity": "sha512-t9z29cJjXf/vxQ8dyhCSpt6H6aSwHTk8cT5I3iy6SMXuFpk5mB6PL6XfC8PCwrPTx93udwKUm9HRteAlTGBLiA==",
|
||||
"version": "1.2.4",
|
||||
"resolved": "https://registry.npmjs.org/rolldown/-/rolldown-1.2.4.tgz",
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||||
"integrity": "sha512-rSr7irW0K7QRWzjdJXqZowkcRdDtjRduh43rBltnVKd0VFq839l1lJoDvGJb6gl7+4rTTCrPWu+YfujUL8Ug7w==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"@oxc-project/types": "=0.139.0",
|
||||
"@oxc-project/types": "=0.144.0",
|
||||
"@rolldown/pluginutils": "^1.0.0"
|
||||
},
|
||||
"bin": {
|
||||
@@ -3450,21 +3559,20 @@
|
||||
"node": "^20.19.0 || >=22.12.0"
|
||||
},
|
||||
"optionalDependencies": {
|
||||
"@rolldown/binding-android-arm64": "1.1.5",
|
||||
"@rolldown/binding-darwin-arm64": "1.1.5",
|
||||
"@rolldown/binding-darwin-x64": "1.1.5",
|
||||
"@rolldown/binding-freebsd-x64": "1.1.5",
|
||||
"@rolldown/binding-linux-arm-gnueabihf": "1.1.5",
|
||||
"@rolldown/binding-linux-arm64-gnu": "1.1.5",
|
||||
"@rolldown/binding-linux-arm64-musl": "1.1.5",
|
||||
"@rolldown/binding-linux-ppc64-gnu": "1.1.5",
|
||||
"@rolldown/binding-linux-s390x-gnu": "1.1.5",
|
||||
"@rolldown/binding-linux-x64-gnu": "1.1.5",
|
||||
"@rolldown/binding-linux-x64-musl": "1.1.5",
|
||||
"@rolldown/binding-openharmony-arm64": "1.1.5",
|
||||
"@rolldown/binding-wasm32-wasi": "1.1.5",
|
||||
"@rolldown/binding-win32-arm64-msvc": "1.1.5",
|
||||
"@rolldown/binding-win32-x64-msvc": "1.1.5"
|
||||
"@rolldown/binding-android-arm64": "1.2.4",
|
||||
"@rolldown/binding-darwin-arm64": "1.2.4",
|
||||
"@rolldown/binding-darwin-x64": "1.2.4",
|
||||
"@rolldown/binding-freebsd-x64": "1.2.4",
|
||||
"@rolldown/binding-linux-arm-gnueabihf": "1.2.4",
|
||||
"@rolldown/binding-linux-arm64-gnu": "1.2.4",
|
||||
"@rolldown/binding-linux-arm64-musl": "1.2.4",
|
||||
"@rolldown/binding-linux-ppc64-gnu": "1.2.4",
|
||||
"@rolldown/binding-linux-s390x-gnu": "1.2.4",
|
||||
"@rolldown/binding-linux-x64-gnu": "1.2.4",
|
||||
"@rolldown/binding-linux-x64-musl": "1.2.4",
|
||||
"@rolldown/binding-openharmony-arm64": "1.2.4",
|
||||
"@rolldown/binding-win32-arm64-msvc": "1.2.4",
|
||||
"@rolldown/binding-win32-x64-msvc": "1.2.4"
|
||||
}
|
||||
},
|
||||
"node_modules/safe-buffer": {
|
||||
@@ -4021,16 +4129,16 @@
|
||||
}
|
||||
},
|
||||
"node_modules/vite": {
|
||||
"version": "8.1.5",
|
||||
"resolved": "https://registry.npmjs.org/vite/-/vite-8.1.5.tgz",
|
||||
"integrity": "sha512-7ULLwsCdYx/nRyrpiEwvqb5TFHrMVZyBt+rg/OAXT7rgj/z+DtTDyKFeLAdDkubDVDKD8jOsndmy7m55XcfUsw==",
|
||||
"version": "8.2.1",
|
||||
"resolved": "https://registry.npmjs.org/vite/-/vite-8.2.1.tgz",
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"integrity": "sha512-EU/eS7BH3XROHh2YnBefjM6DBKA6ZeMZEYQbj7NLWg5wHYlhB8B/Mayd5XsgWq+NFYccDOTemRpdETWR6Ka/lw==",
|
||||
"dev": true,
|
||||
"license": "MIT",
|
||||
"dependencies": {
|
||||
"lightningcss": "^1.32.0",
|
||||
"lightningcss": "^1.33.0",
|
||||
"picomatch": "^4.0.5",
|
||||
"postcss": "^8.5.17",
|
||||
"rolldown": "~1.1.5",
|
||||
"postcss": "^8.5.25",
|
||||
"rolldown": "~1.2.1",
|
||||
"tinyglobby": "^0.2.17"
|
||||
},
|
||||
"bin": {
|
||||
@@ -4047,7 +4155,7 @@
|
||||
},
|
||||
"peerDependencies": {
|
||||
"@types/node": "^20.19.0 || >=22.12.0",
|
||||
"@vitejs/devtools": "^0.3.0",
|
||||
"@vitejs/devtools": "^0.4.0",
|
||||
"esbuild": "^0.27.0 || ^0.28.0",
|
||||
"jiti": ">=1.21.0",
|
||||
"less": "^4.0.0",
|
||||
@@ -4132,9 +4240,9 @@
|
||||
"license": "MIT"
|
||||
},
|
||||
"node_modules/wasm-feature-detect": {
|
||||
"version": "1.8.0",
|
||||
"resolved": "https://registry.npmjs.org/wasm-feature-detect/-/wasm-feature-detect-1.8.0.tgz",
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||||
"integrity": "sha512-zksaLKM2fVlnB5jQQDqKXXwYHLQUVH9es+5TOOHwGOVJOCeRBCiPjwSg+3tN2AdTCzjgli4jijCH290kXb/zWQ==",
|
||||
"version": "1.9.0",
|
||||
"resolved": "https://registry.npmjs.org/wasm-feature-detect/-/wasm-feature-detect-1.9.0.tgz",
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||||
"integrity": "sha512-zonE+xlIIYtxPy++L24ow0hAD8CICb4+FgPyROd3buyXIqsJvUEDkBgfCCoXOd1Hu3DUr0GOfnPIdcGV+YpNaA==",
|
||||
"license": "Apache-2.0"
|
||||
},
|
||||
"node_modules/webidl-conversions": {
|
||||
|
||||
@@ -1,6 +1,6 @@
|
||||
{
|
||||
"name": "@ztimson/ai-utils",
|
||||
"version": "1.3.3",
|
||||
"version": "1.6.1",
|
||||
"description": "AI Utility library",
|
||||
"author": "Zak Timson",
|
||||
"license": "MIT",
|
||||
@@ -26,12 +26,13 @@
|
||||
},
|
||||
"dependencies": {
|
||||
"@anthropic-ai/sdk": "^0.102.0",
|
||||
"@tensorflow/tfjs": "^4.22.0",
|
||||
"@huggingface/transformers": "^4.2.0",
|
||||
"@tensorflow/tfjs": "^4.22.0",
|
||||
"@ztimson/node-utils": "^1.0.7",
|
||||
"@ztimson/utils": "^0.29.4",
|
||||
"cheerio": "^1.2.0",
|
||||
"openai": "^6.42.0",
|
||||
"pdf-parse": "^2.4.5",
|
||||
"tesseract.js": "^7.0.0"
|
||||
},
|
||||
"devDependencies": {
|
||||
|
||||
231
src/antrhopic.ts
231
src/antrhopic.ts
@@ -1,65 +1,63 @@
|
||||
import {Anthropic as anthropic} from '@anthropic-ai/sdk';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse} from '@ztimson/utils';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, makeArray} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMProvider} from './provider.ts';
|
||||
import {TokenPool} from './token-pool.ts';
|
||||
import {convertSchema} from './tools.ts';
|
||||
|
||||
export class Anthropic extends LLMProvider {
|
||||
client!: anthropic;
|
||||
private clients = new Map<string, anthropic>();
|
||||
tokenPool!: TokenPool;
|
||||
|
||||
constructor(public readonly ai: Ai, public readonly apiToken: string, public model: string) {
|
||||
constructor(public readonly ai: Ai, public readonly apiToken: string | string[], public model: string) {
|
||||
super();
|
||||
this.client = new anthropic({apiKey: apiToken});
|
||||
this.tokenPool = new TokenPool(...makeArray(apiToken).filter(Boolean));
|
||||
}
|
||||
|
||||
private toStandard(history: any[]): LLMMessage[] {
|
||||
const timestamp = Date.now();
|
||||
const messages: LLMMessage[] = [];
|
||||
for(let h of history) {
|
||||
if(typeof h.content == 'string') {
|
||||
messages.push(<any>{timestamp, ...h});
|
||||
} else {
|
||||
const textContent = h.content?.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||
if(textContent) messages.push({role: h.role, content: textContent, timestamp: timestamp});
|
||||
h.content.forEach((c: any) => {
|
||||
if(c.type == 'tool_use') {
|
||||
messages.push({role: 'tool', id: c.id, name: c.name, args: c.input, timestamp: c.timestamp, content: undefined});
|
||||
} else if(c.type == 'tool_result') {
|
||||
const m: any = messages.findLast(m => (<any>m).id == c.tool_use_id);
|
||||
if(m) m[c.is_error ? 'error' : 'content'] = c.content;
|
||||
}
|
||||
});
|
||||
}
|
||||
private getClient(token: string): anthropic {
|
||||
let client = this.clients.get(token);
|
||||
if(!client) {
|
||||
client = new anthropic({apiKey: token});
|
||||
this.clients.set(token, client);
|
||||
}
|
||||
return messages;
|
||||
return client;
|
||||
}
|
||||
|
||||
private fromStandard(history: LLMMessage[]): any[] {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
if(history[i].role == 'tool') {
|
||||
const h: any = history[i];
|
||||
history.splice(i, 1,
|
||||
private toWireContent(content: any): any {
|
||||
if(!Array.isArray(content)) return content;
|
||||
return content.map(c => c.type === 'image'
|
||||
? {type: 'image', source: {type: 'base64', media_type: c.mime, data: c.data}}
|
||||
: {type: 'text', text: c.text});
|
||||
}
|
||||
|
||||
/** Convert standard history -> Anthropic wire format */
|
||||
private toWire(history: LLMMessage[]): any[] {
|
||||
const wire: any[] = [];
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool') {
|
||||
wire.push(
|
||||
{role: 'assistant', content: [{type: 'tool_use', id: h.id, name: h.name, input: h.args}]},
|
||||
{role: 'user', content: [{type: 'tool_result', tool_use_id: h.id, is_error: !!h.error, content: h.error || h.content}]}
|
||||
)
|
||||
i++;
|
||||
{role: 'user', content: [{type: 'tool_result', tool_use_id: h.id, is_error: !!h.error, content: h.error || h.content || ''}]}
|
||||
);
|
||||
} else {
|
||||
wire.push({role: h.role, content: this.toWireContent(h.content)});
|
||||
}
|
||||
}
|
||||
return history;
|
||||
return wire;
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res) => {
|
||||
let history = this.fromStandard([
|
||||
...(options.history || []).filter(h => h.role !== 'system'),
|
||||
{role: 'user', content: message, timestamp: Date.now()}
|
||||
]);
|
||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||
if(!options.history) options.history = [];
|
||||
const history = options.history;
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
max_tokens: options.max_tokens || this.ai.options.llm?.max_tokens || 4096,
|
||||
max_tokens: options.maxTokens || this.ai.options.llm?.maxTokens || 4096,
|
||||
system: options.system || this.ai.options.llm?.system || '',
|
||||
temperature: options.temperature || this.ai.options.llm?.temperature || undefined,
|
||||
tools: tools.map(t => ({
|
||||
@@ -69,100 +67,97 @@ export class Anthropic extends LLMProvider {
|
||||
type: 'object',
|
||||
properties: t.args ? objectMap(t.args, (key, value) => ({...value, required: undefined})) : {},
|
||||
required: t.args ? Object.entries(t.args).filter(t => t[1].required).map(t => t[0]) : []
|
||||
},
|
||||
fn: undefined
|
||||
}
|
||||
})),
|
||||
messages: history,
|
||||
stream: !!options.stream,
|
||||
};
|
||||
|
||||
// Add structured output support
|
||||
if(options.schema) {
|
||||
requestParams.output_config = {
|
||||
format: {
|
||||
type: 'json_schema',
|
||||
schema: convertSchema(options.schema)
|
||||
}
|
||||
};
|
||||
requestParams.output_config = {format: {type: 'json_schema', schema: convertSchema(options.schema)}};
|
||||
}
|
||||
|
||||
let resp: any, terminal = false;
|
||||
do {
|
||||
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||
resp = await this.client.messages.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
try {
|
||||
let terminal = false;
|
||||
do {
|
||||
requestParams.messages = this.toWire(history.filter(h => h.role !== 'system'));
|
||||
|
||||
// Streaming mode
|
||||
if(options.stream) {
|
||||
resp.content = [];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.type === 'content_block_start') {
|
||||
if(chunk.content_block.type === 'text') {
|
||||
resp.content.push({type: 'text', text: ''});
|
||||
} else if(chunk.content_block.type === 'tool_use') {
|
||||
resp.content.push({type: 'tool_use', id: chunk.content_block.id, name: chunk.content_block.name, input: <any>''});
|
||||
const callStart = Date.now();
|
||||
const resp: any = await this.tokenPool.run(token => this.getClient(token).messages.create(requestParams)).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(requestParams.messages, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
|
||||
let usage: any, content: any[] = [];
|
||||
if(options.stream) {
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.type === 'content_block_start') {
|
||||
if(chunk.content_block.type === 'text') content.push({type: 'text', text: ''});
|
||||
else if(chunk.content_block.type === 'tool_use') content.push({type: 'tool_use', id: chunk.content_block.id, name: chunk.content_block.name, input: ''});
|
||||
} else if(chunk.type === 'content_block_delta') {
|
||||
if(chunk.delta.type === 'text_delta') {
|
||||
content.at(-1).text += chunk.delta.text;
|
||||
options.stream({text: chunk.delta.text});
|
||||
} else if(chunk.delta.type === 'input_json_delta') {
|
||||
content.at(-1).input += chunk.delta.partial_json;
|
||||
}
|
||||
} else if(chunk.type === 'content_block_stop') {
|
||||
const last = content.at(-1);
|
||||
if(last?.type === 'tool_use') last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
} else if(chunk.type === 'message_delta') {
|
||||
if(chunk.usage) usage = chunk.usage;
|
||||
} else if(chunk.type === 'message_stop') {
|
||||
break;
|
||||
}
|
||||
} else if(chunk.type === 'content_block_delta') {
|
||||
if(chunk.delta.type === 'text_delta') {
|
||||
const text = chunk.delta.text;
|
||||
resp.content.at(-1).text += text;
|
||||
options.stream({text});
|
||||
} else if(chunk.delta.type === 'input_json_delta') {
|
||||
resp.content.at(-1).input += chunk.delta.partial_json;
|
||||
}
|
||||
} else if(chunk.type === 'content_block_stop') {
|
||||
const last = resp.content.at(-1);
|
||||
if(last?.input != null) last.input = last.input ? JSONAttemptParse(last.input, {}) : {};
|
||||
} else if(chunk.type === 'message_stop') {
|
||||
break;
|
||||
}
|
||||
} else {
|
||||
usage = resp.usage;
|
||||
content = resp.content;
|
||||
}
|
||||
}
|
||||
const duration = Date.now() - callStart;
|
||||
const tps = usage?.output_tokens && duration > 0 ? usage.output_tokens / (duration / 1000) : 0;
|
||||
|
||||
// Run tools
|
||||
const toolCalls = resp.content.filter((c: any) => c.type === 'tool_use');
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
history.push({role: 'assistant', content: resp.content, timestamp: Date.now()});
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools.find(findByProp('name', toolCall.name));
|
||||
if(options.stream) options.stream({tool: toolCall.name});
|
||||
if(!tool) return {tool_use_id: toolCall.id, is_error: true, content: 'Tool not found'};
|
||||
try {
|
||||
// Wrap stream so a tool's `done` ends turn gracefully
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(toolCall.input, toolStream, this.ai, toolCall.id);
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result};
|
||||
} catch (err: any) {
|
||||
return {type: 'tool_result', tool_use_id: toolCall.id, is_error: true, content: err?.message || err?.toString() || 'Unknown'};
|
||||
}
|
||||
}));
|
||||
history.push({role: 'user', content: results, timestamp: Date.now()});
|
||||
requestParams.messages = history;
|
||||
}
|
||||
} while (!terminal && !controller.signal.aborted && resp.content.some((c: any) => c.type === 'tool_use'));
|
||||
const toolCalls = content.filter((c: any) => c.type === 'tool_use');
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
const text = content.filter((c: any) => c.type === 'text').map((c: any) => c.text).join('\n\n').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
|
||||
if(!terminal) {
|
||||
const textContent = resp.content.filter((c: any) => c.type == 'text').map((c: any) => c.text).join('\n\n');
|
||||
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now()});
|
||||
const entries = toolCalls.map((tc: any) => {
|
||||
const entry: any = {role: 'tool', id: tc.id, name: tc.name, args: tc.input, content: undefined, timestamp: Date.now()};
|
||||
history.push(entry);
|
||||
return {tc, entry};
|
||||
});
|
||||
|
||||
await Promise.all(entries.map(async ({tc, entry}: any) => {
|
||||
const tool = tools.find(findByProp('name', tc.name));
|
||||
if(options.stream) options.stream({tool: tc.name});
|
||||
if(!tool) { entry.error = 'Tool not found'; return; }
|
||||
try {
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(entry.args, toolStream, this.ai, tc.id);
|
||||
entry.content = typeof result === 'object' ? JSONSanitize(result) : result;
|
||||
} catch(err: any) {
|
||||
entry.error = err?.message || err?.toString() || 'Unknown';
|
||||
}
|
||||
}));
|
||||
} else {
|
||||
terminal = true;
|
||||
const text = content.filter((c: any) => c.type === 'text').map((c: any) => c.text).join('\n\n').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
}
|
||||
} while(!terminal && !controller.signal.aborted);
|
||||
|
||||
if(options.stream) options.stream({done: true});
|
||||
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => h.role === 'assistant' ? str + (h.content || '') : str, '').trim();
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
} catch(err) {
|
||||
rej(err);
|
||||
}
|
||||
history = this.toStandard(history);
|
||||
if(options.history) options.history.splice(0, options.history.length, ...history);
|
||||
if(options.stream) options.stream({done: true});
|
||||
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||
if(h.role === 'assistant') return str + (h.content || '');
|
||||
if(h.role === 'tool') return str + `<tool>${h.name}</tool>\n\n`;
|
||||
return str;
|
||||
}, '').trim();
|
||||
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
}
|
||||
|
||||
85
src/helpers.ts
Normal file
85
src/helpers.ts
Normal file
@@ -0,0 +1,85 @@
|
||||
import {Memory, MemoryCache} from './memory.ts';
|
||||
|
||||
export type MemoryNode = {
|
||||
name: string;
|
||||
missing: boolean;
|
||||
links: string[];
|
||||
backlinks: string[];
|
||||
}
|
||||
|
||||
export function extractLinks(content: string): string[] {
|
||||
if (!content) return [];
|
||||
const matches = content.matchAll(/\[\[([^\]|]+)(?:\|[^\]]*)?\]\]/g);
|
||||
return [...new Set([...matches].map(m => m[1].trim()))];
|
||||
}
|
||||
|
||||
export function rebuildGraph(memories: Memory[] | MemoryCache): MemoryNode[] {
|
||||
const mems = memories instanceof MemoryCache ? memories.memories : memories;
|
||||
const nameSet = new Set(mems.map(m => m.name));
|
||||
|
||||
for (const m of mems) m.links = extractLinks(m.content).filter(l => l !== m.name);
|
||||
for (const m of mems) m.backlinks = [];
|
||||
for (const m of mems) {
|
||||
for (const link of m.links) {
|
||||
const target = mems.find(t => t.name === link);
|
||||
if (target) target.backlinks.push(m.name);
|
||||
}
|
||||
}
|
||||
|
||||
const nodes: MemoryNode[] = mems.map(m => ({
|
||||
name: m.name,
|
||||
missing: false,
|
||||
links: m.links,
|
||||
backlinks: m.backlinks,
|
||||
}));
|
||||
|
||||
const ghosts = new Set<string>();
|
||||
for (const node of nodes) {
|
||||
for (const link of node.links) {
|
||||
if (!nameSet.has(link)) ghosts.add(link);
|
||||
}
|
||||
}
|
||||
|
||||
return [
|
||||
...nodes,
|
||||
...[...ghosts].map(name => ({
|
||||
name,
|
||||
missing: true,
|
||||
links: [],
|
||||
backlinks: nodes.filter(n => n.links.includes(name)).map(n => n.name),
|
||||
})),
|
||||
];
|
||||
}
|
||||
|
||||
export function renderMemoryGraph(nodes: MemoryNode[]): string {
|
||||
if (!nodes.length) return 'No memories yet.';
|
||||
|
||||
const groups = new Map<string, (MemoryNode & {label: string})[]>();
|
||||
for (const node of nodes) {
|
||||
const [prefix, ...rest] = node.name.split('/');
|
||||
const group = rest.length ? prefix : 'Root';
|
||||
const label = rest.length ? rest.join('/') : node.name;
|
||||
if (!groups.has(group)) groups.set(group, []);
|
||||
groups.get(group)!.push({...node, label});
|
||||
}
|
||||
|
||||
const ghostCount = nodes.filter(n => n.missing).length;
|
||||
const lines = [`Memory Graph (${nodes.length} nodes, ${ghostCount} ghost${ghostCount === 1 ? '' : 's'})`, ''];
|
||||
|
||||
for (const group of [...groups.keys()].sort()) {
|
||||
const items = groups.get(group)!.sort((a, b) => a.label.localeCompare(b.label));
|
||||
lines.push(`${group}/`);
|
||||
items.forEach((n, i) => {
|
||||
const last = i === items.length - 1;
|
||||
const branch = last ? '└─' : '├─';
|
||||
const pad = last ? ' ' : '│ ';
|
||||
const tag = n.missing ? ' (ghost)' : '';
|
||||
lines.push(` ${branch} ${n.label}${tag}`);
|
||||
if (n.links.length) lines.push(` ${pad} → ${n.links.join(', ')}`);
|
||||
if (n.backlinks.length) lines.push(` ${pad} ← ${n.backlinks.join(', ')}`);
|
||||
});
|
||||
lines.push('');
|
||||
}
|
||||
|
||||
return lines.join('\n').trimEnd();
|
||||
}
|
||||
@@ -1,9 +1,11 @@
|
||||
export * from './ai';
|
||||
export * from './antrhopic';
|
||||
export * from './audio';
|
||||
export * from './helpers';
|
||||
export * from './llm';
|
||||
export * from './memory';
|
||||
export * from './open-ai';
|
||||
export * from './provider';
|
||||
export * from './token-pool'
|
||||
export * from './tools';
|
||||
export * from './vision';
|
||||
|
||||
@@ -103,9 +103,10 @@ class BoundedMaxHeap<T> {
|
||||
export class KDTree<T = unknown> {
|
||||
private root: KDNode<T> | null = null;
|
||||
private _size = 0;
|
||||
private readonly dims: number;
|
||||
private readonly distanceFn: (a: number[], b: number[]) => number;
|
||||
|
||||
readonly dims: number;
|
||||
|
||||
/**
|
||||
* @param dims Dimensionality of all vectors (must be consistent).
|
||||
* @param metric Distance metric to use. Default: "euclidean".
|
||||
|
||||
323
src/llm.ts
323
src/llm.ts
@@ -1,16 +1,23 @@
|
||||
import {snakeCase} from '@ztimson/utils';
|
||||
import {clean, makeUnique, snakeCase} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {Anthropic} from './antrhopic.ts';
|
||||
import {OpenAi} from './open-ai.ts';
|
||||
import {LLMProvider} from './provider.ts';
|
||||
import {AiTool, AiToolArg} from './tools.ts';
|
||||
import {fileURLToPath} from 'url';
|
||||
import {dirname, join} from 'path';
|
||||
import {spawn} from 'node:child_process';
|
||||
import {Memory, MemoryCache, MemoryManager, MemoryOptions} from './memory.ts';
|
||||
import {Memory, MemoryCache, MemoryManager, MemoryOptions, stripHeader} from './memory.ts';
|
||||
import {mkdtempSync} from 'node:fs';
|
||||
import fs from 'node:fs/promises';
|
||||
import {tmpdir} from 'node:os';
|
||||
import {dirname, join, basename, extname} from 'path';
|
||||
import { PDFParse } from 'pdf-parse';
|
||||
|
||||
export type AnthropicConfig = {proto: 'anthropic', token: string};
|
||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string};
|
||||
const MAX_AGENT_DEPTH = 5;
|
||||
const PDF_OCR_PAGE_THRESHOLD = 12; // above this many pages, OCR scanned pages instead of feeding images to the model
|
||||
|
||||
export type AnthropicConfig = {proto: 'anthropic', token: string | string[]};
|
||||
export type OpenAiConfig = {proto: 'openai', host?: string, token: string | string[]};
|
||||
|
||||
export type Agent = {
|
||||
name: string;
|
||||
@@ -25,13 +32,32 @@ export type Agent = {
|
||||
agents?: string[] | null;
|
||||
}
|
||||
|
||||
export type LLMFile = {
|
||||
/** Path to file on disk */
|
||||
path?: string;
|
||||
/** File content: raw text, base64-encoded binary, or a Buffer */
|
||||
content?: string | Buffer;
|
||||
/** Original filename, used to infer type from extension */
|
||||
name?: string;
|
||||
/** Mime type override, inferred from extension if omitted */
|
||||
mime?: string;
|
||||
/** @internal set once extraction has run, skips re-processing next turn */
|
||||
extracted?: boolean;
|
||||
};
|
||||
|
||||
export type LLMMessage = {
|
||||
/** Message originator */
|
||||
role: 'assistant' | 'system' | 'user';
|
||||
/** Message content */
|
||||
content: string | any;
|
||||
/** Files attached to request */
|
||||
files?: LLMFile[];
|
||||
/** Timestamp */
|
||||
timestamp?: number;
|
||||
/** Response duration in ms */
|
||||
duration?: number;
|
||||
/** Tokens per second */
|
||||
tps?: number;
|
||||
} | {
|
||||
/** Tool call */
|
||||
role: 'tool';
|
||||
@@ -47,6 +73,10 @@ export type LLMMessage = {
|
||||
error?: undefined | string;
|
||||
/** Timestamp */
|
||||
timestamp?: number;
|
||||
/** Response duration in ms */
|
||||
duration?: number;
|
||||
/** Tokens per second */
|
||||
tps?: number;
|
||||
}
|
||||
|
||||
export type LLMRequest = {
|
||||
@@ -57,7 +87,7 @@ export type LLMRequest = {
|
||||
/** Message history */
|
||||
history?: LLMMessage[];
|
||||
/** Max tokens for request */
|
||||
max_tokens?: number;
|
||||
maxTokens?: number;
|
||||
/** 0 = Rigid Logic, 1 = Balanced, 2 = Hyper Creative **/
|
||||
temperature?: number;
|
||||
/** Available tools */
|
||||
@@ -78,6 +108,8 @@ export type LLMRequest = {
|
||||
mcp?: McpServer[];
|
||||
/** Subagents exposed as delegatable/wrapped tools */
|
||||
agents?: Agent[];
|
||||
/** Attach files to request */
|
||||
files?: LLMFile[];
|
||||
/** @internal recursion guard for nested agent delegation */
|
||||
_agentDepth?: number;
|
||||
}
|
||||
@@ -100,9 +132,12 @@ export type Skill = {
|
||||
content: string;
|
||||
}
|
||||
|
||||
const MAX_AGENT_DEPTH = 5;
|
||||
|
||||
class LLM {
|
||||
private static AUDIO_EXT = ['wav','mp3','m4a','flac','ogg','aac','wma'];
|
||||
private static IMAGE_EXT = ['png','jpg','jpeg','bmp','gif','tiff','webp'];
|
||||
private static TEXT_EXT = ['txt','md','csv','json','xml','html','js','ts','py','yaml','yml','log'];
|
||||
private static PDF_EXT = ['pdf'];
|
||||
|
||||
private memoryManager!: MemoryManager;
|
||||
|
||||
defaultModel!: string;
|
||||
@@ -118,40 +153,149 @@ class LLM {
|
||||
this.memoryManager = new MemoryManager(this);
|
||||
}
|
||||
|
||||
private async loadBuffer(file: LLMFile, asText: boolean): Promise<Buffer> {
|
||||
if(file.path) return fs.readFile(file.path);
|
||||
if(Buffer.isBuffer(file.content)) return file.content;
|
||||
if(typeof file.content === 'string') return Buffer.from(file.content, asText ? 'utf-8' : 'base64');
|
||||
throw new Error('No path or content provided');
|
||||
}
|
||||
|
||||
private async writeTemp(name: string, buffer: Buffer): Promise<string> {
|
||||
const path = join(mkdtempSync(join(tmpdir(), 'ai-file-')), name);
|
||||
await fs.writeFile(path, buffer);
|
||||
return path;
|
||||
}
|
||||
|
||||
/**
|
||||
* Wrap agents as tools. Nested delegation is opt-in only (empty by default, like
|
||||
* tools/skills/mcp) and an agent can never call itself even if explicitly whitelisted.
|
||||
* Delegate results are queued in `pending` and spliced into history by `ask()` after
|
||||
* the provider's own end-of-turn history sync has already run.
|
||||
* Extract text from a PDF. Pages with no text layer (scanned/image-only) are handled as either:
|
||||
* - Rendered to images and returned alongside the text so the (vision-capable) model can read them directly
|
||||
* - OCR'd via Tesseract when the doc is too large to reasonably pass as images
|
||||
*/
|
||||
private setupAgent(agents: Agent[] = [], allAgents: Agent[], pending: Map<string, any>, aborts: (() => void)[], depth = 0): AiTool[] {
|
||||
private async resolvePdf(buffer: Buffer): Promise<{text: string, images: {mime: string, data: string}[]}> {
|
||||
const parser = new PDFParse({data: buffer});
|
||||
try {
|
||||
const {text, pages} = await parser.getText();
|
||||
const scanned = (pages || []).filter(p => !p.text?.trim());
|
||||
if(!scanned.length) return {text: text.trim() || '[Empty PDF]', images: []};
|
||||
const total = pages.length;
|
||||
const pageNums = scanned.map(p => p.num);
|
||||
const {pages: shots} = await parser.getScreenshot({partial: pageNums});
|
||||
if(total <= PDF_OCR_PAGE_THRESHOLD) {
|
||||
return {
|
||||
text: text.trim(),
|
||||
images: shots.map(s => ({mime: 'image/png', data: Buffer.from(s.data).toString('base64')}))
|
||||
};
|
||||
}
|
||||
const ocrText = await Promise.all(shots.map(async (s, i) => {
|
||||
const path = await this.writeTemp(`page-${pageNums[i]}.png`, Buffer.from(s.data));
|
||||
try {
|
||||
return await this.ai.vision.ocr(path) || '';
|
||||
} finally {
|
||||
fs.rm(dirname(path), {recursive: true, force: true}).catch(() => {});
|
||||
}
|
||||
}));
|
||||
return {text: [text.trim(), ...ocrText].filter(Boolean).join('\n\n'), images: []};
|
||||
} finally {
|
||||
await parser.destroy();
|
||||
}
|
||||
}
|
||||
|
||||
private async resolveFile(file: LLMFile): Promise<{text?: string, images?: {mime: string, data: string}[]}> {
|
||||
const name = file.name || (file.path ? basename(file.path) : 'file');
|
||||
|
||||
// Already resolved on a previous turn, reuse cached text
|
||||
if(file.extracted) return {text: `<file name="${name}">\n${file.content}\n</file>`};
|
||||
|
||||
const ext = extname(name).slice(1).toLowerCase();
|
||||
const mime = file.mime || '';
|
||||
const isAudio = mime.startsWith('audio/') || LLM.AUDIO_EXT.includes(ext);
|
||||
const isImage = mime.startsWith('image/') || LLM.IMAGE_EXT.includes(ext);
|
||||
const isPdf = mime === 'application/pdf' || LLM.PDF_EXT.includes(ext);
|
||||
const isText = mime.startsWith('text/') || LLM.TEXT_EXT.includes(ext);
|
||||
|
||||
let tmpDir: string | null = null;
|
||||
try {
|
||||
if(isImage) {
|
||||
const data = (await this.loadBuffer(file, false)).toString('base64');
|
||||
return {images: [{mime: mime || `image/${ext === 'jpg' ? 'jpeg' : ext}`, data}]};
|
||||
}
|
||||
|
||||
if(isPdf) {
|
||||
const {text, images} = await this.resolvePdf(await this.loadBuffer(file, false));
|
||||
// Only cache/skip re-processing when we didn't need to hand off images (OCR'd or fully text-based)
|
||||
if(!images.length) {
|
||||
file.content = text;
|
||||
file.extracted = true;
|
||||
delete file.path;
|
||||
}
|
||||
return {text: `<file name="${name}">\n${text || '[Scanned PDF - see attached page images]'}\n</file>`, images};
|
||||
}
|
||||
|
||||
let text: string;
|
||||
if(isAudio) {
|
||||
let path = file.path;
|
||||
if(!path) {
|
||||
const buffer = await this.loadBuffer(file, false);
|
||||
path = await this.writeTemp(name, buffer);
|
||||
tmpDir = dirname(path);
|
||||
}
|
||||
text = await this.ai.audio.asr(path) || '';
|
||||
} else if(isText) {
|
||||
text = (await this.loadBuffer(file, true)).toString('utf-8');
|
||||
} else {
|
||||
text = `Unsupported file type: ${ext || mime}`;
|
||||
}
|
||||
|
||||
// Cache result, skip re-extraction on future turns of the same conversation
|
||||
file.content = text;
|
||||
file.extracted = true;
|
||||
delete file.path;
|
||||
|
||||
return {text: `<file name="${name}">\n${text}\n</file>`};
|
||||
} catch(err: any) {
|
||||
return {text: `<file name="${name}">Failed to process: ${err.message}</file>`};
|
||||
} finally {
|
||||
if(tmpDir) fs.rm(tmpDir, {recursive: true, force: true}).catch(() => {});
|
||||
}
|
||||
}
|
||||
|
||||
private async resolveFiles(files: LLMFile[]): Promise<{text: string, images: {mime: string, data: string}[]}> {
|
||||
const resolved = await Promise.all(files.map(f => this.resolveFile(f)));
|
||||
return {
|
||||
text: resolved.filter(r => r.text).map(r => r.text).join('\n\n'),
|
||||
images: resolved.flatMap(r => r.images || [])
|
||||
};
|
||||
}
|
||||
|
||||
private setupAgent(agents: Agent[] = [], allAgents: Agent[], history: LLMMessage[], aborts: (() => void)[], depth = 0, delegateState: {resp: string | null}): AiTool[] {
|
||||
return agents.map(a => {
|
||||
const toolName = `${a.delegate ? '' : 'sub'}agent_${snakeCase(a.name)}`;
|
||||
return {
|
||||
name: toolName,
|
||||
description: `${a.delegate ? 'Delegate to ' : ''}Subagent: ${a.description || a.name}`,
|
||||
args: {
|
||||
context: {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true},
|
||||
args: clean<any>({
|
||||
context: !a.delegate ? {type: 'string', description: 'Summary of related messages, samples, files, etc...', required: true} : undefined,
|
||||
instructions: {type: 'string', description: 'Detailed instructions for subagent to complete', required: true},
|
||||
},
|
||||
}),
|
||||
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||
if(depth >= MAX_AGENT_DEPTH) return 'Max agent delegation depth exceeded';
|
||||
const subHistory: LLMMessage[] = [];
|
||||
|
||||
// Opt-in only, self always excluded regardless of whitelist
|
||||
const nested = (a.agents || [])
|
||||
.map(name => allAgents.find(x => x.name === name))
|
||||
.filter((x): x is Agent => !!x && x.name !== a.name);
|
||||
|
||||
const request = this.ask(`${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`, {
|
||||
system: `You are a specialized subagent. ${a.delegate ? 'Your output streams directly to the user for the remainder of this turn.' : 'You are wrapped in a tool call that will be analysis by an LLM'}
|
||||
As a subagent, focus on executing your task completely using available tools and returning only the final result - no commentary, questions, or dialogue.
|
||||
const q = a.delegate ? '' : `${args.instructions}${args.context ? `\n\n<context>${args.context}</context>` : ''}`;
|
||||
|
||||
const request = this.ask(q, {
|
||||
system: `You are a specialized subagent being called from an orchestrator
|
||||
${a.delegate ? 'Your output streams directly to the user for the remainder of this turn. You are mid conversation' : 'You are wrapped in a tool call that will be analysis by an LLM'}
|
||||
Dispense with greetings and focus on your instructions using available tools and returning only the final result unless specifically instructed to converse
|
||||
|
||||
${a.system}`,
|
||||
model: a.model || undefined,
|
||||
temperature: a.temperature,
|
||||
stream: a.delegate ? stream : undefined,
|
||||
history: subHistory,
|
||||
history: a.delegate ? history : [],
|
||||
mcp: a.mcp || undefined,
|
||||
skills: a.skills || undefined,
|
||||
tools: a.tools || undefined,
|
||||
@@ -162,7 +306,7 @@ ${a.system}`,
|
||||
const resp = await request;
|
||||
|
||||
if(a.delegate) {
|
||||
pending.set(<string>id, {resp, subHistory});
|
||||
delegateState.resp = resp;
|
||||
return '';
|
||||
}
|
||||
return resp;
|
||||
@@ -204,7 +348,7 @@ ${a.system}`,
|
||||
|
||||
const list = allTools.map(t => `- ${t.name}: ${t.description}`).join('\n');
|
||||
return {
|
||||
prompt: `You have access to the following MCP tools:\n${list}`,
|
||||
prompt: `## MCP\nYou have access to the following MCP tools:\n${list}`,
|
||||
tools: allTools
|
||||
};
|
||||
}
|
||||
@@ -213,7 +357,7 @@ ${a.system}`,
|
||||
if(!skills?.length) return {prompt: '', tools: []};
|
||||
const list = skills.map(s => `- ${s.name}: ${s.description}`).join('\n');
|
||||
return {
|
||||
prompt: `You have access to the following skill documents, use \`read_skill\` to access them:\n${list}`,
|
||||
prompt: `## Skills\nYou have access to the following skill documents, whenever there is overlap between a question and a skill file, use \`skill_read\` to get instructions and background knowledge:\n${list}`,
|
||||
tools: [{
|
||||
name: 'skill_read',
|
||||
description: 'Read the full content of a skill/knowledge document',
|
||||
@@ -229,6 +373,20 @@ ${a.system}`,
|
||||
}
|
||||
}
|
||||
|
||||
private wrapToolTiming(tools: AiTool[], timings: Map<string, {duration: number, tps: number}>): AiTool[] {
|
||||
return tools.map(t => ({
|
||||
...t,
|
||||
fn: async (args: any, stream: any, ai: any, id?: string) => {
|
||||
const start = Date.now();
|
||||
const result = await t.fn(args, stream, ai, id);
|
||||
const duration = Date.now() - start;
|
||||
const tps = duration > 0 ? this.estimateTokens(result) / (duration / 1000) : 0;
|
||||
if(id) timings.set(id, {duration, tps});
|
||||
return result;
|
||||
}
|
||||
}));
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string> {
|
||||
options = <any>{
|
||||
system: '',
|
||||
@@ -248,10 +406,14 @@ ${a.system}`,
|
||||
nestedAborts.forEach(a => a());
|
||||
};
|
||||
|
||||
const promise = (async () => {
|
||||
let promise: any;
|
||||
const requestStart = Date.now();
|
||||
|
||||
promise = (async () => {
|
||||
let tools: AiTool[] = options.tools || this.ai.options.llm?.tools || [];
|
||||
const prompts: string[] = [];
|
||||
let history = options.history || [];
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
// MCP
|
||||
const mcp = options.mcp || this.ai.options?.llm?.mcp;
|
||||
@@ -271,8 +433,8 @@ ${a.system}`,
|
||||
|
||||
// Agents
|
||||
const agents = options.agents || this.ai.options?.llm?.agents;
|
||||
const pendingDelegates = new Map<string, any>();
|
||||
if(agents?.length) tools.push(...this.setupAgent(agents, agents, pendingDelegates, nestedAborts, options._agentDepth || 0));
|
||||
const delegateState: {resp: string | null} = {resp: null};
|
||||
if(agents?.length) tools.push(...this.setupAgent(agents, agents, history, nestedAborts, options._agentDepth || 0, delegateState));
|
||||
|
||||
// Memory
|
||||
const mem = MemoryManager.normalize(options.memory);
|
||||
@@ -295,18 +457,26 @@ ${a.system}`,
|
||||
} else listed.push(r);
|
||||
}
|
||||
|
||||
prompts.unshift(`You have access to the following memory files:
|
||||
${mems.map(m => `- ${m.name}: ${m.description}`).join('\n')}
|
||||
${preloaded.length ? `
|
||||
Relevant memories have been preloaded:
|
||||
${preloaded.map(r => `
|
||||
**${r.name}**
|
||||
${r.description}
|
||||
${r.content}
|
||||
`).join('\n---\n')}
|
||||
` : ''}${listed.length ? `
|
||||
Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.name).join(', ')}
|
||||
` : ''}`.trim());
|
||||
prompts.unshift(`## Memory
|
||||
You have a background memory process which has prefetched relevant information${mem.update ? ' and will create new memories from this conversation' : ''} for you
|
||||
Assume it is perfect and never mention this process to anyone ever
|
||||
Always use your memories to craft a personalized response, they contain links / [[wiki links]] which you use navigate between them
|
||||
${mem.tool ? `You can access memory files via the \`memory_search\` and \`memory_recall\` tools
|
||||
When you need information about the user, \`memory_recall\` \`People/User\` before asking (fetch if not included bellow)
|
||||
When you need information not provided, attempt 1-3 \`memory_search\` calls with distinct queries before asking` : ''}
|
||||
|
||||
${preloaded.length ? `### Prefetched Memories (Most relevant first):
|
||||
|
||||
${preloaded.map(r => `Memory: ${r.name}
|
||||
Description: ${r.description}
|
||||
Linked: ${makeUnique([...r.links, ...r.backlinks]).join(', ')}
|
||||
\`\`\`
|
||||
${stripHeader(r.content)}
|
||||
\`\`\``).join('\n\n')}` : ''}
|
||||
${mem.tool && listed.length ? '\n' + listed.map(r => `Memory: ${r.name}
|
||||
Description: ${r.description}
|
||||
Linked: ${makeUnique([...r.links, ...r.backlinks]).join(', ')}
|
||||
<!-- Truncated -->`).join('\n\n') : ''}`.trim())
|
||||
}
|
||||
if(mem.tool) tools.push(this.memoryManager.tools.read(mem.memory));
|
||||
}
|
||||
@@ -314,52 +484,57 @@ Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.nam
|
||||
|
||||
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||
|
||||
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
||||
request = this.models[m].ask(message, {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
let resp = await request;
|
||||
|
||||
// Spice delegated agents response into history
|
||||
let lastDelegateResp: string | null = null;
|
||||
if(pendingDelegates.size) {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
const h: any = history[i];
|
||||
if(h.role !== 'tool' || !pendingDelegates.has(h.id)) continue;
|
||||
const {resp: delegateResp, subHistory} = pendingDelegates.get(h.id)!;
|
||||
pendingDelegates.delete(h.id);
|
||||
const insert: LLMMessage[] = [...subHistory.filter(sh => sh.role === 'tool'), {role: 'assistant', content: delegateResp, timestamp: Date.now()}];
|
||||
history.splice(i + 1, 0, ...insert);
|
||||
lastDelegateResp = delegateResp;
|
||||
i += insert.length;
|
||||
}
|
||||
// Files
|
||||
const files = options.files || [];
|
||||
const lastMsg = history[history.length - 1];
|
||||
const originalContent = lastMsg?.content;
|
||||
if(files.length && lastMsg?.role === 'user') {
|
||||
lastMsg.files = files;
|
||||
const {text, images} = await this.resolveFiles(files);
|
||||
const merged = text ? `${originalContent}\n\n${text}` : originalContent;
|
||||
lastMsg.content = images.length
|
||||
? [...images.map(i => ({type: 'image', mime: i.mime, data: i.data})), {type: 'text', text: merged}]
|
||||
: merged;
|
||||
}
|
||||
|
||||
// If the orchestrator added no commentary of its own, its answer IS the delegate's answer
|
||||
if(typeof resp === 'string' && !resp.trim() && lastDelegateResp !== null) resp = lastDelegateResp;
|
||||
const toolTimings = new Map<string, {duration: number, tps: number}>();
|
||||
tools = this.wrapToolTiming(tools, toolTimings);
|
||||
|
||||
if(aborted) throw Object.assign(new Error('Aborted'), {name: 'AbortError'});
|
||||
|
||||
prompts.unshift(options.system || this.ai.options.llm?.system || '');
|
||||
request = this.models[m].ask('', {...options, tools, system: prompts.filter(Boolean).join('\n\n')});
|
||||
let resp = await request;
|
||||
|
||||
if(files.length && lastMsg?.role === 'user') lastMsg.content = originalContent;
|
||||
|
||||
// Capture meta (duration / tps)
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool' && toolTimings.has(h.id)) Object.assign(h, toolTimings.get(h.id));
|
||||
}
|
||||
|
||||
if(typeof resp === 'string' && !resp.trim() && delegateState.resp !== null) resp = delegateState.resp;
|
||||
|
||||
// Trim memory injections from history
|
||||
if(mem?.tool) history.splice(0, history.length, ...history.filter(h => h.role !== 'tool' || h.name !== 'memory_recall'));
|
||||
|
||||
// Auto-memorize before compressing
|
||||
if(options.compress && this.estimateTokens(history) >= options.compress.max) {
|
||||
if(mem?.update) await this.memoryManager.memorize(history, mem.memory, {model: options.memoryModel || this.defaultModel, ...options});
|
||||
const compressed = await this.compressHistory(history, options.compress.max, options.compress.min, options);
|
||||
if(options.history) options.history.splice(0, options.history.length, ...compressed);
|
||||
}
|
||||
|
||||
const requestDuration = Date.now() - requestStart;
|
||||
const totalTokens = history
|
||||
.filter((h: any) => h.role === 'assistant' && h.duration && h.tps)
|
||||
.reduce((sum: number, h: any) => sum + h.tps * (h.duration / 1000), 0);
|
||||
const requestTps = requestDuration > 0 ? totalTokens / (requestDuration / 1000) : 0;
|
||||
Object.assign(promise, {duration: requestDuration, tps: requestTps});
|
||||
|
||||
return resp;
|
||||
})();
|
||||
|
||||
return Object.assign(promise, {abort});
|
||||
}
|
||||
|
||||
/**
|
||||
* Digest full conversation history into memory documents.
|
||||
* Call on session end to persist the conversation.
|
||||
*/
|
||||
async updateMemory(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
|
||||
return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
}
|
||||
|
||||
/**
|
||||
* Compress chat history to reduce context size
|
||||
* @param {LLMMessage[]} history Chatlog that will be compressed
|
||||
@@ -539,6 +714,14 @@ Also relevant but not preloaded (use \`memory_recall\`): ${listed.map(r => r.nam
|
||||
};
|
||||
}
|
||||
|
||||
/**
|
||||
* Digest full conversation history into memory documents.
|
||||
* Call on session end to persist the conversation.
|
||||
*/
|
||||
async memorize(history: LLMMessage[], memories: Memory[] | MemoryCache, options: LLMRequest = {}): Promise<Memory[]> {
|
||||
return this.memoryManager.memorize(history, memories, {model: this.defaultModel, ...options});
|
||||
}
|
||||
|
||||
/**
|
||||
* Create a summary of some text
|
||||
* @param {string} text Text to summarize
|
||||
|
||||
945
src/memory.ts
945
src/memory.ts
File diff suppressed because it is too large
Load Diff
250
src/open-ai.ts
250
src/open-ai.ts
@@ -1,88 +1,71 @@
|
||||
import {OpenAI as openAI} from 'openai';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean} from '@ztimson/utils';
|
||||
import {findByProp, objectMap, JSONSanitize, JSONAttemptParse, clean, makeArray} from '@ztimson/utils';
|
||||
import {AbortablePromise, Ai} from './ai.ts';
|
||||
import {LLMMessage, LLMRequest} from './llm.ts';
|
||||
import {LLMProvider} from './provider.ts';
|
||||
import {TokenPool} from './token-pool.ts';
|
||||
import {convertSchema} from './tools.ts';
|
||||
|
||||
export class OpenAi extends LLMProvider {
|
||||
client!: openAI;
|
||||
tokenPool!: TokenPool;
|
||||
private clients = new Map<string, openAI>();
|
||||
|
||||
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string, public model: string) {
|
||||
constructor(public readonly ai: Ai, public readonly host: string | null, public readonly token: string | string[], public model: string) {
|
||||
super();
|
||||
this.client = new openAI(clean({
|
||||
baseURL: host,
|
||||
apiKey: token || (host ? 'ignored' : undefined)
|
||||
}));
|
||||
const tokens = makeArray(token).filter(Boolean);
|
||||
this.tokenPool = new TokenPool(...(tokens.length ? tokens : [host ? 'ignored' : '']));
|
||||
}
|
||||
|
||||
private toStandard(history: any[]): LLMMessage[] {
|
||||
for(let i = 0; i < history.length; i++) {
|
||||
const h = history[i];
|
||||
if(h.role === 'assistant' && h.tool_calls) {
|
||||
const items: any[] = [];
|
||||
if(h.content) items.push({role: 'assistant', content: h.content, timestamp: h.timestamp});
|
||||
items.push(...h.tool_calls.map((tc: any) => ({
|
||||
role: 'tool',
|
||||
id: tc.id,
|
||||
name: tc.function.name,
|
||||
args: JSONAttemptParse(tc.function.arguments, {}),
|
||||
timestamp: h.timestamp
|
||||
})));
|
||||
history.splice(i, 1, ...items);
|
||||
i += items.length - 1;
|
||||
} else if(h.role === 'tool') {
|
||||
const record = history.find(h2 => h.tool_call_id == h2.id);
|
||||
if(record) {
|
||||
if(h.content?.includes('"error":')) record.error = h.content;
|
||||
else record.content = h.content || '';
|
||||
}
|
||||
history.splice(i, 1);
|
||||
i--;
|
||||
}
|
||||
if(!history[i]?.timestamp) history[i].timestamp = Date.now();
|
||||
private getClient(token: string): openAI {
|
||||
let client = this.clients.get(token);
|
||||
if(!client) {
|
||||
client = new openAI(clean({baseURL: this.host, apiKey: token || undefined}));
|
||||
this.clients.set(token, client);
|
||||
}
|
||||
return history;
|
||||
return client;
|
||||
}
|
||||
|
||||
private fromStandard(history: LLMMessage[]): any[] {
|
||||
return history.reduce((result, h) => {
|
||||
private toWireContent(content: any): any {
|
||||
if(!Array.isArray(content)) return content;
|
||||
return content.map(c => c.type === 'image'
|
||||
? {type: 'image_url', image_url: {url: `data:${c.mime};base64,${c.data}`}}
|
||||
: {type: 'text', text: c.text});
|
||||
}
|
||||
|
||||
/** Convert standard history -> OpenAI wire format */
|
||||
private toWire(history: LLMMessage[], system?: string): any[] {
|
||||
const wire: any[] = [];
|
||||
if(system) wire.push({role: 'system', content: system});
|
||||
for(const h of history) {
|
||||
if(h.role === 'tool') {
|
||||
result.push({
|
||||
wire.push({
|
||||
role: 'assistant',
|
||||
content: null,
|
||||
tool_calls: [{ id: h.id, type: 'function', function: { name: h.name, arguments: JSON.stringify(h.args) } }],
|
||||
refusal: null,
|
||||
annotations: [],
|
||||
timestamp: h.timestamp,
|
||||
tool_calls: [{id: h.id, type: 'function', function: {name: h.name, arguments: JSON.stringify(h.args)}}],
|
||||
}, {
|
||||
role: 'tool',
|
||||
tool_call_id: h.id,
|
||||
content: h.error || h.content,
|
||||
timestamp: h.timestamp,
|
||||
content: h.error || h.content || '',
|
||||
});
|
||||
} else {
|
||||
result.push(h);
|
||||
wire.push({role: h.role, content: this.toWireContent(h.content)});
|
||||
}
|
||||
return result;
|
||||
}, [] as any[]);
|
||||
}
|
||||
return wire;
|
||||
}
|
||||
|
||||
ask(message: string, options: LLMRequest = {}): AbortablePromise<string | any> {
|
||||
const controller = new AbortController();
|
||||
return Object.assign(new Promise<any>(async (res, rej) => {
|
||||
const base = (options.history || []).filter(h => h.role !== 'system');
|
||||
let history = this.fromStandard([
|
||||
...(options.system ? [{role: <any>'system', content: options.system, timestamp: Date.now()}] : []),
|
||||
...base,
|
||||
{role: 'user', content: message, timestamp: Date.now()}
|
||||
]);
|
||||
if(!options.history) options.history = [];
|
||||
const history = options.history;
|
||||
if(message) history.push({role: 'user', content: message, timestamp: Date.now()});
|
||||
|
||||
const tools = options.tools || this.ai.options.llm?.tools || [];
|
||||
const requestParams: any = {
|
||||
model: options.model || this.model,
|
||||
messages: history,
|
||||
stream: !!options.stream,
|
||||
max_completion_tokens: options.max_tokens || this.ai.options.llm?.max_tokens || undefined,
|
||||
max_completion_tokens: options.maxTokens || this.ai.options.llm?.maxTokens || undefined,
|
||||
temperature: options.temperature || this.ai.options.llm?.temperature || undefined,
|
||||
tools: tools.map(t => ({
|
||||
type: 'function',
|
||||
@@ -100,101 +83,94 @@ export class OpenAi extends LLMProvider {
|
||||
|
||||
if(options.schema) {
|
||||
const schema = convertSchema(options.schema);
|
||||
requestParams.response_format = {
|
||||
type: 'json_schema',
|
||||
json_schema: {
|
||||
name: 'response',
|
||||
strict: true,
|
||||
schema
|
||||
}
|
||||
};
|
||||
requestParams.response_format = {type: 'json_schema', json_schema: {name: 'response', strict: true, schema}};
|
||||
}
|
||||
if(options.stream) requestParams.stream_options = {include_usage: true};
|
||||
|
||||
let resp: any, terminal = false;
|
||||
do {
|
||||
requestParams.messages = history.map(({timestamp, ...m}) => m);
|
||||
resp = await this.client.chat.completions.create(requestParams).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(history, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
try {
|
||||
let terminal = false;
|
||||
do {
|
||||
requestParams.messages = this.toWire(history.filter(h => h.role !== 'system'), options.system);
|
||||
|
||||
if(options.stream) {
|
||||
resp.choices = [{message: {role: 'assistant', content: '', tool_calls: [], timestamp: Date.now()}}];
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.choices[0].delta.content) {
|
||||
resp.choices[0].message.content += chunk.choices[0].delta.content;
|
||||
options.stream({text: chunk.choices[0].delta.content});
|
||||
}
|
||||
if(chunk.choices[0].delta.tool_calls) {
|
||||
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
|
||||
const existing = resp.choices[0].message.tool_calls.find(tc => tc.index === deltaTC.index);
|
||||
if(existing) {
|
||||
if(deltaTC.id) existing.id = deltaTC.id;
|
||||
if(deltaTC.type) existing.type = deltaTC.type;
|
||||
if(deltaTC.function) {
|
||||
if(!existing.function) existing.function = {};
|
||||
if(deltaTC.function.name) existing.function.name = deltaTC.function.name;
|
||||
if(deltaTC.function.arguments) existing.function.arguments = (existing.function.arguments || '') + deltaTC.function.arguments;
|
||||
const callStart = Date.now();
|
||||
const resp: any = await this.tokenPool.run(token => this.getClient(token).chat.completions.create(requestParams)).catch(err => {
|
||||
err.message += `\n\nMessages:\n${JSON.stringify(requestParams.messages, null, 2)}`;
|
||||
throw err;
|
||||
});
|
||||
|
||||
let usage: any, msg: any = {content: '', tool_calls: []};
|
||||
if(options.stream) {
|
||||
for await (const chunk of resp) {
|
||||
if(controller.signal.aborted) break;
|
||||
if(chunk.usage) usage = chunk.usage;
|
||||
if(chunk.choices[0]?.delta?.content) {
|
||||
msg.content += chunk.choices[0].delta.content;
|
||||
options.stream({text: chunk.choices[0].delta.content});
|
||||
}
|
||||
if(chunk.choices[0]?.delta?.tool_calls) {
|
||||
for(const deltaTC of chunk.choices[0].delta.tool_calls) {
|
||||
const existing = msg.tool_calls.find((tc: any) => tc.index === deltaTC.index);
|
||||
if(existing) {
|
||||
if(deltaTC.id) existing.id = deltaTC.id;
|
||||
if(deltaTC.function?.name) existing.function.name = deltaTC.function.name;
|
||||
if(deltaTC.function?.arguments) existing.function.arguments += deltaTC.function.arguments;
|
||||
} else {
|
||||
msg.tool_calls.push({
|
||||
index: deltaTC.index,
|
||||
id: deltaTC.id || '',
|
||||
function: {name: deltaTC.function?.name || '', arguments: deltaTC.function?.arguments || ''}
|
||||
});
|
||||
}
|
||||
} else {
|
||||
resp.choices[0].message.tool_calls.push({
|
||||
index: deltaTC.index,
|
||||
id: deltaTC.id || '',
|
||||
type: deltaTC.type || 'function',
|
||||
function: {
|
||||
name: deltaTC.function?.name || '',
|
||||
arguments: deltaTC.function?.arguments || ''
|
||||
}
|
||||
});
|
||||
}
|
||||
}
|
||||
}
|
||||
} else {
|
||||
usage = resp.usage;
|
||||
msg = resp.choices[0].message;
|
||||
}
|
||||
}
|
||||
const duration = Date.now() - callStart;
|
||||
const tps = usage?.completion_tokens && duration > 0 ? usage.completion_tokens / (duration / 1000) : 0;
|
||||
|
||||
if(resp.error) throw new Error(resp.error);
|
||||
const toolCalls = resp.choices[0].message.tool_calls || [];
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
history.push(resp.choices[0].message);
|
||||
const results = await Promise.all(toolCalls.map(async (toolCall: any) => {
|
||||
const tool = tools?.find(findByProp('name', toolCall.function.name));
|
||||
if(options.stream) options.stream({tool: toolCall.function.name});
|
||||
if(!tool) return {role: 'tool', tool_call_id: toolCall.id, content: '{"error": "Tool not found"}', timestamp: Date.now()};
|
||||
try {
|
||||
const args = JSONAttemptParse(toolCall.function.arguments, {});
|
||||
// Wrap stream so a tool's `done` ends turn gracefully
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(args, toolStream, this.ai, toolCall.id);
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: typeof result == 'object' ? JSONSanitize(result) : result, timestamp: Date.now()};
|
||||
} catch (err: any) {
|
||||
return {role: 'tool', tool_call_id: toolCall.id, content: JSONSanitize({error: err?.message || err?.toString() || 'Unknown'}), timestamp: Date.now()};
|
||||
}
|
||||
}));
|
||||
history.push(...results);
|
||||
requestParams.messages = history;
|
||||
}
|
||||
} while (!terminal && !controller.signal.aborted && resp.choices?.[0]?.message?.tool_calls?.length);
|
||||
const toolCalls = msg.tool_calls || [];
|
||||
if(toolCalls.length && !controller.signal.aborted) {
|
||||
if(msg.content?.trim()) history.push({role: 'assistant', content: msg.content.trim(), timestamp: Date.now(), duration, tps});
|
||||
|
||||
if(!terminal) {
|
||||
const textContent = resp.choices[0].message.content || '';
|
||||
history.push({role: 'assistant', content: textContent.trim(), timestamp: Date.now()});
|
||||
const entries = toolCalls.map((tc: any) => {
|
||||
const entry: any = {role: 'tool', id: tc.id, name: tc.function.name, args: JSONAttemptParse(tc.function.arguments, {}), content: undefined, timestamp: Date.now()};
|
||||
history.push(entry);
|
||||
return {tc, entry};
|
||||
});
|
||||
|
||||
await Promise.all(entries.map(async ({tc, entry}: any) => {
|
||||
const tool = tools.find(findByProp('name', tc.function.name));
|
||||
if(options.stream) options.stream({tool: tc.function.name});
|
||||
if(!tool) { entry.error = 'Tool not found'; return; }
|
||||
try {
|
||||
const toolStream = options.stream && ((chunk: any) => {
|
||||
if(chunk.done) { terminal = true; return; }
|
||||
options.stream!(chunk);
|
||||
});
|
||||
const result = await tool.fn(entry.args, toolStream, this.ai, tc.id);
|
||||
entry.content = typeof result === 'object' ? JSONSanitize(result) : result;
|
||||
} catch(err: any) {
|
||||
entry.error = err?.message || err?.toString() || 'Unknown';
|
||||
}
|
||||
}));
|
||||
} else {
|
||||
terminal = true;
|
||||
const text = (msg.content || '').trim();
|
||||
if(text) history.push({role: 'assistant', content: text, timestamp: Date.now(), duration, tps});
|
||||
}
|
||||
} while(!terminal && !controller.signal.aborted);
|
||||
|
||||
if(options.stream) options.stream({done: true});
|
||||
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => h.role === 'assistant' ? str + (h.content || '') : str, '').trim();
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
} catch(err) {
|
||||
rej(err);
|
||||
}
|
||||
history = this.toStandard(history);
|
||||
if(options.history) options.history.splice(0, options.history.length, ...history.filter(h => h.role !== 'system'));
|
||||
if(options.stream) options.stream({done: true});
|
||||
|
||||
const turnStart = history.map(h => h.role).lastIndexOf('user');
|
||||
const finalContent = history.slice(turnStart + 1).reduce((str, h) => {
|
||||
if(h.role === 'assistant') return str + (h.content || '');
|
||||
if(h.role === 'tool') return str + `<tool>${h.name}</tool>\n\n`;
|
||||
return str;
|
||||
}, '').trim();
|
||||
|
||||
res(options.schema ? JSONAttemptParse(finalContent, finalContent) : finalContent);
|
||||
}), {abort: () => controller.abort()});
|
||||
}
|
||||
}
|
||||
|
||||
65
src/token-pool.ts
Normal file
65
src/token-pool.ts
Normal file
@@ -0,0 +1,65 @@
|
||||
const DEFAULT_COOLDOWN = 15 * 60 * 1000;
|
||||
|
||||
type TokenState = {
|
||||
token: string;
|
||||
cooldownUntil: number; // 0 = available now
|
||||
lastError?: {code: number, message: string};
|
||||
};
|
||||
|
||||
export class TokenPoolExhaustedError extends Error {
|
||||
constructor(public tokens: Record<string, {code: number, message: string}>) {
|
||||
super(`All tokens exhausted:\n${Object.entries(tokens).map(([t, e]) => `${t}: [${e.code}] ${e.message}`).join('\n')}`);
|
||||
this.name = 'TokenPoolExhaustedError';
|
||||
}
|
||||
}
|
||||
|
||||
export class TokenPool {
|
||||
private states: TokenState[];
|
||||
|
||||
constructor(...tokens: string[]) {
|
||||
this.states = tokens.map(token => ({token, cooldownUntil: 0}));
|
||||
}
|
||||
|
||||
private preview(token: string): string {
|
||||
return token.length <= 8 ? '****' : `${token.slice(0, 4)}...${token.slice(-4)}`;
|
||||
}
|
||||
|
||||
/** Anthropic & OpenAI SDKs both attach `status` to thrown errors */
|
||||
private statusCode(err: any): number {
|
||||
return err?.status ?? err?.response?.status ?? err?.statusCode;
|
||||
}
|
||||
|
||||
private retryAfter(err: any): number {
|
||||
const headers = err?.headers || err?.response?.headers;
|
||||
const raw = headers?.get?.('retry-after') ?? headers?.['retry-after'];
|
||||
if(raw) {
|
||||
const seconds = Number(raw);
|
||||
if(!isNaN(seconds)) return Date.now() + seconds * 1000;
|
||||
const date = new Date(raw).getTime();
|
||||
if(!isNaN(date)) return date;
|
||||
}
|
||||
return Date.now() + DEFAULT_COOLDOWN;
|
||||
}
|
||||
|
||||
async run<T>(fn: (token: string) => Promise<T>): Promise<T> {
|
||||
const now = Date.now();
|
||||
for(const state of this.states) {
|
||||
if(state.cooldownUntil > now) continue;
|
||||
try {
|
||||
const result = await fn(state.token);
|
||||
state.cooldownUntil = 0;
|
||||
state.lastError = undefined;
|
||||
return result;
|
||||
} catch(err: any) {
|
||||
const code = this.statusCode(err);
|
||||
if(![401, 403, 429].includes(code)) throw err;
|
||||
state.cooldownUntil = code === 429 ? this.retryAfter(err) : Date.now() + DEFAULT_COOLDOWN;
|
||||
state.lastError = {code, message: err?.message || 'Unknown error'};
|
||||
}
|
||||
}
|
||||
|
||||
const failures: Record<string, {code: number, message: string}> = {};
|
||||
this.states.forEach(s => { if(s.lastError) failures[this.preview(s.token)] = s.lastError; });
|
||||
throw new TokenPoolExhaustedError(failures);
|
||||
}
|
||||
}
|
||||
Reference in New Issue
Block a user