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Merge pull request #589 from mindcraft-bots/develop

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Models Update
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Max Robinson 2025-08-23 18:07:30 -05:00 • committed by GitHub
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8
README.md
View file

@ -12,7 +12,7 @@ Do not connect this bot to public servers with coding enabled. This project allo
- [Minecraft Java Edition](https://www.minecraft.net/en-us/store/minecraft-java-bedrock-edition-pc) (up to v1.21.1, recommend v1.21.1)
- [Node.js Installed](https://nodejs.org/) (at least v18)
- One of these: [OpenAI API Key](https://openai.com/blog/openai-api) | [Gemini API Key](https://aistudio.google.com/app/apikey) | [Anthropic API Key](https://docs.anthropic.com/claude/docs/getting-access-to-claude) | [Replicate API Key](https://replicate.com/) | [Hugging Face API Key](https://huggingface.co/) | [Groq API Key](https://console.groq.com/keys) | [Ollama Installed](https://ollama.com/download). | [Mistral API Key](https://docs.mistral.ai/getting-started/models/models_overview/) | [Qwen API Key [Intl.]](https://www.alibabacloud.com/help/en/model-studio/developer-reference/get-api-key)/[[cn]](https://help.aliyun.com/zh/model-studio/getting-started/first-api-call-to-qwen?) | [Novita AI API Key](https://novita.ai/settings?utm_source=github_mindcraft&utm_medium=github_readme&utm_campaign=link#key-management) |
- One of these: [OpenAI API Key](https://openai.com/blog/openai-api) | [Gemini API Key](https://aistudio.google.com/app/apikey) | [Anthropic API Key](https://docs.anthropic.com/claude/docs/getting-access-to-claude) | [Replicate API Key](https://replicate.com/) | [Hugging Face API Key](https://huggingface.co/) | [Groq API Key](https://console.groq.com/keys) | [Ollama Installed](https://ollama.com/download). | [Mistral API Key](https://docs.mistral.ai/getting-started/models/models_overview/) | [Qwen API Key [Intl.]](https://www.alibabacloud.com/help/en/model-studio/developer-reference/get-api-key)/[[cn]](https://help.aliyun.com/zh/model-studio/getting-started/first-api-call-to-qwen?) | [Novita AI API Key](https://novita.ai/settings?utm_source=github_mindcraft&utm_medium=github_readme&utm_campaign=link#key-management) | [Cerebras API Key](https://cloud.cerebras.ai) | [Mercury API](https://platform.inceptionlabs.ai/docs)
## Install and Run
@ -64,10 +64,14 @@ You can configure the agent's name, model, and prompts in their profile like `an
| `glhf.chat` | `GHLF_API_KEY` | `glhf/hf:meta-llama/Llama-3.1-405B-Instruct` | [docs](https://glhf.chat/user-settings/api) |
| `hyperbolic` | `HYPERBOLIC_API_KEY` | `hyperbolic/deepseek-ai/DeepSeek-V3` | [docs](https://docs.hyperbolic.xyz/docs/getting-started) |
| `vllm` | n/a | `vllm/llama3` | n/a |
| `cerebras` | `CEREBRAS_API_KEY` | `cerebras/llama-3.3-70b` | [docs](https://inference-docs.cerebras.ai/introduction) |
| `mercury` | `MERCURY_API_KEY` | `mercury-coder-small` | [docs](https://www.inceptionlabs.ai/) |
If you use Ollama, to install the models used by default (generation and embedding), execute the following terminal command:
`ollama pull llama3.1 && ollama pull nomic-embed-text`
To use Azure, you can reuse the `OPENAI_API_KEY` environment variable. You can get the key from the Azure portal. See [azure.json](profiles/azure.json) for an example.
### Online Servers
To connect to online servers your bot will need an official Microsoft/Minecraft account. You can use your own personal one, but will need another account if you want to connect too and play with it. To connect, change these lines in `settings.js`:
```javascript
@ -174,3 +178,5 @@ Some of the node modules that we depend on have bugs in them. To add a patch, ch
url = {https://arxiv.org/abs/2504.17950},
}
```

4
keys.example.json
View file

@ -13,5 +13,7 @@
"GHLF_API_KEY": "",
"HYPERBOLIC_API_KEY": "",
"NOVITA_API_KEY": "",
"OPENROUTER_API_KEY": ""
"OPENROUTER_API_KEY": "",
"CEREBRAS_API_KEY": "",
"MERCURY_API_KEY":""
}

1
package.json
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@ -2,6 +2,7 @@
"type": "module",
"dependencies": {
"@anthropic-ai/sdk": "^0.17.1",
"@cerebras/cerebras_cloud_sdk": "^1.46.0",
"@google/generative-ai": "^0.2.1",
"@huggingface/inference": "^2.8.1",
"@mistralai/mistralai": "^1.1.0",

19
profiles/azure.json Normal file
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@ -0,0 +1,19 @@
{
"name": "azure",
"model": {
"api": "azure",
"url": "https://<your-resource>.openai.azure.com",
"model": "<chat-deployment-name>",
"params": {
"apiVersion": "2024-08-01-preview"
}
},
"embedding": {
"api": "azure",
"url": "https://<your-resource>.openai.azure.com",
"model": "<embedding-deployment-name>",
"params": {
"apiVersion": "2024-08-01-preview"
}
}
}

2
profiles/claude.json
View file

@ -1,7 +1,7 @@
{
"name": "claude",
"model": "claude-3-5-sonnet-latest",
"model": "claude-sonnet-4-20250514",
"embedding": "openai"
}

2
profiles/claude_thinker.json
View file

@ -2,7 +2,7 @@
"name": "claude_thinker",
"model": {
"model": "claude-3-7-sonnet-latest",
"model": "claude-sonnet-4-20250514",
"params": {
"thinking": {
"type": "enabled",

2
profiles/gemini.json
View file

@ -1,7 +1,7 @@
{
"name": "gemini",
"model": "gemini-2.0-flash",
"model": "gemini-2.5-flash",
"cooldown": 5000
}

2
profiles/grok.json
View file

@ -1,7 +1,7 @@
{
"name": "Grok",
"model": "grok-beta",
"model": "grok-3-mini-latest",
"embedding": "openai"
}

9
profiles/mercury.json Normal file
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@ -0,0 +1,9 @@
{
"name": "Mercury",
"cooldown": 5000,
"model": "mercury/mercury-coder-small",
"embedding": "openai"
}

3
settings.js
View file

@ -7,7 +7,7 @@ const settings = {
// the mindserver manages all agents and hosts the UI
"mindserver_port": 8080,
"base_profile": "survival", // survival, creative, assistant, or god_mode
"base_profile": "survival", // survival, assistant, creative, or god_mode
"profiles": [
"./andy.json",
// "./profiles/gpt.json",
@ -18,6 +18,7 @@ const settings = {
// "./profiles/grok.json",
// "./profiles/mistral.json",
// "./profiles/deepseek.json",
//"./profiles/mercury.json",
// using more than 1 profile requires you to /msg each bot indivually
// individual profiles override values from the base profile

2
src/agent/action_manager.js
View file

@ -69,7 +69,7 @@ export class ActionManager {
else {
this.recent_action_counter = 0;
}
if (this.recent_action_counter > 2) {
if (this.recent_action_counter > 3) {
console.warn('Fast action loop detected, cancelling resume.');
this.cancelResume(); // likely cause of repetition
}

47
src/agent/library/skills.js
View file

@ -228,28 +228,33 @@ export async function smeltItem(bot, itemName, num=1) {
await furnace.putInput(mc.getItemId(itemName), null, num);
// wait for the items to smelt
let total = 0;
let collected_last = true;
let smelted_item = null;
await new Promise(resolve => setTimeout(resolve, 200));
let last_collected = Date.now();
while (total < num) {
await new Promise(resolve => setTimeout(resolve, 10000));
console.log('checking...');
let collected = false;
await new Promise(resolve => setTimeout(resolve, 1000));
if (furnace.outputItem()) {
smelted_item = await furnace.takeOutput();
if (smelted_item) {
total += smelted_item.count;
collected = true;
last_collected = Date.now();
}
}
if (!collected && !collected_last) {
break; // if nothing was collected this time or last time
if (Date.now() - last_collected > 11000) {
break; // if nothing has been collected in 11 seconds, stop
}
collected_last = collected;
if (bot.interrupt_code) {
break;
}
}
// take all remaining in input/fuel slots
if (furnace.inputItem()) {
await furnace.takeInput();
}
if (furnace.fuelItem()) {
await furnace.takeFuel();
}
await bot.closeWindow(furnace);
if (placedFurnace) {
@ -1040,7 +1045,7 @@ export async function goToGoal(bot, goal) {
log(bot, `Found destructive path.`);
}
else {
log(bot, `Could not find a path to goal, attempting to navigate anyway using destructive movements.`);
log(bot, `Path not found, but attempting to navigate anyway using destructive movements.`);
}
const doorCheckInterval = startDoorInterval(bot);
@ -1288,11 +1293,29 @@ export async function followPlayer(bot, username, distance=4) {
while (!bot.interrupt_code) {
await new Promise(resolve => setTimeout(resolve, 500));
// in cheat mode, if the distance is too far, teleport to the player
if (bot.modes.isOn('cheat') && bot.entity.position.distanceTo(player.position) > 100 && player.isOnGround) {
const distance_from_player = bot.entity.position.distanceTo(player.position);
const teleport_distance = 100;
const ignore_modes_distance = 30;
const nearby_distance = distance + 2;
if (distance_from_player > teleport_distance && bot.modes.isOn('cheat')) {
// teleport with cheat mode
await goToPlayer(bot, username);
}
const is_nearby = bot.entity.position.distanceTo(player.position) <= distance + 2;
if (is_nearby) {
else if (distance_from_player > ignore_modes_distance) {
// these modes slow down the bot, and we want to catch up
bot.modes.pause('item_collecting');
bot.modes.pause('hunting');
bot.modes.pause('torch_placing');
}
else if (distance_from_player <= ignore_modes_distance) {
bot.modes.unpause('item_collecting');
bot.modes.unpause('hunting');
bot.modes.unpause('torch_placing');
}
if (distance_from_player <= nearby_distance) {
clearInterval(doorCheckInterval);
doorCheckInterval = null;
bot.modes.pause('unstuck');

2
src/agent/modes.js
View file

@ -156,7 +156,7 @@ const modes_list = [
{
name: 'hunting',
description: 'Hunt nearby animals when idle.',
interrupts: [],
interrupts: ['action:followPlayer'],
on: true,
active: false,
update: async function (agent) {

89
src/models/_model_map.js Normal file
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@ -0,0 +1,89 @@
import { promises as fs } from 'fs';
import path from 'path';
import { fileURLToPath, pathToFileURL } from 'url';
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
// Dynamically discover model classes in this directory.
// Each model class must export a static `prefix` string.
const apiMap = await (async () => {
const map = {};
const files = (await fs.readdir(__dirname))
.filter(f => f.endsWith('.js') && f !== '_model_map.js' && f !== 'prompter.js');
for (const file of files) {
try {
const moduleUrl = pathToFileURL(path.join(__dirname, file)).href;
const mod = await import(moduleUrl);
for (const exported of Object.values(mod)) {
if (typeof exported === 'function' && Object.prototype.hasOwnProperty.call(exported, 'prefix')) {
const prefix = exported.prefix;
if (typeof prefix === 'string' && prefix.length > 0) {
map[prefix] = exported;
}
}
}
} catch (e) {
console.warn('Failed to load model module:', file, e?.message || e);
}
}
return map;
})();
export function selectAPI(profile) {
if (typeof profile === 'string' || profile instanceof String) {
profile = {model: profile};
}
// backwards compatibility with local->ollama
if (profile.api?.includes('local') || profile.model?.includes('local')) {
profile.api = 'ollama';
if (profile.model) {
profile.model = profile.model.replace('local', 'ollama');
}
}
if (!profile.api) {
const api = Object.keys(apiMap).find(key => profile.model?.startsWith(key));
if (api) {
profile.api = api;
}
else {
// check for some common models that do not require prefixes
if (profile.model.includes('gpt') || profile.model.includes('o1')|| profile.model.includes('o3'))
profile.api = 'openai';
else if (profile.model.includes('claude'))
profile.api = 'anthropic';
else if (profile.model.includes('gemini'))
profile.api = "google";
else if (profile.model.includes('grok'))
profile.api = 'grok';
else if (profile.model.includes('mistral'))
profile.api = 'mistral';
else if (profile.model.includes('deepseek'))
profile.api = 'deepseek';
else if (profile.model.includes('qwen'))
profile.api = 'qwen';
}
if (!profile.api) {
throw new Error('Unknown model:', profile.model);
}
}
if (!apiMap[profile.api]) {
throw new Error('Unknown api:', profile.api);
}
let model_name = profile.model.replace(profile.api + '/', ''); // remove prefix
profile.model = model_name === "" ? null : model_name; // if model is empty, set to null
return profile;
}
export function createModel(profile) {
if (!!apiMap[profile.model]) {
// if the model value is an api (instead of a specific model name)
// then set model to null so it uses the default model for that api
profile.model = null;
}
if (!apiMap[profile.api]) {
throw new Error('Unknown api:', profile.api);
}
const model = new apiMap[profile.api](profile.model, profile.url, profile.params);
return model;
}

32
src/models/azure.js Normal file
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@ -0,0 +1,32 @@
import { AzureOpenAI } from "openai";
import { getKey, hasKey } from '../utils/keys.js';
import { GPT } from './gpt.js'
export class AzureGPT extends GPT {
static prefix = 'azure';
constructor(model_name, url, params) {
super(model_name, url)
this.model_name = model_name;
this.params = params || {};
const config = {};
if (url)
config.endpoint = url;
config.apiKey = hasKey('AZURE_OPENAI_API_KEY') ? getKey('AZURE_OPENAI_API_KEY') : getKey('OPENAI_API_KEY');
config.deployment = model_name;
if (this.params.apiVersion) {
config.apiVersion = this.params.apiVersion;
delete this.params.apiVersion; // remove from params for later use in requests
}
else {
throw new Error('apiVersion is required in params for azure!');
}
this.openai = new AzureOpenAI(config)
}
}

61
src/models/cerebras.js Normal file
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@ -0,0 +1,61 @@
import CerebrasSDK from '@cerebras/cerebras_cloud_sdk';
import { strictFormat } from '../utils/text.js';
import { getKey } from '../utils/keys.js';
export class Cerebras {
static prefix = 'cerebras';
constructor(model_name, url, params) {
this.model_name = model_name;
this.url = url;
this.params = params;
// Initialize client with API key
this.client = new CerebrasSDK({ apiKey: getKey('CEREBRAS_API_KEY') });
}
async sendRequest(turns, systemMessage, stop_seq = '***') {
// Format messages array
const messages = strictFormat(turns);
messages.unshift({ role: 'system', content: systemMessage });
const pack = {
model: this.model_name || 'gpt-oss-120b',
messages,
stream: false,
...(this.params || {}),
};
let res;
try {
const completion = await this.client.chat.completions.create(pack);
// OpenAI-compatible shape
res = completion.choices?.[0]?.message?.content || '';
} catch (err) {
console.error('Cerebras API error:', err);
res = 'My brain disconnected, try again.';
}
return res;
}
async sendVisionRequest(messages, systemMessage, imageBuffer) {
const imageMessages = [...messages];
imageMessages.push({
role: "user",
content: [
{ type: "text", text: systemMessage },
{
type: "image_url",
image_url: {
url: `data:image/jpeg;base64,${imageBuffer.toString('base64')}`
}
}
]
});
return this.sendRequest(imageMessages, systemMessage);
}
async embed(text) {
throw new Error('Embeddings are not supported by Cerebras.');
}
}

5
src/models/claude.js
View file

@ -3,6 +3,7 @@ import { strictFormat } from '../utils/text.js';
import { getKey } from '../utils/keys.js';
export class Claude {
static prefix = 'anthropic';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params || {};
@ -20,7 +21,7 @@ export class Claude {
const messages = strictFormat(turns);
let res = null;
try {
console.log('Awaiting anthropic api response...')
console.log(`Awaiting anthropic response from ${this.model_name}...`)
if (!this.params.max_tokens) {
if (this.params.thinking?.budget_tokens) {
this.params.max_tokens = this.params.thinking.budget_tokens + 1000;
@ -30,7 +31,7 @@ export class Claude {
}
}
const resp = await this.anthropic.messages.create({
model: this.model_name || "claude-3-sonnet-20240229",
model: this.model_name || "claude-sonnet-4-20250514",
system: systemMessage,
messages: messages,
...(this.params || {})

1
src/models/deepseek.js
View file

@ -3,6 +3,7 @@ import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class DeepSeek {
static prefix = 'deepseek';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;

9
src/models/gemini.js
View file

@ -3,6 +3,7 @@ import { toSinglePrompt, strictFormat } from '../utils/text.js';
import { getKey } from '../utils/keys.js';
export class Gemini {
static prefix = 'google';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;
@ -36,7 +37,7 @@ export class Gemini {
async sendRequest(turns, systemMessage) {
let model;
const modelConfig = {
model: this.model_name || "gemini-1.5-flash",
model: this.model_name || "gemini-2.5-flash",
// systemInstruction does not work bc google is trash
};
if (this.url) {
@ -142,15 +143,15 @@ export class Gemini {
}
async embed(text) {
let model;
let model = this.model_name || "text-embedding-004";
if (this.url) {
model = this.genAI.getGenerativeModel(
{ model: "text-embedding-004" },
{ model },
{ baseUrl: this.url }
);
} else {
model = this.genAI.getGenerativeModel(
{ model: "text-embedding-004" }
{ model }
);
}

1
src/models/glhf.js
View file

@ -2,6 +2,7 @@ import OpenAIApi from 'openai';
import { getKey } from '../utils/keys.js';
export class GLHF {
static prefix = 'glhf';
constructor(model_name, url) {
this.model_name = model_name;
const apiKey = getKey('GHLF_API_KEY');

11
src/models/gpt.js
View file

@ -3,6 +3,7 @@ import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class GPT {
static prefix = 'openai';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;
@ -22,20 +23,21 @@ export class GPT {
async sendRequest(turns, systemMessage, stop_seq='***') {
let messages = [{'role': 'system', 'content': systemMessage}].concat(turns);
messages = strictFormat(messages);
let model = this.model_name || "gpt-4o-mini";
const pack = {
model: this.model_name || "gpt-3.5-turbo",
model: model,
messages,
stop: stop_seq,
...(this.params || {})
};
if (this.model_name.includes('o1') || this.model_name.includes('o3') || this.model_name.includes('5')) {
if (model.includes('o1') || model.includes('o3') || model.includes('5')) {
delete pack.stop;
}
let res = null;
try {
console.log('Awaiting openai api response from model', this.model_name)
console.log('Awaiting openai api response from model', model)
// console.log('Messages:', messages);
let completion = await this.openai.chat.completions.create(pack);
if (completion.choices[0].finish_reason == 'length')
@ -88,6 +90,3 @@ export class GPT {
}
}

8
src/models/grok.js
View file

@ -3,6 +3,7 @@ import { getKey } from '../utils/keys.js';
// xAI doesn't supply a SDK for their models, but fully supports OpenAI and Anthropic SDKs
export class Grok {
static prefix = 'xai';
constructor(model_name, url, params) {
this.model_name = model_name;
this.url = url;
@ -19,13 +20,12 @@ export class Grok {
this.openai = new OpenAIApi(config);
}
async sendRequest(turns, systemMessage, stop_seq='***') {
async sendRequest(turns, systemMessage) {
let messages = [{'role': 'system', 'content': systemMessage}].concat(turns);
const pack = {
model: this.model_name || "grok-beta",
model: this.model_name || "grok-3-mini-latest",
messages,
stop: [stop_seq],
...(this.params || {})
};
@ -42,7 +42,7 @@ export class Grok {
catch (err) {
if ((err.message == 'Context length exceeded' || err.code == 'context_length_exceeded') && turns.length > 1) {
console.log('Context length exceeded, trying again with shorter context.');
return await this.sendRequest(turns.slice(1), systemMessage, stop_seq);
return await this.sendRequest(turns.slice(1), systemMessage);
} else if (err.message.includes('The model expects a single `text` element per message.')) {
console.log(err);
res = 'Vision is only supported by certain models.';

4
src/models/groq.js
View file

@ -6,6 +6,7 @@ import { getKey } from '../utils/keys.js';
// Umbrella class for everything under the sun... That GroqCloud provides, that is.
export class GroqCloudAPI {
static prefix = 'groq';
constructor(model_name, url, params) {
@ -49,7 +50,7 @@ export class GroqCloudAPI {
let completion = await this.groq.chat.completions.create({
"messages": messages,
"model": this.model_name || "llama-3.3-70b-versatile",
"model": this.model_name || "qwen/qwen3-32b",
"stream": false,
"stop": stop_seq,
...(this.params || {})
@ -63,7 +64,6 @@ export class GroqCloudAPI {
if (err.message.includes("content must be a string")) {
res = "Vision is only supported by certain models.";
} else {
console.log(this.model_name);
res = "My brain disconnected, try again.";
}
console.log(err);

1
src/models/huggingface.js
View file

@ -3,6 +3,7 @@ import { getKey } from '../utils/keys.js';
import { HfInference } from "@huggingface/inference";
export class HuggingFace {
static prefix = 'huggingface';
constructor(model_name, url, params) {
// Remove 'huggingface/' prefix if present
this.model_name = model_name.replace('huggingface/', '');

1
src/models/hyperbolic.js
View file

@ -1,6 +1,7 @@
import { getKey } from '../utils/keys.js';
export class Hyperbolic {
static prefix = 'hyperbolic';
constructor(modelName, apiUrl) {
this.modelName = modelName || "deepseek-ai/DeepSeek-V3";
this.apiUrl = apiUrl || "https://api.hyperbolic.xyz/v1/chat/completions";

95
src/models/mercury.js Normal file
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@ -0,0 +1,95 @@
import OpenAIApi from 'openai';
import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class Mercury {
static prefix = 'mercury';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;
let config = {};
if (url)
config.baseURL = url;
else
config.baseURL = "https://api.inceptionlabs.ai/v1";
config.apiKey = getKey('MERCURY_API_KEY');
this.openai = new OpenAIApi(config);
}
async sendRequest(turns, systemMessage, stop_seq='***') {
if (typeof stop_seq === 'string') {
stop_seq = [stop_seq];
} else if (!Array.isArray(stop_seq)) {
stop_seq = [];
}
let messages = [{'role': 'system', 'content': systemMessage}].concat(turns);
messages = strictFormat(messages);
const pack = {
model: this.model_name || "mercury-coder-small",
messages,
stop: stop_seq,
...(this.params || {})
};
let res = null;
try {
console.log('Awaiting mercury api response from model', this.model_name)
// console.log('Messages:', messages);
let completion = await this.openai.chat.completions.create(pack);
if (completion.choices[0].finish_reason == 'length')
throw new Error('Context length exceeded');
console.log('Received.')
res = completion.choices[0].message.content;
}
catch (err) {
if ((err.message == 'Context length exceeded' || err.code == 'context_length_exceeded') && turns.length > 1) {
console.log('Context length exceeded, trying again with shorter context.');
return await this.sendRequest(turns.slice(1), systemMessage, stop_seq);
} else if (err.message.includes('image_url')) {
console.log(err);
res = 'Vision is only supported by certain models.';
} else {
console.log(err);
res = 'My brain disconnected, try again.';
}
}
return res;
}
async sendVisionRequest(messages, systemMessage, imageBuffer) {
const imageMessages = [...messages];
imageMessages.push({
role: "user",
content: [
{ type: "text", text: systemMessage },
{
type: "image_url",
image_url: {
url: `data:image/jpeg;base64,${imageBuffer.toString('base64')}`
}
}
]
});
return this.sendRequest(imageMessages, systemMessage);
}
async embed(text) {
if (text.length > 8191)
text = text.slice(0, 8191);
const embedding = await this.openai.embeddings.create({
model: this.model_name || "text-embedding-3-small",
input: text,
encoding_format: "float",
});
return embedding.data[0].embedding;
}
}

1
src/models/mistral.js
View file

@ -3,6 +3,7 @@ import { getKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class Mistral {
static prefix = 'mistral';
#client;
constructor(model_name, url, params) {

5
src/models/novita.js
View file

@ -4,8 +4,9 @@ import { strictFormat } from '../utils/text.js';
// llama, mistral
export class Novita {
static prefix = 'novita';
constructor(model_name, url, params) {
this.model_name = model_name.replace('novita/', '');
this.model_name = model_name;
this.url = url || 'https://api.novita.ai/v3/openai';
this.params = params;
@ -25,7 +26,7 @@ export class Novita {
messages = strictFormat(messages);
const pack = {
model: this.model_name || "meta-llama/llama-3.1-70b-instruct",
model: this.model_name || "meta-llama/llama-4-scout-17b-16e-instruct",
messages,
stop: [stop_seq],
...(this.params || {})

68
src/models/local.js → src/models/ollama.js
View file

@ -1,6 +1,7 @@
import { strictFormat } from '../utils/text.js';
export class Local {
export class Ollama {
static prefix = 'ollama';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;
@ -10,11 +11,9 @@ export class Local {
}
async sendRequest(turns, systemMessage) {
let model = this.model_name || 'llama3.1'; // Updated to llama3.1, as it is more performant than llama3
let model = this.model_name || 'sweaterdog/andy-4:micro-q8_0';
let messages = strictFormat(turns);
messages.unshift({ role: 'system', content: systemMessage });
// We'll attempt up to 5 times for models with deepseek-r1-esk reasoning if the <think> tags are mismatched.
const maxAttempts = 5;
let attempt = 0;
let finalRes = null;
@ -24,14 +23,14 @@ export class Local {
console.log(`Awaiting local response... (model: ${model}, attempt: ${attempt})`);
let res = null;
try {
res = await this.send(this.chat_endpoint, {
let apiResponse = await this.send(this.chat_endpoint, {
model: model,
messages: messages,
stream: false,
...(this.params || {})
});
if (res) {
res = res['message']['content'];
if (apiResponse) {
res = apiResponse['message']['content'];
} else {
res = 'No response data.';
}
@ -43,36 +42,27 @@ export class Local {
console.log(err);
res = 'My brain disconnected, try again.';
}
}
// If the model name includes "deepseek-r1" or "Andy-3.5-reasoning", then handle the <think> block.
const hasOpenTag = res.includes("<think>");
const hasCloseTag = res.includes("</think>");
// If there's a partial mismatch, retry to get a complete response.
if ((hasOpenTag && !hasCloseTag)) {
console.warn("Partial <think> block detected. Re-generating...");
continue;
}
// If </think> is present but <think> is not, prepend <think>
if (hasCloseTag && !hasOpenTag) {
res = '<think>' + res;
}
// Changed this so if the model reasons, using <think> and </think> but doesn't start the message with <think>, <think> ges prepended to the message so no error occur.
// If both tags appear, remove them (and everything inside).
if (hasOpenTag && hasCloseTag) {
res = res.replace(/<think>[\s\S]*?<\/think>/g, '');
}
const hasOpenTag = res.includes("<think>");
const hasCloseTag = res.includes("</think>");
if ((hasOpenTag && !hasCloseTag)) {
console.warn("Partial <think> block detected. Re-generating...");
if (attempt < maxAttempts) continue;
}
if (hasCloseTag && !hasOpenTag) {
res = '<think>' + res;
}
if (hasOpenTag && hasCloseTag) {
res = res.replace(/<think>[\s\S]*?<\/think>/g, '').trim();
}
finalRes = res;
break; // Exit the loop if we got a valid response.
break;
}
if (finalRes == null) {
console.warn("Could not get a valid <think> block or normal response after max attempts.");
console.warn("Could not get a valid response after max attempts.");
finalRes = 'I thought too hard, sorry, try again.';
}
return finalRes;
@ -104,4 +94,22 @@ export class Local {
}
return data;
}
async sendVisionRequest(messages, systemMessage, imageBuffer) {
const imageMessages = [...messages];
imageMessages.push({
role: "user",
content: [
{ type: "text", text: systemMessage },
{
type: "image_url",
image_url: {
url: `data:image/jpeg;base64,${imageBuffer.toString('base64')}`
}
}
]
});
return this.sendRequest(imageMessages, systemMessage);
}
}

1
src/models/openrouter.js
View file

@ -3,6 +3,7 @@ import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class OpenRouter {
static prefix = 'openrouter';
constructor(model_name, url) {
this.model_name = model_name;

172
src/models/prompter.js
View file

@ -5,26 +5,10 @@ import { SkillLibrary } from "../agent/library/skill_library.js";
import { stringifyTurns } from '../utils/text.js';
import { getCommand } from '../agent/commands/index.js';
import settings from '../agent/settings.js';
import { Gemini } from './gemini.js';
import { GPT } from './gpt.js';
import { Claude } from './claude.js';
import { Mistral } from './mistral.js';
import { ReplicateAPI } from './replicate.js';
import { Local } from './local.js';
import { Novita } from './novita.js';
import { GroqCloudAPI } from './groq.js';
import { HuggingFace } from './huggingface.js';
import { Qwen } from "./qwen.js";
import { Grok } from "./grok.js";
import { DeepSeek } from './deepseek.js';
import { Hyperbolic } from './hyperbolic.js';
import { GLHF } from './glhf.js';
import { OpenRouter } from './openrouter.js';
import { VLLM } from './vllm.js';
import { promises as fs } from 'fs';
import path from 'path';
import { fileURLToPath } from 'url';
import { selectAPI, createModel } from './_model_map.js';
const __filename = fileURLToPath(import.meta.url);
const __dirname = path.dirname(__filename);
@ -66,70 +50,46 @@ export class Prompter {
this.last_prompt_time = 0;
this.awaiting_coding = false;
// try to get "max_tokens" parameter, else null
// for backwards compatibility, move max_tokens to params
let max_tokens = null;
if (this.profile.max_tokens)
max_tokens = this.profile.max_tokens;
let chat_model_profile = this._selectAPI(this.profile.model);
this.chat_model = this._createModel(chat_model_profile);
let chat_model_profile = selectAPI(this.profile.model);
this.chat_model = createModel(chat_model_profile);
if (this.profile.code_model) {
let code_model_profile = this._selectAPI(this.profile.code_model);
this.code_model = this._createModel(code_model_profile);
let code_model_profile = selectAPI(this.profile.code_model);
this.code_model = createModel(code_model_profile);
}
else {
this.code_model = this.chat_model;
}
if (this.profile.vision_model) {
let vision_model_profile = this._selectAPI(this.profile.vision_model);
this.vision_model = this._createModel(vision_model_profile);
let vision_model_profile = selectAPI(this.profile.vision_model);
this.vision_model = createModel(vision_model_profile);
}
else {
this.vision_model = this.chat_model;
}
let embedding = this.profile.embedding;
if (embedding === undefined) {
if (chat_model_profile.api !== 'ollama')
embedding = {api: chat_model_profile.api};
else
embedding = {api: 'none'};
}
else if (typeof embedding === 'string' || embedding instanceof String)
embedding = {api: embedding};
console.log('Using embedding settings:', embedding);
try {
if (embedding.api === 'google')
this.embedding_model = new Gemini(embedding.model, embedding.url);
else if (embedding.api === 'openai')
this.embedding_model = new GPT(embedding.model, embedding.url);
else if (embedding.api === 'replicate')
this.embedding_model = new ReplicateAPI(embedding.model, embedding.url);
else if (embedding.api === 'ollama')
this.embedding_model = new Local(embedding.model, embedding.url);
else if (embedding.api === 'qwen')
this.embedding_model = new Qwen(embedding.model, embedding.url);
else if (embedding.api === 'mistral')
this.embedding_model = new Mistral(embedding.model, embedding.url);
else if (embedding.api === 'huggingface')
this.embedding_model = new HuggingFace(embedding.model, embedding.url);
else if (embedding.api === 'novita')
this.embedding_model = new Novita(embedding.model, embedding.url);
else {
this.embedding_model = null;
let embedding_name = embedding ? embedding.api : '[NOT SPECIFIED]'
console.warn('Unsupported embedding: ' + embedding_name + '. Using word-overlap instead, expect reduced performance. Recommend using a supported embedding model. See Readme.');
let embedding_model_profile = null;
if (this.profile.embedding) {
try {
embedding_model_profile = selectAPI(this.profile.embedding);
} catch (e) {
embedding_model_profile = null;
}
}
catch (err) {
console.warn('Warning: Failed to initialize embedding model:', err.message);
console.log('Continuing anyway, using word-overlap instead.');
this.embedding_model = null;
if (embedding_model_profile) {
this.embedding_model = createModel(embedding_model_profile);
}
else {
this.embedding_model = createModel({api: chat_model_profile.api});
}
this.skill_libary = new SkillLibrary(agent, this.embedding_model);
mkdirSync(`./bots/${name}`, { recursive: true });
writeFileSync(`./bots/${name}/last_profile.json`, JSON.stringify(this.profile, null, 4), (err) => {
@ -140,88 +100,6 @@ export class Prompter {
});
}
_selectAPI(profile) {
if (typeof profile === 'string' || profile instanceof String) {
profile = {model: profile};
}
if (!profile.api) {
if (profile.model.includes('openrouter/'))
profile.api = 'openrouter'; // must do first because shares names with other models
else if (profile.model.includes('ollama/'))
profile.api = 'ollama'; // also must do early because shares names with other models
else if (profile.model.includes('gemini'))
profile.api = 'google';
else if (profile.model.includes('vllm/'))
profile.api = 'vllm';
else if (profile.model.includes('gpt') || profile.model.includes('o1')|| profile.model.includes('o3'))
profile.api = 'openai';
else if (profile.model.includes('claude'))
profile.api = 'anthropic';
else if (profile.model.includes('huggingface/'))
profile.api = "huggingface";
else if (profile.model.includes('replicate/'))
profile.api = 'replicate';
else if (profile.model.includes('mistralai/') || profile.model.includes("mistral/"))
model_profile.api = 'mistral';
else if (profile.model.includes("groq/") || profile.model.includes("groqcloud/"))
profile.api = 'groq';
else if (profile.model.includes("glhf/"))
profile.api = 'glhf';
else if (profile.model.includes("hyperbolic/"))
profile.api = 'hyperbolic';
else if (profile.model.includes('novita/'))
profile.api = 'novita';
else if (profile.model.includes('qwen'))
profile.api = 'qwen';
else if (profile.model.includes('grok'))
profile.api = 'xai';
else if (profile.model.includes('deepseek'))
profile.api = 'deepseek';
else if (profile.model.includes('mistral'))
profile.api = 'mistral';
else
throw new Error('Unknown model:', profile.model);
}
return profile;
}
_createModel(profile) {
let model = null;
if (profile.api === 'google')
model = new Gemini(profile.model, profile.url, profile.params);
else if (profile.api === 'openai')
model = new GPT(profile.model, profile.url, profile.params);
else if (profile.api === 'anthropic')
model = new Claude(profile.model, profile.url, profile.params);
else if (profile.api === 'replicate')
model = new ReplicateAPI(profile.model.replace('replicate/', ''), profile.url, profile.params);
else if (profile.api === 'ollama')
model = new Local(profile.model.replace('ollama/', ''), profile.url, profile.params);
else if (profile.api === 'mistral')
model = new Mistral(profile.model, profile.url, profile.params);
else if (profile.api === 'groq')
model = new GroqCloudAPI(profile.model.replace('groq/', '').replace('groqcloud/', ''), profile.url, profile.params);
else if (profile.api === 'huggingface')
model = new HuggingFace(profile.model, profile.url, profile.params);
else if (profile.api === 'glhf')
model = new GLHF(profile.model.replace('glhf/', ''), profile.url, profile.params);
else if (profile.api === 'hyperbolic')
model = new Hyperbolic(profile.model.replace('hyperbolic/', ''), profile.url, profile.params);
else if (profile.api === 'novita')
model = new Novita(profile.model.replace('novita/', ''), profile.url, profile.params);
else if (profile.api === 'qwen')
model = new Qwen(profile.model, profile.url, profile.params);
else if (profile.api === 'xai')
model = new Grok(profile.model, profile.url, profile.params);
else if (profile.api === 'deepseek')
model = new DeepSeek(profile.model, profile.url, profile.params);
else if (profile.api === 'openrouter')
model = new OpenRouter(profile.model.replace('openrouter/', ''), profile.url, profile.params);
else if (profile.api === 'vllm')
model = new VLLM(profile.model.replace('vllm/', ''), profile.url, profile.params);
else
throw new Error('Unknown API:', profile.api);
return model;
}
getName() {
return this.profile.name;
}
@ -350,7 +228,7 @@ export class Prompter {
console.error('Error: Generated response is not a string', generation);
throw new Error('Generated response is not a string');
}
console.log("Generated response:", generation);
console.log("Generated response:", generation);
await this._saveLog(prompt, messages, generation, 'conversation');
} catch (error) {
@ -367,7 +245,7 @@ export class Prompter {
if (current_msg_time !== this.most_recent_msg_time) {
console.warn(`${this.agent.name} received new message while generating, discarding old response.`);
return '';
}
}
if (generation?.includes('</think>')) {
const [_, afterThink] = generation.split('</think>')
@ -404,7 +282,7 @@ export class Prompter {
await this._saveLog(prompt, to_summarize, resp, 'memSaving');
if (resp?.includes('</think>')) {
const [_, afterThink] = resp.split('</think>')
resp = afterThink
resp = afterThink;
}
return resp;
}
@ -482,6 +360,4 @@ export class Prompter {
logFile = path.join(logDir, logFile);
await fs.appendFile(logFile, String(logEntry), 'utf-8');
}
}

1
src/models/qwen.js
View file

@ -3,6 +3,7 @@ import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class Qwen {
static prefix = 'qwen';
constructor(model_name, url, params) {
this.model_name = model_name;
this.params = params;

1
src/models/replicate.js
View file

@ -4,6 +4,7 @@ import { getKey } from '../utils/keys.js';
// llama, mistral
export class ReplicateAPI {
static prefix = 'replicate';
constructor(model_name, url, params) {
this.model_name = model_name;
this.url = url;

6
src/models/vllm.js
View file

@ -6,6 +6,7 @@ import { getKey, hasKey } from '../utils/keys.js';
import { strictFormat } from '../utils/text.js';
export class VLLM {
static prefix = 'vllm';
constructor(model_name, url) {
this.model_name = model_name;
@ -23,13 +24,14 @@ export class VLLM {
async sendRequest(turns, systemMessage, stop_seq = '***') {
let messages = [{ 'role': 'system', 'content': systemMessage }].concat(turns);
let model = this.model_name || "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B";
if (this.model_name.includes('deepseek') || this.model_name.includes('qwen')) {
if (model.includes('deepseek') || model.includes('qwen')) {
messages = strictFormat(messages);
}
const pack = {
model: this.model_name || "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B",
model: model,
messages,
stop: stop_seq,
};