Merge pull request #589 from mindcraft-bots/develop

Models Update

README.md

@@ -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},
 }
 ```
+
+

keys.example.json

@@ -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":""
 }

package.json

@@ -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",

profiles/azure.json

@@ -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" 
+        }
+    }
+  }

profiles/claude.json

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

profiles/claude_thinker.json

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

profiles/gemini.json

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

profiles/grok.json

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

profiles/mercury.json

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

settings.js

@@ -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

src/agent/action_manager.js

@@ -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
                 }

src/agent/library/skills.js

@@ -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));
+        await new Promise(resolve => setTimeout(resolve, 1000));
-        console.log('checking...');
-        let collected = false;
         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) {
+        if (Date.now() - last_collected > 11000) {
-            break; // if nothing was collected this time or last time
+            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;
+        else if (distance_from_player > ignore_modes_distance) {
-        if (is_nearby) {
+            // 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');

src/agent/modes.js

@@ -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) {

src/models/_model_map.js

@@ -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;
+}

src/models/azure.js

@@ -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)
+    }
+}

src/models/cerebras.js

@@ -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.');
+    }
+}

src/models/claude.js

@@ -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 || {})

src/models/deepseek.js

@@ -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;

src/models/gemini.js

@@ -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 }
             );
         }
 

src/models/glhf.js

@@ -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');

src/models/gpt.js

@@ -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 {
     }
 
 }
-
-
-

src/models/grok.js

@@ -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.';

src/models/groq.js

@@ -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);

src/models/huggingface.js

@@ -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/', '');

src/models/hyperbolic.js

@@ -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";

src/models/mercury.js

@@ -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;
+    }
+
+}
+
+
+

src/models/mistral.js

@@ -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) {

src/models/novita.js

@@ -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 || {})

src/models/ollama.js

@@ -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) {
+                if (apiResponse) {
-                    res = res['message']['content'];
+                    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 (attempt < maxAttempts) 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, '');
+                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);
+    }
 }

src/models/openrouter.js

@@ -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;
 

src/models/prompter.js

@@ -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);
+        let chat_model_profile = selectAPI(this.profile.model);
-        this.chat_model = this._createModel(chat_model_profile);
+        this.chat_model = createModel(chat_model_profile);
 
         if (this.profile.code_model) {
-            let code_model_profile = this._selectAPI(this.profile.code_model);
+            let code_model_profile = selectAPI(this.profile.code_model);
-            this.code_model = this._createModel(code_model_profile);
+            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);
+            let vision_model_profile = selectAPI(this.profile.vision_model);
-            this.vision_model = this._createModel(vision_model_profile);
+            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);
         
+        let embedding_model_profile = null;
+        if (this.profile.embedding) {
             try {
-            if (embedding.api === 'google')
+                embedding_model_profile = selectAPI(this.profile.embedding);
-                this.embedding_model = new Gemini(embedding.model, embedding.url);
+            } catch (e) {
-            else if (embedding.api === 'openai')
+                embedding_model_profile = null;
-                this.embedding_model = new GPT(embedding.model, embedding.url);
+            }
-            else if (embedding.api === 'replicate')
+        }
-                this.embedding_model = new ReplicateAPI(embedding.model, embedding.url);
+        if (embedding_model_profile) {
-            else if (embedding.api === 'ollama')
+            this.embedding_model = createModel(embedding_model_profile);
-                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;
+            this.embedding_model = createModel({api: chat_model_profile.api});
-                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.');
-            }
-        }
-        catch (err) {
-            console.warn('Warning: Failed to initialize embedding model:', err.message);
-            console.log('Continuing anyway, using word-overlap instead.');
-            this.embedding_model = null;
         }
+
         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;
     }
@@ -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');
     }
-
-
 }

src/models/qwen.js

@@ -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;

src/models/replicate.js

@@ -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;

src/models/vllm.js

@@ -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,
         };