Merge pull request #225 from kolbytn/hugging-face

Hugging face

README.md

@@ -10,9 +10,9 @@ This project allows an AI model to write/execute code on your computer that may
 
 ## Requirements
 
-- [OpenAI API Subscription](https://openai.com/blog/openai-api), [Gemini API Subscription](https://aistudio.google.com/app/apikey), [Anthropic API Subscription](https://docs.anthropic.com/claude/docs/getting-access-to-claude), [Replicate API Subscription](https://replicate.com/), [Ollama Installed](https://ollama.com/download), or, a [Groq Account & API Key](https://console.groq.com/keys)
-- [Minecraft Java Edition](https://www.minecraft.net/en-us/store/minecraft-java-bedrock-edition-pc)
+- [Minecraft Java Edition](https://www.minecraft.net/en-us/store/minecraft-java-bedrock-edition-pc) (up to v1.20.4)
 - [Node.js](https://nodejs.org/) (at least v14)
+- 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)
 
 ## Installation
 
@@ -25,6 +25,7 @@ Rename `keys.example.json` to `keys.json` and fill in your API keys, and you can
 | Replicate | `REPLICATE_API_KEY` | `meta/meta-llama-3-70b-instruct` | [docs](https://replicate.com/collections/language-models) |
 | Ollama (local) | n/a | `llama3` | [docs](https://ollama.com/library) |
 | Groq | `GROQCLOUD_API_KEY` | `groq/mixtral-8x7b-32768` | [docs](https://console.groq.com/docs/models) |
+| Hugging Face | `HUGGINGFACE_API_KEY` | `huggingface/mistralai/Mistral-Nemo-Instruct-2407` | [docs](https://huggingface.co/models) |
 
 If you use Ollama, to install the models used by default (generation and embedding), execute the following terminal command:
 `ollama pull llama3 && ollama pull nomic-embed-text`

keys.example.json

@@ -4,5 +4,6 @@
     "GEMINI_API_KEY": "",
     "ANTHROPIC_API_KEY": "",
     "REPLICATE_API_KEY": "",
-    "GROQCLOUD_API_KEY": ""
+    "GROQCLOUD_API_KEY": "",
+    "HUGGINGFACE_API_KEY": ""
 }

package.json

@@ -3,6 +3,7 @@
     "dependencies": {
         "@anthropic-ai/sdk": "^0.17.1",
         "@google/generative-ai": "^0.2.1",
+        "@huggingface/inference": "^2.8.1",
         "google-translate-api-x": "^10.7.1",
         "groq-sdk": "^0.5.0",
         "minecraft-data": "^3.46.2",

src/agent/prompter.js

@@ -11,6 +11,7 @@ import { Claude } from '../models/claude.js';
 import { ReplicateAPI } from '../models/replicate.js';
 import { Local } from '../models/local.js';
 import { GroqCloudAPI } from '../models/groq.js';
+import { HuggingFace } from '../models/huggingface.js';
 
 export class Prompter {
     constructor(agent, fp) {
@@ -36,6 +37,8 @@ export class Prompter {
                 chat.api = 'openai';
             else if (chat.model.includes('claude'))
                 chat.api = 'anthropic';
+            else if (chat.model.includes('huggingface/'))
+                chat.api = "huggingface";
             else if (chat.model.includes('meta/') || chat.model.includes('mistralai/') || chat.model.includes('replicate/'))
                 chat.api = 'replicate';
             else if (chat.model.includes("groq/") || chat.model.includes("groqcloud/"))
@@ -46,19 +49,21 @@ export class Prompter {
 
         console.log('Using chat settings:', chat);
 
-        if (chat.api == 'google')
+        if (chat.api === 'google')
             this.chat_model = new Gemini(chat.model, chat.url);
-        else if (chat.api == 'openai')
+        else if (chat.api === 'openai')
             this.chat_model = new GPT(chat.model, chat.url);
-        else if (chat.api == 'anthropic')
+        else if (chat.api === 'anthropic')
             this.chat_model = new Claude(chat.model, chat.url);
-        else if (chat.api == 'replicate')
+        else if (chat.api === 'replicate')
             this.chat_model = new ReplicateAPI(chat.model, chat.url);
-        else if (chat.api == 'ollama')
+        else if (chat.api === 'ollama')
             this.chat_model = new Local(chat.model, chat.url);
-        else if (chat.api == 'groq') {
+        else if (chat.api === 'groq') {
             this.chat_model = new GroqCloudAPI(chat.model.replace('groq/', '').replace('groqcloud/', ''), chat.url, max_tokens ? max_tokens : 8192);
         }
+        else if (chat.api === 'huggingface')
+            this.chat_model = new HuggingFace(chat.model, chat.url);
         else
             throw new Error('Unknown API:', api);
 
@@ -74,13 +79,13 @@ export class Prompter {
 
         console.log('Using embedding settings:', embedding);
 
-        if (embedding.api == 'google')
+        if (embedding.api === 'google')
             this.embedding_model = new Gemini(embedding.model, embedding.url);
-        else if (embedding.api == 'openai')
+        else if (embedding.api === 'openai')
             this.embedding_model = new GPT(embedding.model, embedding.url);
-        else if (embedding.api == 'replicate') 
+        else if (embedding.api === 'replicate')
             this.embedding_model = new ReplicateAPI(embedding.model, embedding.url);
-        else if (embedding.api == 'ollama')
+        else if (embedding.api === 'ollama')
             this.embedding_model = new Local(embedding.model, embedding.url);
         else {
             this.embedding_model = null;

src/models/huggingface.js

@@ -0,0 +1,44 @@
+import {toSinglePrompt} from '../utils/text.js';
+import {getKey} from '../utils/keys.js';
+import {HfInference} from "@huggingface/inference";
+
+export class HuggingFace {
+    constructor(model_name, url) {
+        this.model_name = model_name.replace('huggingface/','');
+        this.url = url;
+
+        if (this.url) {
+            console.warn("Hugging Face doesn't support custom urls!");
+        }
+
+        this.huggingface = new HfInference(getKey('HUGGINGFACE_API_KEY'));
+    }
+
+    async sendRequest(turns, systemMessage) {
+        const stop_seq = '***';
+        const prompt = toSinglePrompt(turns, null, stop_seq);
+        let model_name = this.model_name || 'meta-llama/Meta-Llama-3-8B';
+
+        const input = systemMessage + "\n" + prompt;
+        let res = '';
+        try {
+            console.log('Awaiting Hugging Face API response...');
+            for await (const chunk of this.huggingface.chatCompletionStream({
+                model: model_name,
+                messages: [{ role: "user", content: input }]
+            })) {
+                res += (chunk.choices[0]?.delta?.content || "");
+            }
+        } catch (err) {
+            console.log(err);
+            res = 'My brain disconnected, try again.';
+        }
+        console.log('Received.');
+        console.log(res);
+        return res;
+    }
+
+    async embed(text) {
+        throw new Error('Embeddings are not supported by HuggingFace.');
+    }
+}