feat: add Chutes AI as LLM provider

frontend/src/components/LLMSelection/ChutesAiOptions/index.jsx

@@ -0,0 +1,114 @@
+import { useState, useEffect } from "react";
+import System from "@/models/system";
+
+export default function ChutesAiOptions({ settings }) {
+  const [inputValue, setInputValue] = useState(settings?.ChutesApiKey);
+  const [apiKey, setApiKey] = useState(settings?.ChutesApiKey);
+
+  return (
+    <div className="flex gap-[36px] mt-1.5">
+      <div className="flex flex-col w-60">
+        <label className="text-white text-sm font-semibold block mb-3">
+          Chutes API Key
+        </label>
+        <input
+          type="password"
+          name="ChutesApiKey"
+          className="border-none bg-theme-settings-input-bg text-white placeholder:text-theme-settings-input-placeholder text-sm rounded-lg focus:outline-primary-button active:outline-primary-button outline-none block w-full p-2.5"
+          placeholder="Chutes API Key"
+          defaultValue={settings?.ChutesApiKey ? "*".repeat(20) : ""}
+          required={true}
+          autoComplete="off"
+          spellCheck={false}
+          onChange={(e) => setInputValue(e.target.value)}
+          onBlur={() => setApiKey(inputValue)}
+        />
+      </div>
+
+      {!settings?.credentialsOnly && (
+        <ChutesAIModelSelection settings={settings} apiKey={apiKey} />
+      )}
+    </div>
+  );
+}
+
+function ChutesAIModelSelection({ apiKey, settings }) {
+  const [customModels, setCustomModels] = useState([]);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    async function findCustomModels() {
+      if (!apiKey) {
+        setCustomModels([]);
+        setLoading(true);
+        return;
+      }
+
+      try {
+        setLoading(true);
+        const { models } = await System.customModels("chutes", apiKey);
+        setCustomModels(models || []);
+      } catch (error) {
+        console.error("Failed to fetch custom models:", error);
+        setCustomModels([]);
+      } finally {
+        setLoading(false);
+      }
+    }
+    findCustomModels();
+  }, [apiKey]);
+
+  if (loading) {
+    return (
+      <div className="flex flex-col w-60">
+        <label className="text-white text-sm font-semibold block mb-3">
+          Chat Model Selection
+        </label>
+        <select
+          name="ChutesModelPref"
+          disabled={true}
+          className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+        >
+          <option disabled={true} selected={true}>
+            --loading available models--
+          </option>
+        </select>
+        <p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
+          Enter a valid API key to view all available models for your account.
+        </p>
+      </div>
+    );
+  }
+
+  return (
+    <div className="flex flex-col w-60">
+      <label className="text-white text-sm font-semibold block mb-3">
+        Chat Model Selection
+      </label>
+      <select
+        name="ChutesModelPref"
+        required={true}
+        className="border-none bg-theme-settings-input-bg border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+      >
+        {customModels.length > 0 && (
+          <optgroup label="Available models">
+            {customModels.map((model) => {
+              return (
+                <option
+                  key={model.id}
+                  value={model.id}
+                  selected={settings?.ChutesModelPref === model.id}
+                >
+                  {model.id}
+                </option>
+              );
+            })}
+          </optgroup>
+        )}
+      </select>
+      <p className="text-xs leading-[18px] font-base text-white text-opacity-60 mt-2">
+        Select the Chutes AI model you want to use for your conversations.
+      </p>
+    </div>
+  );
+}

frontend/src/components/ProviderPrivacy/constants.js

@@ -45,6 +45,7 @@ import DockerModelRunnerLogo from "@/media/llmprovider/docker-model-runner.png";
 import PrivateModeLogo from "@/media/llmprovider/privatemode.png";
 import SambaNovaLogo from "@/media/llmprovider/sambanova.png";
 import LemonadeLogo from "@/media/llmprovider/lemonade.png";
+import ChutesLogo from "@/media/llmprovider/chutes.png";
 
 const LLM_PROVIDER_PRIVACY_MAP = {
   openai: {
@@ -252,6 +253,11 @@ const LLM_PROVIDER_PRIVACY_MAP = {
     ],
     logo: LemonadeLogo,
   },
+  chutes: {
+    name: "Chutes AI",
+    policyUrl: "https://chutes.ai/privacy",
+    logo: ChutesLogo,
+  },
 };
 
 const VECTOR_DB_PROVIDER_PRIVACY_MAP = {

frontend/src/hooks/useGetProvidersModels.js

@@ -32,6 +32,7 @@ const PROVIDER_DEFAULT_MODELS = {
   "generic-openai": [],
   bedrock: [],
   xai: ["grok-beta"],
+  chutes: [],
 };
 
 // For providers with large model lists (e.g. togetherAi) - we subgroup the options

frontend/src/pages/GeneralSettings/LLMPreference/index.jsx

@@ -41,6 +41,7 @@ import DockerModelRunnerLogo from "@/media/llmprovider/docker-model-runner.png";
 import PrivateModeLogo from "@/media/llmprovider/privatemode.png";
 import SambaNovaLogo from "@/media/llmprovider/sambanova.png";
 import LemonadeLogo from "@/media/llmprovider/lemonade.png";
+import ChutesLogo from "@/media/llmprovider/chutes.png";
 
 import PreLoader from "@/components/Preloader";
 import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
@@ -79,6 +80,7 @@ import DockerModelRunnerOptions from "@/components/LLMSelection/DockerModelRunne
 import PrivateModeOptions from "@/components/LLMSelection/PrivateModeOptions";
 import SambaNovaOptions from "@/components/LLMSelection/SambaNovaOptions";
 import LemonadeOptions from "@/components/LLMSelection/LemonadeOptions";
+import ChutesAiOptions from "@/components/LLMSelection/ChutesAiOptions";
 
 import LLMItem from "@/components/LLMSelection/LLMItem";
 import { CaretUpDown, MagnifyingGlass, X } from "@phosphor-icons/react";
@@ -401,6 +403,15 @@ export const AVAILABLE_LLM_PROVIDERS = [
     description: "Run GiteeAI's powerful LLMs.",
     requiredConfig: ["GiteeAIApiKey"],
   },
+  {
+    name: "Chutes AI",
+    value: "chutes",
+    logo: ChutesLogo,
+    options: (settings) => <ChutesAiOptions settings={settings} />,
+    description:
+      "Decentralized AI inference on Bittensor SN64, TEE-secured, OpenAI-compatible.",
+    requiredConfig: ["ChutesApiKey"],
+  },
   {
     name: "Generic OpenAI",
     value: "generic-openai",

frontend/src/pages/OnboardingFlow/Steps/LLMPreference/index.jsx

@@ -35,6 +35,7 @@ import DockerModelRunnerLogo from "@/media/llmprovider/docker-model-runner.png";
 import PrivateModeLogo from "@/media/llmprovider/privatemode.png";
 import SambaNovaLogo from "@/media/llmprovider/sambanova.png";
 import LemonadeLogo from "@/media/llmprovider/lemonade.png";
+import ChutesLogo from "@/media/llmprovider/chutes.png";
 
 import OpenAiOptions from "@/components/LLMSelection/OpenAiOptions";
 import GenericOpenAiOptions from "@/components/LLMSelection/GenericOpenAiOptions";
@@ -71,6 +72,7 @@ import DockerModelRunnerOptions from "@/components/LLMSelection/DockerModelRunne
 import PrivateModeOptions from "@/components/LLMSelection/PrivateModeOptions";
 import SambaNovaOptions from "@/components/LLMSelection/SambaNovaOptions";
 import LemonadeOptions from "@/components/LLMSelection/LemonadeOptions";
+import ChutesAiOptions from "@/components/LLMSelection/ChutesAiOptions";
 
 import LLMItem from "@/components/LLMSelection/LLMItem";
 import System from "@/models/system";
@@ -336,6 +338,14 @@ const LLMS = [
     options: (settings) => <GiteeAiOptions settings={settings} />,
     description: "Run GiteeAI's powerful LLMs.",
   },
+  {
+    name: "Chutes AI",
+    value: "chutes",
+    logo: ChutesLogo,
+    options: (settings) => <ChutesAiOptions settings={settings} />,
+    description:
+      "Decentralized AI inference on Bittensor SN64, TEE-secured, OpenAI-compatible.",
+  },
 ];
 
 export default function LLMPreference({

server/utils/AiProviders/chutes/index.js

@@ -0,0 +1,186 @@
+const { NativeEmbedder } = require("../../EmbeddingEngines/native");
+const {
+  LLMPerformanceMonitor,
+} = require("../../helpers/chat/LLMPerformanceMonitor");
+const {
+  handleDefaultStreamResponseV2,
+} = require("../../helpers/chat/responses");
+const { MODEL_MAP } = require("../modelMap");
+
+class ChutesLLM {
+  constructor(embedder = null, modelPreference = null) {
+    const { OpenAI: OpenAIApi } = require("openai");
+    if (!process.env.CHUTES_API_KEY)
+      throw new Error("No Chutes API key was set.");
+
+    this.className = "ChutesLLM";
+    this.openai = new OpenAIApi({
+      baseURL: "https://llm.chutes.ai/v1",
+      apiKey: process.env.CHUTES_API_KEY,
+    });
+    this.model =
+      modelPreference || process.env.CHUTES_MODEL_PREF || "chutes/DeepSeek-V3.2-TEE";
+    this.limits = {
+      history: this.promptWindowLimit() * 0.15,
+      system: this.promptWindowLimit() * 0.15,
+      user: this.promptWindowLimit() * 0.7,
+    };
+
+    this.embedder = embedder ?? new NativeEmbedder();
+    this.defaultTemp = 0.7;
+  }
+
+  #appendContext(contextTexts = []) {
+    if (!contextTexts || !contextTexts.length) return "";
+    return (
+      "\nContext:\n" +
+      contextTexts
+        .map((text, i) => {
+          return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+        })
+        .join("")
+    );
+  }
+
+  #log(text, ...args) {
+    console.log(`\x1b[32m[ChutesAI]\x1b[0m ${text}`, ...args);
+  }
+
+  streamingEnabled() {
+    return "streamGetChatCompletion" in this;
+  }
+
+  static promptWindowLimit(modelName) {
+    return MODEL_MAP.get("chutes", modelName) ?? 65536;
+  }
+
+  promptWindowLimit() {
+    return MODEL_MAP.get("chutes", this.model) ?? 65536;
+  }
+
+  async isValidChatCompletionModel(modelName = "") {
+    return !!modelName;
+  }
+
+  /**
+   * Generates appropriate content array for a message + attachments.
+   */
+  #generateContent({ userPrompt, attachments = [] }) {
+    if (!attachments.length) return userPrompt;
+    const content = [{ type: "text", text: userPrompt }];
+    for (let attachment of attachments) {
+      content.push({
+        type: "image_url",
+        image_url: {
+          url: attachment.contentString,
+        },
+      });
+    }
+    return content.flat();
+  }
+
+  constructPrompt({
+    systemPrompt = "",
+    contextTexts = [],
+    chatHistory = [],
+    userPrompt = "",
+    attachments = [],
+  }) {
+    const prompt = [
+      {
+        role: "system",
+        content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
+      },
+      ...chatHistory,
+      {
+        role: "user",
+        content: attachments.length
+          ? this.#generateContent({ userPrompt, attachments })
+          : userPrompt,
+      },
+    ];
+    return prompt;
+  }
+
+  async getChatCompletion(messages = null, { temperature = 0.7 }) {
+    if (!(await this.isValidChatCompletionModel(this.model)))
+      throw new Error(
+        `ChutesAI:chatCompletion: ${this.model} is not valid for chat completion!`
+      );
+
+    const result = await LLMPerformanceMonitor.measureAsyncFunction(
+      this.openai.chat.completions
+        .create({
+          model: this.model,
+          messages,
+          temperature,
+        })
+        .catch((e) => {
+          throw new Error(e.message);
+        })
+    );
+
+    if (
+      !result.output.hasOwnProperty("choices") ||
+      result.output.choices.length === 0
+    )
+      return null;
+
+    return {
+      textResponse: result.output.choices[0].message.content,
+      metrics: {
+        prompt_tokens: result.output.usage?.prompt_tokens || 0,
+        completion_tokens: result.output.usage?.completion_tokens || 0,
+        total_tokens: result.output.usage?.total_tokens || 0,
+        outputTps: result.output.usage?.completion_tokens / (result.output.usage?.completion_time || 1),
+        duration: result.output.usage?.total_time,
+        model: this.model,
+        provider: this.className,
+        timestamp: new Date(),
+      },
+    };
+  }
+
+  async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
+    if (!(await this.isValidChatCompletionModel(this.model)))
+      throw new Error(
+        `ChutesAI:streamChatCompletion: ${this.model} is not valid for chat completion!`
+      );
+
+    const measuredStreamRequest = await LLMPerformanceMonitor.measureStream({
+      func: this.openai.chat.completions.create({
+        model: this.model,
+        stream: true,
+        messages,
+        temperature,
+      }),
+      messages,
+      runPromptTokenCalculation: false,
+      modelTag: this.model,
+      provider: this.className,
+    });
+    return measuredStreamRequest;
+  }
+
+  handleStream(response, stream, responseProps) {
+    return handleDefaultStreamResponseV2(response, stream, responseProps);
+  }
+
+  async embedTextInput(textInput) {
+    return await this.embedder.embedTextInput(textInput);
+  }
+
+  async embedChunks(textChunks = []) {
+    return await this.embedder.embedChunks(textChunks);
+  }
+
+  async compressMessages(promptArgs = {}, rawHistory = []) {
+    const { messageArrayCompressor } = require("../../helpers/chat");
+    const messageArray = this.constructPrompt(promptArgs);
+    return await messageArrayCompressor(this, messageArray, rawHistory);
+  }
+}
+
+module.exports = {
+  ChutesLLM,
+};