forgot files for DPAIS

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

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+import React, { useEffect, useState } from "react";
+import { CaretDown, CaretUp } from "@phosphor-icons/react";
+import System from "@/models/system";
+import PreLoader from "@/components/Preloader";
+import { DPAIS_COMMON_URLS } from "@/utils/constants";
+import useProviderEndpointAutoDiscovery from "@/hooks/useProviderEndpointAutoDiscovery";
+
+export default function DellProAIStudioOptions({
+  settings,
+  showAlert = false,
+}) {
+  const {
+    autoDetecting: loading,
+    basePath,
+    basePathValue,
+    showAdvancedControls,
+    setShowAdvancedControls,
+    handleAutoDetectClick,
+  } = useProviderEndpointAutoDiscovery({
+    provider: "dpais",
+    initialBasePath: settings?.DellProAiStudioBasePath,
+    ENDPOINTS: DPAIS_COMMON_URLS,
+  });
+
+  return (
+    <div className="w-full flex flex-col gap-y-7">
+      <div className="w-full flex items-center gap-[36px] mt-1.5">
+        {!settings?.credentialsOnly && (
+          <>
+            <DellProAiStudioModelSelection
+              settings={settings}
+              basePath={basePath.value}
+            />
+            <div className="flex flex-col w-60">
+              <label className="text-white text-sm font-semibold block mb-2">
+                Token context window
+              </label>
+              <input
+                type="number"
+                name="DellProAiStudioTokenLimit"
+                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="4096"
+                min={1}
+                onScroll={(e) => e.target.blur()}
+                defaultValue={settings?.DellProAiStudioTokenLimit}
+                required={true}
+                autoComplete="off"
+              />
+            </div>
+          </>
+        )}
+      </div>
+      <div className="flex justify-start mt-4">
+        <button
+          onClick={(e) => {
+            e.preventDefault();
+            setShowAdvancedControls(!showAdvancedControls);
+          }}
+          className="border-none text-theme-text-primary hover:text-theme-text-secondary flex items-center text-sm"
+        >
+          {showAdvancedControls ? "Hide" : "Show"} advanced settings
+          {showAdvancedControls ? (
+            <CaretUp size={14} className="ml-1" />
+          ) : (
+            <CaretDown size={14} className="ml-1" />
+          )}
+        </button>
+      </div>
+      <div hidden={!showAdvancedControls}>
+        <div className="w-full flex items-center gap-4">
+          <div className="flex flex-col w-fit">
+            <div className="flex justify-between items-center mb-2 gap-x-2">
+              <label className="text-white text-sm font-semibold">
+                Dell Pro AI Studio Base URL
+              </label>
+              {loading ? (
+                <PreLoader size="6" />
+              ) : (
+                <>
+                  {!basePathValue.value && (
+                    <button
+                      onClick={handleAutoDetectClick}
+                      className="bg-primary-button text-xs font-medium px-2 py-1 rounded-lg hover:bg-secondary hover:text-white shadow-[0_4px_14px_rgba(0,0,0,0.25)]"
+                    >
+                      Auto-Detect
+                    </button>
+                  )}
+                </>
+              )}
+            </div>
+            <input
+              type="url"
+              name="DellProAiStudioBasePath"
+              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="http://localhost:8553/v1"
+              value={basePathValue.value}
+              required={true}
+              autoComplete="off"
+              spellCheck={false}
+              onChange={basePath.onChange}
+              onBlur={basePath.onBlur}
+            />
+          </div>
+        </div>
+      </div>
+    </div>
+  );
+}
+
+function DellProAiStudioModelSelection({ settings, basePath = null }) {
+  const [customModels, setCustomModels] = useState([]);
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    async function findCustomModels() {
+      if (!basePath) {
+        setCustomModels([]);
+        setLoading(false);
+        return;
+      }
+      setLoading(true);
+      const { models } = await System.customModels(
+        "dpais",
+        null,
+        basePath,
+        2_000
+      );
+      setCustomModels(models || []);
+      setLoading(false);
+    }
+    findCustomModels();
+  }, [basePath]);
+
+  if (loading || customModels.length == 0) {
+    return (
+      <div className="flex flex-col w-60">
+        <label className="text-white text-sm font-semibold block mb-2">
+          Chat Model Selection
+        </label>
+        <select
+          name="DellProAiStudioModelPref"
+          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>
+      </div>
+    );
+  }
+
+  return (
+    <div className="flex flex-col w-60">
+      <label className="text-white text-sm font-semibold block mb-2">
+        Chat Model Selection
+      </label>
+      <select
+        name="DellProAiStudioModelPref"
+        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="Your loaded models">
+            {customModels.map((model) => {
+              return (
+                <option
+                  key={model.id}
+                  value={model.id}
+                  selected={settings.DellProAiStudioModelPref === model.id}
+                >
+                  {model.id}
+                </option>
+              );
+            })}
+          </optgroup>
+        )}
+      </select>
+    </div>
+  );
+}

server/utils/AiProviders/dellProAiStudio/index.js

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+const { NativeEmbedder } = require("../../EmbeddingEngines/native");
+const {
+  handleDefaultStreamResponseV2,
+  formatChatHistory,
+} = require("../../helpers/chat/responses");
+const {
+  LLMPerformanceMonitor,
+} = require("../../helpers/chat/LLMPerformanceMonitor");
+
+//  hybrid of openAi LLM chat completion for Dell Pro AI Studio
+class DellProAiStudioLLM {
+  constructor(embedder = null, modelPreference = null) {
+    if (!process.env.DPAIS_LLM_BASE_PATH)
+      throw new Error("No Dell Pro AI Studio Base Path was set.");
+
+    const { OpenAI: OpenAIApi } = require("openai");
+    this.dpais = new OpenAIApi({
+      baseURL: DellProAiStudioLLM.parseBasePath(),
+      apiKey: null,
+    });
+
+    this.model = modelPreference || process.env.DPAIS_LLM_MODEL_PREF;
+    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;
+    this.log(
+      `Dell Pro AI Studio LLM initialized with ${this.model}. ctx: ${this.promptWindowLimit()}`
+    );
+  }
+
+  /**
+   * Parse the base path for the Dell Pro AI Studio API
+   * so we can use it for inference requests
+   * @param {string} providedBasePath
+   * @returns {string}
+   */
+  static parseBasePath(providedBasePath = process.env.DPAIS_LLM_BASE_PATH) {
+    try {
+      const baseURL = new URL(providedBasePath);
+      const basePath = `${baseURL.origin}/v1/openai`;
+      return basePath;
+    } catch (e) {
+      return null;
+    }
+  }
+
+  log(text, ...args) {
+    console.log(`\x1b[36m[${this.constructor.name}]\x1b[0m ${text}`, ...args);
+  }
+
+  #appendContext(contextTexts = []) {
+    if (!contextTexts || !contextTexts.length) return "";
+    return (
+      "\nContext:\n" +
+      contextTexts
+        .map((text, i) => {
+          return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+        })
+        .join("")
+    );
+  }
+
+  streamingEnabled() {
+    return "streamGetChatCompletion" in this;
+  }
+
+  static promptWindowLimit(_modelName) {
+    const limit = process.env.DPAIS_LLM_MODEL_TOKEN_LIMIT || 4096;
+    if (!limit || isNaN(Number(limit)))
+      throw new Error("No Dell Pro AI Studio token context limit was set.");
+    return Number(limit);
+  }
+
+  // Ensure the user set a value for the token limit
+  // and if undefined - assume 4096 window.
+  promptWindowLimit() {
+    const limit = process.env.DPAIS_LLM_MODEL_TOKEN_LIMIT || 4096;
+    if (!limit || isNaN(Number(limit)))
+      throw new Error("No Dell Pro AI Studio token context limit was set.");
+    return Number(limit);
+  }
+
+  async isValidChatCompletionModel(_ = "") {
+    return true;
+  }
+
+  /**
+   * Generates appropriate content array for a message + attachments.
+   * @param {{userPrompt:string, attachments: import("../../helpers").Attachment[]}}
+   * @returns {string|object[]}
+   */
+  #generateContent({ userPrompt, attachments = [] }) {
+    if (!attachments.length) return userPrompt;
+
+    const content = [{ type: "text", text: userPrompt }];
+    for (let attachment of attachments) {
+      content.push({
+        type: "image_url",
+        image_url: {
+          url: attachment.contentString,
+          detail: "auto",
+        },
+      });
+    }
+    return content.flat();
+  }
+
+  /**
+   * Construct the user prompt for this model.
+   * @param {{attachments: import("../../helpers").Attachment[]}} param0
+   * @returns
+   */
+  constructPrompt({
+    systemPrompt = "",
+    contextTexts = [],
+    chatHistory = [],
+    userPrompt = "",
+    _attachments = [], // not used for Dell Pro AI Studio - `attachments` passed in is ignored
+  }) {
+    const prompt = {
+      role: "system",
+      content: `${systemPrompt}${this.#appendContext(contextTexts)}`,
+    };
+    return [
+      prompt,
+      ...formatChatHistory(chatHistory, this.#generateContent),
+      {
+        role: "user",
+        content: this.#generateContent({ userPrompt, _attachments }),
+      },
+    ];
+  }
+
+  async getChatCompletion(messages = null, { temperature = 0.7 }) {
+    if (!this.model)
+      throw new Error(
+        `Dell Pro AI Studio chat: ${this.model} is not valid or defined model for chat completion!`
+      );
+
+    const result = await LLMPerformanceMonitor.measureAsyncFunction(
+      this.dpais.chat.completions.create({
+        model: this.model,
+        messages,
+        temperature,
+      })
+    );
+
+    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.duration,
+        duration: result.duration,
+      },
+    };
+  }
+
+  async streamGetChatCompletion(messages = null, { temperature = 0.7 }) {
+    if (!this.model)
+      throw new Error(
+        `Dell Pro AI Studio chat: ${this.model} is not valid or defined model for chat completion!`
+      );
+
+    const measuredStreamRequest = await LLMPerformanceMonitor.measureStream(
+      this.dpais.chat.completions.create({
+        model: this.model,
+        stream: true,
+        messages,
+        temperature,
+      }),
+      messages
+    );
+    return measuredStreamRequest;
+  }
+
+  handleStream(response, stream, responseProps) {
+    return handleDefaultStreamResponseV2(response, stream, responseProps);
+  }
+
+  // Simple wrapper for dynamic embedder & normalize interface for all LLM implementations
+  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 = {
+  DellProAiStudioLLM,
+};

server/utils/agents/aibitat/providers/dellProAiStudio.js

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+const OpenAI = require("openai");
+const Provider = require("./ai-provider.js");
+const InheritMultiple = require("./helpers/classes.js");
+const UnTooled = require("./helpers/untooled.js");
+const {
+  DellProAiStudioLLM,
+} = require("../../../AiProviders/dellProAiStudio/index.js");
+
+/**
+ * The agent provider for Dell Pro AI Studio.
+ */
+class DellProAiStudioProvider extends InheritMultiple([Provider, UnTooled]) {
+  model;
+
+  /**
+   *
+   * @param {{model?: string}} config
+   */
+  constructor(config = {}) {
+    super();
+    const model = config?.model || process.env.DPAIS_LLM_MODEL_PREF;
+    const client = new OpenAI({
+      baseURL: DellProAiStudioLLM.parseBasePath(), // Will use process.env.DPAIS_LLM_BASE_PATH if not provided
+      apiKey: null,
+    });
+
+    this._client = client;
+    this.model = model;
+    this.verbose = true;
+  }
+
+  get client() {
+    return this._client;
+  }
+
+  async #handleFunctionCallChat({ messages = [] }) {
+    return await this.client.chat.completions
+      .create({
+        model: this.model,
+        messages,
+      })
+      .then((result) => {
+        if (!result.hasOwnProperty("choices"))
+          throw new Error("DellProAiStudio chat: No results!");
+        if (result.choices.length === 0)
+          throw new Error("DellProAiStudio chat: No results length!");
+        return result.choices[0].message.content;
+      })
+      .catch((_) => {
+        return null;
+      });
+  }
+
+  /**
+   * Create a completion based on the received messages.
+   *
+   * @param messages A list of messages to send to the API.
+   * @param functions
+   * @returns The completion.
+   */
+  async complete(messages, functions = []) {
+    try {
+      let completion;
+      if (functions.length > 0) {
+        const { toolCall, text } = await this.functionCall(
+          messages,
+          functions,
+          this.#handleFunctionCallChat.bind(this)
+        );
+
+        if (toolCall !== null) {
+          this.providerLog(`Valid tool call found - running ${toolCall.name}.`);
+          this.deduplicator.trackRun(toolCall.name, toolCall.arguments);
+          return {
+            result: null,
+            functionCall: {
+              name: toolCall.name,
+              arguments: toolCall.arguments,
+            },
+            cost: 0,
+          };
+        }
+        completion = { content: text };
+      }
+
+      if (!completion?.content) {
+        this.providerLog(
+          "Will assume chat completion without tool call inputs."
+        );
+        const response = await this.client.chat.completions.create({
+          model: this.model,
+          messages: this.cleanMsgs(messages),
+        });
+        completion = response.choices[0].message;
+      }
+
+      // The UnTooled class inherited Deduplicator is mostly useful to prevent the agent
+      // from calling the exact same function over and over in a loop within a single chat exchange
+      // _but_ we should enable it to call previously used tools in a new chat interaction.
+      this.deduplicator.reset("runs");
+      return {
+        result: completion.content,
+        cost: 0,
+      };
+    } catch (error) {
+      throw error;
+    }
+  }
+
+  /**
+   * Get the cost of the completion.
+   *
+   * @param _usage The completion to get the cost for.
+   * @returns The cost of the completion.
+   * Stubbed since LMStudio has no cost basis.
+   */
+  getCost(_usage) {
+    return 0;
+  }
+}
+
+module.exports = DellProAiStudioProvider;