Add support for gemini authenticated models endpoint (#2868)

* Add support for gemini authenticated models endpoint
add customModels entry
add un-authed fallback to default listing
separate models by expiermental status
resolves #2866

* add back improved logic for apiVersion decision making

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

+import System from "@/models/system";
+import { useEffect, useState } from "react";
+
 export default function GeminiLLMOptions({ settings }) {
+  const [inputValue, setInputValue] = useState(settings?.GeminiLLMApiKey);
+  const [geminiApiKey, setGeminiApiKey] = useState(settings?.GeminiLLMApiKey);
+
   return (
     <div className="w-full flex flex-col">
       <div className="w-full flex items-center gap-[36px] mt-1.5">
@@ -15,56 +21,14 @@ export default function GeminiLLMOptions({ settings }) {
             required={true}
             autoComplete="off"
             spellCheck={false}
+            onChange={(e) => setInputValue(e.target.value)}
+            onBlur={() => setGeminiApiKey(inputValue)}
           />
         </div>
 
         {!settings?.credentialsOnly && (
           <>
-            <div className="flex flex-col w-60">
-              <label className="text-white text-sm font-semibold block mb-3">
-                Chat Model Selection
-              </label>
-              <select
-                name="GeminiLLMModelPref"
-                defaultValue={settings?.GeminiLLMModelPref || "gemini-pro"}
-                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"
-              >
-                <optgroup label="Stable Models">
-                  {[
-                    "gemini-pro",
-                    "gemini-1.0-pro",
-                    "gemini-1.5-pro-latest",
-                    "gemini-1.5-flash-latest",
-                  ].map((model) => {
-                    return (
-                      <option key={model} value={model}>
-                        {model}
-                      </option>
-                    );
-                  })}
-                </optgroup>
-                <optgroup label="Experimental Models">
-                  {[
-                    "gemini-1.5-pro-exp-0801",
-                    "gemini-1.5-pro-exp-0827",
-                    "gemini-1.5-flash-exp-0827",
-                    "gemini-1.5-flash-8b-exp-0827",
-                    "gemini-exp-1114",
-                    "gemini-exp-1121",
-                    "gemini-exp-1206",
-                    "learnlm-1.5-pro-experimental",
-                    "gemini-2.0-flash-exp",
-                  ].map((model) => {
-                    return (
-                      <option key={model} value={model}>
-                        {model}
-                      </option>
-                    );
-                  })}
-                </optgroup>
-              </select>
-            </div>
+            <GeminiModelSelection apiKey={geminiApiKey} settings={settings} />
             <div className="flex flex-col w-60">
               <label className="text-white text-sm font-semibold block mb-3">
                 Safety Setting
@@ -91,3 +55,79 @@ export default function GeminiLLMOptions({ settings }) {
     </div>
   );
 }
+
+function GeminiModelSelection({ apiKey, settings }) {
+  const [groupedModels, setGroupedModels] = useState({});
+  const [loading, setLoading] = useState(true);
+
+  useEffect(() => {
+    async function findCustomModels() {
+      setLoading(true);
+      const { models } = await System.customModels("gemini", apiKey);
+
+      if (models?.length > 0) {
+        const modelsByOrganization = models.reduce((acc, model) => {
+          acc[model.experimental ? "Experimental" : "Stable"] =
+            acc[model.experimental ? "Experimental" : "Stable"] || [];
+          acc[model.experimental ? "Experimental" : "Stable"].push(model);
+          return acc;
+        }, {});
+        setGroupedModels(modelsByOrganization);
+      }
+      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="GeminiLLMModelPref"
+          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-3">
+        Chat Model Selection
+      </label>
+      <select
+        name="GeminiLLMModelPref"
+        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"
+      >
+        {Object.keys(groupedModels)
+          .sort((a, b) => {
+            if (a === "Stable") return -1;
+            if (b === "Stable") return 1;
+            return a.localeCompare(b);
+          })
+          .map((organization) => (
+            <optgroup key={organization} label={organization}>
+              {groupedModels[organization].map((model) => (
+                <option
+                  key={model.id}
+                  value={model.id}
+                  selected={settings?.GeminiLLMModelPref === model.id}
+                >
+                  {model.name}
+                </option>
+              ))}
+            </optgroup>
+          ))}
+      </select>
+    </div>
+  );
+}

server/utils/AiProviders/gemini/defaultModals.js

+const { MODEL_MAP } = require("../modelMap");
+
+const stableModels = [
+  "gemini-pro",
+  "gemini-1.0-pro",
+  "gemini-1.5-pro-latest",
+  "gemini-1.5-flash-latest",
+];
+
+const experimentalModels = [
+  "gemini-1.5-pro-exp-0801",
+  "gemini-1.5-pro-exp-0827",
+  "gemini-1.5-flash-exp-0827",
+  "gemini-1.5-flash-8b-exp-0827",
+  "gemini-exp-1114",
+  "gemini-exp-1121",
+  "gemini-exp-1206",
+  "learnlm-1.5-pro-experimental",
+  "gemini-2.0-flash-exp",
+];
+
+// There are some models that are only available in the v1beta API
+// and some models that are only available in the v1 API
+// generally, v1beta models have `exp` in the name, but not always
+// so we check for both against a static list as well.
+const v1BetaModels = ["gemini-1.5-pro-latest", "gemini-1.5-flash-latest"];
+
+const defaultGeminiModels = [
+  ...stableModels.map((model) => ({
+    id: model,
+    name: model,
+    contextWindow: MODEL_MAP.gemini[model],
+    experimental: false,
+  })),
+  ...experimentalModels.map((model) => ({
+    id: model,
+    name: model,
+    contextWindow: MODEL_MAP.gemini[model],
+    experimental: true,
+  })),
+];
+
+module.exports = {
+  defaultGeminiModels,
+  v1BetaModels,
+};

server/utils/AiProviders/gemini/index.js

@@ -7,6 +7,7 @@ const {
   clientAbortedHandler,
 } = require("../../helpers/chat/responses");
 const { MODEL_MAP } = require("../modelMap");
+const { defaultGeminiModels, v1BetaModels } = require("./defaultModals");
 
 class GeminiLLM {
   constructor(embedder = null, modelPreference = null) {
@@ -21,22 +22,17 @@ class GeminiLLM {
     this.gemini = genAI.getGenerativeModel(
       { model: this.model },
       {
-        // Gemini-1.5-pro-* and Gemini-1.5-flash are only available on the v1beta API.
-        apiVersion: [
-          "gemini-1.5-pro-latest",
-          "gemini-1.5-flash-latest",
-          "gemini-1.5-pro-exp-0801",
-          "gemini-1.5-pro-exp-0827",
-          "gemini-1.5-flash-exp-0827",
-          "gemini-1.5-flash-8b-exp-0827",
-          "gemini-exp-1114",
-          "gemini-exp-1121",
-          "gemini-exp-1206",
-          "learnlm-1.5-pro-experimental",
-          "gemini-2.0-flash-exp",
-        ].includes(this.model)
-          ? "v1beta"
-          : "v1",
+        apiVersion:
+          /**
+           * There are some models that are only available in the v1beta API
+           * and some models that are only available in the v1 API
+           * generally, v1beta models have `exp` in the name, but not always
+           * so we check for both against a static list as well.
+           * @see {v1BetaModels}
+           */
+          this.model.includes("exp") || v1BetaModels.includes(this.model)
+            ? "v1beta"
+            : "v1",
       }
     );
     this.limits = {
@@ -48,6 +44,11 @@ class GeminiLLM {
     this.embedder = embedder ?? new NativeEmbedder();
     this.defaultTemp = 0.7; // not used for Gemini
     this.safetyThreshold = this.#fetchSafetyThreshold();
+    this.#log(`Initialized with model: ${this.model}`);
+  }
+
+  #log(text, ...args) {
+    console.log(`\x1b[32m[GeminiLLM]\x1b[0m ${text}`, ...args);
   }
 
   #appendContext(contextTexts = []) {
@@ -109,25 +110,63 @@ class GeminiLLM {
     return MODEL_MAP.gemini[this.model] ?? 30_720;
   }
 
-  isValidChatCompletionModel(modelName = "") {
-    const validModels = [
-      "gemini-pro",
-      "gemini-1.0-pro",
-      "gemini-1.5-pro-latest",
-      "gemini-1.5-flash-latest",
-      "gemini-1.5-pro-exp-0801",
-      "gemini-1.5-pro-exp-0827",
-      "gemini-1.5-flash-exp-0827",
-      "gemini-1.5-flash-8b-exp-0827",
-      "gemini-exp-1114",
-      "gemini-exp-1121",
-      "gemini-exp-1206",
-      "learnlm-1.5-pro-experimental",
-      "gemini-2.0-flash-exp",
-    ];
-    return validModels.includes(modelName);
+  /**
+   * Fetches Gemini models from the Google Generative AI API
+   * @param {string} apiKey - The API key to use for the request
+   * @param {number} limit - The maximum number of models to fetch
+   * @param {string} pageToken - The page token to use for pagination
+   * @returns {Promise<[{id: string, name: string, contextWindow: number, experimental: boolean}]>} A promise that resolves to an array of Gemini models
+   */
+  static async fetchModels(apiKey, limit = 1_000, pageToken = null) {
+    const url = new URL(
+      "https://generativelanguage.googleapis.com/v1beta/models"
+    );
+    url.searchParams.set("pageSize", limit);
+    url.searchParams.set("key", apiKey);
+    if (pageToken) url.searchParams.set("pageToken", pageToken);
+
+    return fetch(url.toString(), {
+      method: "GET",
+      headers: { "Content-Type": "application/json" },
+    })
+      .then((res) => res.json())
+      .then((data) => {
+        if (data.error) throw new Error(data.error.message);
+        return data.models ?? [];
+      })
+      .then((models) =>
+        models
+          .filter(
+            (model) => !model.displayName.toLowerCase().includes("tuning")
+          )
+          .filter((model) =>
+            model.supportedGenerationMethods.includes("generateContent")
+          ) //  Only generateContent is supported
+          .map((model) => {
+            return {
+              id: model.name.split("/").pop(),
+              name: model.displayName,
+              contextWindow: model.inputTokenLimit,
+              experimental: model.name.includes("exp"),
+            };
+          })
+      )
+      .catch((e) => {
+        console.error(`Gemini:getGeminiModels`, e.message);
+        return defaultGeminiModels;
+      });
   }
 
+  /**
+   * Checks if a model is valid for chat completion (unused)
+   * @deprecated
+   * @param {string} modelName - The name of the model to check
+   * @returns {Promise<boolean>} A promise that resolves to a boolean indicating if the model is valid
+   */
+  async isValidChatCompletionModel(modelName = "") {
+    const models = await this.fetchModels(true);
+    return models.some((model) => model.id === modelName);
+  }
   /**
    * Generates appropriate content array for a message + attachments.
    * @param {{userPrompt:string, attachments: import("../../helpers").Attachment[]}}
@@ -218,11 +257,6 @@ class GeminiLLM {
   }
 
   async getChatCompletion(messages = [], _opts = {}) {
-    if (!this.isValidChatCompletionModel(this.model))
-      throw new Error(
-        `Gemini chat: ${this.model} is not valid for chat completion!`
-      );
-
     const prompt = messages.find(
       (chat) => chat.role === "USER_PROMPT"
     )?.content;
@@ -256,11 +290,6 @@ class GeminiLLM {
   }
 
   async streamGetChatCompletion(messages = [], _opts = {}) {
-    if (!this.isValidChatCompletionModel(this.model))
-      throw new Error(
-        `Gemini chat: ${this.model} is not valid for chat completion!`
-      );
-
     const prompt = messages.find(
       (chat) => chat.role === "USER_PROMPT"
     )?.content;

server/utils/helpers/customModels.js

@@ -7,6 +7,7 @@ const { ElevenLabsTTS } = require("../TextToSpeech/elevenLabs");
 const { fetchNovitaModels } = require("../AiProviders/novita");
 const { parseLMStudioBasePath } = require("../AiProviders/lmStudio");
 const { parseNvidiaNimBasePath } = require("../AiProviders/nvidiaNim");
+const { GeminiLLM } = require("../AiProviders/gemini");
 
 const SUPPORT_CUSTOM_MODELS = [
   "openai",
@@ -28,6 +29,7 @@ const SUPPORT_CUSTOM_MODELS = [
   "apipie",
   "novita",
   "xai",
+  "gemini",
 ];
 
 async function getCustomModels(provider = "", apiKey = null, basePath = null) {
@@ -73,6 +75,8 @@ async function getCustomModels(provider = "", apiKey = null, basePath = null) {
       return await getXAIModels(apiKey);
     case "nvidia-nim":
       return await getNvidiaNimModels(basePath);
+    case "gemini":
+      return await getGeminiModels(apiKey);
     default:
       return { models: [], error: "Invalid provider for custom models" };
   }
@@ -572,6 +576,17 @@ async function getNvidiaNimModels(basePath = null) {
   }
 }
 
+async function getGeminiModels(_apiKey = null) {
+  const apiKey =
+    _apiKey === true
+      ? process.env.GEMINI_API_KEY
+      : _apiKey || process.env.GEMINI_API_KEY || null;
+  const models = await GeminiLLM.fetchModels(apiKey);
+  // Api Key was successful so lets save it for future uses
+  if (models.length > 0 && !!apiKey) process.env.GEMINI_API_KEY = apiKey;
+  return { models, error: null };
+}
+
 module.exports = {
   getCustomModels,
 };

server/utils/helpers/updateENV.js

@@ -52,7 +52,7 @@ const KEY_MAPPING = {
   },
   GeminiLLMModelPref: {
     envKey: "GEMINI_LLM_MODEL_PREF",
-    checks: [isNotEmpty, validGeminiModel],
+    checks: [isNotEmpty],
   },
   GeminiSafetySetting: {
     envKey: "GEMINI_SAFETY_SETTING",
@@ -724,27 +724,6 @@ function supportedTranscriptionProvider(input = "") {
     : `${input} is not a valid transcription model provider.`;
 }
 
-function validGeminiModel(input = "") {
-  const validModels = [
-    "gemini-pro",
-    "gemini-1.0-pro",
-    "gemini-1.5-pro-latest",
-    "gemini-1.5-flash-latest",
-    "gemini-1.5-pro-exp-0801",
-    "gemini-1.5-pro-exp-0827",
-    "gemini-1.5-flash-exp-0827",
-    "gemini-1.5-flash-8b-exp-0827",
-    "gemini-exp-1114",
-    "gemini-exp-1121",
-    "gemini-exp-1206",
-    "learnlm-1.5-pro-experimental",
-    "gemini-2.0-flash-exp",
-  ];
-  return validModels.includes(input)
-    ? null
-    : `Invalid Model type. Must be one of ${validModels.join(", ")}.`;
-}
-
 function validGeminiSafetySetting(input = "") {
   const validModes = [
     "BLOCK_NONE",