Add LLM support for Google Gemini-Pro (#492)

resolves #489

README.md

@@ -58,6 +58,7 @@ Some cool features of AnythingLLM
 - [OpenAI](https://openai.com)
 - [Azure OpenAI](https://azure.microsoft.com/en-us/products/ai-services/openai-service)
 - [Anthropic ClaudeV2](https://www.anthropic.com/)
+- [Google Gemini Pro](https://ai.google.dev/)
 - [LM Studio (all models)](https://lmstudio.ai)
 - [LocalAi (all models)](https://localai.io/)
 

docker/.env.example

@@ -11,6 +11,10 @@ GID='1000'
 # OPEN_AI_KEY=
 # OPEN_MODEL_PREF='gpt-3.5-turbo'
 
+# LLM_PROVIDER='gemini'
+# GEMINI_API_KEY=
+# GEMINI_LLM_MODEL_PREF='gemini-pro'
+
 # LLM_PROVIDER='azure'
 # AZURE_OPENAI_ENDPOINT=
 # AZURE_OPENAI_KEY=

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

@@ -0,0 +1,43 @@
+export default function GeminiLLMOptions({ settings }) {
+  return (
+    <div className="w-full flex flex-col">
+      <div className="w-full flex items-center gap-4">
+        <div className="flex flex-col w-60">
+          <label className="text-white text-sm font-semibold block mb-4">
+            Google AI API Key
+          </label>
+          <input
+            type="password"
+            name="GeminiLLMApiKey"
+            className="bg-zinc-900 text-white placeholder-white placeholder-opacity-60 text-sm rounded-lg focus:border-white block w-full p-2.5"
+            placeholder="Google Gemini API Key"
+            defaultValue={settings?.GeminiLLMApiKey ? "*".repeat(20) : ""}
+            required={true}
+            autoComplete="off"
+            spellCheck={false}
+          />
+        </div>
+
+        <div className="flex flex-col w-60">
+          <label className="text-white text-sm font-semibold block mb-4">
+            Chat Model Selection
+          </label>
+          <select
+            name="GeminiLLMModelPref"
+            defaultValue={settings?.GeminiLLMModelPref || "gemini-pro"}
+            required={true}
+            className="bg-zinc-900 border border-gray-500 text-white text-sm rounded-lg block w-full p-2.5"
+          >
+            {["gemini-pro"].map((model) => {
+              return (
+                <option key={model} value={model}>
+                  {model}
+                </option>
+              );
+            })}
+          </select>
+        </div>
+      </div>
+    </div>
+  );
+}

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

@@ -46,10 +46,10 @@ export default function GeneralEmbeddingPreference() {
 
     const { error } = await System.updateSystem(settingsData);
     if (error) {
-      showToast(`Failed to save LLM settings: ${error}`, "error");
+      showToast(`Failed to save embedding settings: ${error}`, "error");
       setHasChanges(true);
     } else {
-      showToast("LLM preferences saved successfully.", "success");
+      showToast("Embedding preferences saved successfully.", "success");
       setHasChanges(false);
     }
     setSaving(false);
@@ -132,7 +132,7 @@ export default function GeneralEmbeddingPreference() {
                 <div className="text-white text-sm font-medium py-4">
                   Embedding Providers
                 </div>
-                <div className="w-full flex md:flex-wrap overflow-x-scroll gap-4 max-w-[900px]">
+                <div className="w-full flex md:flex-wrap overflow-x-scroll gap-4">
                   <input
                     hidden={true}
                     name="EmbeddingEngine"
@@ -174,7 +174,7 @@ export default function GeneralEmbeddingPreference() {
                     onClick={updateChoice}
                   />
                 </div>
-                <div className="mt-10 flex flex-wrap gap-4 max-w-[800px]">
+                <div className="mt-10 flex flex-wrap gap-4">
                   {embeddingChoice === "native" && <NativeEmbeddingOptions />}
                   {embeddingChoice === "openai" && (
                     <OpenAiOptions settings={settings} />

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

@@ -7,6 +7,7 @@ import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
 import OpenAiLogo from "@/media/llmprovider/openai.png";
 import AzureOpenAiLogo from "@/media/llmprovider/azure.png";
 import AnthropicLogo from "@/media/llmprovider/anthropic.png";
+import GeminiLogo from "@/media/llmprovider/gemini.png";
 import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
 import LocalAiLogo from "@/media/llmprovider/localai.png";
 import PreLoader from "@/components/Preloader";
@@ -17,6 +18,7 @@ import AnthropicAiOptions from "@/components/LLMSelection/AnthropicAiOptions";
 import LMStudioOptions from "@/components/LLMSelection/LMStudioOptions";
 import LocalAiOptions from "@/components/LLMSelection/LocalAiOptions";
 import NativeLLMOptions from "@/components/LLMSelection/NativeLLMOptions";
+import GeminiLLMOptions from "@/components/LLMSelection/GeminiLLMOptions";
 
 export default function GeneralLLMPreference() {
   const [saving, setSaving] = useState(false);
@@ -105,13 +107,13 @@ export default function GeneralLLMPreference() {
               <div className="text-white text-sm font-medium py-4">
                 LLM Providers
               </div>
-              <div className="w-full flex md:flex-wrap overflow-x-scroll gap-4 max-w-[900px]">
+              <div className="w-full flex md:flex-wrap overflow-x-scroll gap-4">
                 <input hidden={true} name="LLMProvider" value={llmChoice} />
                 <LLMProviderOption
                   name="OpenAI"
                   value="openai"
                   link="openai.com"
-                  description="The standard option for most non-commercial use. Provides both chat and embedding."
+                  description="The standard option for most non-commercial use."
                   checked={llmChoice === "openai"}
                   image={OpenAiLogo}
                   onClick={updateLLMChoice}
@@ -120,7 +122,7 @@ export default function GeneralLLMPreference() {
                   name="Azure OpenAI"
                   value="azure"
                   link="azure.microsoft.com"
-                  description="The enterprise option of OpenAI hosted on Azure services. Provides both chat and embedding."
+                  description="The enterprise option of OpenAI hosted on Azure services."
                   checked={llmChoice === "azure"}
                   image={AzureOpenAiLogo}
                   onClick={updateLLMChoice}
@@ -129,11 +131,20 @@ export default function GeneralLLMPreference() {
                   name="Anthropic Claude 2"
                   value="anthropic"
                   link="anthropic.com"
-                  description="A friendly AI Assistant hosted by Anthropic. Provides chat services only!"
+                  description="A friendly AI Assistant hosted by Anthropic."
                   checked={llmChoice === "anthropic"}
                   image={AnthropicLogo}
                   onClick={updateLLMChoice}
                 />
+                <LLMProviderOption
+                  name="Google Gemini"
+                  value="gemini"
+                  link="ai.google.dev"
+                  description="Google's largest and most capable AI model"
+                  checked={llmChoice === "gemini"}
+                  image={GeminiLogo}
+                  onClick={updateLLMChoice}
+                />
                 <LLMProviderOption
                   name="LM Studio"
                   value="lmstudio"
@@ -173,6 +184,9 @@ export default function GeneralLLMPreference() {
                 {llmChoice === "anthropic" && (
                   <AnthropicAiOptions settings={settings} showAlert={true} />
                 )}
+                {llmChoice === "gemini" && (
+                  <GeminiLLMOptions settings={settings} />
+                )}
                 {llmChoice === "lmstudio" && (
                   <LMStudioOptions settings={settings} showAlert={true} />
                 )}

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

@@ -55,10 +55,10 @@ export default function GeneralVectorDatabase() {
 
     const { error } = await System.updateSystem(settingsData);
     if (error) {
-      showToast(`Failed to save LLM settings: ${error}`, "error");
+      showToast(`Failed to save vector database settings: ${error}`, "error");
       setHasChanges(true);
     } else {
-      showToast("LLM preferences saved successfully.", "success");
+      showToast("Vector database preferences saved successfully.", "success");
       setHasChanges(false);
     }
     setSaving(false);

frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/DataHandling/index.jsx

@@ -4,6 +4,7 @@ import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
 import OpenAiLogo from "@/media/llmprovider/openai.png";
 import AzureOpenAiLogo from "@/media/llmprovider/azure.png";
 import AnthropicLogo from "@/media/llmprovider/anthropic.png";
+import GeminiLogo from "@/media/llmprovider/gemini.png";
 import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
 import LocalAiLogo from "@/media/llmprovider/localai.png";
 import ChromaLogo from "@/media/vectordbs/chroma.png";
@@ -38,6 +39,14 @@ const LLM_SELECTION_PRIVACY = {
     ],
     logo: AnthropicLogo,
   },
+  gemini: {
+    name: "Google Gemini",
+    description: [
+      "Your chats are de-identified and used in training",
+      "Your prompts and document text are visible in responses to Google",
+    ],
+    logo: GeminiLogo,
+  },
   lmstudio: {
     name: "LMStudio",
     description: [

frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/EmbeddingSelection/index.jsx

@@ -76,7 +76,7 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) {
               name="OpenAI"
               value="openai"
               link="openai.com"
-              description="The standard option for most non-commercial use. Provides both chat and embedding."
+              description="The standard option for most non-commercial use."
               checked={embeddingChoice === "openai"}
               image={OpenAiLogo}
               onClick={updateChoice}
@@ -85,7 +85,7 @@ function EmbeddingSelection({ nextStep, prevStep, currentStep }) {
               name="Azure OpenAI"
               value="azure"
               link="azure.microsoft.com"
-              description="The enterprise option of OpenAI hosted on Azure services. Provides both chat and embedding."
+              description="The enterprise option of OpenAI hosted on Azure services."
               checked={embeddingChoice === "azure"}
               image={AzureOpenAiLogo}
               onClick={updateChoice}

frontend/src/pages/OnboardingFlow/OnboardingModal/Steps/LLMSelection/index.jsx

@@ -3,6 +3,7 @@ import AnythingLLMIcon from "@/media/logo/anything-llm-icon.png";
 import OpenAiLogo from "@/media/llmprovider/openai.png";
 import AzureOpenAiLogo from "@/media/llmprovider/azure.png";
 import AnthropicLogo from "@/media/llmprovider/anthropic.png";
+import GeminiLogo from "@/media/llmprovider/gemini.png";
 import LMStudioLogo from "@/media/llmprovider/lmstudio.png";
 import LocalAiLogo from "@/media/llmprovider/localai.png";
 import System from "@/models/system";
@@ -14,6 +15,7 @@ import AnthropicAiOptions from "@/components/LLMSelection/AnthropicAiOptions";
 import LMStudioOptions from "@/components/LLMSelection/LMStudioOptions";
 import LocalAiOptions from "@/components/LLMSelection/LocalAiOptions";
 import NativeLLMOptions from "@/components/LLMSelection/NativeLLMOptions";
+import GeminiLLMOptions from "@/components/LLMSelection/GeminiLLMOptions";
 
 function LLMSelection({ nextStep, prevStep, currentStep }) {
   const [llmChoice, setLLMChoice] = useState("openai");
@@ -71,7 +73,7 @@ function LLMSelection({ nextStep, prevStep, currentStep }) {
               name="OpenAI"
               value="openai"
               link="openai.com"
-              description="The standard option for most non-commercial use. Provides both chat and embedding."
+              description="The standard option for most non-commercial use."
               checked={llmChoice === "openai"}
               image={OpenAiLogo}
               onClick={updateLLMChoice}
@@ -80,7 +82,7 @@ function LLMSelection({ nextStep, prevStep, currentStep }) {
               name="Azure OpenAI"
               value="azure"
               link="azure.microsoft.com"
-              description="The enterprise option of OpenAI hosted on Azure services. Provides both chat and embedding."
+              description="The enterprise option of OpenAI hosted on Azure services."
               checked={llmChoice === "azure"}
               image={AzureOpenAiLogo}
               onClick={updateLLMChoice}
@@ -94,6 +96,15 @@ function LLMSelection({ nextStep, prevStep, currentStep }) {
               image={AnthropicLogo}
               onClick={updateLLMChoice}
             />
+            <LLMProviderOption
+              name="Google Gemini"
+              value="gemini"
+              link="ai.google.dev"
+              description="Google's largest and most capable AI model"
+              checked={llmChoice === "gemini"}
+              image={GeminiLogo}
+              onClick={updateLLMChoice}
+            />
             <LLMProviderOption
               name="LM Studio"
               value="lmstudio"
@@ -127,6 +138,7 @@ function LLMSelection({ nextStep, prevStep, currentStep }) {
             {llmChoice === "anthropic" && (
               <AnthropicAiOptions settings={settings} />
             )}
+            {llmChoice === "gemini" && <GeminiLLMOptions settings={settings} />}
             {llmChoice === "lmstudio" && (
               <LMStudioOptions settings={settings} />
             )}

server/.env.example

@@ -8,6 +8,10 @@ JWT_SECRET="my-random-string-for-seeding" # Please generate random string at lea
 # OPEN_AI_KEY=
 # OPEN_MODEL_PREF='gpt-3.5-turbo'
 
+# LLM_PROVIDER='gemini'
+# GEMINI_API_KEY=
+# GEMINI_LLM_MODEL_PREF='gemini-pro'
+
 # LLM_PROVIDER='azure'
 # AZURE_OPENAI_ENDPOINT=
 # AZURE_OPENAI_KEY=

server/models/systemSettings.js

@@ -87,6 +87,20 @@ const SystemSettings = {
           }
         : {}),
 
+      ...(llmProvider === "gemini"
+        ? {
+            GeminiLLMApiKey: !!process.env.GEMINI_API_KEY,
+            GeminiLLMModelPref:
+              process.env.GEMINI_LLM_MODEL_PREF || "gemini-pro",
+
+            // For embedding credentials when Gemini is selected.
+            OpenAiKey: !!process.env.OPEN_AI_KEY,
+            AzureOpenAiEndpoint: process.env.AZURE_OPENAI_ENDPOINT,
+            AzureOpenAiKey: !!process.env.AZURE_OPENAI_KEY,
+            AzureOpenAiEmbeddingModelPref: process.env.EMBEDDING_MODEL_PREF,
+          }
+        : {}),
+
       ...(llmProvider === "lmstudio"
         ? {
             LMStudioBasePath: process.env.LMSTUDIO_BASE_PATH,

server/package.json

@@ -22,6 +22,7 @@
   "dependencies": {
     "@anthropic-ai/sdk": "^0.8.1",
     "@azure/openai": "^1.0.0-beta.3",
+    "@google/generative-ai": "^0.1.3",
     "@googleapis/youtube": "^9.0.0",
     "@pinecone-database/pinecone": "^0.1.6",
     "@prisma/client": "5.3.0",

server/utils/AiProviders/gemini/index.js

@@ -0,0 +1,200 @@
+const { v4 } = require("uuid");
+const { chatPrompt } = require("../../chats");
+
+class GeminiLLM {
+  constructor(embedder = null) {
+    if (!process.env.GEMINI_API_KEY)
+      throw new Error("No Gemini API key was set.");
+
+    // Docs: https://ai.google.dev/tutorials/node_quickstart
+    const { GoogleGenerativeAI } = require("@google/generative-ai");
+    const genAI = new GoogleGenerativeAI(process.env.GEMINI_API_KEY);
+    this.model = process.env.GEMINI_LLM_MODEL_PREF || "gemini-pro";
+    this.gemini = genAI.getGenerativeModel({ model: this.model });
+    this.limits = {
+      history: this.promptWindowLimit() * 0.15,
+      system: this.promptWindowLimit() * 0.15,
+      user: this.promptWindowLimit() * 0.7,
+    };
+
+    if (!embedder)
+      throw new Error(
+        "INVALID GEMINI LLM SETUP. No embedding engine has been set. Go to instance settings and set up an embedding interface to use Gemini as your LLM."
+      );
+    this.embedder = embedder;
+    this.answerKey = v4().split("-")[0];
+  }
+
+  streamingEnabled() {
+    return "streamChat" in this && "streamGetChatCompletion" in this;
+  }
+
+  promptWindowLimit() {
+    switch (this.model) {
+      case "gemini-pro":
+        return 30_720;
+      default:
+        return 30_720; // assume a gemini-pro model
+    }
+  }
+
+  isValidChatCompletionModel(modelName = "") {
+    const validModels = ["gemini-pro"];
+    return validModels.includes(modelName);
+  }
+
+  // Moderation cannot be done with Gemini.
+  // Not implemented so must be stubbed
+  async isSafe(_input = "") {
+    return { safe: true, reasons: [] };
+  }
+
+  constructPrompt({
+    systemPrompt = "",
+    contextTexts = [],
+    chatHistory = [],
+    userPrompt = "",
+  }) {
+    const prompt = {
+      role: "system",
+      content: `${systemPrompt}
+Context:
+    ${contextTexts
+      .map((text, i) => {
+        return `[CONTEXT ${i}]:\n${text}\n[END CONTEXT ${i}]\n\n`;
+      })
+      .join("")}`,
+    };
+    return [
+      prompt,
+      { role: "assistant", content: "Okay." },
+      ...chatHistory,
+      { role: "USER_PROMPT", content: userPrompt },
+    ];
+  }
+
+  // This will take an OpenAi format message array and only pluck valid roles from it.
+  formatMessages(messages = []) {
+    // Gemini roles are either user || model.
+    // and all "content" is relabeled to "parts"
+    return messages
+      .map((message) => {
+        if (message.role === "system")
+          return { role: "user", parts: message.content };
+        if (message.role === "user")
+          return { role: "user", parts: message.content };
+        if (message.role === "assistant")
+          return { role: "model", parts: message.content };
+        return null;
+      })
+      .filter((msg) => !!msg);
+  }
+
+  async sendChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
+    if (!this.isValidChatCompletionModel(this.model))
+      throw new Error(
+        `Gemini chat: ${this.model} is not valid for chat completion!`
+      );
+
+    const compressedHistory = await this.compressMessages(
+      {
+        systemPrompt: chatPrompt(workspace),
+        chatHistory,
+      },
+      rawHistory
+    );
+
+    const chatThread = this.gemini.startChat({
+      history: this.formatMessages(compressedHistory),
+    });
+    const result = await chatThread.sendMessage(prompt);
+    const response = result.response;
+    const responseText = response.text();
+
+    if (!responseText) throw new Error("Gemini: No response could be parsed.");
+
+    return responseText;
+  }
+
+  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;
+    const chatThread = this.gemini.startChat({
+      history: this.formatMessages(messages),
+    });
+    const result = await chatThread.sendMessage(prompt);
+    const response = result.response;
+    const responseText = response.text();
+
+    if (!responseText) throw new Error("Gemini: No response could be parsed.");
+
+    return responseText;
+  }
+
+  async streamChat(chatHistory = [], prompt, workspace = {}, rawHistory = []) {
+    if (!this.isValidChatCompletionModel(this.model))
+      throw new Error(
+        `Gemini chat: ${this.model} is not valid for chat completion!`
+      );
+
+    const compressedHistory = await this.compressMessages(
+      {
+        systemPrompt: chatPrompt(workspace),
+        chatHistory,
+      },
+      rawHistory
+    );
+
+    const chatThread = this.gemini.startChat({
+      history: this.formatMessages(compressedHistory),
+    });
+    const responseStream = await chatThread.sendMessageStream(prompt);
+    if (!responseStream.stream)
+      throw new Error("Could not stream response stream from Gemini.");
+
+    return { type: "geminiStream", ...responseStream };
+  }
+
+  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;
+    const chatThread = this.gemini.startChat({
+      history: this.formatMessages(messages),
+    });
+    const responseStream = await chatThread.sendMessageStream(prompt);
+    if (!responseStream.stream)
+      throw new Error("Could not stream response stream from Gemini.");
+
+    return { type: "geminiStream", ...responseStream };
+  }
+
+  async compressMessages(promptArgs = {}, rawHistory = []) {
+    const { messageArrayCompressor } = require("../../helpers/chat");
+    const messageArray = this.constructPrompt(promptArgs);
+    return await messageArrayCompressor(this, messageArray, rawHistory);
+  }
+
+  // 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);
+  }
+}
+
+module.exports = {
+  GeminiLLM,
+};

server/utils/chats/stream.js

@@ -202,6 +202,35 @@ async function streamEmptyEmbeddingChat({
 function handleStreamResponses(response, stream, responseProps) {
   const { uuid = uuidv4(), sources = [] } = responseProps;
 
+  // Gemini likes to return a stream asyncIterator which will
+  // be a totally different object than other models.
+  if (stream?.type === "geminiStream") {
+    return new Promise(async (resolve) => {
+      let fullText = "";
+      for await (const chunk of stream.stream) {
+        fullText += chunk.text();
+        writeResponseChunk(response, {
+          uuid,
+          sources: [],
+          type: "textResponseChunk",
+          textResponse: chunk.text(),
+          close: false,
+          error: false,
+        });
+      }
+
+      writeResponseChunk(response, {
+        uuid,
+        sources,
+        type: "textResponseChunk",
+        textResponse: "",
+        close: true,
+        error: false,
+      });
+      resolve(fullText);
+    });
+  }
+
   // If stream is not a regular OpenAI Stream (like if using native model)
   // we can just iterate the stream content instead.
   if (!stream.hasOwnProperty("data")) {

server/utils/helpers/index.js

@@ -34,6 +34,9 @@ function getLLMProvider() {
     case "anthropic":
       const { AnthropicLLM } = require("../AiProviders/anthropic");
       return new AnthropicLLM(embedder);
+    case "gemini":
+      const { GeminiLLM } = require("../AiProviders/gemini");
+      return new GeminiLLM(embedder);
     case "lmstudio":
       const { LMStudioLLM } = require("../AiProviders/lmStudio");
       return new LMStudioLLM(embedder);

server/utils/helpers/updateENV.js

@@ -44,6 +44,15 @@ const KEY_MAPPING = {
     checks: [isNotEmpty, validAnthropicModel],
   },
 
+  GeminiLLMApiKey: {
+    envKey: "GEMINI_API_KEY",
+    checks: [isNotEmpty],
+  },
+  GeminiLLMModelPref: {
+    envKey: "GEMINI_LLM_MODEL_PREF",
+    checks: [isNotEmpty, validGeminiModel],
+  },
+
   // LMStudio Settings
   LMStudioBasePath: {
     envKey: "LMSTUDIO_BASE_PATH",
@@ -204,12 +213,20 @@ function supportedLLM(input = "") {
     "openai",
     "azure",
     "anthropic",
+    "gemini",
     "lmstudio",
     "localai",
     "native",
   ].includes(input);
 }
 
+function validGeminiModel(input = "") {
+  const validModels = ["gemini-pro"];
+  return validModels.includes(input)
+    ? null
+    : `Invalid Model type. Must be one of ${validModels.join(", ")}.`;
+}
+
 function validAnthropicModel(input = "") {
   const validModels = ["claude-2", "claude-instant-1"];
   return validModels.includes(input)

server/yarn.lock

@@ -140,6 +140,11 @@
   resolved "https://registry.yarnpkg.com/@gar/promisify/-/promisify-1.1.3.tgz#555193ab2e3bb3b6adc3d551c9c030d9e860daf6"
   integrity sha512-k2Ty1JcVojjJFwrg/ThKi2ujJ7XNLYaFGNB/bWT9wGR+oSMJHMa5w+CUq6p/pVrKeNNgA7pCqEcjSnHVoqJQFw==
 
+"@google/generative-ai@^0.1.3":
+  version "0.1.3"
+  resolved "https://registry.yarnpkg.com/@google/generative-ai/-/generative-ai-0.1.3.tgz#8e529d4d86c85b64d297b4abf1a653d613a09a9f"
+  integrity sha512-Cm4uJX1sKarpm1mje/MiOIinM7zdUUrQp/5/qGPAgznbdd/B9zup5ehT6c1qGqycFcSopTA1J1HpqHS5kJR8hQ==
+
 "@googleapis/youtube@^9.0.0":
   version "9.0.0"
   resolved "https://registry.yarnpkg.com/@googleapis/youtube/-/youtube-9.0.0.tgz#e45f6f5f7eac198c6391782b94b3ca54bacf0b63"