Fix count tokens to include model params

.changeset/rare-birds-bow.md

@@ -0,0 +1,5 @@
+---
+"@google/generative-ai": patch
+---
+
+Fix countTokens to include any params set on the model instance.

package.json

@@ -31,6 +31,7 @@
     "@web/test-runner": "^0.18.0",
     "chai": "^4.3.10",
     "chai-as-promised": "^7.1.1",
+    "chai-deep-equal-ignore-undefined": "^1.1.1",
     "eslint": "^8.52.0",
     "eslint-plugin-import": "^2.29.0",
     "eslint-plugin-unused-imports": "^3.0.0",

packages/main/src/models/generative-model.test.ts

@@ -240,6 +240,7 @@ describe("GenerativeModel", () => {
       "apiKey",
       {
         model: "my-model",
+        systemInstruction: "you are a cat",
       },
       {
         apiVersion: "v2000",
@@ -257,7 +258,9 @@ describe("GenerativeModel", () => {
       request.Task.COUNT_TOKENS,
       match.any,
       false,
-      match.any,
+      match((value: string) => {
+        return value.includes("hello") && value.includes("you are a cat");
+      }),
       match((value) => {
         return value.apiVersion === "v2000";
       }),

packages/main/src/models/generative-model.ts

@@ -164,7 +164,15 @@ export class GenerativeModel {
   async countTokens(
     request: CountTokensRequest | string | Array<string | Part>,
   ): Promise<CountTokensResponse> {
-    const formattedParams = formatCountTokensInput(request, this.model);
+    const formattedParams = formatCountTokensInput(request, {
+      model: this.model,
+      generationConfig: this.generationConfig,
+      safetySettings: this.safetySettings,
+      tools: this.tools,
+      toolConfig: this.toolConfig,
+      systemInstruction: this.systemInstruction,
+      cachedContent: this.cachedContent,
+    });
     return countTokens(
       this.apiKey,
       this.model,

packages/main/src/requests/request-helpers.test.ts

@@ -17,10 +17,15 @@
 
 import { expect, use } from "chai";
 import * as sinonChai from "sinon-chai";
+import chaiDeepEqualIgnoreUndefined from "chai-deep-equal-ignore-undefined";
 import { Content } from "../../types";
-import { formatGenerateContentInput } from "./request-helpers";
+import {
+  formatCountTokensInput,
+  formatGenerateContentInput,
+} from "./request-helpers";
 
 use(sinonChai);
+use(chaiDeepEqualIgnoreUndefined);
 
 describe("request formatting methods", () => {
   describe("formatGenerateContentInput", () => {
@@ -172,4 +177,102 @@ describe("request formatting methods", () => {
       });
     });
   });
+  describe("formatCountTokensInput", () => {
+    it("formats a text string into a count request", () => {
+      const result = formatCountTokensInput("some text content", {
+        model: "gemini-1.5-flash",
+      });
+      expect(result.generateContentRequest).to.deepEqualIgnoreUndefined({
+        model: "gemini-1.5-flash",
+        contents: [
+          {
+            role: "user",
+            parts: [{ text: "some text content" }],
+          },
+        ],
+      });
+    });
+    it("formats a text string into a count request, along with model params", () => {
+      const result = formatCountTokensInput("some text content", {
+        model: "gemini-1.5-flash",
+        systemInstruction: "hello",
+        tools: [{ codeExecution: {} }],
+        cachedContent: { name: "mycache", contents: [] },
+      });
+      expect(result.generateContentRequest).to.deepEqualIgnoreUndefined({
+        model: "gemini-1.5-flash",
+        contents: [
+          {
+            role: "user",
+            parts: [{ text: "some text content" }],
+          },
+        ],
+        systemInstruction: "hello",
+        tools: [{ codeExecution: {} }],
+        cachedContent: "mycache",
+      });
+    });
+    it("formats a 'contents' style count request, along with model params", () => {
+      const result = formatCountTokensInput(
+        {
+          contents: [
+            {
+              role: "user",
+              parts: [{ text: "some text content" }],
+            },
+          ],
+        },
+        {
+          model: "gemini-1.5-flash",
+          systemInstruction: "hello",
+          tools: [{ codeExecution: {} }],
+          cachedContent: { name: "mycache", contents: [] },
+        },
+      );
+      expect(result.generateContentRequest).to.deepEqualIgnoreUndefined({
+        model: "gemini-1.5-flash",
+        contents: [
+          {
+            role: "user",
+            parts: [{ text: "some text content" }],
+          },
+        ],
+        systemInstruction: "hello",
+        tools: [{ codeExecution: {} }],
+        cachedContent: "mycache",
+      });
+    });
+    it("formats a 'generateContentRequest' style count request, along with model params", () => {
+      const result = formatCountTokensInput(
+        {
+          generateContentRequest: {
+            contents: [
+              {
+                role: "user",
+                parts: [{ text: "some text content" }],
+              },
+            ],
+          },
+        },
+        {
+          model: "gemini-1.5-flash",
+          systemInstruction: "hello",
+          tools: [{ codeExecution: {} }],
+          cachedContent: { name: "mycache", contents: [] },
+        },
+      );
+      expect(result.generateContentRequest).to.deepEqualIgnoreUndefined({
+        model: "gemini-1.5-flash",
+        contents: [
+          {
+            role: "user",
+            parts: [{ text: "some text content" }],
+          },
+        ],
+        systemInstruction: "hello",
+        tools: [{ codeExecution: {} }],
+        cachedContent: "mycache",
+      });
+    });
+  });
 });

packages/main/src/requests/request-helpers.ts

@@ -20,8 +20,10 @@ import {
   CountTokensRequest,
   EmbedContentRequest,
   GenerateContentRequest,
+  ModelParams,
   Part,
   _CountTokensRequestInternal,
+  _GenerateContentRequestInternal,
 } from "../../types";
 import {
   GoogleGenerativeAIError,
@@ -111,9 +113,18 @@ function assignRoleToPartsAndValidateSendMessageRequest(
 
 export function formatCountTokensInput(
   params: CountTokensRequest | string | Array<string | Part>,
-  model: string,
+  modelParams?: ModelParams,
 ): _CountTokensRequestInternal {
-  let formattedRequest: _CountTokensRequestInternal = {};
+  let formattedGenerateContentRequest: _GenerateContentRequestInternal = {
+    model: modelParams?.model,
+    generationConfig: modelParams?.generationConfig,
+    safetySettings: modelParams?.safetySettings,
+    tools: modelParams?.tools,
+    toolConfig: modelParams?.toolConfig,
+    systemInstruction: modelParams?.systemInstruction,
+    cachedContent: modelParams?.cachedContent?.name,
+    contents: [],
+  };
   const containsGenerateContentRequest =
     (params as CountTokensRequest).generateContentRequest != null;
   if ((params as CountTokensRequest).contents) {
@@ -122,16 +133,20 @@ export function formatCountTokensInput(
         "CountTokensRequest must have one of contents or generateContentRequest, not both.",
       );
     }
-    formattedRequest = { ...(params as CountTokensRequest) };
+    formattedGenerateContentRequest.contents = (
+      params as CountTokensRequest
+    ).contents;
   } else if (containsGenerateContentRequest) {
-    formattedRequest = { ...(params as CountTokensRequest) };
-    formattedRequest.generateContentRequest.model = model;
+    formattedGenerateContentRequest = {
+      ...formattedGenerateContentRequest,
+      ...(params as CountTokensRequest).generateContentRequest,
+    };
   } else {
     // Array or string
     const content = formatNewContent(params as string | Array<string | Part>);
-    formattedRequest.contents = [content];
+    formattedGenerateContentRequest.contents = [content];
   }
-  return formattedRequest;
+  return { generateContentRequest: formattedGenerateContentRequest };
 }
 
 export function formatGenerateContentInput(

samples/count_tokens.js

@@ -287,36 +287,30 @@ async function tokensCachedContent() {
   });
 
   const genAI = new GoogleGenerativeAI(process.env.API_KEY);
-  const model = genAI.getGenerativeModel({
-    model: "models/gemini-1.5-flash",
-  });
+  const model = genAI.getGenerativeModelFromCachedContent(cacheResult);
+
+  const prompt = "Please give a short summary of this file.";
 
   // Call `countTokens` to get the input token count
   // of the combined text and file (`totalTokens`).
-  const result = await model.countTokens({
-    generateContentRequest: {
-      contents: [
-        {
-          role: "user",
-          parts: [{ text: "Please give a short summary of this file." }],
-        },
-      ],
-      cachedContent: cacheResult.name,
-    },
-  });
+  const result = await model.countTokens(prompt);
 
   console.log(result.totalTokens); // 10
 
-  const generateResult = await model.generateContent(
-    "Please give a short summary of this file.",
-  );
+  const generateResult = await model.generateContent(prompt);
 
   // On the response for `generateContent`, use `usageMetadata`
   // to get separate input and output token counts
   // (`promptTokenCount` and `candidatesTokenCount`, respectively),
-  // as well as the combined token count (`totalTokenCount`).
+  // as well as the cached content token count and the combined total
+  // token count.
   console.log(generateResult.response.usageMetadata);
-  // { promptTokenCount: 10, candidatesTokenCount: 31, totalTokenCount: 41 }
+  // {
+  //   promptTokenCount: 323396,
+  //   candidatesTokenCount: 113,
+  //   totalTokenCount: 323509,
+  //   cachedContentTokenCount: 323386
+  // }
 
   await cacheManager.delete(cacheResult.name);
   // [END tokens_cached_content]
@@ -329,22 +323,12 @@ async function tokensSystemInstruction() {
   const genAI = new GoogleGenerativeAI(process.env.API_KEY);
   const model = genAI.getGenerativeModel({
     model: "models/gemini-1.5-flash",
+    systemInstruction: "You are a cat. Your name is Neko.",
   });
 
-  const result = await model.countTokens({
-    generateContentRequest: {
-      contents: [
-        {
-          role: "user",
-          parts: [{ text: "The quick brown fox jumps over the lazy dog." }],
-        },
-      ],
-      systemInstruction: {
-        role: "system",
-        parts: [{ text: "You are a cat. Your name is Neko." }],
-      },
-    },
-  });
+  const result = await model.countTokens(
+    "The quick brown fox jumps over the lazy dog.",
+  );
 
   console.log(result);
   // {
@@ -360,9 +344,6 @@ async function tokensTools() {
   // Make sure to include these imports:
   // import { GoogleGenerativeAI } from "@google/generative-ai";
   const genAI = new GoogleGenerativeAI(process.env.API_KEY);
-  const model = genAI.getGenerativeModel({
-    model: "models/gemini-1.5-flash",
-  });
 
   const functionDeclarations = [
     { name: "add" },
@@ -371,22 +352,15 @@ async function tokensTools() {
     { name: "divide" },
   ];
 
-  const result = await model.countTokens({
-    generateContentRequest: {
-      contents: [
-        {
-          role: "user",
-          parts: [
-            {
-              text: "I have 57 cats, each owns 44 mittens, how many mittens is that in total?",
-            },
-          ],
-        },
-      ],
-      tools: [{ functionDeclarations }],
-    },
+  const model = genAI.getGenerativeModel({
+    model: "models/gemini-1.5-flash",
+    tools: [{ functionDeclarations }],
   });
 
+  const result = await model.countTokens(
+    "I have 57 cats, each owns 44 mittens, how many mittens is that in total?",
+  );
+
   console.log(result);
   // {
   //   totalTokens: 99,

yarn.lock

@@ -2389,6 +2389,11 @@ chai-as-promised@^7.1.1:
   dependencies:
     check-error "^1.0.2"
 
+chai-deep-equal-ignore-undefined@^1.1.1:
+  version "1.1.1"
+  resolved "https://registry.yarnpkg.com/chai-deep-equal-ignore-undefined/-/chai-deep-equal-ignore-undefined-1.1.1.tgz#c9e3736fed06c83572f03c592c025cf2703fd1a1"
+  integrity sha512-BE4nUR2Jbqmmv8A0EuAydFRB/lXgXWAfa9TvO3YzHeGHAU7ZRwPZyu074oDl/CZtNXM7jXINpQxKBOe7N0P4bg==
+
 chai@^4.3.10:
   version "4.3.10"
   resolved "https://registry.yarnpkg.com/chai/-/chai-4.3.10.tgz#d784cec635e3b7e2ffb66446a63b4e33bd390384"