Add a modelName option to the command line runners

library/runner-cli/advanced_runner.ts

@@ -157,7 +157,8 @@ async function main(): Promise<void> {
       "-a, --additionalContext <context>",
       "A short description of the conversation to add context."
     )
-    .option("-v, --vertexProject <project>", "The Vertex Project name.");
+    .option("-v, --vertexProject <project>", "The Vertex Project name.")
+    .option("-m, --modelName <model>", "The name of the model to use (defaults to gemini-2.5-pro-preview-06-05).");
   program.parse(process.argv);
   const options = program.opts();
 
@@ -187,7 +188,8 @@ async function main(): Promise<void> {
     options.vertexProject,
     comments,
     undefined,
-    options.additionalContext
+    options.additionalContext,
+    options.modelName
   );
   writeFileSync(options.outputBasename + "-summary.json", JSON.stringify(summary, null, 2));
 }

library/runner-cli/categorization_runner.ts

@@ -48,6 +48,7 @@ async function main(): Promise<void> {
     .option("-o, --outputFile <file>", "The output file name.")
     .option("-i, --inputFile <file>", "The input file name.")
     .option("-t, --topics <comma separated list>", "Optional list of top-level topics.")
+    .option("-m, --modelName <model>", "The name of the model to use (defaults to gemini-2.5-pro-preview-06-05).")
     .option(
       "-d, --topicDepth [number]",
       "If set, will learn only topics (1), topics and subtopics (2), or topics, subtopics, and subsubtopics (3). The default is 2.",
@@ -80,7 +81,7 @@ async function main(): Promise<void> {
 
   // Learn topics and categorize comments.
   const sensemaker = new Sensemaker({
-    defaultModel: new VertexModel(options.vertexProject, "global"),
+    defaultModel: new VertexModel(options.vertexProject, "global", options.modelName),
   });
   const topics = options.topics ? getTopics(options.topics) : undefined;
   const categorizedComments = await sensemaker.categorizeComments(

library/runner-cli/runner.ts

@@ -53,7 +53,8 @@ async function main(): Promise<void> {
       "-a, --additionalContext <context>",
       "A short description of the conversation to add context."
     )
-    .option("-v, --vertexProject <project>", "The Vertex Project name.");
+    .option("-v, --vertexProject <project>", "The Vertex Project name.")
+    .option("-m, --modelName <model>", "The name of the model to use (defaults to gemini-2.5-pro-preview-06-05).");
   program.parse(process.argv);
   const options = program.opts();
 
@@ -63,7 +64,8 @@ async function main(): Promise<void> {
     options.vertexProject,
     comments,
     undefined,
-    options.additionalContext
+    options.additionalContext,
+    options.modelName
   );
 
   const markdownContent = summary.getText("MARKDOWN");

library/runner-cli/runner_utils.ts

@@ -126,14 +126,16 @@ export function writeSummaryToGroundedCSV(summary: Summary, outputFilePath: stri
  * Identify topics and subtopics when input data has not already been categorized.
  * @param project The Vertex GCloud project name
  * @param comments The comments from which topics need to be identified
+ * @param modelName Optional name of the model to use (defaults to gemini-2.5-pro-preview-06-05)
  * @returns Promise resolving to a Topic collection containing the newly discovered topics and subtopics for the given comments
  */
 export async function getTopicsAndSubtopics(
   project: string,
-  comments: Comment[]
+  comments: Comment[],
+  modelName?: string
 ): Promise<Topic[]> {
   const sensemaker = new Sensemaker({
-    defaultModel: new VertexModel(project, "global"),
+    defaultModel: new VertexModel(project, "global", modelName),
   });
   return await sensemaker.learnTopics(comments, true);
 }
@@ -144,16 +146,18 @@ export async function getTopicsAndSubtopics(
  * @param comments The comments to summarize
  * @param topics The input topics to categorize against
  * @param additionalContext Additional context about the conversation to pass through
+ * @param modelName Optional name of the model to use (defaults to gemini-2.5-pro-preview-06-05)
  * @returns Promise resolving to a Summary object containing the summary of the comments
  */
 export async function getSummary(
   project: string,
   comments: Comment[],
   topics?: Topic[],
-  additionalContext?: string
+  additionalContext?: string,
+  modelName?: string
 ): Promise<Summary> {
   const sensemaker = new Sensemaker({
-    defaultModel: new VertexModel(project, "global"),
+    defaultModel: new VertexModel(project, "global", modelName),
   });
   // TODO: Make the summariation type an argument and add it as a flag in runner.ts. The data
   // requirements (like requiring votes) would also need updated.