update pre-commit prettier to 3.3.2 (#77)

.pre-commit-config.yaml

@@ -25,8 +25,8 @@ repos:
           )$
         args: [-L rouge]
 
-  - repo: https://github.com/pre-commit/mirrors-prettier
-    rev: v2.7.1
+  - repo: https://github.com/rbubley/mirrors-prettier
+    rev: v3.3.2
     hooks:
       - id: prettier
         exclude: ^(extension/|.*\.json$)

evals/src/autoevals.eval.ts

@@ -47,7 +47,7 @@ const datasets = [
 
 const runScorerT = wrapTraced(async function runScorer(
   scorer: string,
-  input: any
+  input: any,
 ) {
   switch (scorer) {
     case "Factuality":

evals/src/sync_datasets.ts

@@ -17,8 +17,8 @@ async function getCoqa(): Promise<z.infer<typeof coqaSchema>[]> {
     await duckq(
       conn,
       `SELECT * FROM 'hf://datasets/stanfordnlp/coqa/data/validation-00000-of-00001.parquet'
-        LIMIT 20`
-    )
+        LIMIT 20`,
+    ),
   );
 }
 
@@ -75,7 +75,7 @@ async function coqaContextRelevancy(): Promise<ContextRelevancyCase[]> {
 
     const input = questions[0];
     const contexts = answers.answer_start.map((answer_start, i) =>
-      story.substring(answer_start, answers.answer_end[i])
+      story.substring(answer_start, answers.answer_end[i]),
     );
 
     cases.push({

js/json.ts

@@ -23,7 +23,7 @@ export const JSONDiff: ScorerWithPartial<
       score: await jsonDiff(output, expected, stringScorer, numberScorer),
     };
   },
-  "JSONDiff"
+  "JSONDiff",
 );
 
 /**
@@ -43,7 +43,7 @@ async function jsonDiff(
   o1: any,
   o2: any,
   stringScorer: Scorer<string, {}>,
-  numberScorer: Scorer<number, {}>
+  numberScorer: Scorer<number, {}>,
 ): Promise<number | null> {
   if (isObject(o1) && isObject(o2)) {
     if (Object.keys(o1).length == 0 && Object.keys(o2).length == 0) {
@@ -54,13 +54,13 @@ async function jsonDiff(
       Object.fromEntries(
         Object.keys(o1)
           .concat(Object.keys(o2))
-          .map((k) => [k, true])
-      )
+          .map((k) => [k, true]),
+      ),
     );
 
     const baseScores = (
       await Promise.all(
-        allKeys.map((k) => jsonDiff(o1[k], o2[k], stringScorer, numberScorer))
+        allKeys.map((k) => jsonDiff(o1[k], o2[k], stringScorer, numberScorer)),
       )
     ).filter((s) => s !== null) as number[];
     return baseScores.reduce((acc, s) => acc + s, 0) / baseScores.length;
@@ -73,7 +73,7 @@ async function jsonDiff(
       await Promise.all(
         Array.from({
           length: Math.min(o1.length, o2.length),
-        }).map((_, i) => jsonDiff(o1[i], o2[i], stringScorer, numberScorer))
+        }).map((_, i) => jsonDiff(o1[i], o2[i], stringScorer, numberScorer)),
       )
     ).filter((s) => s !== null) as number[];
     return (

js/list.ts

@@ -44,10 +44,10 @@ export const ListContains: ScorerWithPartial<
                 output: output_item,
                 expected: expected_item,
               })
-            ).score ?? 0
-        )
-      )
-    )
+            ).score ?? 0,
+        ),
+      ),
+    ),
   );
 
   if (similarities.length === 1 && similarities[0].length === 1) {
@@ -68,7 +68,7 @@ export const ListContains: ScorerWithPartial<
             expected: expected[c],
             score: similarities[r][c],
           }
-        : null
+        : null,
     )
     .filter((pair) => pair !== null) as Array<{
     output: string;

js/llm.ts

@@ -50,7 +50,7 @@ const COT_RESPONSE_SCHEMA = {
 
 export function buildClassificationTools(
   useCoT: boolean,
-  choiceStrings: string[]
+  choiceStrings: string[],
 ): ChatCompletionTool[] {
   const params = useCoT ? COT_RESPONSE_SCHEMA : PLAIN_RESPONSE_SCHEMA;
   const enumParams = {
@@ -83,7 +83,7 @@ export type OpenAIClassifierArgs<RenderArgs> = {
   RenderArgs;
 
 export async function OpenAIClassifier<RenderArgs, Output>(
-  args: ScorerArgs<Output, OpenAIClassifierArgs<RenderArgs>>
+  args: ScorerArgs<Output, OpenAIClassifierArgs<RenderArgs>>,
 ): Promise<Score> {
   const {
     name,
@@ -144,7 +144,7 @@ export async function OpenAIClassifier<RenderArgs, Output>(
       openAiBaseUrl,
       openAiDefaultHeaders,
       openAiDangerouslyAllowBrowser,
-    }
+    },
   );
 
   if (resp.choices.length > 0) {
@@ -159,7 +159,7 @@ export async function OpenAIClassifier<RenderArgs, Output>(
 
 function parseResponse(
   resp: ChatCompletionMessage,
-  choiceScores: Record<string, number>
+  choiceScores: Record<string, number>,
 ): Omit<Score, "name"> {
   let score = 0;
   const metadata: Record<string, unknown> = {};
@@ -210,7 +210,7 @@ export function LLMClassifierFromTemplate<RenderArgs>({
 }): Scorer<string, LLMClassifierArgs<RenderArgs>> {
   const choiceStrings = Object.keys(choiceScores);
   const ret = async (
-    runtimeArgs: ScorerArgs<string, LLMClassifierArgs<RenderArgs>>
+    runtimeArgs: ScorerArgs<string, LLMClassifierArgs<RenderArgs>>,
   ) => {
     const useCoT = runtimeArgs.useCoT ?? useCoTArg ?? true;
 
@@ -259,7 +259,7 @@ export interface ModelGradedSpec {
 
 export function LLMClassifierFromSpec<RenderArgs>(
   name: string,
-  spec: ModelGradedSpec
+  spec: ModelGradedSpec,
 ): Scorer<any, LLMClassifierArgs<RenderArgs>> {
   return LLMClassifierFromTemplate({
     name,
@@ -273,15 +273,15 @@ export function LLMClassifierFromSpec<RenderArgs>(
 
 export function LLMClassifierFromSpecFile<RenderArgs>(
   name: string,
-  templateName: keyof typeof templates
+  templateName: keyof typeof templates,
 ): Scorer<any, LLMClassifierArgs<RenderArgs>> {
   const doc = yaml.load(templates[templateName]) as ModelGradedSpec;
   return LLMClassifierFromSpec(name, doc);
 }
 
 function buildLLMClassifier<RenderArgs>(
   name: string,
-  templateName: keyof typeof templates
+  templateName: keyof typeof templates,
 ): ScorerWithPartial<string, LLMClassifierArgs<RenderArgs>> {
   if (!(templateName in templates)) {
     throw new Error(`Model template ${name} not found`);
@@ -290,9 +290,9 @@ function buildLLMClassifier<RenderArgs>(
   return makePartial(
     LLMClassifierFromSpecFile<RenderArgs>(
       name,
-      templateName as keyof typeof templates
+      templateName as keyof typeof templates,
     ),
-    name
+    name,
   );
 }
 
@@ -302,7 +302,7 @@ function buildLLMClassifier<RenderArgs>(
  */
 export const Battle = buildLLMClassifier<{ instructions: string }>(
   "Battle",
-  "battle"
+  "battle",
 );
 
 /**
@@ -311,7 +311,7 @@ export const Battle = buildLLMClassifier<{ instructions: string }>(
  */
 export const ClosedQA = buildLLMClassifier<{ input: string; criteria: any }>(
   "ClosedQA",
-  "closed_q_a"
+  "closed_q_a",
 );
 
 /**
@@ -333,7 +333,7 @@ export const Factuality = buildLLMClassifier<{
  */
 export const Possible = buildLLMClassifier<{ input: string }>(
   "Possible",
-  "possible"
+  "possible",
 );
 
 /**
@@ -351,7 +351,7 @@ export const Sql = buildLLMClassifier<{ input: string }>("Sql", "sql");
  */
 export const Summary = buildLLMClassifier<{ input: string }>(
   "Summary",
-  "summary"
+  "summary",
 );
 
 /**

js/number.ts

@@ -22,5 +22,5 @@ export const NumericDiff: ScorerWithPartial<number, {}> = makePartial(
       score,
     };
   },
-  "NumericDiff"
+  "NumericDiff",
 );

js/oai.ts

@@ -62,7 +62,7 @@ declare global {
 
 export async function cachedChatCompletion(
   params: CachedLLMParams,
-  options: { cache?: ChatCache } & OpenAIAuth
+  options: { cache?: ChatCache } & OpenAIAuth,
 ): Promise<ChatCompletion> {
   let openai = buildOpenAIClient(options);
   return await openai.chat.completions.create(params);

js/partial.ts

@@ -10,7 +10,7 @@ export interface ScorerWithPartial<Output, Extra>
 
 export function makePartial<Output, Extra>(
   fn: Scorer<Output, Extra>,
-  name?: string
+  name?: string,
 ): ScorerWithPartial<Output, Extra> {
   const ret: any = fn.bind({});
   ret.partial = (args: Partial<ScorerArgs<Output, Extra>>) => {