chore: Update dependencies and fix import paths

src/lib/huggingfaceTransformer.ts

@@ -1,7 +1,7 @@
 import { Embeddings, type EmbeddingsParams } from "@langchain/core/embeddings";
 import { chunkArray } from "@langchain/core/utils/chunk_array";
 
-export interface HuggingFaceTransformersEmbeddingsParams extends EmbeddingsParams {
+export interface HuggingFaceTransformersEmbeddingsParameters extends EmbeddingsParams {
   modelName: string;
 
   model: string;
@@ -13,7 +13,10 @@ export interface HuggingFaceTransformersEmbeddingsParams extends EmbeddingsParam
   stripNewLines?: boolean;
 }
 
-export class HuggingFaceTransformersEmbeddings extends Embeddings implements HuggingFaceTransformersEmbeddingsParams {
+export class HuggingFaceTransformersEmbeddings
+  extends Embeddings
+  implements HuggingFaceTransformersEmbeddingsParameters
+{
   modelName = "Xenova/all-MiniLM-L6-v2";
 
   model = "Xenova/all-MiniLM-L6-v2";
@@ -27,7 +30,7 @@ export class HuggingFaceTransformersEmbeddings extends Embeddings implements Hug
   // eslint-disable-next-line @typescript-eslint/no-explicit-any
   private pipelinePromise: Promise<any>;
 
-  constructor(fields?: Partial<HuggingFaceTransformersEmbeddingsParams>) {
+  constructor(fields?: Partial<HuggingFaceTransformersEmbeddingsParameters>) {
     super(fields ?? {});
 
     this.modelName = fields?.model ?? fields?.modelName ?? this.model;
@@ -37,16 +40,15 @@ export class HuggingFaceTransformersEmbeddings extends Embeddings implements Hug
   }
 
   async embedDocuments(texts: string[]): Promise<number[][]> {
-    const batches = chunkArray(this.stripNewLines ? texts.map(t => t.replace(/\n/g, " ")) : texts, this.batchSize);
+    const batches = chunkArray(this.stripNewLines ? texts.map(t => t.replaceAll("\n", " ")) : texts, this.batchSize);
 
     const batchRequests = batches.map(batch => this.runEmbedding(batch));
     const batchResponses = await Promise.all(batchRequests);
     const embeddings: number[][] = [];
 
-    for (let i = 0; i < batchResponses.length; i += 1) {
-      const batchResponse = batchResponses[i];
-      for (let j = 0; j < batchResponse.length; j += 1) {
-        embeddings.push(batchResponse[j]);
+    for (const batchResponse of batchResponses) {
+      for (const element of batchResponse) {
+        embeddings.push(element);
       }
     }
 
@@ -54,7 +56,7 @@ export class HuggingFaceTransformersEmbeddings extends Embeddings implements Hug
   }
 
   async embedQuery(text: string): Promise<number[]> {
-    const data = await this.runEmbedding([this.stripNewLines ? text.replace(/\n/g, " ") : text]);
+    const data = await this.runEmbedding([this.stripNewLines ? text.replaceAll("\n", " ") : text]);
     return data[0];
   }
 

src/lib/outputParsers/listLineOutputParser.ts

@@ -1,15 +1,15 @@
 import { BaseOutputParser } from "@langchain/core/output_parsers";
 
-interface LineListOutputParserArgs {
+interface LineListOutputParserArguments {
   key?: string;
 }
 
 class LineListOutputParser extends BaseOutputParser<string[]> {
   private key = "questions";
 
-  constructor(args?: LineListOutputParserArgs) {
+  constructor(arguments_?: LineListOutputParserArguments) {
     super();
-    this.key = args.key ?? this.key;
+    this.key = arguments_.key ?? this.key;
   }
 
   static lc_name() {

src/lib/providers.ts

@@ -36,8 +36,8 @@ export const getAvailableChatModelProviders = async () => {
           temperature: 0.7,
         }),
       };
-    } catch (err) {
-      logger.error(`Error loading OpenAI models: ${err}`);
+    } catch (error) {
+      logger.error(`Error loading OpenAI models: ${error}`);
     }
   }
 
@@ -85,8 +85,8 @@ export const getAvailableChatModelProviders = async () => {
           },
         ),
       };
-    } catch (err) {
-      logger.error(`Error loading Groq models: ${err}`);
+    } catch (error) {
+      logger.error(`Error loading Groq models: ${error}`);
     }
   }
 
@@ -101,16 +101,17 @@ export const getAvailableChatModelProviders = async () => {
       // eslint-disable-next-line @typescript-eslint/no-explicit-any
       const { models: ollamaModels } = (await response.json()) as any;
 
-      models["ollama"] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new ChatOllama({
+      // eslint-disable-next-line unicorn/no-array-reduce
+      models["ollama"] = ollamaModels.reduce((accumulator, model) => {
+        accumulator[model.model] = new ChatOllama({
           baseUrl: ollamaEndpoint,
           model: model.model,
           temperature: 0.7,
         });
-        return acc;
+        return accumulator;
       }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama models: ${err}`);
+    } catch (error) {
+      logger.error(`Error loading Ollama models: ${error}`);
     }
   }
 
@@ -137,8 +138,8 @@ export const getAvailableEmbeddingModelProviders = async () => {
           modelName: "text-embedding-3-large",
         }),
       };
-    } catch (err) {
-      logger.error(`Error loading OpenAI embeddings: ${err}`);
+    } catch (error) {
+      logger.error(`Error loading OpenAI embeddings: ${error}`);
     }
   }
 
@@ -153,15 +154,16 @@ export const getAvailableEmbeddingModelProviders = async () => {
       // eslint-disable-next-line @typescript-eslint/no-explicit-any
       const { models: ollamaModels } = (await response.json()) as any;
 
-      models["ollama"] = ollamaModels.reduce((acc, model) => {
-        acc[model.model] = new OllamaEmbeddings({
+      // eslint-disable-next-line unicorn/no-array-reduce
+      models["ollama"] = ollamaModels.reduce((accumulator, model) => {
+        accumulator[model.model] = new OllamaEmbeddings({
           baseUrl: ollamaEndpoint,
           model: model.model,
         });
-        return acc;
+        return accumulator;
       }, {});
-    } catch (err) {
-      logger.error(`Error loading Ollama embeddings: ${err}`);
+    } catch (error) {
+      logger.error(`Error loading Ollama embeddings: ${error}`);
     }
   }
 
@@ -177,8 +179,8 @@ export const getAvailableEmbeddingModelProviders = async () => {
         modelName: "Xenova/bert-base-multilingual-uncased",
       }),
     };
-  } catch (err) {
-    logger.error(`Error loading local embeddings: ${err}`);
+  } catch (error) {
+    logger.error(`Error loading local embeddings: ${error}`);
   }
 
   return models;

src/lib/searxng.ts

@@ -19,20 +19,20 @@ interface SearxngSearchResult {
   iframe_src?: string;
 }
 
-export const searchSearxng = async (query: string, opts?: SearxngSearchOptions) => {
+export const searchSearxng = async (query: string, options?: SearxngSearchOptions) => {
   const searxngURL = getSearxngApiEndpoint();
 
   const url = new URL(`${searxngURL}/search?format=json`);
   url.searchParams.append("q", query);
 
-  if (opts) {
-    Object.keys(opts).forEach(key => {
-      if (Array.isArray(opts[key])) {
-        url.searchParams.append(key, opts[key].join(","));
-        return;
+  if (options) {
+    for (const key of Object.keys(options)) {
+      if (Array.isArray(options[key])) {
+        url.searchParams.append(key, options[key].join(","));
+        continue;
       }
-      url.searchParams.append(key, opts[key]);
-    });
+      url.searchParams.append(key, options[key]);
+    }
   }
 
   const res = await axios.get(url.toString());