Add initial code for retreival ranking for normalisation

.gitignore

@@ -0,0 +1,2 @@
+# TEMP
+literature/

agent/.gitignore

@@ -1,3 +1,8 @@
+# -------- Ours --------
+tools/clan/*.csv
+tools/clan/*.json
+
+# --------- Github -----------
 # Logs
 logs
 *.log

agent/nodes/tool.ts

@@ -2,7 +2,7 @@ import { AIMessage, ToolMessage } from "@langchain/core/messages";
 import { GraphNode } from "@langchain/langgraph";
 import { MessagesState } from "../state";
 
-export function createToolNode(tools): GraphNode<typeof MessagesState> {
+export function createToolNode(tools: any): GraphNode<typeof MessagesState> {
   return async (state) => {
     const lastMessage = state.messages.at(-1);
 

agent/package.json

@@ -10,14 +10,20 @@
     "dev": "tsx run.ts"
   },
   "dependencies": {
+    "@huggingface/transformers": "^3.8.1",
     "@langchain/core": "^1.1.17",
     "@langchain/langgraph": "^1.1.2",
     "@langchain/langgraph-sdk": "^1.5.5",
     "@langchain/openai": "^1.2.3",
+    "compute-cosine-similarity": "^1.1.0",
+    "csv-parse": "^6.1.0",
     "dotenv": "^17.2.3",
-    "langchain": "^1.2.14"
+    "fs": "^0.0.1-security",
+    "langchain": "^1.2.14",
+    "winston": "^3.19.0"
   },
   "devDependencies": {
+    "@types/node": "^25.1.0",
     "tsx": "^4.21.0"
   }
 }

agent/tools/clan/retreiveExamples.ts

@@ -0,0 +1,107 @@
+import { parse } from "csv-parse";
+import fs from "fs";
+import { pipeline, cos_sim } from "@huggingface/transformers";
+import { logger } from "../../utils/logger";
+
+const CSV_PATH = "./tools/clan/dev-eng.csv";
+const CACHE_PATH = "./tools/clan/dev-eng.embeddings.json";
+
+type EmbeddingCache = {
+  texts: string[];
+  embeddings: number[][];
+};
+
+export type NormalisedMatch = {
+  index: number; 
+  score: number; 
+  text: string
+};
+
+let texts: string[] = [];
+let embeddings: number[][] = [];
+
+const featureExtractor = await pipeline(
+  "feature-extraction",
+  "Xenova/all-MiniLM-L6-v2"
+);
+
+
+async function loadOrBuildCache(): Promise<void> {
+  if (fs.existsSync(CACHE_PATH)) {
+    logger.info("Loading embeddings from cache");
+
+    const raw = fs.readFileSync(CACHE_PATH, "utf-8");
+    const cache: EmbeddingCache = JSON.parse(raw);
+
+    texts = cache.texts;
+
+    embeddings = cache.embeddings.map(e => Array.from(e));
+
+    logger.info("Loaded %s embeddings", embeddings.length);
+    return;
+  }
+
+  logger.warn("Cache not found. Generating embeddings", embeddings.length);
+
+  await buildCacheFromCSV();
+
+  const cache: EmbeddingCache = {
+    texts,
+    embeddings,
+  };
+
+  fs.writeFileSync(CACHE_PATH, JSON.stringify(cache));
+
+  logger.info("Cached %s embeddings", embeddings.length);
+}
+
+async function buildCacheFromCSV(): Promise<void> {
+  let count = 0;
+
+  const stream = fs.createReadStream(CSV_PATH).pipe(parse());
+
+  for await (const row of stream) {
+    const text = row[0];
+    if (!text) continue;
+
+    const output = await featureExtractor(text, {
+      pooling: "mean",
+      normalize: true,
+    });
+
+    texts.push(text);
+    const vector = Array.from(output.data as Float32Array);
+    embeddings.push(vector);
+
+
+    count++;
+    if (count % 100 === 0) {
+      logger.info("Processed %s", count);
+    }
+  }
+}
+
+export async function calculateSimilarity(query: string,topK = 5): Promise<NormalisedMatch[]> {
+  const queryEmbedding = await featureExtractor(query, {
+    pooling: "mean",
+    normalize: true,
+  });
+
+  return embeddings
+    .map((embedding, index) => ({
+      index,
+      score: cos_sim(embedding, queryEmbedding.data as number[]),
+      text: texts[index],
+    }))
+    .sort((a, b) => b.score - a.score)
+    .slice(0, topK);
+}
+
+//TEMP: testing code
+await loadOrBuildCache();
+
+const results = await calculateSimilarity(
+  "Wonderful to see London has taken a stand to defend freedom and the right to choose."
+);
+
+console.log(results);

agent/utils/logger.ts

@@ -0,0 +1,16 @@
+import winston from "winston";
+
+export const logger = winston.createLogger({
+  level: "info",
+  format: winston.format.combine(
+    winston.format.splat(),
+    winston.format.colorize(),
+    winston.format.timestamp({ format: "HH:mm:ss" }),
+    winston.format.printf(({ level, message, timestamp }) => {
+      return `${timestamp} ${level}: ${message}`;
+    })
+  ),
+  transports: [
+    new winston.transports.Console(),
+  ],
+});