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refactor: rename tools

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bendtherules
2026-04-08 18:40:45 +05:30
parent 30debd2cf9
commit c109acba01
11 changed files with 158 additions and 153 deletions
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src/test/manual/test-search-spec-sections.ts
+57
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#!/usr/bin/env bun
/**
* Manual test script for ask262_search_spec_sections agent tool.
* Tests the semantic vector search functionality.
*
* Usage: bun run src/test/manual/test-search-spec-sections.ts ["your search query"]
*
* Examples:
* bun run src/test/manual/test-search-spec-sections.ts
* bun run src/test/manual/test-search-spec-sections.ts "how does array prototype map work"
* bun run src/test/manual/test-search-spec-sections.ts "for statement evaluation"
*/
import * as lancedbSdk from "@lancedb/lancedb";
import { OllamaEmbeddings } from "@langchain/ollama";
import { createSearchSpecSectionsTool } from "../../agent-tools";
import { EMBEDDING_MODEL, STORAGE_DIR } from "../../constants";
async function main() {
// Get query from command line or use default
const query =
process.argv[2] ||
"how does the if statement evaluation work in javascript";
console.log("=== Testing ask262_search_spec_sections Tool ===\n");
console.log(`Query: "${query}"\n`);
console.log("Loading database and embeddings...");
try {
const embeddings = new OllamaEmbeddings({
model: EMBEDDING_MODEL,
});
const db = await lancedbSdk.connect(STORAGE_DIR);
const table = await db.openTable("spec_vectors");
console.log("✓ Database loaded\n");
console.log("Creating tool...");
const searchSpecSectionsTool = createSearchSpecSectionsTool(
table,
embeddings,
);
console.log("✓ Tool created\n");
console.log("Executing tool...\n");
const result = await searchSpecSectionsTool.func({ query });
console.log("=== TOOL OUTPUT ===");
console.log(result);
console.log("\n=== END OUTPUT ===");
} catch (error) {
console.error("\n✗ Error:", error);
process.exit(1);
}
}
main().catch(console.error);
src/test/manual/test-spec-retriever.ts
-35
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@@ -1,35 +0,0 @@
/**
* Manual test script for spec_retriever agent tool
* Usage: bun run src/test/manual/test-spec-retriever.ts "your search query"
*/
import * as lancedbSdk from "@lancedb/lancedb";
import { OllamaEmbeddings } from "@langchain/ollama";
import { createSpecRetrieverTool } from "../../agent-tools";
import { EMBEDDING_MODEL, STORAGE_DIR } from "../../constants";
async function main() {
const query = process.argv[2] || "array.[[DefineOwnProperty]]";
console.log(`Testing spec_retriever with query: "${query}"`);
console.log("Loading database and embeddings...\n");
const embeddings = new OllamaEmbeddings({
model: EMBEDDING_MODEL,
});
const db = await lancedbSdk.connect(STORAGE_DIR);
const table = await db.openTable("spec_vectors");
console.log("Creating tool...\n");
const specRetrieverTool = createSpecRetrieverTool(table, embeddings);
console.log("Executing tool...\n");
const result = await specRetrieverTool.func({ query });
console.log("=== TOOL OUTPUT ===");
console.log(result);
console.log("\n=== END OUTPUT ===");
}
main().catch(console.error);