feat(benchmarks): add hashline-edit benchmark agent and deps

Standalone headless agent using Vercel AI SDK v6 with FriendliAI provider.
Imports hashline-edit pure functions directly from src/ for benchmarking
the edit tool against LLMs (Minimax M2.5 via FriendliAI).

Ultraworked with [Sisyphus](https://github.com/code-yeongyu/oh-my-opencode)

Co-authored-by: Sisyphus <clio-agent@sisyphuslabs.ai>

benchmarks/headless.ts

@@ -0,0 +1,190 @@
+#!/usr/bin/env bun
+import { readFile, writeFile, mkdir } from "node:fs/promises"
+import { join, dirname } from "node:path"
+import { stepCountIs, streamText, type CoreMessage } from "ai"
+import { tool } from "ai"
+import { createFriendli } from "@friendliai/ai-provider"
+import { z } from "zod"
+import { formatHashLines } from "../src/tools/hashline-edit/hash-computation"
+import { normalizeHashlineEdits } from "../src/tools/hashline-edit/normalize-edits"
+import { applyHashlineEditsWithReport } from "../src/tools/hashline-edit/edit-operations"
+import { canonicalizeFileText, restoreFileText } from "../src/tools/hashline-edit/file-text-canonicalization"
+
+const DEFAULT_MODEL = "MiniMaxAI/MiniMax-M2.5"
+const MAX_STEPS = 50
+const sessionId = `bench-${Date.now()}-${Math.random().toString(36).slice(2, 8)}`
+
+const emit = (event: Record<string, unknown>) =>
+  console.log(JSON.stringify({ sessionId, timestamp: new Date().toISOString(), ...event }))
+
+// ── CLI ──────────────────────────────────────────────────────
+function parseArgs(): { prompt: string; modelId: string } {
+  const args = process.argv.slice(2)
+  let prompt = ""
+  let modelId = DEFAULT_MODEL
+  for (let i = 0; i < args.length; i++) {
+    if ((args[i] === "-p" || args[i] === "--prompt") && args[i + 1]) {
+      prompt = args[++i]
+    } else if ((args[i] === "-m" || args[i] === "--model") && args[i + 1]) {
+      modelId = args[++i]
+    } else if (args[i] === "--reasoning-mode" && args[i + 1]) {
+      i++ // consume
+    }
+    // --no-translate, --think consumed silently
+  }
+  if (!prompt) {
+    console.error("Usage: bun run benchmarks/headless.ts -p <prompt> [-m <model>]")
+    process.exit(1)
+  }
+  return { prompt, modelId }
+}
+
+// ── Tools ────────────────────────────────────────────────────
+const readFileTool = tool({
+  description: "Read a file with hashline-tagged content (LINE#ID format)",
+  inputSchema: z.object({ path: z.string().describe("File path") }),
+  execute: async ({ path }) => {
+    const fullPath = join(process.cwd(), path)
+    try {
+      const content = await readFile(fullPath, "utf-8")
+      const lines = content.split("\n")
+      const tagged = formatHashLines(content)
+      return `OK - read file\npath: ${path}\nlines: ${lines.length}\n\n${tagged}`
+    } catch {
+      return `Error: File not found: ${path}`
+    }
+  },
+})
+
+const editFileTool = tool({
+  description: "Edit a file using hashline anchors (LINE#ID format)",
+  inputSchema: z.object({
+    path: z.string(),
+    edits: z.array(
+      z.object({
+        op: z.enum(["replace", "append", "prepend"]),
+        pos: z.string().optional(),
+        end: z.string().optional(),
+        lines: z.union([z.array(z.string()), z.string(), z.null()]),
+      })
+    ).min(1),
+  }),
+  execute: async ({ path, edits }) => {
+    const fullPath = join(process.cwd(), path)
+    try {
+      let rawContent = ""
+      let exists = true
+      try {
+        rawContent = await readFile(fullPath, "utf-8")
+      } catch {
+        exists = false
+      }
+
+      const normalized = normalizeHashlineEdits(edits)
+
+      if (!exists) {
+        const canCreate = normalized.every(
+          (e) => (e.op === "append" || e.op === "prepend") && !e.pos
+        )
+        if (!canCreate) return `Error: File not found: ${path}`
+      }
+
+      const envelope = canonicalizeFileText(rawContent)
+      const result = applyHashlineEditsWithReport(envelope.content, normalized)
+
+      if (result.content === envelope.content) {
+        return `Error: No changes made to ${path}. The edits produced identical content.`
+      }
+
+      const writeContent = restoreFileText(result.content, envelope)
+      await mkdir(dirname(fullPath), { recursive: true })
+      await writeFile(fullPath, writeContent, "utf-8")
+
+      const oldLineCount = rawContent.split("\n").length
+      const newLineCount = writeContent.split("\n").length
+      const delta = newLineCount - oldLineCount
+      const sign = delta > 0 ? "+" : ""
+      const action = exists ? "Updated" : "Created"
+      return `${action} ${path}\n${edits.length} edit(s) applied, ${sign}${delta} line(s)`
+    } catch (error) {
+      return `Error: ${error instanceof Error ? error.message : String(error)}`
+    }
+  },
+})
+
+// ── Agent Loop ───────────────────────────────────────────────
+async function run() {
+  const { prompt, modelId } = parseArgs()
+
+  const friendli = createFriendli({ apiKey: process.env.FRIENDLI_TOKEN! })
+  const model = friendli(modelId)
+  const tools = { read_file: readFileTool, edit_file: editFileTool }
+
+  emit({ type: "user", content: prompt })
+
+  const messages: CoreMessage[] = [{ role: "user", content: prompt }]
+  const system =
+    "You are a code editing assistant. Use read_file to read files and edit_file to edit them. " +
+    "Always read a file before editing it to get fresh LINE#ID anchors."
+
+  for (let step = 0; step < MAX_STEPS; step++) {
+    const stream = streamText({
+      model,
+      tools,
+      messages,
+      system,
+      stopWhen: stepCountIs(1),
+    })
+
+    let currentText = ""
+    for await (const part of stream.fullStream) {
+      switch (part.type) {
+        case "text-delta":
+          currentText += part.text
+          break
+        case "tool-call":
+          emit({
+            type: "tool_call",
+            tool_call_id: part.toolCallId,
+            tool_name: part.toolName,
+            tool_input: part.args,
+            model: modelId,
+          })
+          break
+        case "tool-result":
+          emit({
+            type: "tool_result",
+            tool_call_id: part.toolCallId,
+            output: typeof part.result === "string" ? part.result : JSON.stringify(part.result),
+          })
+          break
+      }
+    }
+
+    const response = await stream.response
+    messages.push(...response.messages)
+
+    const finishReason = await stream.finishReason
+    if (finishReason !== "tool-calls") {
+      if (currentText.trim()) {
+        emit({ type: "assistant", content: currentText, model: modelId })
+      }
+      break
+    }
+  }
+}
+
+// ── Signal + Startup ─────────────────────────────────────────
+process.once("SIGINT", () => process.exit(0))
+process.once("SIGTERM", () => process.exit(143))
+
+const startTime = Date.now()
+run()
+  .catch((error) => {
+    emit({ type: "error", error: error instanceof Error ? error.message : String(error) })
+    process.exit(1)
+  })
+  .then(() => {
+    const elapsed = ((Date.now() - startTime) / 1000).toFixed(2)
+    console.error(`[headless] Completed in ${elapsed}s`)
+  })