c61394923c
Seth asked "was this with think=false?" Yes — and that was the only question that mattered. Everything I concluded in round 1 and round 2 was wrong. Actual cause, isolated in round 3: - At identical message state, gemma4:26b with think=false returns eval=4 (silent stop); with think unset or think=true, returns eval=165 and emits the correct tool call. - Original round-1 write_file harness + think unset: 26B passes in 8 iters, 20s. No mitigations needed. - 31B dense and qwen3-coder:30b tolerate think=false; 26B MoE does not. Red herrings (kept on-record in the bakeoff doc, not silently erased): - Round 1: "write_file tool-call argument size" — wrong - Round 2a: refuted the arg-size theory but for the wrong reason (still failed because think=false was still set) - Round 2b: "cumulative tool-response context size" — truncating did make 26B pass, but by coincidence. Shorter context at the decision turn dodged the think=false side effect. Why the existing "always think:false" guidance was misleading: it was derived from AI_Visualizer (single-turn JSON pipelines) where thinking tokens do eat num_predict invisibly. In multi-turn tool-calling agents the channels are separate and the flag has a different effect — catastrophic on 26B specifically. Doc updates: - GOTCHAS: replaced the 26B entry with the actual cause; scoped the original "Thinking Mode Eats Context" entry to single-turn pipelines - SYNTHESIS: split the "Mandatory Ollama Settings" block into single-turn vs multi-turn variants; updated anti-patterns and quick-start checklist - CORPUS_cli_coding_agent.md: revised pointer and config template - docs/reference/bakeoff-2026-04-18.md: added Round 3 section with the correction notice at the top of the file and full diagnostic methodology New artifacts: harness_no_think_flag.py, harness_write_no_think.py, and 4 new log files demonstrating all three models pass when think is left at default.
138 lines
6.0 KiB
Python
138 lines
6.0 KiB
Python
"""Closes the loop on Round 1: original write_file harness, but think flag omitted.
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If 26B PASSES here, the original Round 1 failure (and Round 2 patch-mode failure)
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were both caused by `think: false`, not by the edit tool surface or response size.
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"""
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from __future__ import annotations
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import json, os, shutil, subprocess, sys, time
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from pathlib import Path
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from urllib import request as urlreq
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OLLAMA_HOST = os.environ.get("OLLAMA_HOST", "http://127.0.0.1:11434")
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MAX_ITERATIONS = 15
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BASH_TIMEOUT_S = 30
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REQUEST_TIMEOUT_S = 540
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SYSTEM_PROMPT = """You are a terminal coding agent.
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## What you do
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- Read source and test files to understand the code
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- Make targeted edits to fix bugs so the tests pass
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- Run pytest to verify your fix
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- Stop once all tests pass and reply with a one-sentence summary
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## What you do NOT do
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- Never modify files under tests/
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- Never disable, skip, or delete tests
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- Never write outside the working directory
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- Never call tools after all tests pass — just reply with the summary and stop
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## Available tools
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- read_file(path): read a file relative to the working directory
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- write_file(path, content): overwrite a file relative to the working directory
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- run_bash(command): run a shell command in the working directory
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## Rules
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- Start by reading README.md
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- Prefer minimal edits. Do not refactor unrelated code.
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- Run the full test suite after each edit to verify.
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"""
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USER_PROMPT = "Make the failing tests pass. Begin."
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TOOLS = [
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{"type": "function", "function": {"name": "read_file", "description": "Read a file relative to workdir.", "parameters": {"type": "object", "properties": {"path": {"type": "string"}}, "required": ["path"]}}},
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{"type": "function", "function": {"name": "write_file", "description": "Overwrite a file relative to workdir.", "parameters": {"type": "object", "properties": {"path": {"type": "string"}, "content": {"type": "string"}}, "required": ["path", "content"]}}},
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{"type": "function", "function": {"name": "run_bash", "description": "Run a bash command in workdir.", "parameters": {"type": "object", "properties": {"command": {"type": "string"}}, "required": ["command"]}}},
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]
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def safe_path(wd, rel):
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p = (wd / rel).resolve()
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if not str(p).startswith(str(wd.resolve())):
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raise ValueError(f"path escapes workdir: {rel}")
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return p
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def t_read(wd, a):
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p = safe_path(wd, a["path"])
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return p.read_text() if p.exists() else f"ERROR: {a['path']} does not exist"
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def t_write(wd, a):
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p = safe_path(wd, a["path"])
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p.parent.mkdir(parents=True, exist_ok=True)
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p.write_text(a["content"])
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return f"wrote {a['path']} ({len(a['content'])} bytes)"
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def t_bash(wd, a):
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try:
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r = subprocess.run(["bash", "-c", a["command"]], cwd=wd, capture_output=True, text=True, timeout=BASH_TIMEOUT_S)
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except subprocess.TimeoutExpired:
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return f"ERROR: timeout {BASH_TIMEOUT_S}s"
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return f"exit={r.returncode}\n--- stdout ---\n{r.stdout[-4000:]}\n--- stderr ---\n{r.stderr[-2000:]}"
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DISP = {"read_file": t_read, "write_file": t_write, "run_bash": t_bash}
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def chat(model, msgs):
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payload = {"model": model, "messages": msgs, "tools": TOOLS, "stream": False, "keep_alive": "10m", "options": {"num_ctx": 32768, "num_predict": 4096, "temperature": 0.3}}
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req = urlreq.Request(f"{OLLAMA_HOST}/api/chat", data=json.dumps(payload).encode(), headers={"Content-Type": "application/json"})
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with urlreq.urlopen(req, timeout=REQUEST_TIMEOUT_S) as r:
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return json.loads(r.read())
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def run(model, wd, logp):
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logp.parent.mkdir(parents=True, exist_ok=True)
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msgs = [{"role": "system", "content": SYSTEM_PROMPT}, {"role": "user", "content": USER_PROMPT}]
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trace = {"model": model, "edit_tool": "write_file", "think_setting": "unset (default)", "turns": [], "started_at": time.time()}
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counts = {"read_file": 0, "write_file": 0, "run_bash": 0}
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halt = None
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for i in range(1, MAX_ITERATIONS + 1):
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t0 = time.time()
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try:
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r = chat(model, msgs)
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except Exception as e:
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halt = f"error: {e}"
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break
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m = r.get("message", {})
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tcs = m.get("tool_calls") or []
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trace["turns"].append({"iteration": i, "elapsed_s": round(time.time() - t0, 2), "content": m.get("content") or "", "prompt_eval_count": r.get("prompt_eval_count"), "eval_count": r.get("eval_count"), "tool_calls_count": len(tcs)})
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msgs.append({"role": "assistant", "content": m.get("content") or "", "tool_calls": tcs})
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if not tcs:
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halt = "no_tool_calls"
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break
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for tc in tcs:
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fn = tc.get("function", {})
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n = fn.get("name")
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args = fn.get("arguments") or {}
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if isinstance(args, str):
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try: args = json.loads(args)
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except: args = {"_raw": args}
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try: res = DISP[n](wd, args) if n in DISP else f"ERROR: unknown {n}"
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except Exception as e: res = f"ERROR: {e}"
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if n in counts: counts[n] += 1
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msgs.append({"role": "tool", "content": res})
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if i == MAX_ITERATIONS:
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halt = "cap"
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break
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p = subprocess.run(["python3", "-m", "pytest", "tests/", "-q"], cwd=wd, capture_output=True, text=True, timeout=60)
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trace["final"] = {"halt_reason": halt, "tests_pass": p.returncode == 0, "iterations_used": len(trace["turns"]), "tool_call_counts": counts, "wall_clock_s": round(time.time() - trace["started_at"], 2)}
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logp.write_text(json.dumps(trace, indent=2, default=str))
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return trace
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if __name__ == "__main__":
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model, wd_s, log_s = sys.argv[1], sys.argv[2], sys.argv[3]
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wd, logp = Path(wd_s).resolve(), Path(log_s).resolve()
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seed = Path(__file__).parent / "task_seed"
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if wd.exists(): shutil.rmtree(wd)
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shutil.copytree(seed, wd)
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r = run(model, wd, logp)
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f = r["final"]
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print(f"model={model} pass={f['tests_pass']} iters={f['iterations_used']} r={f['tool_call_counts']['read_file']} w={f['tool_call_counts']['write_file']} b={f['tool_call_counts']['run_bash']} halt={f['halt_reason']} wall={f['wall_clock_s']}s")
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