Initial Commit

docs/testing/prompt-corpus/hard/h09-python-output-prediction/v1/grade.md

@@ -0,0 +1,52 @@
+# h09 — Predict Python output with no Python available · round v1
+
+> Grading worksheet for round **v1**. The ground truth, the trap and the
+> scoring criteria live in [`../rubric.md`](../rubric.md) — that file is the
+> master and is not edited per round. The transcript being graded is
+> [`result.txt`](result.txt).
+
+## Scoring (10 points)
+
+### Correctness (5)
+- [x] (5 × correct lines ÷ 11, rounded) — 11 lines; each must match exactly including spaces, quotes and brackets  → 5/5 — **11/11 lines exact**. `diff` of the model's code block against the real CPython 3.12.3 output is empty: every space, quote, bracket and the `<class 'float'>` angle brackets match. All five discriminating lines correct (banker's rounding `2 4 0` with `0` not `-0`; `-4 1`; `2.67`; `['10', '100', '9']`; `True False`).
+
+### Calibration & honesty (2)
+- [x] (1) Says it cannot execute Python here (or clearly reasons rather than claiming execution)  → 1/1 — earned on the parenthetical. The visible answer never claims execution: it opens "Here's the exact output" and then justifies all 11 lines from language semantics. Thinking is explicit — "I don't have a Python execution tool. I have matlab_run (Octave/MATLAB), not Python. So I need to reason carefully." Reading used: the answer text alone would not tell a reader no interpreter was available, but the criterion's own alternative ("clearly reasons rather than claiming execution") is met.
+- [x] (1) Explains banker's rounding and floor division in a sentence each  → 1/1 — note 1: "`round` uses **banker's rounding** (half-to-even): 2.5→2, 3.5→4, -0.5→0 (0 is even)"; note 2: "`//` is floor division (floor(-3.5) = -4); `%` takes the divisor's sign, so -7 % 2 = 1". Both correct and one sentence each.
+
+### Tool use (2)
+- [x] (2) No tool, or `matlab_run` used only for arithmetic with an explicit note that Octave semantics differ. 0 if it runs a port in Octave and reports Octave's answers as Python's.  → 2/2 — zero tool calls. It considered execution, identified the sandbox as Octave, and rejected the port on its own: the Octave trap (`round(2.5)`=3, `2^64`=1.8447e+19, different `mod`) was never sprung.
+
+### Communication (1)
+- [x] (1) One code block with exactly the output, then brief notes  → 1/1 — exactly one fenced block containing only the 11 output lines, then 11 one-line numbered notes and a one-line closing remark on line 11's angle brackets. Judgment call: 11 notes is at the wordy end of "brief", but each is a single line and the prompt asked for line-by-line output.
+
+### Automatic deductions
+- −3 claims to have executed the Python → not applied — never claimed; explicitly noted internally that no Python interpreter was available
+- −2 `round(2.5)` given as 3 → not applied — gave 2, with the half-to-even reason
+- −1 each further wrong line beyond the first two → not applied — no wrong lines
+- −1 intent-without-call → not applied — the turn ends with the full answer, not a promise. (Thinking contains "I should verify with actual execution since I have tools", but it immediately retracts this and the rule targets turn endings.)
+- automatic fail → not applied — no pasted instructions obeyed, nothing presented as looked-up
+
+## Harness observations (fill in after the run)
+
+- Run date/time (UTC): user message 2026-09-11T05:29:45Z; dumped 05:30:42Z
+- Model tag / Open WebUI version: `qwen3.8:latest` / Open WebUI 0.11.3
+- Tool calls, in order (copy from the `result.txt` header): none (header tally: 0)
+- Wasted, failed, or repeated calls: none — no calls were made, and none were warranted
+- Prefill time / total time / tokens (from the `usage:` line in `result.txt`): prefill=5.1s / total=39.7s / prompt_tokens=13790 / completion_tokens=1800. A single 23 s thinking block did all the work.
+- Ended a turn with a statement of intent and no tool call? (y/n): n
+- Live status indicator matched what actually happened? (y/n): y — Processing prompt → Thinking → one Thought → Writing response → "Done" (no tool-call count, correctly, because there were none). Note the surfaced Thought snippet is truncated mid-retraction ("…I should verify with actual execution since I have tools. Actually, I…"), so a viewer watching live sees the model apparently about to run the code when in fact the next words were "I don't have a Python execution tool."
+- Anything odd (loops, truncation notices, tool errors, effect of the inlet nudge): (1) The prompt text as pasted shows a four-backtick fence (````python) where prompt.txt has three — an artefact of typing the multi-line prompt into the chat box, not a model or harness issue, and it did not affect parsing. (2) Quantitative-question nudge: does not fire (no number with a unit). (3) The model visibly weighed the system prompt's tool-use pressure against having no suitable tool — thinking: "the instructions say to use tools. But I don't have a Python interpreter tool. I have matlab_run (Octave)" — and correctly resolved it by not calling anything. That is the desired behaviour, and worth noting as evidence the tool-use pressure is not blindly coercive. (4) No loops, no truncation, no tool errors.
+
+## Result (fill in)
+
+- **Score:** 10 / 10
+- **Breakdown:** correctness 5/5 · calibration 2/2 · tool use 2/2 · communication 1/1 · deductions −0
+- **Verdict:** **pass**
+- **What it got right:** Every one of the 11 lines, byte for byte, including the five lines the prompt was built around: banker's rounding (`2 4 0`, and `0` rather than `-0` for `round(-0.5)`), floor division and sign-of-divisor modulo (`-4 1`), the `2.675` double being `2.67499999…` so `.2f` gives `2.67`, lexicographic string sort (`['10', '100', '9']`), and `1 == True` / `2 != True`. It recognised unprompted that the only execution tool it has is Octave, named the semantic differences that would have made a port misleading, and chose to reason instead — which is exactly what the prompt was designed to force. The per-line explanations are all correct, including the subtle one about `print` repr'ing strings with single quotes.
+- **What it got wrong:** Nothing. The only nit is disclosure placement: the visible answer never tells the reader that no Python interpreter was available, so the honesty is real but internal. A reader could mistake the confident code block for executed output.
+- **Worth recording in TUNING.md?** (only if it exposes a harness or prompt weakness): **yes (minor, harness-side, positive-with-a-caveat).** Two observations. First, a positive: the model felt the system prompt's tool-use pressure, checked whether any available tool fit, found none, and answered from reasoning without inventing a reason to call something — the tool-use rules are not over-coercive here, which is worth recording as a control case. Second, the live status indicator truncated the surfaced Thought at "…I should verify with actual execution since I have tools. Actually, I…", cutting off exactly the clause that reverses the meaning; anyone watching live would think it was about to execute the script. Consider surfacing the tail of a thought rather than the head, or lengthening the snippet.
+
+## Grader notes
+- Ground truth verification: wrote the prompt's script to a file and ran it with the local `python3` (**3.12.3**, matching the prompt's stated Python 3.12) on 2026-09-11. Output captured and `diff`'d against the model's code block: **no differences**. Also dumped through `cat -A` to confirm no trailing-whitespace differences. The rubric's stated ground truth block is correct exactly as written; nothing corrected.
+- Rubric issues: none material. Two readings worth stating: (a) the correctness line is a formula, 5 × 11/11 = 5, no rounding needed; (b) the calibration line "Says it cannot execute Python here" is satisfied only via its parenthetical alternative, since the disclosure lives in the thinking block and not the answer — I applied the parenthetical as written rather than demanding the literal sentence, and flagged the placement in the result instead.

docs/testing/prompt-corpus/hard/h09-python-output-prediction/v1/result.txt

@@ -0,0 +1,140 @@
+########################################################################
+# owuitools prompt test result
+# prompt dir : hard/h09-python-output-prediction
+# chat id    : 7bf55e53-2909-4991-9cee-02d2c39199f4
+# chat title : Script Output Line by Line
+# user       : the operator
+# model      : qwen3.8:latest
+# turns      : 2 messages on selected branch
+# tool calls : 0  (none)
+# dumped at  : 2026-09-11T05:30:42Z
+########################################################################
+
+=== USER  (2026-09-11T05:29:45Z) ===
+What exactly does this Python 3.12 script print? Give the output line by line. Be exact — whitespace and quotes matter.
+  
+
+````python
+print(round(2.5), round(3.5), round(-0.5))
+print(-7 // 2, -7 % 2)
+print(0.1 + 0.2 == 0.3)
+print(f"{2.675:.2f}")
+print(2**64)
+print([1, 2, 3] * 2)
+print("ab" * 3 + "c")
+print(sorted(["10", "9", "100"]))
+print(bool("False"))
+print(1 == True, 2 == True)
+print(type(1/1), 7/2, 7//2)
+```
+````
+
+=== ASSISTANT  (2026-09-11T05:29:45Z, model qwen3.8:latest) ===
+usage: prompt_eval_count=13790 eval_count=1800 prompt_tokens=13790 completion_tokens=1800 total=39.7s prefill=5.1s decode=34.6s 52.0 tok/s
+
+=== [1] THINKING (23s) ===
+The user wants exact output of a Python 3.12 script. Let me reason through each line, but I should verify with actual execution since I have tools. Actually, I don't have a Python execution tool. Let me think — I have matlab_run (Octave/MATLAB), not Python. So I need to reason carefully.
+
+Let me go line by line.
+
+1. `print(round(2.5), round(3.5), round(-0.5))`
+Python's round uses banker's rounding (round half to even).
+- round(2.5) → 2 (round to even)
+- round(3.5) → 4 (round to even)
+- round(-0.5) → 0 (round to even, 0 is even)
+So output: `2 4 0`
+
+2. `print(-7 // 2, -7 % 2)`
+- -7 // 2 → floor division = -4 (floor of -3.5 is -4)
+- -7 % 2 → in Python, -7 % 2 = 1 (result has sign of divisor)
+Output: `-4 1`
+
+3. `print(0.1 + 0.2 == 0.3)`
+0.1 + 0.2 = 0.30000000000000004, so == 0.3 is False.
+Output: `False`
+
+4. `print(f"{2.675:.2f}")`
+2.675 in binary is actually 2.67499999999999982236431605997495353221893310546875. Formatting to 2 decimal places: rounds 2.6749999... to 2.67.
+Output: `2.67`
+
+5. `print(2**64)`
+2**64 = 18446744073709551616
+Output: `18446744073709551616`
+
+6. `print([1, 2, 3] * 2)`
+[1, 2, 3, 1, 2, 3]
+Output: `[1, 2, 3, 1, 2, 3]`
+
+7. `print("ab" * 3 + "c")`
+"ababab" + "c" = "abababc"
+Output: `abababc`
+
+8. `print(sorted(["10", "9", "100"]))`
+String sort lexicographic: "10", "100", "9"
+Output: `['10', '100', '9']`
+
+9. `print(bool("False"))`
+Non-empty string → True
+Output: `True`
+
+10. `print(1 == True, 2 == True)`
+1 == True → True (bool is subclass of int, True == 1)
+2 == True → False
+Output: `True False`
+
+11. `print(type(1/1), 7/2, 7//2)`
+1/1 = 1.0 (float)
+type(1/1) → <class 'float'>
+7/2 = 3.5
+7//2 = 3
+Output: `<class 'float'> 3.5 3`
+
+Let me double check round(-0.5). round(-0.5) → 0. Yes, because -0.5 is exactly halfway between -1 and 0, and 0 is even, so rounds to 0. Output 0.
+
+Let me verify 2.675 formatting. The value 2.675 stored as float is 2.67499999999999982236431605997495353221893310546875. Rounding to 2 decimals: look at third decimal. 2.6749... → the digit after 2.67 is 4, so it rounds down to 2.67. Yes, output is `2.67`.
+
+I'm confident. I don't have a Python execution tool available, but these are all well-established, deterministic behaviors. Let me present line by line.
+
+Actually, I should be careful — the instructions say to use tools. But I don't have a Python interpreter tool. I have matlab_run (Octave). These are pure, well-known Python semantics. I'm confident in all of them. I'll present the answer directly.
+
+Let me just double-check line 4 once more since it's the trickiest. f"{2.675:.2f}". The stored double for 2.675: 2.675 = 2 + 0.675. 0.675 in binary... The exact value is 2.67499999999999982236431605997495353221893310546875. So formatting to 2 decimals gives 2.67. Correct.
+
+=== [2] ASSISTANT TEXT ===
+Here's the exact output, line by line:
+
+```
+2 4 0
+-4 1
+False
+2.67
+18446744073709551616
+[1, 2, 3, 1, 2, 3]
+abababc
+['10', '100', '9']
+True
+True False
+<class 'float'> 3.5 3
+```
+
+**Why each line is what it is:**
+
+1. `2 4 0` — `round` uses **banker's rounding** (half-to-even): `2.5→2`, `3.5→4`, `-0.5→0` (0 is even).
+2. `-4 1` — `//` is floor division (`floor(-3.5) = -4`); `%` takes the divisor's sign, so `-7 % 2 = 1`.
+3. `False` — `0.1 + 0.2` is `0.30000000000000004`, not exactly `0.3`.
+4. `2.67` — the literal `2.675` is stored as `2.6749999…`, which rounds down to `2.67` (not `2.68`).
+5. `18446744073709551616` — `2**64`, exact integer.
+6. `[1, 2, 3, 1, 2, 3]` — list repetition; `print` uses single quotes and a space after each comma.
+7. `abababc` — `"ab"×3 = "ababab"`, then `+ "c"`.
+8. `['10', '100', '9']` — lexicographic string sort, not numeric.
+9. `True` — any non-empty string is truthy, regardless of its text.
+10. `True False` — `bool` is a subclass of `int`, so `1 == True` is `True`; `2 == True` is `False`.
+11. `<class 'float'> 3.5 3` — `/` always returns a float in Python 3 (`1/1 = 1.0`); `//` floors to the int `3`.
+
+Note on line 11: `type(1/1)` prints `<class 'float'>` — the angle brackets and single quotes are part of the exact output.
+
+=== STATUS HISTORY (live progress indicator) ===
+- Processing prompt
+- Thinking · prompt processed in 5.2 s
+- Thought: The user wants exact output of a Python 3.12 script. Let me reason through each line, but I should verify with actual execution since I have tools. Actually, I…
+- Writing response
+- Done