171 lines
8.4 KiB
Plaintext
171 lines
8.4 KiB
Plaintext
MODEL: gpt-oss-120b
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PATH: /home/qrf/.cache/llama.cpp/openai_gpt-oss-120b-Q4_K_M/openai_gpt-oss-120b-Q4_K_M-00001-of-00002.gguf
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STARTED: 2026-07-12 15:23:42
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========================================================================
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TASK t1_fizzbuzz
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Create a file `fizzbuzz.py` in the scratch dir containing a function `fb(n)` that returns a list of strings for 1..n: 'Fizz' for multiples of 3, 'Buzz' for multiples of 5, 'FizzBuzz' for both, else the number as a string. Then run it to verify it works. When the file exists and runs without error, call done.
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[turn 1] raw: {"tool": "write_file", "args": {"path": "fizzbuzz.py", "content": "def fb(n):\n \"\"\"Return a list of strings for numbers 1..n with FizzBuzz rules.\n Multiples of 3 -> 'Fizz', multiples of 5 ->
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[turn 1] BAD CALL: no valid tool JSON found
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[turn 2] raw: {"tool":"write_file","args":{"path":"fizzbuzz.py","content":"def fb(n):\n \"\"\"Return a list of strings for numbers 1..n with FizzBuzz rules.\n Multiples of 3 -> 'Fizz', multiples of 5 -> 'Buzz
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[turn 2] tool=write_file -> wrote fizzbuzz.py (556 bytes)
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[turn 3] raw: {"tool":"run_python","args":{"path":"fizzbuzz.py"}}
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[turn 3] tool=run_python -> exit=0
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stdout:
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['1', '2', 'Fizz', '4', 'Buzz', 'Fizz', '7', '8', 'Fizz', 'Buzz', '11', 'Fizz', '13', '14', 'FizzBuzz']
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stderr:
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[turn 4] raw: {"tool":"done","args":{"summary":"Created fizzbuzz.py with fb function; verified output for n=15 matches expected FizzBuzz list."}}
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[turn 4] DONE: Created fizzbuzz.py with fb function; verified output for n=15 matches expected FizzBuzz list.
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RESULT: solved=True (graded pass) | turns=4 terminated=done called_done=True bad_calls=1
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========================================================================
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TASK t2_fix_bug
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A file `buggy.py` already exists in the scratch dir. It has a function `has_dup(xs)` that should return True if the list has any duplicates, but it has a bug. Read it, fix the bug in place, and run it to confirm the included tests pass. Then call done.
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[turn 1] raw: {"tool": "list_dir", "args": {}}
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[turn 1] tool=list_dir -> buggy.py
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[turn 2] raw: {"tool": "read_file", "args": {"path": "buggy.py"}}
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[turn 2] tool=read_file -> def has_dup(xs):
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seen = set()
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for x in xs:
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if x in seen:
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return False
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seen.add(x)
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return True
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if __name__ == "__main__":
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assert has_dup([1,2,3,1]) == True
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assert has_dup([1,2,3]) == False
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print("tests pass")
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[turn 3] raw: {"tool": "write_file", "args": {"path": "buggy.py", "content": "def has_dup(xs):\n seen = set()\n for x in xs:\n if x in seen:\n return True\n seen.add(x)\n return Fa
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[turn 3] tool=write_file -> wrote buggy.py (261 bytes)
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[turn 4] raw: {"tool": "run_python", "args": {"path": "buggy.py"}}
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[turn 4] tool=run_python -> exit=0
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stdout:
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tests pass
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stderr:
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[turn 5] raw: {"tool": "done", "args": {"summary": "Fixed has_dup to correctly detect duplicates and all tests pass."}}
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[turn 5] DONE: Fixed has_dup to correctly detect duplicates and all tests pass.
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RESULT: solved=True (graded pass) | turns=5 terminated=done called_done=True bad_calls=0
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========================================================================
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TASK t3_pipeline
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Build a two-step pipeline. First create `gen.py` that writes the numbers 1 through 20, one per line, to a file called `nums.txt`. Run it. Then create `sum.py` that reads `nums.txt` and prints the sum of the numbers. Run it and confirm it prints 210. Then call done.
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[turn 1] raw: We need to output JSON tool call.{"tool": "write_file", "args": {"path": "gen.py", "content": "with open('nums.txt', 'w') as f:\n for i in range(1, 21):\n f.write(f\"{i}\\n\")\n"}}
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[turn 1] tool=write_file -> wrote gen.py (86 bytes)
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[turn 2] raw: {"tool": "run_python", "args": {"path": "gen.py"}}
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[turn 2] tool=run_python -> exit=0
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stdout:
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stderr:
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[turn 3] raw: {"tool": "write_file", "args": {"path": "sum.py", "content": "total = 0\nwith open('nums.txt') as f:\n for line in f:\n total += int(line.strip())\nprint(total)\n"}}
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[turn 3] tool=write_file -> wrote sum.py (105 bytes)
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[turn 4] raw: {"tool": "run_python", "args": {"path": "sum.py"}}
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[turn 4] tool=run_python -> exit=0
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stdout:
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210
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stderr:
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[turn 5] raw: {"tool": "done", "args": {"summary": "Generated nums.txt with numbers 1-20, summed to 210."}}
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[turn 5] DONE: Generated nums.txt with numbers 1-20, summed to 210.
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RESULT: solved=True (prints 210) | turns=5 terminated=done called_done=True bad_calls=0
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========================================================================
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TASK t4_debug_loop
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Create `stats.py` with a function `mean_std(xs)` returning a tuple of the arithmetic mean and the population standard deviation of a list of numbers. It must print mean_std([2,4,4,4,5,5,7,9]) which should be (5.0, 2.0). Run it and confirm the output is exactly (5.0, 2.0). If not, fix and re-run until correct, then call done.
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[turn 1] raw: {"tool": "write_file", "args": {"path": "stats.py", "content": "import math\n\ndef mean_std(xs):\n \"\"\"Return (mean, population standard deviation) of list xs.\"\"\"\n n = len(xs)\n if n ==
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[turn 1] BAD CALL: no valid tool JSON found
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[turn 2] raw: {"tool": "write_file", "args": {"path": "stats.py", "content": "import math\n\ndef mean_std(xs):\n \"\"\"Return (mean, population standard deviation) of list xs.\"\"\"\n n = len(xs)\n if n ==
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[turn 2] BAD CALL: no valid tool JSON found
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[turn 3] raw: {"tool":"write_file","args":{"path":"stats.py","content":"import math\n\ndef mean_std(xs):\n \"\"\"Return (mean, population standard deviation) of list xs.\"\"\"\n n = len(xs)\n if n == 0:\n
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[turn 3] BAD CALL: no valid tool JSON found
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[turn 4] raw: We need to respond with a valid tool call JSON. Let's do list_dir.{"tool":"list_dir","args":{}}
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[turn 4] tool=list_dir -> (empty)
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[turn 5] raw: {"tool":"write_file","args":{"path":"stats.py","content":"import math\n\ndef mean_std(xs):\n \"\"\"Return (mean, population standard deviation) of list xs.\"\"\"\n n = len(xs)\n if n == 0:\n
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[turn 5] tool=write_file -> wrote stats.py (376 bytes)
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[turn 6] raw: {"tool":"run_python","args":{"path":"stats.py"}}
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[turn 6] tool=run_python -> exit=0
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stdout:
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(5.0, 2.0)
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stderr:
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[turn 7] raw: {"tool":"done","args":{"summary":"Created stats.py with mean_std function; verified output (5.0, 2.0)."}}
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[turn 7] DONE: Created stats.py with mean_std function; verified output (5.0, 2.0).
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RESULT: solved=True (correct output) | turns=7 terminated=done called_done=True bad_calls=3
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========================================================================
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TASK t5_parse
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Create `parse.py` with a function `parse_kv(text)` that parses lines of the form 'key=value' (one per line, ignore blank lines) into a dict, with values converted to int when they are all digits. Include a test in the file: parse_kv('a=1\nb=hello\n\nc=42') must equal {'a':1,'b':'hello','c':42}. Run it, assert the test passes, then call done.
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[turn 1] raw: We need to output a tool call to write_file.{"tool": "write_file", "args": {"path": "parse.py", "content": "def parse_kv(text: str) -> dict:\n \"\"\"Parse lines of the form 'key=value' into a dict.
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[turn 1] tool=write_file -> wrote parse.py (804 bytes)
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[turn 2] raw: {"tool": "run_python", "args": {"path": "parse.py"}}
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[turn 2] tool=run_python -> exit=0
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stdout:
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All tests passed.
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stderr:
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[turn 3] raw: {"tool": "done", "args": {"summary": "Created parse.py with parse_kv function and test; all tests passed."}}
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[turn 3] DONE: Created parse.py with parse_kv function and test; all tests passed.
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RESULT: solved=True (graded pass) | turns=3 terminated=done called_done=True bad_calls=0
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========================================================================
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SUMMARY (machine readable):
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[
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{
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"task": "t1_fizzbuzz",
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"solved": true,
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"turns": 4,
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"terminated": "done",
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"called_done": true,
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"bad_calls": 1
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},
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{
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"task": "t2_fix_bug",
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"solved": true,
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"turns": 5,
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"terminated": "done",
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"called_done": true,
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"bad_calls": 0
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},
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{
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"task": "t3_pipeline",
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"solved": true,
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"turns": 5,
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"terminated": "done",
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"called_done": true,
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"bad_calls": 0
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},
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{
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"task": "t4_debug_loop",
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"solved": true,
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"turns": 7,
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"terminated": "done",
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"called_done": true,
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"bad_calls": 3
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},
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{
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"task": "t5_parse",
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"solved": true,
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"turns": 3,
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"terminated": "done",
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"called_done": true,
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"bad_calls": 0
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}
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]
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SOLVED: 5/5 | CLEAN_TERMINATIONS: 5/5 | TOTAL_TIME: 78s
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=== RUN COMPLETE ===
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