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Merge pull request #17 from lenianiva/experiments/minif2f 

experiment: MiniF2F
This commit is contained in:
Leni Aniva 2024-10-05 22:35:35 -07:00 committed by GitHub
parent 009ae08894 159da09c9d
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14 changed files with 254 additions and 76 deletions
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1
experiments/minif2f/.gitignore vendored Normal file
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@ -0,0 +1 @@
/output*

3
experiments/minif2f/MiniF2F/.gitignore vendored Normal file
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@ -0,0 +1,3 @@
/build
/lakefile.olean
/lake-packages/*

2
experiments/minif2f/MiniF2F/MiniF2F.lean Normal file
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@ -0,0 +1,2 @@
import Aesop
import Mathlib

75
experiments/minif2f/MiniF2F/lake-manifest.json Normal file
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@ -0,0 +1,75 @@
{"version": "1.1.0",
"packagesDir": ".lake/packages",
"packages":
[{"url": "https://github.com/leanprover-community/batteries",
"type": "git",
"subDir": null,
"scope": "",
"rev": "2ead90d24b4fac3a05c9c4294daa39bd8686fb98",
"name": "batteries",
"manifestFile": "lake-manifest.json",
"inputRev": "main",
"inherited": true,
"configFile": "lakefile.lean"},
{"url": "https://github.com/leanprover-community/aesop.git",
"type": "git",
"subDir": null,
"scope": "",
"rev": "a64fe24aa94e21404940e9217363a9a1ed9a33a6",
"name": "aesop",
"manifestFile": "lake-manifest.json",
"inputRev": "v4.10.0-rc1",
"inherited": false,
"configFile": "lakefile.toml"},
{"url": "https://github.com/leanprover-community/quote4",
"type": "git",
"subDir": null,
"scope": "leanprover-community",
"rev": "a7bfa63f5dddbcab2d4e0569c4cac74b2585e2c6",
"name": "Qq",
"manifestFile": "lake-manifest.json",
"inputRev": "master",
"inherited": true,
"configFile": "lakefile.lean"},
{"url": "https://github.com/leanprover-community/ProofWidgets4",
"type": "git",
"subDir": null,
"scope": "leanprover-community",
"rev": "d1b33202c3a29a079f292de65ea438648123b635",
"name": "proofwidgets",
"manifestFile": "lake-manifest.json",
"inputRev": "v0.0.39",
"inherited": true,
"configFile": "lakefile.lean"},
{"url": "https://github.com/leanprover/lean4-cli",
"type": "git",
"subDir": null,
"scope": "",
"rev": "a11566029bd9ec4f68a65394e8c3ff1af74c1a29",
"name": "Cli",
"manifestFile": "lake-manifest.json",
"inputRev": "main",
"inherited": true,
"configFile": "lakefile.lean"},
{"url": "https://github.com/leanprover-community/import-graph",
"type": "git",
"subDir": null,
"scope": "leanprover-community",
"rev": "d366a602cc4a325a6f9db3a3991dfa6d6cf409c5",
"name": "importGraph",
"manifestFile": "lake-manifest.json",
"inputRev": "main",
"inherited": true,
"configFile": "lakefile.toml"},
{"url": "https://github.com/leanprover-community/mathlib4.git",
"type": "git",
"subDir": null,
"scope": "",
"rev": "f5c3f06aa7f6d6c221786d2890c345a00e6341f8",
"name": "mathlib",
"manifestFile": "lake-manifest.json",
"inputRev": "v4.10.0-rc1",
"inherited": false,
"configFile": "lakefile.lean"}],
"name": "MiniF2F",
"lakeDir": ".lake"}

12
experiments/minif2f/MiniF2F/lakefile.lean Normal file
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@ -0,0 +1,12 @@
import Lake
open Lake DSL
require aesop from git
"https://github.com/leanprover-community/aesop.git" @ "v4.10.0-rc1"
require mathlib from git
"https://github.com/leanprover-community/mathlib4.git" @ "v4.10.0-rc1"
package MiniF2F
@[default_target]
lean_lib MiniF2F

1
experiments/minif2f/MiniF2F/lean-toolchain Symbolic link
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@ -0,0 +1 @@
../../../src/lean-toolchain

16
experiments/minif2f/README.md
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@ -1,7 +1,19 @@
# MiniF2F
This is an experiment on running a LLM prover on miniF2F data. Run with
This is an experiment on running a LLM prover on miniF2F data. Build the project
`MiniF2F` with `lake build`, and run with
```sh
python3 experiments/minif2f/main.py [--dry-run]
python3 experiments/minif2f/main.py [--dry-run] [--use-llm]
```
Read the help message carefully.
## Developing
Run unit tests with
``` sh
python3 -m model.{llm_agent,gen_tactic}
```

62
experiments/minif2f/main.py
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@ -3,33 +3,40 @@
import subprocess, json, argparse
from typing import Optional
from pathlib import Path
from pantograph.server import Server, ServerError
from termcolor import colored
from pantograph.server import Server, ServerError, DEFAULT_CORE_OPTIONS
from pantograph.search import SearchResult
from pantograph.search_llm import LLMAgent
from model.llm_agent import LLMAgent
from model.options import CORE_OPTIONS
PATH_EXPERIMENT = Path(__file__).parent.resolve()
def get_project_and_lean_path():
cwd = Path(__file__).parent.resolve() / 'Example'
cwd = PATH_EXPERIMENT / 'MiniF2F'
p = subprocess.check_output(['lake', 'env', 'printenv', 'LEAN_PATH'], cwd=cwd)
return cwd, p
def read_test_data(use_valid: bool):
jsonl_path = Path(__file__).parent / ('valid.jsonl' if use_valid else 'test.jsonl')
jsonl_path = PATH_EXPERIMENT / ('valid.jsonl' if use_valid else 'test.jsonl')
with open(jsonl_path, 'r') as f:
return [json.loads(l) for l in list(f)]
def try_test_data(server, agent, entry: dict, max_steps: int, max_trials_per_goal: int) -> Optional[SearchResult]:
command = entry["formal_statement"]
print(command)
informal_stmt = entry["informal_stmt"]
informal_proof = entry["informal_proof"]
agent.informal_stmt = entry["informal_stmt"]
agent.informal_proof = entry["informal_proof"]
goal_state, = server.load_sorry(command)
goal_states = server.load_sorry(command)
if len(goal_states) == 0:
return None
goal_state, = goal_states
try:
return agent.search(
server=server,
goal_state=goal_state,
informal_stmt=informal_stmt,
informal_proof=informal_proof,
verbose=True,
max_steps=max_steps,
max_trials_per_goal=max_trials_per_goal
@ -44,7 +51,7 @@ def output_file_name(datum, use_hammer: bool, use_llm: bool):
folder += '-hammer'
if use_llm:
folder += '-llm'
folder = Path(__file__).parent / folder
folder = PATH_EXPERIMENT / folder
folder.mkdir(exist_ok=True, parents=True)
return folder / f"{name}.json"
@ -63,11 +70,30 @@ def run_eval(args):
file_name = output_file_name(datum, args.use_hammer, args.use_llm)
placeholder_file_name = file_name.with_suffix('.placeholder')
if file_name.is_file():
print(f"Skipping {datum['id']}")
print(colored(f"Skipping {datum['id']}", "green"))
continue
server = Server(imports=["Example"], project_path=project_path, lean_path=lean_path, options=["maxHeartbeats=0"])
agent = LLMAgent(server, use_hammer=args.use_hammer, use_llm=args.use_llm)
result = try_test_data(server, agent, datum, max_steps=args.max_steps, max_trials_per_goal=args.max_trials_per_goal)
print(colored(f"Evaluating on {datum['id']} ...", "blue"))
server = Server(
imports=["Mathlib", "Aesop"],
project_path=project_path,
lean_path=lean_path,
core_options=CORE_OPTIONS,
)
agent = LLMAgent(
server,
use_hammer=args.use_hammer,
use_llm=args.use_llm,
feedback_turns=args.feedback_turns,
)
result = try_test_data(
server,
agent,
datum,
max_steps=args.max_steps,
max_trials_per_goal=args.max_trials_per_goal,
)
print(colored(f"Result on {datum['id']}: {result}", "blue"))
#server.gc()
if result is None:
with open(placeholder_file_name, 'w') as f:
json.dump({ 'id': datum['id'] }, f)
@ -80,7 +106,8 @@ def run_eval(args):
if __name__ == '__main__':
parser = argparse.ArgumentParser(
prog='MiniF2F Search',
description='Executes LLM on MiniF2F Search')
description='Executes LLM on MiniF2F Search',
)
parser.add_argument('--use-hammer', action='store_true')
parser.add_argument(
'--dry-run',
@ -88,8 +115,9 @@ if __name__ == '__main__':
help="List the data used, but don't run")
parser.add_argument('--validation', action='store_true')
parser.add_argument('--use-llm', action='store_true')
parser.add_argument('-s', '--max-steps', default=50)
parser.add_argument('-t', '--max-trials-per-goal', default=2)
parser.add_argument('--max-steps', default=50)
parser.add_argument('--max-trials-per-goal', default=2)
parser.add_argument('--feedback-turns', default=2)
args = parser.parse_args()
if args.dry_run:

0
experiments/minif2f/model/__init__.py Normal file
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49
pantograph/gen_tactic.py → experiments/minif2f/model/gen_tactic.py
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@ -1,7 +1,12 @@
"""
Tactic generation functions for the LLM agent
"""
from pantograph.server import Server, ServerError, TacticFailure
from pantograph.expr import Variable, Goal, TacticCalc
import unittest
import sglang as sgl
from termcolor import colored
import unittest
from .options import CORE_OPTIONS
LEAN4_INTRO = '''/-- A sequence `u` of real numbers converges to `l` if `∀ ε > 0, ∃ N, ∀ n ≥ N, |u_n - l| ≤ ε`.
This condition will be spelled `seq_limit u l`. -/
@ -78,6 +83,8 @@ example (n : Nat) (h : n = 0) (t : Tuple α n) : Tuple α 0 := by
exact t
'''
PREFIX_CURRENT_GOAL = "The current goal: "
@sgl.function
def multi_turn_question(s, question_1, question_2):
s += sgl.system("You are a helpful assistant.")
@ -88,34 +95,43 @@ def multi_turn_question(s, question_1, question_2):
@sgl.function
def select_tactic(s, server, state, goal_id,informal_stmt="", informal_proof="", feedback_turns = 5):
def select_tactic(
s, server, state, goal_id,
informal_stmt: str = "",
informal_proof: str = "",
feedback_turns: int = 5):
s += sgl.system("You are an expert in Lean. Choose the next ONE tactic to run given the current proof state and goals.")
s += sgl.user(LEAN4_REWRITE)
s += sgl.user("The current proof state: GoalState(state_id=0, goals=[Goal(variables=[], target='∀ (a b: Nat), (b = 2) -> 1 + a + 1 = a + b', name=None, is_conversion=False)])")
s += sgl.assistant("```intros a b h```")
s += sgl.user("The current proof state: GoalState(state_id=1, goals=[Goal(variables=[Variable(t='Nat', v=None, name='a'), Variable(t='Nat', v=None, name='b'), Variable(t='b = 2', v=None, name='h')], target='1 + a + 1 = a + b', name=None, is_conversion=False)])")
s += sgl.assistant('TacticCalc("1 + a + 1 = a + 1 + 1")')
#s += sgl.user("The current proof state: GoalState(state_id=0, goals=[Goal(variables=[], target='∀ (a b: Nat), (b = 2) -> 1 + a + 1 = a + b', name=None, is_conversion=False)])")
#s += sgl.assistant("```intros a b h```")
#s += sgl.user("The current proof state: GoalState(state_id=1, goals=[Goal(variables=[Variable(t='Nat', v=None, name='a'), Variable(t='Nat', v=None, name='b'), Variable(t='b = 2', v=None, name='h')], target='1 + a + 1 = a + b', name=None, is_conversion=False)])")
#s += sgl.assistant('TacticCalc("1 + a + 1 = a + 1 + 1")')
s += sgl.user(f"{PREFIX_CURRENT_GOAL}p : Prop\n⊢ ∀ (q: Prop), Or p q -> Or q p")
s += sgl.assistant('```\nintro q\n```')
s += sgl.user(f"{PREFIX_CURRENT_GOAL}a b c : Nat\n⊢ a + b + c = a + c + b")
s += sgl.assistant('```\nrw [Nat.add_assoc, Nat.add_comm b, ← Nat.add_assoc]\n```')
if informal_stmt and informal_proof:
s += sgl.user("informal theorem statement: "+ informal_stmt)
s += sgl.user("informal theorem statement: " + informal_stmt)
s += sgl.user("informal proof: " + informal_proof)
s += sgl.user("The current proof state: " + str(state) + "")
s += sgl.user(f"{PREFIX_CURRENT_GOAL}{state.goals[goal_id]}")
for i in range(feedback_turns):
with s.copy() as tmp:
tmp += sgl.assistant(sgl.gen("tactic", max_tokens=64))
# print("==tmp===")
# print(tmp["tactic"])
tactic = extract_code_from_llm_output(tmp["tactic"])
s += sgl.assistant("```"+tactic+"```")
tactic = postprocess_reply(extract_code_from_llm_output(tmp["tactic"]))
s += sgl.assistant(f"```\n{tactic}\n```")
success, new_state = apply_tactic(server, state, goal_id, tactic)
# print("===execute===")
# print(success, new_state )
if not success:
print(colored("[Tactic]", "red"), tactic)
with s.user():
s += "This answer got Lean compile error:\n" + str(new_state) + "\n"
s += f"This answer got a Lean compile error:\n{new_state}\n"
s += "Please try again by taking the Lean compiler feedback."
else:
print(colored("[Tactic]", "green"), tactic)
return tactic, new_state
return None, None
@ -143,13 +159,19 @@ def extract_code_from_llm_output(reply):
return reply
return reply
def postprocess_reply(reply):
reply = reply.strip()
if reply and reply[-1] == ",":
reply = reply[:-1]
return reply
class TestServerSGL(unittest.TestCase):
def test_conv_calc_sgl(self):
n_trails = 5
sgl.set_default_backend(sgl.OpenAI("gpt-4"))
server = Server()
server = Server(core_options=CORE_OPTIONS)
state0 = server.goal_start("∀ (a b: Nat), (b = 2) -> 1 + a + 1 = a + b")
print("==========state0============")
print(state0)
@ -236,4 +258,3 @@ class TestServerSGL(unittest.TestCase):
if __name__ == '__main__':
unittest.main()

29
pantograph/search_llm.py → experiments/minif2f/model/llm_agent.py
View File

@ -3,7 +3,8 @@ import collections, unittest
from pantograph.search import Agent
from pantograph.server import Server, TacticFailure, ServerError
from pantograph.expr import Expr, Tactic, GoalState
from pantograph.gen_tactic import LEAN4_REWRITE, select_tactic
from .gen_tactic import LEAN4_REWRITE, select_tactic
from .options import CORE_OPTIONS
import sglang as sgl
class LLMAgent(Agent):
@ -12,7 +13,9 @@ class LLMAgent(Agent):
"""
def __init__(self, server,
use_hammer=True, use_llm=True):
use_hammer=True,
use_llm=True,
feedback_turns=3):
super().__init__()
self.n_trials = 5
self.server = server
@ -24,6 +27,7 @@ class LLMAgent(Agent):
self.use_hammer = use_hammer
self.use_llm = use_llm
self.feedback_turns = feedback_turns
if use_hammer:
self.tactics = [
"aesop",
@ -34,7 +38,14 @@ class LLMAgent(Agent):
else:
self.tactics = []
def next_tactic(self, state: GoalState, goal_id: int, informal_stmt:str="", informal_proof:str="") -> Optional[Tactic]:
self.informal_stmt = ""
self.informal_proof = ""
def next_tactic(
self,
state: GoalState,
goal_id: int,
) -> Optional[Tactic]:
key = (state.state_id, goal_id)
i = self.goal_tactic_id_map[key]
@ -46,7 +57,13 @@ class LLMAgent(Agent):
new_state = None
for ii in range(self.n_trials):
print(f"===============trail {str(ii)}============")
s = select_tactic.run(server = self.server, state=state, goal_id = goal_id, informal_stmt=informal_stmt, informal_proof=informal_proof)
s = select_tactic.run(
server=self.server,
state=state,
goal_id=goal_id,
informal_stmt=self.informal_stmt,
informal_proof=self.informal_proof,
feedback_turns=self.feedback_turns)
tactic, new_state = s.ret_value
for m in s.messages():
print(m["role"], ":", m["content"])
@ -78,7 +95,7 @@ class TestSearch(unittest.TestCase):
def test_solve(self):
server = Server()
server = Server(core_options=CORE_OPTIONS)
agent = LLMAgent(server, use_hammer=False)
goal_state = server.goal_start("∀ (p q: Prop), p -> p")
flag = agent.search(server=server, goal_state=goal_state, verbose=True)
@ -86,7 +103,7 @@ class TestSearch(unittest.TestCase):
self.assertTrue(flag)
def test_solve_big(self):
server = Server()
server = Server(core_options=CORE_OPTIONS)
agent = LLMAgent(server, use_hammer=False)
goal_state = server.goal_start("∀ (p q: Prop), Or p q -> Or q p")
flag = agent.search(server=server, goal_state=goal_state, verbose=True)

2
experiments/minif2f/model/options.py Normal file
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@ -0,0 +1,2 @@
from pantograph.server import DEFAULT_CORE_OPTIONS
CORE_OPTIONS = DEFAULT_CORE_OPTIONS + ["tactic.hygienic=false"]

56
poetry.lock generated
View File

@ -793,13 +793,13 @@ test = ["flaky", "ipyparallel", "pre-commit", "pytest (>=7.0)", "pytest-asyncio
[[package]]
name = "ipython"
version = "8.27.0"
version = "8.28.0"
description = "IPython: Productive Interactive Computing"
optional = false
python-versions = ">=3.10"
files = [
{file = "ipython-8.27.0-py3-none-any.whl", hash = "sha256:f68b3cb8bde357a5d7adc9598d57e22a45dfbea19eb6b98286fa3b288c9cd55c"},
{file = "ipython-8.27.0.tar.gz", hash = "sha256:0b99a2dc9f15fd68692e898e5568725c6d49c527d36a9fb5960ffbdeaa82ff7e"},
{file = "ipython-8.28.0-py3-none-any.whl", hash = "sha256:530ef1e7bb693724d3cdc37287c80b07ad9b25986c007a53aa1857272dac3f35"},
{file = "ipython-8.28.0.tar.gz", hash = "sha256:0d0d15ca1e01faeb868ef56bc7ee5a0de5bd66885735682e8a322ae289a13d1a"},
]
[package.dependencies]
@ -2047,25 +2047,29 @@ files = [
[[package]]
name = "pywin32"
version = "306"
version = "307"
description = "Python for Window Extensions"
optional = false
python-versions = "*"
files = [
{file = "pywin32-306-cp310-cp310-win32.whl", hash = "sha256:06d3420a5155ba65f0b72f2699b5bacf3109f36acbe8923765c22938a69dfc8d"},
{file = "pywin32-306-cp310-cp310-win_amd64.whl", hash = "sha256:84f4471dbca1887ea3803d8848a1616429ac94a4a8d05f4bc9c5dcfd42ca99c8"},
{file = "pywin32-306-cp311-cp311-win32.whl", hash = "sha256:e65028133d15b64d2ed8f06dd9fbc268352478d4f9289e69c190ecd6818b6407"},
{file = "pywin32-306-cp311-cp311-win_amd64.whl", hash = "sha256:a7639f51c184c0272e93f244eb24dafca9b1855707d94c192d4a0b4c01e1100e"},
{file = "pywin32-306-cp311-cp311-win_arm64.whl", hash = "sha256:70dba0c913d19f942a2db25217d9a1b726c278f483a919f1abfed79c9cf64d3a"},
{file = "pywin32-306-cp312-cp312-win32.whl", hash = "sha256:383229d515657f4e3ed1343da8be101000562bf514591ff383ae940cad65458b"},
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]
[[package]]
@ -2954,13 +2958,13 @@ test = ["pytest", "ruff"]
[[package]]
name = "tomli"
version = "2.0.1"
version = "2.0.2"
description = "A lil' TOML parser"
optional = false
python-versions = ">=3.7"
python-versions = ">=3.8"
files = [
{file = "tomli-2.0.1-py3-none-any.whl", hash = "sha256:939de3e7a6161af0c887ef91b7d41a53e7c5a1ca976325f429cb46ea9bc30ecc"},
{file = "tomli-2.0.1.tar.gz", hash = "sha256:de526c12914f0c550d15924c62d72abc48d6fe7364aa87328337a31007fe8a4f"},
{file = "tomli-2.0.2-py3-none-any.whl", hash = "sha256:2ebe24485c53d303f690b0ec092806a085f07af5a5aa1464f3931eec36caaa38"},
{file = "tomli-2.0.2.tar.gz", hash = "sha256:d46d457a85337051c36524bc5349dd91b1877838e2979ac5ced3e710ed8a60ed"},
]
[[package]]
@ -3101,13 +3105,13 @@ tutorials = ["matplotlib", "pandas", "tabulate", "torch"]
[[package]]
name = "types-python-dateutil"
version = "2.9.0.20240906"
version = "2.9.0.20241003"
description = "Typing stubs for python-dateutil"
optional = false
python-versions = ">=3.8"
files = [
{file = "types-python-dateutil-2.9.0.20240906.tar.gz", hash = "sha256:9706c3b68284c25adffc47319ecc7947e5bb86b3773f843c73906fd598bc176e"},
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{file = "types-python-dateutil-2.9.0.20241003.tar.gz", hash = "sha256:58cb85449b2a56d6684e41aeefb4c4280631246a0da1a719bdbe6f3fb0317446"},
{file = "types_python_dateutil-2.9.0.20241003-py3-none-any.whl", hash = "sha256:250e1d8e80e7bbc3a6c99b907762711d1a1cdd00e978ad39cb5940f6f0a87f3d"},
]
[[package]]
@ -3250,4 +3254,4 @@ test = ["websockets"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "d992431714365397c4080f70aa7d146d7819976703bce96637f574856283d704"
content-hash = "b198bb707b86539e6c8edfe2b7377d47387aaaf053bb68b135ccd15361736030"

8
pyproject.toml
View File

@ -7,12 +7,8 @@ license = "GPL-3"
readme = "README.md"
[tool.poetry.dependencies]
# vllm = "0.4.1"
numpy = "^1.26.4"
pexpect = "^4.9.0"
python = "^3.10"
sglang = "^0.1.16"
torch = "2.2.1"
[tool.poetry.build]
generate-setup-file = false
@ -22,11 +18,15 @@ script = "build.py"
# Experiment related dependencies here to not clutter the main project dependencies.
fire = "0.6.0"
notebook = "^7.2.1"
numpy = "^1.26.4"
openai = "^1.31.0"
sglang = "^0.1.16"
tenacity = "8.3.0"
tiktoken = "^0.7.0"
torch = "2.2.1"
wandb = "0.17.0"
termcolor = "^2.4.0"
# vllm = "0.4.1"
[build-system]
requires = ["poetry-core"]