search llm passed
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2d12e87126
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@ -1,4 +1,4 @@
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from pantograph.server import Server, ServerError
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from pantograph.server import Server, ServerError, TacticFailure
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from pantograph.expr import Variable, Goal, TacticCalc
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import unittest
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import sglang as sgl
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@ -105,19 +105,24 @@ def select_tactic(s, server, state, goal_id, feedback_turns = 5):
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tactic = extract_code_from_llm_output(tmp["tactic"])
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s += sgl.assistant("```"+tactic+"```")
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success, new_state = apply_tactic(server, state, goal_id, tactic)
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print("===execute===")
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print(success, new_state )
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if not success:
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with s.user():
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s += "This answer got Lean compile error:\n" + str(new_state) + "\n"
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s += "Please try again by taking the Lean compiler feedback."
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else:
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return new_state
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return tactic, new_state
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return None, None
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def apply_tactic(server, state, goal_id, tactic):
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try:
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new_state = server.goal_tactic(state, goal_id=goal_id, tactic=tactic)
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except ServerError as e:
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return False, e
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except TacticFailure as e:
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return False, e
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return True, new_state
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def extract_code_from_llm_output(reply):
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@ -1,5 +1,5 @@
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from dataclasses import dataclass
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from typing import override, Optional
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from typing import Optional
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import collections, unittest
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from pantograph.server import Server, TacticFailure
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@ -140,7 +140,6 @@ class DumbAgent(Agent):
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"assumption",
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]
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@override
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def next_tactic(self, state: GoalState, goal_id: int) -> Optional[Tactic]:
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key = (state.state_id, goal_id)
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i = self.goal_tactic_id_map[key]
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@ -1,17 +1,18 @@
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import search
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from dataclasses import dataclass
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from typing import override, Optional
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from typing import Optional
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import collections, unittest
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from pantograph.search import Agent
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from pantograph.server import Server, TacticFailure, ServerError
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from pantograph.expr import Expr, Tactic, GoalState
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from pantograph.gen_tactic import LEAN4_REWRITE, select_tactic
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import sglang as sgl
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class LLMAgent(search.Agent):
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class LLMAgent(Agent):
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def __init__(self):
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def __init__(self, server):
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super().__init__()
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self.n_trials = 5
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self.server = server
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sgl.set_default_backend(sgl.OpenAI("gpt-4"))
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self.goal_tactic_id_map = collections.defaultdict(lambda : 0)
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self.intros = [
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@ -27,7 +28,6 @@ class LLMAgent(search.Agent):
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"assumption",
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]
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@override
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def next_tactic(self, state: GoalState, goal_id: int) -> Optional[Tactic]:
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key = (state.state_id, goal_id)
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i = self.goal_tactic_id_map[key]
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@ -45,19 +45,44 @@ class LLMAgent(search.Agent):
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self.goal_tactic_id_map[key] = i + 1
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new_state = None
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for i in range(self.n_trails):
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print(f"===============trail {str(i)}============")
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for ii in range(self.n_trials):
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print(f"===============trail {str(ii)}============")
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try:
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state = select_tactic.run(self.server, state, goal_id = 1)
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state = select_tactic.run(server = self.server, state=state, goal_id = goal_id)
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tactic, new_state = state.ret_value
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for m in state.messages():
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print(m["role"], ":", m["content"])
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print("\n-- new state --\n", new_state)
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break
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if tactic:
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return tactic
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except ServerError as e:
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print(f"server error: {e}")
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continue
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except TacticFailure as e:
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print(f"tactic failure: {e}")
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continue
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return tactics[i]
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class TestSearch(unittest.TestCase):
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def test_solve(self):
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server = Server()
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agent = LLMAgent(server)
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flag = agent.search(server=server, target="∀ (p q: Prop), p -> p", verbose=True)
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#flag = agent.search(server=server, target="∀ (p q: Prop), Or p q -> Or q p", verbose=True)
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self.assertTrue(flag)
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def test_solve_big(self):
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server = Server()
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agent = LLMAgent(server)
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flag = agent.search(server=server, target="∀ (p q: Prop), Or p q -> Or q p", verbose=True)
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self.assertTrue(flag)
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if __name__ == '__main__':
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unittest.main()
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