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d430ac1
add retries and readme
swyxio Mar 30, 2025
23238b3
store my prompts
swyxio Mar 30, 2025
e67f79b
continuebutton
swyxio Mar 30, 2025
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2 changes: 2 additions & 0 deletions pokemon-example/.gitignore
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Original file line number Diff line number Diff line change
@@ -0,0 +1,2 @@
__pycache__
logs
205 changes: 106 additions & 99 deletions pokemon-example/eva.py
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Expand Up @@ -375,106 +375,120 @@ async def initialize_state(self, morph_instance: 'MorphInstance') -> Instance[S,
pass


async def run(task: VerifiedTask[S, A, R, T], agent: Agent[S, A, R, T], max_steps: int = 100,
verify_every_step: bool = False, ttl_seconds: Optional[int] = None) -> Tuple[VerificationResult[R], Trajectory[S, A, R, T]]:
async def initialize_run(task: VerifiedTask[S, A, R, T], agent: Agent[S, A, R, T], ttl_seconds: Optional[int] = None) -> Tuple[Instance[S, T], Trajectory[S, A, R, T], 'MorphInstance']:
"""
Run an agent on a task until the task is complete or max_steps is reached.
Initialize a run by creating the Morph instance and initial state.

Returns:
Tuple of (initial_state, trajectory, morph_instance)
Comment on lines -378 to +383
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@swyxio swyxio Mar 30, 2025

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specificaly break up run into initialize and continue steps

and dont eagerly stop instances

"""
log(LogLevel.INFO, f"Running agent for task",
extra={"task": task.instruction, "max_steps": max_steps, "verify_every_step": verify_every_step})

agent.set_objective(task.instruction)

# Start a Morph instance from the task's snapshot
log(LogLevel.INFO, f"Starting Morph instance",
extra={"snapshot_id": task.snapshot_id})
# Create a new Morph instance from the snapshot
log(LogLevel.INFO, "Creating MorphInstance", extra={"snapshot_id": task.snapshot_id})
morph_instance = MorphInstance(task.snapshot_id, task.metadata, ttl_seconds)
log(LogLevel.INFO, "Created MorphInstance")

# Initialize the state
log(LogLevel.INFO, "Initializing state with MorphInstance")
initial_state = await agent.initialize_state(morph_instance)
log(LogLevel.INFO, "Initialized state")

try:
# Initialize the agent's state and trajectory
initial_state = await agent.initialize_state(morph_instance)

# Set morph_instance reference
if hasattr(initial_state.state, '_morph_instance'):
object.__setattr__(initial_state.state, '_morph_instance', morph_instance)

if hasattr(agent, 'trajectory') and agent.trajectory is not None:
trajectory = agent.trajectory
else:
trajectory = Trajectory[S, A, R, T]()
agent.trajectory = trajectory
# Set up trajectory
if hasattr(agent, 'trajectory') and agent.trajectory is not None:
trajectory = agent.trajectory
else:
trajectory = Trajectory[S, A, R, T]()
agent.trajectory = trajectory

# Bind the agent to the instance
if hasattr(agent, 'bind_instance'):
agent.bind_instance(morph_instance)

# Initialize with the initial state
trajectory.add_step(initial_state)

return initial_state, trajectory, morph_instance


# Bind the agent to the instance
if hasattr(agent, 'bind_instance'):
agent.bind_instance(morph_instance)

# Initialize with the initial state
trajectory.add_step(initial_state)

current_state = trajectory.current_state
if current_state is None:
error_msg = "No initial state available"
log(LogLevel.ERROR, error_msg)
raise ValueError(error_msg)

for step_num in range(max_steps):
log(LogLevel.INFO, f"Starting step execution",
extra={"step_num": step_num+1, "max_steps": max_steps})

# Execute a step - now with await
log(LogLevel.INFO, "Determining next action...")
action = await agent.run_step(current_state)
log(LogLevel.INFO, f"Selected action", extra={"action": str(action)})

# Apply the action to get a new state - now with await
log(LogLevel.INFO, f"Applying action", extra={"action": str(action)})
new_state_value = await agent.apply_action(current_state.state, action)
new_state = current_state.__class__(new_state_value)

# Ensure morph_instance reference is preserved
if hasattr(new_state.state, '_morph_instance'):
object.__setattr__(new_state.state, '_morph_instance', morph_instance)

# Record the step
trajectory.add_step(new_state, action)

# Update current state
current_state = new_state
async def continue_run(task: VerifiedTask[S, A, R, T], agent: Agent[S, A, R, T],
trajectory: Trajectory[S, A, R, T], morph_instance: 'MorphInstance',
max_steps: int = 100, verify_every_step: bool = False) -> Tuple[VerificationResult[R], Trajectory[S, A, R, T]]:
"""
Continue execution for max_steps more steps from the current state.
"""
current_state = trajectory.current_state
if current_state is None:
error_msg = "No current state available"
log(LogLevel.ERROR, error_msg)
raise ValueError(error_msg)

start_step = len(trajectory.steps)
for step_num in range(max_steps):
log(LogLevel.INFO, f"Starting step execution",
extra={"step_num": start_step + step_num + 1})

# Execute a step
log(LogLevel.INFO, "Determining next action...")
action = await agent.run_step(current_state)
log(LogLevel.INFO, f"Selected action", extra={"action": str(action)})

# Apply the action to get a new state
log(LogLevel.INFO, f"Applying action", extra={"action": str(action)})
new_state_value = await agent.apply_action(current_state.state, action)
new_state = current_state.__class__(new_state_value)

# Ensure morph_instance reference is preserved
if hasattr(new_state.state, '_morph_instance'):
object.__setattr__(new_state.state, '_morph_instance', morph_instance)

# Record the step
trajectory.add_step(new_state, action)

# Update current state
current_state = new_state

# Check if we should verify
if verify_every_step or step_num == max_steps - 1:
log(LogLevel.INFO, "Verifying current state...")
result = task.verify(current_state, trajectory.actions)
trajectory.steps[-1].result = result

# Check if we should verify
if verify_every_step or step_num == max_steps - 1:
log(LogLevel.INFO, "Verifying current state...")
result = task.verify(current_state, trajectory.actions)
trajectory.steps[-1].result = result

if result.success:
log(LogLevel.SUCCESS, f"Task completed successfully",
extra={"steps_taken": step_num+1})
trajectory.summarize()
return result, trajectory

# If we reached max steps without success:
log(LogLevel.WARNING, f"Reached maximum steps without success",
extra={"max_steps": max_steps})

if trajectory.final_result is not None:
trajectory.summarize()
return trajectory.final_result, trajectory

result = VerificationResult(
value=None,
success=False,
message=f"Failed to complete task within {max_steps} steps",
details={"last_state": str(current_state.state)}
)
result.log()
if result.success:
log(LogLevel.SUCCESS, f"Task completed successfully",
extra={"steps_taken": start_step + step_num + 1})
trajectory.summarize()
return result, trajectory

# If we reached max steps without success:
log(LogLevel.WARNING, f"Reached maximum steps without success",
extra={"max_steps": max_steps})

if trajectory.final_result is not None:
trajectory.summarize()
return result, trajectory
return trajectory.final_result, trajectory

result = VerificationResult(
value=None,
success=False,
message=f"Failed to complete task within {max_steps} steps",
details={"last_state": str(current_state.state)}
)
result.log()
trajectory.summarize()
return result, trajectory

async def run(task: VerifiedTask[S, A, R, T], agent: Agent[S, A, R, T], max_steps: int = 100,
verify_every_step: bool = False, ttl_seconds: Optional[int] = None) -> Tuple[VerificationResult[R], Trajectory[S, A, R, T]]:
"""
Run an agent on a task until the task is complete or max_steps is reached.
"""
try:
initial_state, trajectory, morph_instance = await initialize_run(task, agent, ttl_seconds)
return await continue_run(task, agent, trajectory, morph_instance, max_steps, verify_every_step)

except Exception as e:
log(LogLevel.ERROR, f"Error in run: {str(e)}")
raise
finally:
# Always clean up the Morph instance
morph_instance.stop()
log(LogLevel.INFO, "Run completed")

async def run_step(task: VerifiedTask[S, A, R, T], agent: Agent[S, A, R, T],
trajectory: Trajectory[S, A, R, T], verify: bool = False) -> Tuple[Instance[S, T], Optional[VerificationResult[R]]]:
Expand Down Expand Up @@ -621,11 +635,4 @@ def stop(self) -> None:

def __del__(self) -> None:
"""Ensure the instance is stopped when this object is garbage collected."""
try:
if hasattr(self, 'instance') and self.instance:
self.stop()
except (AttributeError, Exception):
# Ignore errors during garbage collection
pass


pass
1 change: 1 addition & 0 deletions pokemon-example/instructions.md
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Expand Up @@ -6,6 +6,7 @@ uv pip install dotenv
uv pip install morphcloud
uv pip install pillow
uv pip install mcp
uv pip install fastapi

# if you do not have a snapshot
uv run setup_romwatch_server.py
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