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from copy import deepcopy
from typing import Any, Dict
from aiflows.base_flows import SequentialFlow
from aiflows.utils import logging
logging.set_verbosity_debug()
log = logging.get_logger(__name__)
class InteractiveCodeGenFlow(SequentialFlow):
"""This flow writes code in an interactive manner. It is a sequential flow composed of:
1. MemoryReading: reads in the code library.
2. CodeGenerator: generates code based on the goal and functions in the code library.
3. CodeFileEditor: writes the generated code to a temp file for the user to see, edit and provide feedback.
4. ParseFeedback: opens up the temp file with vscode and parses the feedback from the user.
*Input Interface*:
- `goal`
*Output Interface*:
- `code`
- `feedback`
- `temp_code_file_location`
*Configuration Parameters*:
- `input_interface`: the input interface of the flow.
- `output_interface`: the output interface of the flow.
- `subflows_config`: the configuration of the subflows.
- `early_exit_key`: the key in the state dict that indicates whether the flow should exit early.
- `topology`: the topology of the subflows.
"""
REQUIRED_KEYS_CONFIG = ["max_rounds", "early_exit_key", "topology", "memory_files"]
def __init__(
self,
memory_files: Dict[str, Any],
**kwargs
):
"""
This function initializes the flow.
:param memory_files: the memory files that are used in the flow.
:type memory_files: Dict[str, Any]
:param kwargs: the keyword arguments.
:type kwargs: Any
"""
super().__init__(**kwargs)
self.memory_files = memory_files
@classmethod
def instantiate_from_config(cls, config):
"""
This function instantiates the flow from a configuration.
:param config: the configuration of the flow.
:type config: Dict[str, Any]
:return: the instantiated flow.
:rtype: Flow
"""
flow_config = deepcopy(config)
kwargs = {"flow_config": flow_config}
# ~~~ Set up memory file ~~~
memory_files = flow_config["memory_files"]
kwargs.update({"memory_files": memory_files})
# ~~~ Set up subflows ~~~
kwargs.update({"subflows": cls._set_up_subflows(flow_config)})
# ~~~ Instantiate flow ~~~
return cls(**kwargs)
def run(self, input_data: Dict[str, Any]) -> Dict[str, Any]:
"""
This function runs the flow.
:param input_data: the input data to the flow.
:type input_data: Dict[str, Any]
:return: the output data from the flow.
:rtype: Dict[str, Any]
"""
# ~~~ sets the input_data in the flow_state dict ~~~
self._state_update_dict(update_data=input_data)
# ~~~ set the memory file to the flow state ~~~
self._state_update_dict(update_data={"memory_files": self.memory_files})
max_rounds = self.flow_config.get("max_rounds", 1)
if max_rounds is None:
log.info(f"Running {self.flow_config['name']} without `max_rounds` until the early exit condition is met.")
self._sequential_run(max_rounds=max_rounds)
output = self._get_output_from_state()
return output
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