feat(agent): Introduce Python code execution as prompt strategy #7142
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## master #7142 +/- ##
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+ Coverage 22.53% 24.08% +1.54%
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Files 66 67 +1
Lines 2702 2774 +72
Branches 307 312 +5
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+ Hits 609 668 +59
- Misses 2060 2070 +10
- Partials 33 36 +3
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Should this be in forge?? |
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majdyz
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May 15, 2024
| from .base import BaseAgent, BaseAgentActionProposal | ||
| from .prompt_strategies.one_shot import OneShotAgentActionProposal |
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OneShotAgentActionProposal is not part of .agent
majdyz
commented
May 15, 2024
| @@ -97,19 +103,20 @@ def __init__( | |||
| llm_provider: ChatModelProvider, | |||
| file_storage: FileStorage, | |||
| legacy_config: Config, | |||
| prompt_strategy_class: type[PromptStrategy] = CodeFlowAgentPromptStrategy, | |||
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decouple agent.py & OneShot. pass this class for custom prompt strategy
majdyz
commented
May 15, 2024
| if not parsed_response.python_code: | ||
| raise ValueError("python_code is empty") | ||
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| available_functions = { |
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This is for the generated code validation.
majdyz
commented
May 15, 2024
autogpts/autogpt/autogpt/app/cli.py
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| @@ -2,18 +2,21 @@ | |||
| from logging import _nameToLevel as logLevelMap | |||
| from pathlib import Path | |||
| from typing import Optional | |||
| from dotenv import load_dotenv | |||
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Ignore this, for debugging purpose, will revert
majdyz
commented
May 15, 2024
| logger = logging.getLogger(__name__) | ||
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| class CodeFlowExecutionComponent(CommandProvider): |
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So... BaseAgentActionProposal use use_tool which only executes a single tool, and it's already intertwined with the agent implementation. So my approach on having this code flow execution is by returning BaseAgentActionProposal that use this newly created tool, which is basically executing python code using already existing other tools as variables.
majdyz
commented
May 15, 2024
| @@ -158,6 +159,37 @@ def fmt_line(self) -> str: | |||
| ) | |||
| return f"{self.name}: {self.description}. Params: ({params})" | |||
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| def fmt_header(self, callable=None) -> str: | |||
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callable part here is unused, will revert
majdyz
commented
May 15, 2024
| @@ -443,6 +443,8 @@ async def create_chat_completion( | |||
| if not parse_errors: | |||
| try: | |||
| parsed_result = completion_parser(assistant_msg) | |||
| if isinstance(parsed_result, Coroutine): | |||
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So completion_parser needs to be async for the code validation, I did this instead of changing the whole usage of it to async.
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Background
Add support for executing agent steps by running Python code. This allows for more complicated composite function calls within each step of agent execution.
Changes ποΈ
PromptStrategy:CodeFlowAgentPromptStrategyundercode_flow.pyutils.functionpackage that handle a python code validation that utilizeruff&pyRightas the validation engines.CodeFlowAgentPromptStrategyas the existing default strategy.PR Quality Scorecard β¨
+2 pts+5 pts+5 pts+5 pts-4 pts+4 pts+5 pts-5 ptsagbenchmarkto verify that these changes do not regress performance? β+10 pts