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Added async support to PlanAndExecute Chain (#8239)

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- Description: Adds async support to the PlanAndExecute Chain

Maintainer responsibilities:
  - Async: @agola11

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
This commit is contained in:
Daniel Alexander Brenot 2023-07-26 18:16:07 -04:00 committed by GitHub
parent a3ac9b23eb
commit bf1357f584
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GPG Key ID: 4AEE18F83AFDEB23
2 changed files with 72 additions and 2 deletions
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37
libs/experimental/langchain_experimental/plan_and_execute/agent_executor.py
View File

@ -1,6 +1,9 @@
from typing import Any, Dict, List, Optional
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.callbacks.manager import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain.chains.base import Chain
from pydantic import Field
@ -58,3 +61,35 @@ class PlanAndExecute(Chain):
)
self.step_container.add_step(step, response)
return {self.output_key: self.step_container.get_final_response()}
async def _acall(
self,
inputs: Dict[str, Any],
run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
) -> Dict[str, Any]:
plan = await self.planner.aplan(
inputs,
callbacks=run_manager.get_child() if run_manager else None,
)
if run_manager:
await run_manager.on_text(str(plan), verbose=self.verbose)
for step in plan.steps:
_new_inputs = {
"previous_steps": self.step_container,
"current_step": step,
"objective": inputs[self.input_key],
}
new_inputs = {**_new_inputs, **inputs}
response = await self.executor.astep(
new_inputs,
callbacks=run_manager.get_child() if run_manager else None,
)
if run_manager:
await run_manager.on_text(
f"*****\n\nStep: {step.value}", verbose=self.verbose
)
await run_manager.on_text(
f"\n\nResponse: {response.response}", verbose=self.verbose
)
self.step_container.add_step(step, response)
return {self.output_key: self.step_container.get_final_response()}

37
libs/langchain/langchain/experimental/plan_and_execute/agent_executor.py
View File

@ -2,7 +2,10 @@ from typing import Any, Dict, List, Optional
from pydantic import Field
from langchain.callbacks.manager import CallbackManagerForChainRun
from langchain.callbacks.manager import (
AsyncCallbackManagerForChainRun,
CallbackManagerForChainRun,
)
from langchain.chains.base import Chain
from langchain.experimental.plan_and_execute.executors.base import BaseExecutor
from langchain.experimental.plan_and_execute.planners.base import BasePlanner
@ -63,3 +66,35 @@ class PlanAndExecute(Chain):
)
self.step_container.add_step(step, response)
return {self.output_key: self.step_container.get_final_response()}
async def _acall(
self,
inputs: Dict[str, Any],
run_manager: Optional[AsyncCallbackManagerForChainRun] = None,
) -> Dict[str, Any]:
plan = await self.planner.aplan(
inputs,
callbacks=run_manager.get_child() if run_manager else None,
)
if run_manager:
await run_manager.on_text(str(plan), verbose=self.verbose)
for step in plan.steps:
_new_inputs = {
"previous_steps": self.step_container,
"current_step": step,
"objective": inputs[self.input_key],
}
new_inputs = {**_new_inputs, **inputs}
response = await self.executor.astep(
new_inputs,
callbacks=run_manager.get_child() if run_manager else None,
)
if run_manager:
await run_manager.on_text(
f"*****\n\nStep: {step.value}", verbose=self.verbose
)
await run_manager.on_text(
f"\n\nResponse: {response.response}", verbose=self.verbose
)
self.step_container.add_step(step, response)
return {self.output_key: self.step_container.get_final_response()}