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|
"""Base pipeline class for running a sequence of pipes."""
import asyncio
import logging
from enum import Enum
from typing import Any, AsyncGenerator, Optional
from ..logging.kv_logger import KVLoggingSingleton
from ..logging.run_manager import RunManager, manage_run
from ..pipes.base_pipe import AsyncPipe, AsyncState
logger = logging.getLogger(__name__)
class PipelineTypes(Enum):
EVAL = "eval"
INGESTION = "ingestion"
SEARCH = "search"
RAG = "rag"
OTHER = "other"
class AsyncPipeline:
"""Pipeline class for running a sequence of pipes."""
pipeline_type: str = "other"
def __init__(
self,
pipe_logger: Optional[KVLoggingSingleton] = None,
run_manager: Optional[RunManager] = None,
):
self.pipes: list[AsyncPipe] = []
self.upstream_outputs: list[list[dict[str, str]]] = []
self.pipe_logger = pipe_logger or KVLoggingSingleton()
self.run_manager = run_manager or RunManager(self.pipe_logger)
self.futures = {}
self.level = 0
def add_pipe(
self,
pipe: AsyncPipe,
add_upstream_outputs: Optional[list[dict[str, str]]] = None,
*args,
**kwargs,
) -> None:
"""Add a pipe to the pipeline."""
self.pipes.append(pipe)
if not add_upstream_outputs:
add_upstream_outputs = []
self.upstream_outputs.append(add_upstream_outputs)
async def run(
self,
input: Any,
state: Optional[AsyncState] = None,
stream: bool = False,
run_manager: Optional[RunManager] = None,
log_run_info: bool = True,
*args: Any,
**kwargs: Any,
):
"""Run the pipeline."""
run_manager = run_manager or self.run_manager
try:
PipelineTypes(self.pipeline_type)
except ValueError:
raise ValueError(
f"Invalid pipeline type: {self.pipeline_type}, must be one of {PipelineTypes.__members__.keys()}"
)
self.state = state or AsyncState()
current_input = input
async with manage_run(run_manager, self.pipeline_type):
if log_run_info:
await run_manager.log_run_info(
key="pipeline_type",
value=self.pipeline_type,
is_info_log=True,
)
try:
for pipe_num in range(len(self.pipes)):
config_name = self.pipes[pipe_num].config.name
self.futures[config_name] = asyncio.Future()
current_input = self._run_pipe(
pipe_num,
current_input,
run_manager,
*args,
**kwargs,
)
self.futures[config_name].set_result(current_input)
if not stream:
final_result = await self._consume_all(current_input)
return final_result
else:
return current_input
except Exception as error:
logger.error(f"Pipeline failed with error: {error}")
raise error
async def _consume_all(self, gen: AsyncGenerator) -> list[Any]:
result = []
async for item in gen:
if hasattr(
item, "__aiter__"
): # Check if the item is an async generator
sub_result = await self._consume_all(item)
result.extend(sub_result)
else:
result.append(item)
return result
async def _run_pipe(
self,
pipe_num: int,
input: Any,
run_manager: RunManager,
*args: Any,
**kwargs: Any,
):
# Collect inputs, waiting for the necessary futures
pipe = self.pipes[pipe_num]
add_upstream_outputs = self.sort_upstream_outputs(
self.upstream_outputs[pipe_num]
)
input_dict = {"message": input}
# Group upstream outputs by prev_pipe_name
grouped_upstream_outputs = {}
for upstream_input in add_upstream_outputs:
upstream_pipe_name = upstream_input["prev_pipe_name"]
if upstream_pipe_name not in grouped_upstream_outputs:
grouped_upstream_outputs[upstream_pipe_name] = []
grouped_upstream_outputs[upstream_pipe_name].append(upstream_input)
for (
upstream_pipe_name,
upstream_inputs,
) in grouped_upstream_outputs.items():
async def resolve_future_output(future):
result = future.result()
# consume the async generator
return [item async for item in result]
async def replay_items_as_async_gen(items):
for item in items:
yield item
temp_results = await resolve_future_output(
self.futures[upstream_pipe_name]
)
if upstream_pipe_name == self.pipes[pipe_num - 1].config.name:
input_dict["message"] = replay_items_as_async_gen(temp_results)
for upstream_input in upstream_inputs:
outputs = await self.state.get(upstream_pipe_name, "output")
prev_output_field = upstream_input.get(
"prev_output_field", None
)
if not prev_output_field:
raise ValueError(
"`prev_output_field` must be specified in the upstream_input"
)
input_dict[upstream_input["input_field"]] = outputs[
prev_output_field
]
# Handle the pipe generator
async for ele in await pipe.run(
pipe.Input(**input_dict),
self.state,
run_manager,
*args,
**kwargs,
):
yield ele
def sort_upstream_outputs(
self, add_upstream_outputs: list[dict[str, str]]
) -> list[dict[str, str]]:
pipe_name_to_index = {
pipe.config.name: index for index, pipe in enumerate(self.pipes)
}
def get_pipe_index(upstream_output):
return pipe_name_to_index[upstream_output["prev_pipe_name"]]
sorted_outputs = sorted(
add_upstream_outputs, key=get_pipe_index, reverse=True
)
return sorted_outputs
class EvalPipeline(AsyncPipeline):
"""A pipeline for evaluation."""
pipeline_type: str = "eval"
async def run(
self,
input: Any,
state: Optional[AsyncState] = None,
stream: bool = False,
run_manager: Optional[RunManager] = None,
*args: Any,
**kwargs: Any,
):
return await super().run(
input, state, stream, run_manager, *args, **kwargs
)
def add_pipe(
self,
pipe: AsyncPipe,
add_upstream_outputs: Optional[list[dict[str, str]]] = None,
*args,
**kwargs,
) -> None:
logger.debug(f"Adding pipe {pipe.config.name} to the EvalPipeline")
return super().add_pipe(pipe, add_upstream_outputs, *args, **kwargs)
async def dequeue_requests(queue: asyncio.Queue) -> AsyncGenerator:
"""Create an async generator to dequeue requests."""
while True:
request = await queue.get()
if request is None:
break
yield request
|
