phoenix-oss/llama-stack-mirror
0
0
Fork 1
mirror of https://github.com/meta-llama/llama-stack.git synced 2026-01-02 21:24:31 +00:00
Code Issues Projects Releases Packages Wiki Activity Actions

Added output type to PreprocessorResponse.

Browse source
This commit is contained in:
ilya-kolchinsky 2025-03-06 14:05:05 +01:00
parent b981181b25
commit 4c81a72214
7 changed files with 33 additions and 25 deletions
Download patch file Download diff file Expand all files Collapse all files

24
llama_stack/distribution/utils/chain.py
View file

@ -9,7 +9,6 @@ from typing import List
from llama_stack.apis.preprocessing import (
Preprocessing,
PreprocessingDataType,
PreprocessorChain,
PreprocessorInput,
PreprocessorResponse,
@ -18,17 +17,11 @@ from llama_stack.apis.preprocessing import (
log = logging.getLogger(__name__)
def validate_chain(chain_impls: List[Preprocessing], is_rag_chain: bool) -> bool:
def validate_chain(chain_impls: List[Preprocessing]) -> bool:
if len(chain_impls) == 0:
log.error("Empty preprocessing chain was provided")
return False
if is_rag_chain and PreprocessingDataType.chunks not in chain_impls[-1].output_types:
log.error(
f"RAG preprocessing chain must end with a chunk-producing preprocessor, but the last preprocessor in the provided chain only supports {chain_impls[-1].output_types}"
)
return False
for current_preprocessor, next_preprocessor in pairwise(chain_impls):
current_output_types = current_preprocessor.output_types
next_input_types = next_preprocessor.input_types
@ -46,13 +39,13 @@ async def execute_preprocessor_chain(
preprocessor_chain: PreprocessorChain,
preprocessor_chain_impls: List[Preprocessing],
preprocessor_inputs: List[PreprocessorInput],
is_rag_chain: bool,
) -> PreprocessorResponse:
if not validate_chain(preprocessor_chain_impls, is_rag_chain):
return PreprocessorResponse(status=False, results=[])
if not validate_chain(preprocessor_chain_impls):
return PreprocessorResponse(success=False, results=[])
current_inputs = preprocessor_inputs
current_outputs = []
current_result_type = None
# TODO: replace with a parallel implementation
for i, current_params in enumerate(preprocessor_chain):
@ -62,10 +55,13 @@ async def execute_preprocessor_chain(
preprocessor_inputs=current_inputs,
options=current_params.options,
)
if not response.status:
if not response.success:
log.error(f"Preprocessor {current_params.preprocessor_id} returned an error")
return PreprocessorResponse(status=False, results=[])
return PreprocessorResponse(
success=False, preprocessor_output_type=response.preprocessor_output_type, results=[]
)
current_outputs = response.results
current_inputs = current_outputs
current_result_type = response.preprocessor_output_type
return PreprocessorResponse(status=True, results=current_outputs)
return PreprocessorResponse(success=True, preprocessor_output_type=current_result_type, results=current_outputs)