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255 | class BedrockRerank(BaseNodePostprocessor):
top_n: int = Field(default=2, description="Top N nodes to return.")
rerank_model_name: str = Field(
default=Models.COHERE_RERANK_V3_5.value,
description="The modelId of the Bedrock model to use.",
)
rerank_model_arn: Optional[str] = Field(
default=None,
description="Optional custom model ARN to use.",
)
profile_name: Optional[str] = Field(
default=None,
description=(
"The name of AWS profile to use. "
"If not given, then the default profile is used."
),
)
aws_access_key_id: Optional[str] = Field(
default=None, description="AWS Access Key ID to use."
)
aws_secret_access_key: Optional[str] = Field(
default=None, description="AWS Secret Access Key to use."
)
aws_session_token: Optional[str] = Field(
default=None, description="AWS Session Token to use."
)
region_name: Optional[str] = Field(
default=None,
description=(
"AWS region name to use. Uses region configured in AWS CLI if not passed."
),
)
botocore_session: Optional[Any] = Field(
default=None,
description="Use this Botocore session instead of creating a new default one.",
exclude=True,
)
botocore_config: Optional[Any] = Field(
default=None,
description=(
"Custom configuration object to use instead of the default generated one."
),
exclude=True,
)
max_retries: int = Field(
default=10,
description="The maximum number of API retries.",
gt=0,
)
timeout: float = Field(
default=60.0,
description=(
"The timeout for the Bedrock API request in seconds. "
"It will be used for both connect and read timeouts."
),
)
additional_kwargs: Dict[str, Any] = Field(
default_factory=dict,
description="Additional kwargs for the Bedrock client.",
)
_client: Any = PrivateAttr()
_model_package_arn: str = PrivateAttr()
def __init__(
self,
top_n: int = 2,
rerank_model_name: str = Models.COHERE_RERANK_V3_5.value,
rerank_model_arn: Optional[str] = None,
profile_name: Optional[str] = None,
aws_access_key_id: Optional[str] = None,
aws_secret_access_key: Optional[str] = None,
aws_session_token: Optional[str] = None,
region_name: Optional[str] = None,
client: Optional[Any] = None,
botocore_session: Optional[Any] = None,
botocore_config: Optional[Any] = None,
additional_kwargs: Optional[Dict[str, Any]] = None,
max_retries: int = 10,
timeout: float = 60.0,
**kwargs: Any,
):
super().__init__(**kwargs)
self.top_n = top_n
self.rerank_model_name = rerank_model_name
self.rerank_model_arn = rerank_model_arn
self.profile_name = profile_name
self.aws_access_key_id = aws_access_key_id
self.aws_secret_access_key = aws_secret_access_key
self.aws_session_token = aws_session_token
self.region_name = region_name
self.botocore_session = botocore_session
self.botocore_config = botocore_config
self.max_retries = max_retries
self.timeout = timeout
self.additional_kwargs = additional_kwargs or {}
session_kwargs = {
"profile_name": self.profile_name,
"region_name": self.region_name,
"aws_access_key_id": self.aws_access_key_id,
"aws_secret_access_key": self.aws_secret_access_key,
"aws_session_token": self.aws_session_token,
"botocore_session": self.botocore_session,
}
try:
import boto3
from botocore.config import Config
config = (
Config(
retries={"max_attempts": self.max_retries, "mode": "standard"},
connect_timeout=self.timeout,
read_timeout=self.timeout,
)
if self.botocore_config is None
else self.botocore_config
)
session = boto3.Session(**session_kwargs)
except ImportError:
raise ImportError(
"The 'boto3' package was not found. Install it with 'pip install boto3'"
)
self.region_name = self.region_name or session.region_name
if client is not None:
self._client = client
else:
try:
self._client = session.client("bedrock-agent-runtime", config=config)
except Exception as e:
raise ValueError(f"Failed to create Bedrock Agent Runtime client: {e}")
if self.rerank_model_arn:
self._model_package_arn = self.rerank_model_arn
else:
self._model_package_arn = f"arn:aws:bedrock:{self.region_name}::foundation-model/{self.rerank_model_name}"
@classmethod
def class_name(cls) -> str:
return "AWSBedrockRerank"
def _postprocess_nodes(
self,
nodes: List[NodeWithScore],
query_bundle: Optional[QueryBundle] = None,
) -> List[NodeWithScore]:
if dispatcher:
dispatcher.event(
ReRankStartEvent(
query=query_bundle,
nodes=nodes,
top_n=self.top_n,
model_name=self.rerank_model_name,
)
)
if query_bundle is None:
raise ValueError("Missing query bundle in extra info.")
if len(nodes) == 0:
return []
with self.callback_manager.event(
CBEventType.RERANKING,
payload={
EventPayload.NODES: nodes,
EventPayload.MODEL_NAME: self.rerank_model_name,
EventPayload.QUERY_STR: query_bundle.query_str,
EventPayload.TOP_K: self.top_n,
},
) as event:
texts = [
node.node.get_content(metadata_mode=MetadataMode.EMBED)
for node in nodes
]
# Prepare the text sources for AWS Bedrock
text_sources = []
for text in texts:
text_sources.append(
{
"type": "INLINE",
"inlineDocumentSource": {
"type": "TEXT",
"textDocument": {"text": text},
},
}
)
# change top_n if the number of nodes is less than top_n
if len(nodes) < self.top_n:
self.top_n = len(nodes)
queries = [
{
"type": "TEXT",
"textQuery": {"text": query_bundle.query_str},
}
]
rerankingConfiguration = {
"type": "BEDROCK_RERANKING_MODEL",
"bedrockRerankingConfiguration": {
"numberOfResults": self.top_n,
"modelConfiguration": {
"modelArn": self._model_package_arn,
},
},
}
try:
response = self._client.rerank(
queries=queries,
sources=text_sources,
rerankingConfiguration=rerankingConfiguration,
)
results = response["results"]
except Exception as e:
raise RuntimeError(f"Failed to invoke AWS Bedrock model: {e}")
new_nodes = []
for result in results:
index = result["index"]
relevance_score = result.get("relevanceScore", 0.0)
new_node_with_score = NodeWithScore(
node=nodes[index].node,
score=relevance_score,
)
new_nodes.append(new_node_with_score)
event.on_end(payload={EventPayload.NODES: new_nodes})
dispatcher.event(ReRankEndEvent(nodes=new_nodes))
return new_nodes
|