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265 | class WatsonxRerank(BaseNodePostprocessor):
"""
IBM watsonx.ai Rerank.
Example:
`pip install llama-index-postprocessor-ibm`
```python
from llama_index.postprocessor.ibm import WatsonxRerank
watsonx_llm = WatsonxRerank(
model_id="<RERANK MODEL>",
url="https://us-south.ml.cloud.ibm.com",
apikey="*****",
project_id="*****",
)
```
"""
model_id: str = Field(description="Type of model to use.")
top_n: Optional[int] = Field(
default=None,
description="Number of top results to return.",
)
truncate_input_tokens: Optional[int] = Field(
default=None,
description="""Represents the maximum number of input tokens accepted.""",
)
project_id: Optional[str] = Field(
default=None,
description="ID of the Watson Studio project.",
frozen=True,
)
space_id: Optional[str] = Field(
default=None, description="ID of the Watson Studio space.", frozen=True
)
url: Optional[SecretStr] = Field(
default=None,
description="Url to Watson Machine Learning or CPD instance",
frozen=True,
)
apikey: Optional[SecretStr] = Field(
default=None,
description="Apikey to Watson Machine Learning or CPD instance",
frozen=True,
)
token: Optional[SecretStr] = Field(
default=None, description="Token to CPD instance", frozen=True
)
password: Optional[SecretStr] = Field(
default=None, description="Password to CPD instance", frozen=True
)
username: Optional[SecretStr] = Field(
default=None, description="Username to CPD instance", frozen=True
)
instance_id: Optional[SecretStr] = Field(
default=None, description="Instance_id of CPD instance", frozen=True
)
version: Optional[SecretStr] = Field(
default=None, description="Version of CPD instance", frozen=True
)
verify: Union[str, bool, None] = Field(
default=None,
description="""
User can pass as verify one of following:
the path to a CA_BUNDLE file
the path of directory with certificates of trusted CAs
True - default path to truststore will be taken
False - no verification will be made
""",
frozen=True,
)
_client: Optional[APIClient] = PrivateAttr()
_watsonx_rerank: Rerank = PrivateAttr()
def __init__(
self,
model_id: Optional[str] = None,
top_n: Optional[int] = None,
truncate_input_tokens: Optional[int] = None,
project_id: Optional[str] = None,
space_id: Optional[str] = None,
url: Optional[str] = None,
apikey: Optional[str] = None,
token: Optional[str] = None,
password: Optional[str] = None,
username: Optional[str] = None,
instance_id: Optional[str] = None,
version: Optional[str] = None,
verify: Union[str, bool, None] = None,
api_client: Optional[APIClient] = None,
callback_manager: Optional[CallbackManager] = None,
**kwargs: Any,
) -> None:
"""
Initialize watsonx.ai Rerank.
"""
callback_manager = callback_manager or CallbackManager([])
creds = (
resolve_watsonx_credentials(
url=url,
apikey=apikey,
token=token,
username=username,
password=password,
instance_id=instance_id,
)
if not isinstance(api_client, APIClient)
else {}
)
super().__init__(
model_id=model_id,
top_n=top_n,
truncate_input_tokens=truncate_input_tokens,
project_id=project_id,
space_id=space_id,
url=creds.get("url"),
apikey=creds.get("apikey"),
token=creds.get("token"),
password=creds.get("password"),
username=creds.get("username"),
instance_id=creds.get("instance_id"),
version=version,
verify=verify,
_client=api_client,
callback_manager=callback_manager,
**kwargs,
)
self._client = api_client
self._watsonx_rerank = Rerank(
model_id=model_id,
params=self.params,
credentials=(
Credentials.from_dict(
{
key: value.get_secret_value() if value else None
for key, value in self._get_credential_kwargs().items()
},
_verify=self.verify,
)
if creds
else None
),
project_id=self.project_id,
space_id=self.space_id,
verify=verify,
api_client=api_client,
)
@classmethod
def class_name(cls) -> str:
"""Get Class Name."""
return "WatsonxRerank"
def _get_credential_kwargs(self) -> Dict[str, SecretStr | None]:
return {
"url": self.url,
"apikey": self.apikey,
"token": self.token,
"password": self.password,
"username": self.username,
"instance_id": self.instance_id,
"version": self.version,
}
@property
def params(self) -> RerankParameters:
rerank_return_options: RerankReturnOptions = RerankReturnOptions(
top_n=self.top_n,
inputs=False,
query=False,
)
return RerankParameters(
truncate_input_tokens=self.truncate_input_tokens,
return_options=rerank_return_options,
)
def _postprocess_nodes(
self,
nodes: List[NodeWithScore],
query_bundle: Optional[QueryBundle] = None,
) -> List[NodeWithScore]:
dispatcher.event(
ReRankStartEvent(
query=query_bundle,
nodes=nodes,
top_n=self.top_n,
model_name=self.model_id,
)
)
if query_bundle is None:
raise ValueError("Query bundle must be provided.")
if len(nodes) == 0:
return []
texts = [
node.node.get_content(metadata_mode=MetadataMode.EMBED) for node in nodes
]
results = self._watsonx_rerank.generate(
query=query_bundle.query_str,
inputs=texts,
params=self.params,
)
new_nodes = []
for result in results.get("results", []):
new_node_with_score = NodeWithScore(
node=nodes[result["index"]].node,
score=result["score"],
)
new_nodes.append(new_node_with_score)
dispatcher.event(ReRankEndEvent(nodes=new_nodes))
return new_nodes
|
