from __future__ import annotations
from copy import deepcopy
from typing import Any, Dict, List, Optional, Sequence, Union
from ibm_watsonx_ai import APIClient, Credentials # type: ignore
from ibm_watsonx_ai.foundation_models import Rerank # type: ignore
from ibm_watsonx_ai.foundation_models.schema import ( # type: ignore
RerankParameters,
)
from langchain_core.callbacks import Callbacks
from langchain_core.documents import BaseDocumentCompressor, Document
from langchain_core.utils.utils import secret_from_env
from pydantic import ConfigDict, Field, SecretStr, model_validator
from typing_extensions import Self
from langchain_ibm.utils import check_for_attribute, extract_params
[docs]
class WatsonxRerank(BaseDocumentCompressor):
"""Document compressor that uses `watsonx Rerank API`."""
model_id: str
"""Type of model to use."""
project_id: Optional[str] = None
"""ID of the Watson Studio project."""
space_id: Optional[str] = None
"""ID of the Watson Studio space."""
url: SecretStr = Field(
alias="url", default_factory=secret_from_env("WATSONX_URL", default=None)
)
"""URL to the Watson Machine Learning or CPD instance."""
apikey: Optional[SecretStr] = Field(
alias="apikey", default_factory=secret_from_env("WATSONX_APIKEY", default=None)
)
"""API key to the Watson Machine Learning or CPD instance."""
token: Optional[SecretStr] = Field(
alias="token", default_factory=secret_from_env("WATSONX_TOKEN", default=None)
)
"""Token to the CPD instance."""
password: Optional[SecretStr] = Field(
alias="password",
default_factory=secret_from_env("WATSONX_PASSWORD", default=None),
)
"""Password to the CPD instance."""
username: Optional[SecretStr] = Field(
alias="username",
default_factory=secret_from_env("WATSONX_USERNAME", default=None),
)
"""Username to the CPD instance."""
instance_id: Optional[SecretStr] = Field(
alias="instance_id",
default_factory=secret_from_env("WATSONX_INSTANCE_ID", default=None),
)
"""Instance_id of the CPD instance."""
version: Optional[SecretStr] = None
"""Version of the CPD instance."""
params: Optional[Union[dict, RerankParameters]] = None
"""Model parameters to use during request generation."""
verify: Union[str, bool, None] = None
"""You can pass one of following as verify:
* 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"""
validate_model: bool = True
"""Model ID validation."""
streaming: bool = False
""" Whether to stream the results or not. """
watsonx_rerank: Rerank = Field(default=None, exclude=True) #: :meta private:
watsonx_client: Optional[APIClient] = Field(default=None, exclude=True)
model_config = ConfigDict(
arbitrary_types_allowed=True,
extra="forbid",
protected_namespaces=(),
)
@property
def lc_secrets(self) -> Dict[str, str]:
"""A map of constructor argument names to secret ids.
For example:
{
"url": "WATSONX_URL",
"apikey": "WATSONX_APIKEY",
"token": "WATSONX_TOKEN",
"password": "WATSONX_PASSWORD",
"username": "WATSONX_USERNAME",
"instance_id": "WATSONX_INSTANCE_ID",
}
"""
return {
"url": "WATSONX_URL",
"apikey": "WATSONX_APIKEY",
"token": "WATSONX_TOKEN",
"password": "WATSONX_PASSWORD",
"username": "WATSONX_USERNAME",
"instance_id": "WATSONX_INSTANCE_ID",
}
@model_validator(mode="after")
def validate_environment(self) -> Self:
"""Validate that credentials and python package exists in environment."""
if isinstance(self.watsonx_client, APIClient):
watsonx_rerank = Rerank(
model_id=self.model_id,
params=self.params,
api_client=self.watsonx_client,
project_id=self.project_id,
space_id=self.space_id,
verify=self.verify,
)
self.watsonx_rerank = watsonx_rerank
else:
check_for_attribute(self.url, "url", "WATSONX_URL")
if "cloud.ibm.com" in self.url.get_secret_value():
check_for_attribute(self.apikey, "apikey", "WATSONX_APIKEY")
else:
if not self.token and not self.password and not self.apikey:
raise ValueError(
"Did not find 'token', 'password' or 'apikey',"
" please add an environment variable"
" `WATSONX_TOKEN`, 'WATSONX_PASSWORD' or 'WATSONX_APIKEY' "
"which contains it,"
" or pass 'token', 'password' or 'apikey'"
" as a named parameter."
)
elif self.token:
check_for_attribute(self.token, "token", "WATSONX_TOKEN")
elif self.password:
check_for_attribute(self.password, "password", "WATSONX_PASSWORD")
check_for_attribute(self.username, "username", "WATSONX_USERNAME")
elif self.apikey:
check_for_attribute(self.apikey, "apikey", "WATSONX_APIKEY")
check_for_attribute(self.username, "username", "WATSONX_USERNAME")
if not self.instance_id:
check_for_attribute(
self.instance_id, "instance_id", "WATSONX_INSTANCE_ID"
)
credentials = Credentials(
url=self.url.get_secret_value() if self.url else None,
api_key=self.apikey.get_secret_value() if self.apikey else None,
token=self.token.get_secret_value() if self.token else None,
password=self.password.get_secret_value() if self.password else None,
username=self.username.get_secret_value() if self.username else None,
instance_id=self.instance_id.get_secret_value()
if self.instance_id
else None,
version=self.version.get_secret_value() if self.version else None,
verify=self.verify,
)
watsonx_rerank = Rerank(
model_id=self.model_id,
credentials=credentials,
params=self.params,
project_id=self.project_id,
space_id=self.space_id,
verify=self.verify,
)
self.watsonx_rerank = watsonx_rerank
return self
[docs]
def rerank(
self,
documents: Sequence[Union[str, Document, dict]],
query: str,
**kwargs: Any,
) -> List[Dict[str, Any]]:
if len(documents) == 0: # to avoid empty api call
return []
docs = [
doc.page_content if isinstance(doc, Document) else doc for doc in documents
]
params = extract_params(kwargs, self.params)
results = self.watsonx_rerank.generate(
query=query, inputs=docs, **(kwargs | {"params": params})
)
result_dicts = []
for res in results["results"]:
result_dicts.append(
{"index": res.get("index"), "relevance_score": res.get("score")}
)
return result_dicts
[docs]
def compress_documents(
self,
documents: Sequence[Document],
query: str,
callbacks: Optional[Callbacks] = None,
**kwargs: Any,
) -> Sequence[Document]:
"""
Compress documents using watsonx's rerank API.
Args:
documents: A sequence of documents to compress.
query: The query to use for compressing the documents.
callbacks: Callbacks to run during the compression process.
Returns:
A sequence of compressed documents.
"""
compressed = []
for res in self.rerank(documents, query, **kwargs):
doc = documents[res["index"]]
doc_copy = Document(doc.page_content, metadata=deepcopy(doc.metadata))
doc_copy.metadata["relevance_score"] = res["relevance_score"]
compressed.append(doc_copy)
return compressed
