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280 | class DashScopeCloudIndex(BaseManagedIndex):
"""DashScope Cloud Platform Index."""
def __init__(
self,
name: str,
nodes: Optional[List[BaseNode]] = None,
transformations: Optional[List[TransformComponent]] = None,
timeout: int = 60,
workspace_id: Optional[str] = None,
api_key: Optional[str] = None,
base_url: Optional[str] = DASHSCOPE_DEFAULT_BASE_URL,
show_progress: bool = False,
callback_manager: Optional[CallbackManager] = None,
**kwargs: Any,
) -> None:
"""Initialize the Platform Index."""
self.name = name
self.transformations = transformations or []
if nodes is not None:
raise ValueError(
"DashScopeCloudIndex does not support nodes on initialization"
)
self.workspace_id = workspace_id or os.environ.get("DASHSCOPE_WORKSPACE_ID")
self._api_key = api_key or os.environ.get("DASHSCOPE_API_KEY")
self._base_url = os.environ.get("DASHSCOPE_BASE_URL", None) or base_url
self._headers = {
"Content-Type": "application/json",
"Accept-Encoding": "utf-8",
"X-DashScope-WorkSpace": self.workspace_id,
"Authorization": "Bearer " + self._api_key,
"X-DashScope-OpenAPISource": "CloudSDK",
}
self._timeout = timeout
self._show_progress = show_progress
self._service_context = None
self._callback_manager = callback_manager or Settings.callback_manager
@classmethod
def from_documents( # type: ignore
cls: Type["DashScopeCloudIndex"],
documents: List[Document],
name: str,
transformations: Optional[List[TransformComponent]] = None,
workspace_id: Optional[str] = None,
api_key: Optional[str] = None,
base_url: Optional[str] = None,
timeout: int = 60,
verbose: bool = True,
**kwargs: Any,
) -> "DashScopeCloudIndex":
"""Build a DashScope index from a sequence of documents."""
pipeline_create = get_pipeline_create(
name, transformations or default_transformations(), documents
)
workspace_id = workspace_id or os.environ.get("DASHSCOPE_WORKSPACE_ID")
api_key = api_key or os.environ.get("DASHSCOPE_API_KEY")
base_url = (
base_url
or os.environ.get("DASHSCOPE_BASE_URL", None)
or DASHSCOPE_DEFAULT_BASE_URL
)
headers = {
"Content-Type": "application/json",
"Accept-Encoding": "utf-8",
"X-DashScope-WorkSpace": workspace_id,
"Authorization": "Bearer " + api_key,
"X-DashScope-OpenAPISource": "CloudSDK",
}
response = requests.put(
base_url + UPSERT_PIPELINE_ENDPOINT,
data=json.dumps(pipeline_create),
headers=headers,
)
response_text = response.json()
pipeline_id = response_text.get("id", None)
if response_text.get("code", "") != Status.SUCCESS.value or pipeline_id is None:
raise ValueError(
f"Failed to create index: {response_text.get('message', '')}\n{response_text}"
)
if verbose:
print(f"Starting creating index {name}, pipeline_id: {pipeline_id}")
response = requests.post(
base_url + START_PIPELINE_ENDPOINT.format(pipeline_id=pipeline_id),
headers=headers,
)
response_text = response.json()
ingestion_id = response_text.get("ingestionId", None)
if (
response_text.get("code", "") != Status.SUCCESS.value
or ingestion_id is None
):
raise ValueError(
f"Failed to start ingestion: {response_text.get('message', '')}\n{response_text}"
)
if verbose:
print(f"Starting ingestion for index {name}, ingestion_id: {ingestion_id}")
ingestion_status, failed_docs = run_ingestion(
base_url
+ CHECK_INGESTION_ENDPOINT.format(
pipeline_id=pipeline_id, ingestion_id=ingestion_id
),
headers,
verbose,
)
if verbose:
print(f"ingestion_status {ingestion_status}")
print(f"failed_docs: {failed_docs}")
if ingestion_status == "FAILED":
print("Index {name} created failed!")
return None
if verbose:
print(f"Index {name} created successfully!")
return cls(
name,
transformations=transformations,
workspace_id=workspace_id,
api_key=api_key,
base_url=base_url,
timeout=timeout,
**kwargs,
)
def as_retriever(self, **kwargs: Any) -> BaseRetriever:
"""Return a Retriever for this managed index."""
from llama_index.indices.managed.dashscope.retriever import (
DashScopeCloudRetriever,
)
return DashScopeCloudRetriever(
self.name,
**kwargs,
)
def as_query_engine(self, **kwargs: Any) -> BaseQueryEngine:
from llama_index.core.query_engine.retriever_query_engine import (
RetrieverQueryEngine,
)
kwargs["retriever"] = self.as_retriever(**kwargs)
return RetrieverQueryEngine.from_args(**kwargs)
def _insert(
self,
documents: List[Document],
transformations: Optional[List[TransformComponent]] = None,
verbose: bool = True,
**insert_kwargs: Any,
) -> None:
"""Insert a set of documents (each a node)."""
pipeline_id = get_pipeline_id(
self._base_url + PIPELINE_SIMPLE_ENDPOINT,
self._headers,
{"pipeline_name": self.name},
)
doc_insert = get_doc_insert(
transformations or default_transformations(),
documents,
)
response = requests.put(
self._base_url + INSERT_DOC_ENDPOINT.format(pipeline_id=pipeline_id),
data=json.dumps(doc_insert),
headers=self._headers,
)
response_text = response.json()
ingestion_id = response_text.get("ingestionId", None)
if (
response_text.get("code", "") != Status.SUCCESS.value
or ingestion_id is None
):
raise ValueError(
f"Failed to insert documents: {response_text.get('message', '')}\n{response_text}"
)
ingestion_status, failed_docs = run_ingestion(
self._base_url
+ CHECK_INGESTION_ENDPOINT.format(
pipeline_id=pipeline_id, ingestion_id=ingestion_id
),
self._headers,
verbose,
)
if verbose:
print(f"ingestion_status {ingestion_status}")
print(f"failed_docs: {failed_docs}")
def delete_ref_doc(
self,
ref_doc_ids: Union[str, List[str]],
verbose: bool = True,
**delete_kwargs: Any,
) -> None:
"""Delete documents in index."""
if isinstance(ref_doc_ids, str):
ref_doc_ids = [ref_doc_ids]
pipeline_id = get_pipeline_id(
self._base_url + PIPELINE_SIMPLE_ENDPOINT,
self._headers,
{"pipeline_name": self.name},
)
doc_delete = get_doc_delete(ref_doc_ids)
response = requests.post(
self._base_url + DELETE_DOC_ENDPOINT.format(pipeline_id=pipeline_id),
json=doc_delete,
headers=self._headers,
)
response_text = response.json()
if response_text.get("code", "") != Status.SUCCESS.value:
raise ValueError(
f"Failed to delete documents: {response_text.get('message', '')}\n{response_text}"
)
if verbose:
print(f"Delete documents {ref_doc_ids} successfully!")
def update_ref_doc(self, document: Document, **update_kwargs: Any) -> None:
"""Update a document and it's corresponding nodes."""
raise NotImplementedError("update_ref_doc not implemented.")
|
