Vectara RAG 包。
源代码位于 llama-index-packs/llama-index-packs-vectara-rag/llama_index/packs/vectara_rag/base.py
get_modules
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42 | class VectaraRagPack(BaseLlamaPack):
"""Vectara RAG pack."""
def __init__(
self,
nodes: Optional[List[TextNode]] = None,
similarity_top_k: int = 5,
**kwargs: Any,
):
self._index = VectaraIndex(nodes)
vectara_kwargs = kwargs.get("vectara_kwargs", {})
if "summary_enabled" not in vectara_kwargs:
vectara_kwargs["summary_enabled"] = True
self._query_engine = self._index.as_query_engine(
similarity_top_k=similarity_top_k,
**kwargs,
)
def get_modules(self) -> Dict[str, Any]:
"""Get modules."""
return {
"index": self._index,
"query_engine": self._query_engine,
}
def retrieve(self, query_str: str) -> Any:
"""Retrieve."""
return self._query_engine.retrieve(query_str)
def run(self, *args: Any, **kwargs: Any) -> Any:
"""Run the pipeline."""
return self._query_engine.query(*args, **kwargs)
|
获取模块。
get_modules() -> Dict[str, Any]
retrieve
get_modules
| def get_modules(self) -> Dict[str, Any]:
"""Get modules."""
return {
"index": self._index,
"query_engine": self._query_engine,
}
|
检索。
retrieve(query_str: str) -> Any
run
get_modules
| def retrieve(self, query_str: str) -> Any:
"""Retrieve."""
return self._query_engine.retrieve(query_str)
|
运行管道。
run(*args: Any, **kwargs: Any) -> Any
返回顶部
get_modules
| def run(self, *args: Any, **kwargs: Any) -> Any:
"""Run the pipeline."""
return self._query_engine.query(*args, **kwargs)
|
