mirror of
https://github.com/hwchase17/langchain
synced 2024-11-16 06:13:16 +00:00
ed58eeb9c5
Moved the following modules to new package langchain-community in a backwards compatible fashion: ``` mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community mv langchain/langchain/adapters community/langchain_community mv langchain/langchain/callbacks community/langchain_community/callbacks mv langchain/langchain/chat_loaders community/langchain_community mv langchain/langchain/chat_models community/langchain_community mv langchain/langchain/document_loaders community/langchain_community mv langchain/langchain/docstore community/langchain_community mv langchain/langchain/document_transformers community/langchain_community mv langchain/langchain/embeddings community/langchain_community mv langchain/langchain/graphs community/langchain_community mv langchain/langchain/llms community/langchain_community mv langchain/langchain/memory/chat_message_histories community/langchain_community mv langchain/langchain/retrievers community/langchain_community mv langchain/langchain/storage community/langchain_community mv langchain/langchain/tools community/langchain_community mv langchain/langchain/utilities community/langchain_community mv langchain/langchain/vectorstores community/langchain_community mv langchain/langchain/agents/agent_toolkits community/langchain_community mv langchain/langchain/cache.py community/langchain_community ``` Moved the following to core ``` mv langchain/langchain/utils/json_schema.py core/langchain_core/utils mv langchain/langchain/utils/html.py core/langchain_core/utils mv langchain/langchain/utils/strings.py core/langchain_core/utils cat langchain/langchain/utils/env.py >> core/langchain_core/utils/env.py rm langchain/langchain/utils/env.py ``` See .scripts/community_split/script_integrations.sh for all changes
66 lines
2.2 KiB
Python
66 lines
2.2 KiB
Python
from typing import Iterator, List, Optional, Sequence
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from langchain_core.documents import Document
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from langchain_community.document_loaders.base import BaseLoader
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class FaunaLoader(BaseLoader):
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"""Load from `FaunaDB`.
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Attributes:
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query (str): The FQL query string to execute.
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page_content_field (str): The field that contains the content of each page.
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secret (str): The secret key for authenticating to FaunaDB.
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metadata_fields (Optional[Sequence[str]]):
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Optional list of field names to include in metadata.
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"""
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def __init__(
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self,
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query: str,
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page_content_field: str,
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secret: str,
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metadata_fields: Optional[Sequence[str]] = None,
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):
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self.query = query
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self.page_content_field = page_content_field
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self.secret = secret
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self.metadata_fields = metadata_fields
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def load(self) -> List[Document]:
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return list(self.lazy_load())
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def lazy_load(self) -> Iterator[Document]:
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try:
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from fauna import Page, fql
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from fauna.client import Client
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from fauna.encoding import QuerySuccess
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except ImportError:
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raise ImportError(
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"Could not import fauna python package. "
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"Please install it with `pip install fauna`."
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)
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# Create Fauna Client
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client = Client(secret=self.secret)
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# Run FQL Query
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response: QuerySuccess = client.query(fql(self.query))
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page: Page = response.data
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for result in page:
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if result is not None:
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document_dict = dict(result.items())
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page_content = ""
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for key, value in document_dict.items():
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if key == self.page_content_field:
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page_content = value
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document: Document = Document(
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page_content=page_content,
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metadata={"id": result.id, "ts": result.ts},
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)
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yield document
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if page.after is not None:
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yield Document(
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page_content="Next Page Exists",
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metadata={"after": page.after},
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)
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