langchain/libs/community/langchain_community/utilities/outline.py

96 lines
3.3 KiB
Python
Raw Normal View History

community[major], core[patch], langchain[patch], experimental[patch]: Create langchain-community (#14463) 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
2023-12-11 21:53:30 +00:00
"""Util that calls Outline."""
import logging
from typing import Any, Dict, List, Optional
import requests
from langchain_core.documents import Document
from langchain_core.pydantic_v1 import BaseModel, root_validator
from langchain_core.utils import get_from_dict_or_env
logger = logging.getLogger(__name__)
OUTLINE_MAX_QUERY_LENGTH = 300
class OutlineAPIWrapper(BaseModel):
"""Wrapper around OutlineAPI.
This wrapper will use the Outline API to query the documents of your instance.
By default it will return the document content of the top-k results.
It limits the document content by doc_content_chars_max.
"""
top_k_results: int = 3
load_all_available_meta: bool = False
doc_content_chars_max: int = 4000
outline_instance_url: Optional[str] = None
outline_api_key: Optional[str] = None
outline_search_endpoint: str = "/api/documents.search"
@root_validator()
def validate_environment(cls, values: Dict) -> Dict:
"""Validate that instance url and api key exists in environment."""
outline_instance_url = get_from_dict_or_env(
values, "outline_instance_url", "OUTLINE_INSTANCE_URL"
)
values["outline_instance_url"] = outline_instance_url
outline_api_key = get_from_dict_or_env(
values, "outline_api_key", "OUTLINE_API_KEY"
)
values["outline_api_key"] = outline_api_key
return values
def _result_to_document(self, outline_res: Any) -> Document:
main_meta = {
"title": outline_res["document"]["title"],
"source": self.outline_instance_url + outline_res["document"]["url"],
}
add_meta = (
{
"id": outline_res["document"]["id"],
"ranking": outline_res["ranking"],
"collection_id": outline_res["document"]["collectionId"],
"parent_document_id": outline_res["document"]["parentDocumentId"],
"revision": outline_res["document"]["revision"],
"created_by": outline_res["document"]["createdBy"]["name"],
}
if self.load_all_available_meta
else {}
)
doc = Document(
page_content=outline_res["document"]["text"][: self.doc_content_chars_max],
metadata={
**main_meta,
**add_meta,
},
)
return doc
def _outline_api_query(self, query: str) -> List:
raw_result = requests.post(
f"{self.outline_instance_url}{self.outline_search_endpoint}",
data={"query": query, "limit": self.top_k_results},
headers={"Authorization": f"Bearer {self.outline_api_key}"},
)
if not raw_result.ok:
raise ValueError("Outline API returned an error: ", raw_result.text)
return raw_result.json()["data"]
def run(self, query: str) -> List[Document]:
"""
Run Outline search and get the document content plus the meta information.
Returns: a list of documents.
"""
results = self._outline_api_query(query[:OUTLINE_MAX_QUERY_LENGTH])
docs = []
for result in results[: self.top_k_results]:
if doc := self._result_to_document(result):
docs.append(doc)
return docs