mirror of
https://github.com/hwchase17/langchain
synced 2024-11-08 07:10:35 +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
75 lines
2.3 KiB
Python
75 lines
2.3 KiB
Python
from typing import List, Optional
|
|
|
|
import aiohttp
|
|
import requests
|
|
from langchain_core.callbacks import (
|
|
AsyncCallbackManagerForRetrieverRun,
|
|
CallbackManagerForRetrieverRun,
|
|
)
|
|
from langchain_core.documents import Document
|
|
from langchain_core.retrievers import BaseRetriever
|
|
|
|
|
|
class DataberryRetriever(BaseRetriever):
|
|
"""`Databerry API` retriever."""
|
|
|
|
datastore_url: str
|
|
top_k: Optional[int]
|
|
api_key: Optional[str]
|
|
|
|
def _get_relevant_documents(
|
|
self, query: str, *, run_manager: CallbackManagerForRetrieverRun
|
|
) -> List[Document]:
|
|
response = requests.post(
|
|
self.datastore_url,
|
|
json={
|
|
"query": query,
|
|
**({"topK": self.top_k} if self.top_k is not None else {}),
|
|
},
|
|
headers={
|
|
"Content-Type": "application/json",
|
|
**(
|
|
{"Authorization": f"Bearer {self.api_key}"}
|
|
if self.api_key is not None
|
|
else {}
|
|
),
|
|
},
|
|
)
|
|
data = response.json()
|
|
return [
|
|
Document(
|
|
page_content=r["text"],
|
|
metadata={"source": r["source"], "score": r["score"]},
|
|
)
|
|
for r in data["results"]
|
|
]
|
|
|
|
async def _aget_relevant_documents(
|
|
self, query: str, *, run_manager: AsyncCallbackManagerForRetrieverRun
|
|
) -> List[Document]:
|
|
async with aiohttp.ClientSession() as session:
|
|
async with session.request(
|
|
"POST",
|
|
self.datastore_url,
|
|
json={
|
|
"query": query,
|
|
**({"topK": self.top_k} if self.top_k is not None else {}),
|
|
},
|
|
headers={
|
|
"Content-Type": "application/json",
|
|
**(
|
|
{"Authorization": f"Bearer {self.api_key}"}
|
|
if self.api_key is not None
|
|
else {}
|
|
),
|
|
},
|
|
) as response:
|
|
data = await response.json()
|
|
return [
|
|
Document(
|
|
page_content=r["text"],
|
|
metadata={"source": r["source"], "score": r["score"]},
|
|
)
|
|
for r in data["results"]
|
|
]
|