Files
deer-flow/src/rag/ragflow.py
Xun 0e64c52975 refactor: Refactors the retriever function to use async/await (#821)
* refactor: Refactors the retriever function to use async/await
2026-01-20 19:56:26 +08:00

156 lines
4.7 KiB
Python

# Copyright (c) 2025 Bytedance Ltd. and/or its affiliates
# SPDX-License-Identifier: MIT
import asyncio
import os
from typing import List, Optional
from urllib.parse import urlparse
import requests
from src.rag.retriever import Chunk, Document, Resource, Retriever
class RAGFlowProvider(Retriever):
"""
RAGFlowProvider is a provider that uses RAGFlow to retrieve documents.
"""
api_url: str
api_key: str
page_size: int = 10
cross_languages: Optional[List[str]] = None
def __init__(self):
api_url = os.getenv("RAGFLOW_API_URL")
if not api_url:
raise ValueError("RAGFLOW_API_URL is not set")
self.api_url = api_url
api_key = os.getenv("RAGFLOW_API_KEY")
if not api_key:
raise ValueError("RAGFLOW_API_KEY is not set")
self.api_key = api_key
page_size = os.getenv("RAGFLOW_PAGE_SIZE")
if page_size:
self.page_size = int(page_size)
self.cross_languages = None
cross_languages = os.getenv("RAGFLOW_CROSS_LANGUAGES")
if cross_languages:
self.cross_languages = cross_languages.split(",")
def query_relevant_documents(
self, query: str, resources: list[Resource] = []
) -> list[Document]:
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
}
dataset_ids: list[str] = []
document_ids: list[str] = []
for resource in resources:
dataset_id, document_id = parse_uri(resource.uri)
dataset_ids.append(dataset_id)
if document_id:
document_ids.append(document_id)
payload = {
"question": query,
"dataset_ids": dataset_ids,
"document_ids": document_ids,
"page_size": self.page_size,
}
if self.cross_languages:
payload["cross_languages"] = self.cross_languages
response = requests.post(
f"{self.api_url}/api/v1/retrieval", headers=headers, json=payload
)
if response.status_code != 200:
raise Exception(f"Failed to query documents: {response.text}")
result = response.json()
data = result.get("data", {})
doc_aggs = data.get("doc_aggs", [])
docs: dict[str, Document] = {
doc.get("doc_id"): Document(
id=doc.get("doc_id"),
title=doc.get("doc_name"),
chunks=[],
)
for doc in doc_aggs
}
for chunk in data.get("chunks", []):
doc = docs.get(chunk.get("document_id"))
if doc:
doc.chunks.append(
Chunk(
content=chunk.get("content"),
similarity=chunk.get("similarity"),
)
)
return list(docs.values())
async def query_relevant_documents_async(
self, query: str, resources: list[Resource] = []
) -> list[Document]:
"""
Asynchronous version of query_relevant_documents.
Wraps the synchronous implementation in asyncio.to_thread() to avoid blocking the event loop.
"""
return await asyncio.to_thread(
self.query_relevant_documents, query, resources
)
def list_resources(self, query: str | None = None) -> list[Resource]:
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json",
}
params = {}
if query:
params["name"] = query
response = requests.get(
f"{self.api_url}/api/v1/datasets", headers=headers, params=params
)
if response.status_code != 200:
raise Exception(f"Failed to list resources: {response.text}")
result = response.json()
resources = []
for item in result.get("data", []):
item = Resource(
uri=f"rag://dataset/{item.get('id')}",
title=item.get("name", ""),
description=item.get("description", ""),
)
resources.append(item)
return resources
async def list_resources_async(self, query: str | None = None) -> list[Resource]:
"""
Asynchronous version of list_resources.
Wraps the synchronous implementation in asyncio.to_thread() to avoid blocking the event loop.
"""
return await asyncio.to_thread(self.list_resources, query)
def parse_uri(uri: str) -> tuple[str, str]:
parsed = urlparse(uri)
if parsed.scheme != "rag":
raise ValueError(f"Invalid URI: {uri}")
return parsed.path.split("/")[1], parsed.fragment