mirror of
https://github.com/open-webui/open-webui
synced 2025-06-26 18:26:48 +00:00
chore: format
This commit is contained in:
@@ -32,7 +32,12 @@ from open_webui.config import (
|
||||
)
|
||||
|
||||
from open_webui.constants import ERROR_MESSAGES
|
||||
from open_webui.env import ENV, SRC_LOG_LEVELS, DEVICE_TYPE, ENABLE_FORWARD_USER_INFO_HEADERS
|
||||
from open_webui.env import (
|
||||
ENV,
|
||||
SRC_LOG_LEVELS,
|
||||
DEVICE_TYPE,
|
||||
ENABLE_FORWARD_USER_INFO_HEADERS,
|
||||
)
|
||||
|
||||
from fastapi import Depends, FastAPI, File, HTTPException, Request, UploadFile, status
|
||||
from fastapi.middleware.cors import CORSMiddleware
|
||||
@@ -48,7 +53,11 @@ MAX_FILE_SIZE = MAX_FILE_SIZE_MB * 1024 * 1024 # Convert MB to bytes
|
||||
log = logging.getLogger(__name__)
|
||||
log.setLevel(SRC_LOG_LEVELS["AUDIO"])
|
||||
|
||||
app = FastAPI(docs_url="/docs" if ENV == "dev" else None, openapi_url="/openapi.json" if ENV == "dev" else None, redoc_url=None)
|
||||
app = FastAPI(
|
||||
docs_url="/docs" if ENV == "dev" else None,
|
||||
openapi_url="/openapi.json" if ENV == "dev" else None,
|
||||
redoc_url=None,
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
|
||||
@@ -48,7 +48,11 @@ log.setLevel(SRC_LOG_LEVELS["IMAGES"])
|
||||
IMAGE_CACHE_DIR = Path(CACHE_DIR).joinpath("./image/generations/")
|
||||
IMAGE_CACHE_DIR.mkdir(parents=True, exist_ok=True)
|
||||
|
||||
app = FastAPI(docs_url="/docs" if ENV == "dev" else None, openapi_url="/openapi.json" if ENV == "dev" else None, redoc_url=None)
|
||||
app = FastAPI(
|
||||
docs_url="/docs" if ENV == "dev" else None,
|
||||
openapi_url="/openapi.json" if ENV == "dev" else None,
|
||||
redoc_url=None,
|
||||
)
|
||||
|
||||
app.add_middleware(
|
||||
CORSMiddleware,
|
||||
|
||||
@@ -127,7 +127,11 @@ from langchain_core.documents import Document
|
||||
log = logging.getLogger(__name__)
|
||||
log.setLevel(SRC_LOG_LEVELS["RAG"])
|
||||
|
||||
app = FastAPI(docs_url="/docs" if ENV == "dev" else None, openapi_url="/openapi.json" if ENV == "dev" else None, redoc_url=None)
|
||||
app = FastAPI(
|
||||
docs_url="/docs" if ENV == "dev" else None,
|
||||
openapi_url="/openapi.json" if ENV == "dev" else None,
|
||||
redoc_url=None,
|
||||
)
|
||||
|
||||
app.state.config = AppConfig()
|
||||
|
||||
@@ -537,7 +541,7 @@ async def update_rag_config(form_data: ConfigUpdateForm, user=Depends(get_admin_
|
||||
|
||||
if form_data.web is not None:
|
||||
app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION = (
|
||||
#Note: When UI "Bypass SSL verification for Websites"=True then ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION=False
|
||||
# Note: When UI "Bypass SSL verification for Websites"=True then ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION=False
|
||||
form_data.web.web_loader_ssl_verification
|
||||
)
|
||||
|
||||
@@ -1230,7 +1234,9 @@ def process_web_search(form_data: SearchForm, user=Depends(get_verified_user)):
|
||||
|
||||
urls = [result.link for result in web_results]
|
||||
|
||||
loader = get_web_loader(urls, verify_ssl=app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION)
|
||||
loader = get_web_loader(
|
||||
urls, verify_ssl=app.state.config.ENABLE_RAG_WEB_LOADER_SSL_VERIFICATION
|
||||
)
|
||||
docs = loader.load()
|
||||
|
||||
save_docs_to_vector_db(docs, collection_name, overwrite=True)
|
||||
|
||||
@@ -27,7 +27,9 @@ class ChromaClient:
|
||||
if CHROMA_CLIENT_AUTH_PROVIDER is not None:
|
||||
settings_dict["chroma_client_auth_provider"] = CHROMA_CLIENT_AUTH_PROVIDER
|
||||
if CHROMA_CLIENT_AUTH_CREDENTIALS is not None:
|
||||
settings_dict["chroma_client_auth_credentials"] = CHROMA_CLIENT_AUTH_CREDENTIALS
|
||||
settings_dict["chroma_client_auth_credentials"] = (
|
||||
CHROMA_CLIENT_AUTH_CREDENTIALS
|
||||
)
|
||||
|
||||
if CHROMA_HTTP_HOST != "":
|
||||
self.client = chromadb.HttpClient(
|
||||
|
||||
@@ -7,9 +7,10 @@ from open_webui.config import (
|
||||
OPENSEARCH_SSL,
|
||||
OPENSEARCH_CERT_VERIFY,
|
||||
OPENSEARCH_USERNAME,
|
||||
OPENSEARCH_PASSWORD
|
||||
OPENSEARCH_PASSWORD,
|
||||
)
|
||||
|
||||
|
||||
class OpenSearchClient:
|
||||
def __init__(self):
|
||||
self.index_prefix = "open_webui"
|
||||
@@ -25,10 +26,10 @@ class OpenSearchClient:
|
||||
documents = []
|
||||
metadatas = []
|
||||
|
||||
for hit in result['hits']['hits']:
|
||||
ids.append(hit['_id'])
|
||||
documents.append(hit['_source'].get("text"))
|
||||
metadatas.append(hit['_source'].get("metadata"))
|
||||
for hit in result["hits"]["hits"]:
|
||||
ids.append(hit["_id"])
|
||||
documents.append(hit["_source"].get("text"))
|
||||
metadatas.append(hit["_source"].get("metadata"))
|
||||
|
||||
return GetResult(ids=ids, documents=documents, metadatas=metadatas)
|
||||
|
||||
@@ -38,13 +39,15 @@ class OpenSearchClient:
|
||||
documents = []
|
||||
metadatas = []
|
||||
|
||||
for hit in result['hits']['hits']:
|
||||
ids.append(hit['_id'])
|
||||
distances.append(hit['_score'])
|
||||
documents.append(hit['_source'].get("text"))
|
||||
metadatas.append(hit['_source'].get("metadata"))
|
||||
for hit in result["hits"]["hits"]:
|
||||
ids.append(hit["_id"])
|
||||
distances.append(hit["_score"])
|
||||
documents.append(hit["_source"].get("text"))
|
||||
metadatas.append(hit["_source"].get("metadata"))
|
||||
|
||||
return SearchResult(ids=ids, distances=distances, documents=documents, metadatas=metadatas)
|
||||
return SearchResult(
|
||||
ids=ids, distances=distances, documents=documents, metadatas=metadatas
|
||||
)
|
||||
|
||||
def _create_index(self, index_name: str, dimension: int):
|
||||
body = {
|
||||
@@ -52,20 +55,20 @@ class OpenSearchClient:
|
||||
"properties": {
|
||||
"id": {"type": "keyword"},
|
||||
"vector": {
|
||||
"type": "dense_vector",
|
||||
"dims": dimension, # Adjust based on your vector dimensions
|
||||
"index": true,
|
||||
"similarity": "faiss",
|
||||
"method": {
|
||||
"type": "dense_vector",
|
||||
"dims": dimension, # Adjust based on your vector dimensions
|
||||
"index": true,
|
||||
"similarity": "faiss",
|
||||
"method": {
|
||||
"name": "hnsw",
|
||||
"space_type": "ip", # Use inner product to approximate cosine similarity
|
||||
"engine": "faiss",
|
||||
"ef_construction": 128,
|
||||
"m": 16
|
||||
}
|
||||
"m": 16,
|
||||
},
|
||||
},
|
||||
"text": {"type": "text"},
|
||||
"metadata": {"type": "object"}
|
||||
"metadata": {"type": "object"},
|
||||
}
|
||||
}
|
||||
}
|
||||
@@ -73,19 +76,21 @@ class OpenSearchClient:
|
||||
|
||||
def _create_batches(self, items: list[VectorItem], batch_size=100):
|
||||
for i in range(0, len(items), batch_size):
|
||||
yield items[i:i + batch_size]
|
||||
|
||||
yield items[i : i + batch_size]
|
||||
|
||||
def has_collection(self, index_name: str) -> bool:
|
||||
# has_collection here means has index.
|
||||
# has_collection here means has index.
|
||||
# We are simply adapting to the norms of the other DBs.
|
||||
return self.client.indices.exists(index=f"{self.index_prefix}_{index_name}")
|
||||
|
||||
def delete_colleciton(self, index_name: str):
|
||||
# delete_collection here means delete index.
|
||||
# delete_collection here means delete index.
|
||||
# We are simply adapting to the norms of the other DBs.
|
||||
self.client.indices.delete(index=f"{self.index_prefix}_{index_name}")
|
||||
|
||||
def search(self, index_name: str, vectors: list[list[float]], limit: int) -> Optional[SearchResult]:
|
||||
def search(
|
||||
self, index_name: str, vectors: list[list[float]], limit: int
|
||||
) -> Optional[SearchResult]:
|
||||
query = {
|
||||
"size": limit,
|
||||
"_source": ["text", "metadata"],
|
||||
@@ -94,15 +99,16 @@ class OpenSearchClient:
|
||||
"query": {"match_all": {}},
|
||||
"script": {
|
||||
"source": "cosineSimilarity(params.vector, 'vector') + 1.0",
|
||||
"params": {"vector": vectors[0]} # Assuming single query vector
|
||||
}
|
||||
"params": {
|
||||
"vector": vectors[0]
|
||||
}, # Assuming single query vector
|
||||
},
|
||||
}
|
||||
}
|
||||
},
|
||||
}
|
||||
|
||||
result = self.client.search(
|
||||
index=f"{self.index_prefix}_{index_name}",
|
||||
body=query
|
||||
index=f"{self.index_prefix}_{index_name}", body=query
|
||||
)
|
||||
|
||||
return self._result_to_search_result(result)
|
||||
@@ -112,12 +118,11 @@ class OpenSearchClient:
|
||||
self._create_index(index_name, dimension)
|
||||
|
||||
def get(self, index_name: str) -> Optional[GetResult]:
|
||||
query = {
|
||||
"query": {"match_all": {}},
|
||||
"_source": ["text", "metadata"]
|
||||
}
|
||||
query = {"query": {"match_all": {}}, "_source": ["text", "metadata"]}
|
||||
|
||||
result = self.client.search(index=f"{self.index_prefix}_{index_name}", body=query)
|
||||
result = self.client.search(
|
||||
index=f"{self.index_prefix}_{index_name}", body=query
|
||||
)
|
||||
return self._result_to_get_result(result)
|
||||
|
||||
def insert(self, index_name: str, items: list[VectorItem]):
|
||||
@@ -126,7 +131,16 @@ class OpenSearchClient:
|
||||
|
||||
for batch in self._create_batches(items):
|
||||
actions = [
|
||||
{"index": {"_id": item["id"], "_source": {"vector": item["vector"], "text": item["text"], "metadata": item["metadata"]}}}
|
||||
{
|
||||
"index": {
|
||||
"_id": item["id"],
|
||||
"_source": {
|
||||
"vector": item["vector"],
|
||||
"text": item["text"],
|
||||
"metadata": item["metadata"],
|
||||
},
|
||||
}
|
||||
}
|
||||
for item in batch
|
||||
]
|
||||
self.client.bulk(actions)
|
||||
@@ -137,13 +151,25 @@ class OpenSearchClient:
|
||||
|
||||
for batch in self._create_batches(items):
|
||||
actions = [
|
||||
{"index": {"_id": item["id"], "_source": {"vector": item["vector"], "text": item["text"], "metadata": item["metadata"]}}}
|
||||
{
|
||||
"index": {
|
||||
"_id": item["id"],
|
||||
"_source": {
|
||||
"vector": item["vector"],
|
||||
"text": item["text"],
|
||||
"metadata": item["metadata"],
|
||||
},
|
||||
}
|
||||
}
|
||||
for item in batch
|
||||
]
|
||||
self.client.bulk(actions)
|
||||
|
||||
def delete(self, index_name: str, ids: list[str]):
|
||||
actions = [{"delete": {"_index": f"{self.index_prefix}_{index_name}", "_id": id}} for id in ids]
|
||||
actions = [
|
||||
{"delete": {"_index": f"{self.index_prefix}_{index_name}", "_id": id}}
|
||||
for id in ids
|
||||
]
|
||||
self.client.bulk(body=actions)
|
||||
|
||||
def reset(self):
|
||||
|
||||
@@ -44,7 +44,9 @@ class PgvectorClient:
|
||||
|
||||
self.session = Session
|
||||
else:
|
||||
engine = create_engine(PGVECTOR_DB_URL, pool_pre_ping=True, poolclass=NullPool)
|
||||
engine = create_engine(
|
||||
PGVECTOR_DB_URL, pool_pre_ping=True, poolclass=NullPool
|
||||
)
|
||||
SessionLocal = sessionmaker(
|
||||
autocommit=False, autoflush=False, bind=engine, expire_on_commit=False
|
||||
)
|
||||
|
||||
@@ -15,10 +15,11 @@ class QdrantClient:
|
||||
self.collection_prefix = "open-webui"
|
||||
self.QDRANT_URI = QDRANT_URI
|
||||
self.QDRANT_API_KEY = QDRANT_API_KEY
|
||||
self.client = Qclient(
|
||||
url=self.QDRANT_URI,
|
||||
api_key=self.QDRANT_API_KEY
|
||||
) if self.QDRANT_URI else None
|
||||
self.client = (
|
||||
Qclient(url=self.QDRANT_URI, api_key=self.QDRANT_API_KEY)
|
||||
if self.QDRANT_URI
|
||||
else None
|
||||
)
|
||||
|
||||
def _result_to_get_result(self, points) -> GetResult:
|
||||
ids = []
|
||||
|
||||
@@ -1,6 +1,5 @@
|
||||
|
||||
import logging
|
||||
import os
|
||||
import os
|
||||
from pprint import pprint
|
||||
from typing import Optional
|
||||
import requests
|
||||
@@ -10,15 +9,22 @@ import argparse
|
||||
|
||||
log = logging.getLogger(__name__)
|
||||
log.setLevel(SRC_LOG_LEVELS["RAG"])
|
||||
'''
|
||||
"""
|
||||
Documentation: https://docs.microsoft.com/en-us/bing/search-apis/bing-web-search/overview
|
||||
'''
|
||||
"""
|
||||
|
||||
|
||||
def search_bing(
|
||||
subscription_key: str, endpoint: str, locale: str, query: str, count: int, filter_list: Optional[list[str]] = None
|
||||
subscription_key: str,
|
||||
endpoint: str,
|
||||
locale: str,
|
||||
query: str,
|
||||
count: int,
|
||||
filter_list: Optional[list[str]] = None,
|
||||
) -> list[SearchResult]:
|
||||
mkt = locale
|
||||
params = { 'q': query, 'mkt': mkt, 'answerCount': count }
|
||||
headers = { 'Ocp-Apim-Subscription-Key': subscription_key }
|
||||
params = {"q": query, "mkt": mkt, "answerCount": count}
|
||||
headers = {"Ocp-Apim-Subscription-Key": subscription_key}
|
||||
|
||||
try:
|
||||
response = requests.get(endpoint, headers=headers, params=params)
|
||||
@@ -38,15 +44,30 @@ def search_bing(
|
||||
except Exception as ex:
|
||||
log.error(f"Error: {ex}")
|
||||
raise ex
|
||||
|
||||
|
||||
|
||||
def main():
|
||||
parser = argparse.ArgumentParser(description="Search Bing from the command line.")
|
||||
parser.add_argument("query", type=str, default="Top 10 international news today", help="The search query.")
|
||||
parser.add_argument("--count", type=int, default=10, help="Number of search results to return.")
|
||||
parser.add_argument("--filter", nargs='*', help="List of filters to apply to the search results.")
|
||||
parser.add_argument("--locale", type=str, default="en-US", help="The locale to use for the search, maps to market in api")
|
||||
|
||||
parser.add_argument(
|
||||
"query",
|
||||
type=str,
|
||||
default="Top 10 international news today",
|
||||
help="The search query.",
|
||||
)
|
||||
parser.add_argument(
|
||||
"--count", type=int, default=10, help="Number of search results to return."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--filter", nargs="*", help="List of filters to apply to the search results."
|
||||
)
|
||||
parser.add_argument(
|
||||
"--locale",
|
||||
type=str,
|
||||
default="en-US",
|
||||
help="The locale to use for the search, maps to market in api",
|
||||
)
|
||||
|
||||
args = parser.parse_args()
|
||||
|
||||
|
||||
results = search_bing(args.locale, args.query, args.count, args.filter)
|
||||
pprint(results)
|
||||
pprint(results)
|
||||
|
||||
Reference in New Issue
Block a user