Merge pull request #5311 from open-webui/dev

dev
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Timothy Jaeryang Baek 2024-09-10 02:30:02 +01:00 committed by GitHub
commit d5f13dd9e0
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4 changed files with 12 additions and 66 deletions

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@ -21,14 +21,14 @@ from open_webui.config import (
AUDIO_TTS_VOICE,
CACHE_DIR,
CORS_ALLOW_ORIGIN,
DEVICE_TYPE,
WHISPER_MODEL,
WHISPER_MODEL_AUTO_UPDATE,
WHISPER_MODEL_DIR,
AppConfig,
)
from open_webui.constants import ERROR_MESSAGES
from open_webui.env import SRC_LOG_LEVELS
from open_webui.env import SRC_LOG_LEVELS, DEVICE_TYPE
from fastapi import Depends, FastAPI, File, HTTPException, Request, UploadFile, status
from fastapi.middleware.cors import CORSMiddleware
from fastapi.responses import FileResponse

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@ -44,7 +44,6 @@ from open_webui.config import (
CHUNK_SIZE,
CONTENT_EXTRACTION_ENGINE,
CORS_ALLOW_ORIGIN,
DEVICE_TYPE,
DOCS_DIR,
ENABLE_RAG_HYBRID_SEARCH,
ENABLE_RAG_LOCAL_WEB_FETCH,

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@ -539,40 +539,6 @@ Path(TOOLS_DIR).mkdir(parents=True, exist_ok=True)
FUNCTIONS_DIR = os.getenv("FUNCTIONS_DIR", f"{DATA_DIR}/functions")
Path(FUNCTIONS_DIR).mkdir(parents=True, exist_ok=True)
####################################
# LITELLM_CONFIG
####################################
def create_config_file(file_path):
directory = os.path.dirname(file_path)
# Check if directory exists, if not, create it
if not os.path.exists(directory):
os.makedirs(directory)
# Data to write into the YAML file
config_data = {
"general_settings": {},
"litellm_settings": {},
"model_list": [],
"router_settings": {},
}
# Write data to YAML file
with open(file_path, "w") as file:
yaml.dump(config_data, file)
LITELLM_CONFIG_PATH = f"{DATA_DIR}/litellm/config.yaml"
# if not os.path.exists(LITELLM_CONFIG_PATH):
# log.info("Config file doesn't exist. Creating...")
# create_config_file(LITELLM_CONFIG_PATH)
# log.info("Config file created successfully.")
####################################
# OLLAMA_BASE_URL
####################################
@ -922,7 +888,7 @@ TOOLS_FUNCTION_CALLING_PROMPT_TEMPLATE = PersistentConfig(
####################################
# RAG document content extraction
# Vector Database
####################################
VECTOR_DB = os.environ.get("VECTOR_DB", "chroma")
@ -1051,34 +1017,6 @@ RAG_RERANKING_MODEL_TRUST_REMOTE_CODE = (
os.environ.get("RAG_RERANKING_MODEL_TRUST_REMOTE_CODE", "").lower() == "true"
)
if CHROMA_HTTP_HOST != "":
CHROMA_CLIENT = chromadb.HttpClient(
host=CHROMA_HTTP_HOST,
port=CHROMA_HTTP_PORT,
headers=CHROMA_HTTP_HEADERS,
ssl=CHROMA_HTTP_SSL,
tenant=CHROMA_TENANT,
database=CHROMA_DATABASE,
settings=Settings(allow_reset=True, anonymized_telemetry=False),
)
else:
CHROMA_CLIENT = chromadb.PersistentClient(
path=CHROMA_DATA_PATH,
settings=Settings(allow_reset=True, anonymized_telemetry=False),
tenant=CHROMA_TENANT,
database=CHROMA_DATABASE,
)
# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
if USE_CUDA.lower() == "true":
DEVICE_TYPE = "cuda"
else:
DEVICE_TYPE = "cpu"
CHUNK_SIZE = PersistentConfig(
"CHUNK_SIZE", "rag.chunk_size", int(os.environ.get("CHUNK_SIZE", "1500"))
)

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@ -32,6 +32,15 @@ except ImportError:
print("dotenv not installed, skipping...")
# device type embedding models - "cpu" (default), "cuda" (nvidia gpu required) or "mps" (apple silicon) - choosing this right can lead to better performance
USE_CUDA = os.environ.get("USE_CUDA_DOCKER", "false")
if USE_CUDA.lower() == "true":
DEVICE_TYPE = "cuda"
else:
DEVICE_TYPE = "cpu"
####################################
# LOGGING
####################################