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Merge remote-tracking branch 'origin/main' into fix/upgrade_path

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This commit is contained in:
Lucas Oliveira 2025-11-26 19:58:54 -03:00
commit f0b86c107b
15 changed files with 10629 additions and 4112 deletions
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2
Dockerfile.langflow
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@ -1,4 +1,4 @@
FROM langflowai/langflow-nightly:1.7.0.dev19
FROM langflowai/langflow-nightly:1.7.0.dev21
EXPOSE 7860

3
docker-compose-cpu.yml
View file

@ -130,7 +130,8 @@ services:
- FILENAME=None
- MIMETYPE=None
- FILESIZE=0
- LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT=JWT,OPENRAG-QUERY-FILTER,OPENSEARCH_PASSWORD,OWNER,OWNER_NAME,OWNER_EMAIL,CONNECTOR_TYPE,FILENAME,MIMETYPE,FILESIZE
- SELECTED_EMBEDDING_MODEL=${SELECTED_EMBEDDING_MODEL:-}
- LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT=JWT,OPENRAG-QUERY-FILTER,OPENSEARCH_PASSWORD,OWNER,OWNER_NAME,OWNER_EMAIL,CONNECTOR_TYPE,FILENAME,MIMETYPE,FILESIZE,SELECTED_EMBEDDING_MODEL
- LANGFLOW_LOG_LEVEL=DEBUG
- LANGFLOW_AUTO_LOGIN=${LANGFLOW_AUTO_LOGIN}
- LANGFLOW_SUPERUSER=${LANGFLOW_SUPERUSER}

34
docker-compose.yml
View file

@ -45,9 +45,9 @@ services:
openrag-backend:
image: langflowai/openrag-backend:${OPENRAG_VERSION:-latest}
# build:
# context: .
# dockerfile: Dockerfile.backend
build:
context: .
dockerfile: Dockerfile.backend
container_name: openrag-backend
depends_on:
- langflow
@ -87,9 +87,9 @@ services:
openrag-frontend:
image: langflowai/openrag-frontend:${OPENRAG_VERSION:-latest}
# build:
# context: .
# dockerfile: Dockerfile.frontend
build:
context: .
dockerfile: Dockerfile.frontend
container_name: openrag-frontend
depends_on:
- openrag-backend
@ -102,20 +102,20 @@ services:
volumes:
- ./flows:/app/flows:U,z
image: langflowai/openrag-langflow:${LANGFLOW_VERSION:-latest}
# build:
# context: .
# dockerfile: Dockerfile.langflow
build:
context: .
dockerfile: Dockerfile.langflow
container_name: langflow
ports:
- "7860:7860"
environment:
- LANGFLOW_DEACTIVATE_TRACING=true
- OPENAI_API_KEY=${OPENAI_API_KEY}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY}
- WATSONX_API_KEY=${WATSONX_API_KEY}
- WATSONX_ENDPOINT=${WATSONX_ENDPOINT}
- WATSONX_PROJECT_ID=${WATSONX_PROJECT_ID}
- OLLAMA_BASE_URL=${OLLAMA_ENDPOINT}
- OPENAI_API_KEY=${OPENAI_API_KEY:-None}
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-None}
- WATSONX_API_KEY=${WATSONX_API_KEY:-None}
- WATSONX_ENDPOINT=${WATSONX_ENDPOINT:-None}
- WATSONX_PROJECT_ID=${WATSONX_PROJECT_ID:-None}
- OLLAMA_BASE_URL=${OLLAMA_ENDPOINT:-None}
- LANGFLOW_LOAD_FLOWS_PATH=/app/flows
- LANGFLOW_SECRET_KEY=${LANGFLOW_SECRET_KEY}
- JWT=None
@ -129,7 +129,9 @@ services:
- FILENAME=None
- MIMETYPE=None
- FILESIZE=0
- LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT=JWT,OPENRAG-QUERY-FILTER,OPENSEARCH_PASSWORD,OWNER,OWNER_NAME,OWNER_EMAIL,CONNECTOR_TYPE,FILENAME,MIMETYPE,FILESIZE
- SELECTED_EMBEDDING_MODEL=${SELECTED_EMBEDDING_MODEL:-}
- OPENSEARCH_PASSWORD=${OPENSEARCH_PASSWORD}
- LANGFLOW_VARIABLES_TO_GET_FROM_ENVIRONMENT=JWT,OPENRAG-QUERY-FILTER,OPENSEARCH_PASSWORD,OWNER,OWNER_NAME,OWNER_EMAIL,CONNECTOR_TYPE,FILENAME,MIMETYPE,FILESIZE,SELECTED_EMBEDDING_MODEL,OPENAI_API_KEY,ANTHROPIC_API_KEY,WATSONX_API_KEY,WATSONX_ENDPOINT,WATSONX_PROJECT_ID,OLLAMA_BASE_URL
- LANGFLOW_LOG_LEVEL=DEBUG
- LANGFLOW_AUTO_LOGIN=${LANGFLOW_AUTO_LOGIN}
- LANGFLOW_SUPERUSER=${LANGFLOW_SUPERUSER}

2914
flows/ingestion_flow.json
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3990
flows/openrag_agent.json
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3723
flows/openrag_nudges.json
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3735
flows/openrag_url_mcp.json
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73
frontend/components/navigation.tsx
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@ -91,6 +91,10 @@ export function Navigation({
const { loading } = useLoadingStore();
useEffect(() => {
console.log("loading", loading);
}, [loading]);
const [previousConversationCount, setPreviousConversationCount] = useState(0);
const [deleteModalOpen, setDeleteModalOpen] = useState(false);
const [conversationToDelete, setConversationToDelete] =
@ -391,8 +395,70 @@ export function Navigation({
No conversations yet
</div>
) : (
conversations.map((conversation) => (
<button
<>
{/* Optimistic rendering: Show placeholder conversation button while loading */}
{(() => {
// Show placeholder when:
// 1. Loading is true AND conversation doesn't exist yet (creating new conversation), OR
// 2. currentConversationId exists but isn't in conversations yet (gap between response and list update)
const conversationExists = currentConversationId
? conversations.some(
(conv) => conv.response_id === currentConversationId,
)
: false;
const shouldShowPlaceholder =
!conversationExists &&
(loading ||
(currentConversationId !== null &&
currentConversationId !== undefined));
// Use placeholderConversation if available
// Otherwise create a placeholder with currentConversationId if it exists
// Or use a temporary ID if we're loading but don't have an ID yet
const placeholderToShow =
placeholderConversation
? placeholderConversation
: currentConversationId
? {
response_id: currentConversationId,
title: "",
endpoint: endpoint,
messages: [],
total_messages: 0,
}
: loading
? {
response_id: `loading-${Date.now()}`,
title: "",
endpoint: endpoint,
messages: [],
total_messages: 0,
}
: null;
return (
shouldShowPlaceholder &&
placeholderToShow && (
<button
key={placeholderToShow.response_id}
type="button"
className="w-full px-3 h-11 rounded-lg bg-accent group relative text-left cursor-not-allowed"
disabled
>
<div className="flex items-center justify-between">
<div className="flex-1 min-w-0">
<div className="text-sm font-medium text-muted-foreground truncate">
<span className="thinking-dots"></span>
</div>
</div>
</div>
</button>
)
);
})()}
{conversations.map((conversation) => (
<button
key={conversation.response_id}
type="button"
className={`w-full px-3 h-11 rounded-lg group relative text-left ${
@ -467,7 +533,8 @@ export function Navigation({
</DropdownMenu>
</div>
</button>
))
))}
</>
)}
</>
)}

61
src/api/settings.py
View file

@ -14,6 +14,7 @@ from config.settings import (
clients,
get_openrag_config,
config_manager,
is_no_auth_mode,
)
from api.provider_validation import validate_provider_setup
@ -560,6 +561,9 @@ async def update_settings(request, session_manager):
# Update global variables
await _update_langflow_global_variables(current_config)
if "embedding_provider" in body or "embedding_model" in body:
await _update_mcp_servers_with_provider_credentials(current_config)
# Update model values if provider or model changed
if "llm_provider" in body or "llm_model" in body or "embedding_provider" in body or "embedding_model" in body:
@ -582,7 +586,7 @@ async def update_settings(request, session_manager):
)
async def onboarding(request, flows_service):
async def onboarding(request, flows_service, session_manager=None):
"""Handle onboarding configuration setup"""
try:
# Get current configuration
@ -828,6 +832,9 @@ async def onboarding(request, flows_service):
current_config.providers.openai.api_key != "" or
current_config.providers.anthropic.api_key != ""):
await _update_langflow_global_variables(current_config)
if "embedding_provider" in body or "embedding_model" in body:
await _update_mcp_servers_with_provider_credentials(current_config, session_manager)
# Update model values if provider or model fields were provided
if "llm_provider" in body or "llm_model" in body or "embedding_provider" in body or "embedding_model" in body:
@ -973,11 +980,56 @@ async def _update_langflow_global_variables(config):
)
logger.info("Set OLLAMA_BASE_URL global variable in Langflow")
if config.knowledge.embedding_model:
await clients._create_langflow_global_variable(
"SELECTED_EMBEDDING_MODEL", config.knowledge.embedding_model, modify=True
)
logger.info(
f"Set SELECTED_EMBEDDING_MODEL global variable to {config.knowledge.embedding_model}"
)
except Exception as e:
logger.error(f"Failed to update Langflow global variables: {str(e)}")
raise
async def _update_mcp_servers_with_provider_credentials(config, session_manager = None):
# Update MCP servers with provider credentials
try:
from services.langflow_mcp_service import LangflowMCPService
from utils.langflow_headers import build_mcp_global_vars_from_config
mcp_service = LangflowMCPService()
# Build global vars using utility function
mcp_global_vars = build_mcp_global_vars_from_config(config)
# In no-auth mode, add the anonymous JWT token and user details
if is_no_auth_mode() and session_manager:
from session_manager import AnonymousUser
# Create/get anonymous JWT for no-auth mode
anonymous_jwt = session_manager.get_effective_jwt_token(None, None)
if anonymous_jwt:
mcp_global_vars["JWT"] = anonymous_jwt
# Add anonymous user details
anonymous_user = AnonymousUser()
mcp_global_vars["OWNER"] = anonymous_user.user_id # "anonymous"
mcp_global_vars["OWNER_NAME"] = f'"{anonymous_user.name}"' # "Anonymous User" (quoted)
mcp_global_vars["OWNER_EMAIL"] = anonymous_user.email # "anonymous@localhost"
logger.debug("Added anonymous JWT and user details to MCP servers for no-auth mode")
if mcp_global_vars:
result = await mcp_service.update_mcp_servers_with_global_vars(mcp_global_vars)
logger.info("Updated MCP servers with provider credentials after settings change", **result)
except Exception as mcp_error:
logger.warning(f"Failed to update MCP servers after settings change: {str(mcp_error)}")
# Don't fail the entire settings update if MCP update fails
async def _update_langflow_model_values(config, flows_service):
"""Update model values across Langflow flows"""
try:
@ -1055,7 +1107,7 @@ async def _update_langflow_chunk_settings(config, flows_service):
raise
async def reapply_all_settings():
async def reapply_all_settings(session_manager = None):
"""
Reapply all current configuration settings to Langflow flows and global variables.
This is called when flows are detected to have been reset.
@ -1066,6 +1118,11 @@ async def reapply_all_settings():
logger.info("Reapplying all settings to Langflow flows and global variables")
if config.knowledge.embedding_model or config.knowledge.embedding_provider:
await _update_mcp_servers_with_provider_credentials(config, session_manager)
else:
logger.info("No embedding model or provider configured, skipping MCP server update")
# Update all Langflow settings using helper functions
try:
await _update_langflow_global_variables(config)

60
src/main.py
View file

@ -370,7 +370,7 @@ async def _ingest_default_documents_langflow(services, file_paths):
# Prepare tweaks for default documents with anonymous user metadata
default_tweaks = {
"OpenSearchHybrid-Ve6bS": {
"OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4": {
"docs_metadata": [
{"key": "owner", "value": None},
{"key": "owner_name", "value": anonymous_user.name},
@ -433,6 +433,55 @@ async def _ingest_default_documents_openrag(services, file_paths):
)
async def _update_mcp_servers_with_provider_credentials(services):
"""Update MCP servers with provider credentials at startup.
This is especially important for no-auth mode where users don't go through
the OAuth login flow that would normally set these credentials.
"""
try:
auth_service = services.get("auth_service")
session_manager = services.get("session_manager")
if not auth_service or not auth_service.langflow_mcp_service:
logger.debug("MCP service not available, skipping credential update")
return
config = get_openrag_config()
# Build global vars with provider credentials using utility function
from utils.langflow_headers import build_mcp_global_vars_from_config
global_vars = build_mcp_global_vars_from_config(config)
# In no-auth mode, add the anonymous JWT token and user details
if is_no_auth_mode() and session_manager:
from session_manager import AnonymousUser
# Create/get anonymous JWT for no-auth mode
anonymous_jwt = session_manager.get_effective_jwt_token(None, None)
if anonymous_jwt:
global_vars["JWT"] = anonymous_jwt
# Add anonymous user details
anonymous_user = AnonymousUser()
global_vars["OWNER"] = anonymous_user.user_id # "anonymous"
global_vars["OWNER_NAME"] = f'"{anonymous_user.name}"' # "Anonymous User" (quoted for spaces)
global_vars["OWNER_EMAIL"] = anonymous_user.email # "anonymous@localhost"
logger.info("Added anonymous JWT and user details to MCP servers for no-auth mode")
if global_vars:
result = await auth_service.langflow_mcp_service.update_mcp_servers_with_global_vars(global_vars)
logger.info("Updated MCP servers with provider credentials at startup", **result)
else:
logger.debug("No provider credentials configured, skipping MCP server update")
except Exception as e:
logger.warning("Failed to update MCP servers with provider credentials at startup", error=str(e))
# Don't fail startup if MCP update fails
async def startup_tasks(services):
"""Startup tasks"""
logger.info("Starting startup tasks")
@ -445,6 +494,9 @@ async def startup_tasks(services):
# Configure alerting security
await configure_alerting_security()
# Update MCP servers with provider credentials (especially important for no-auth mode)
await _update_mcp_servers_with_provider_credentials(services)
# Check if flows were reset and reapply settings if config is edited
try:
@ -1075,7 +1127,11 @@ async def create_app():
Route(
"/onboarding",
require_auth(services["session_manager"])(
partial(settings.onboarding, flows_service=services["flows_service"])
partial(
settings.onboarding,
flows_service=services["flows_service"],
session_manager=services["session_manager"]
)
),
methods=["POST"],
),

6
src/models/processors.py
View file

@ -743,9 +743,9 @@ class LangflowFileProcessor(TaskProcessor):
if metadata_tweaks:
# Initialize the OpenSearch component tweaks if not already present
if "OpenSearchHybrid-Ve6bS" not in final_tweaks:
final_tweaks["OpenSearchHybrid-Ve6bS"] = {}
final_tweaks["OpenSearchHybrid-Ve6bS"]["docs_metadata"] = metadata_tweaks
if "OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4" not in final_tweaks:
final_tweaks["OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4"] = {}
final_tweaks["OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4"]["docs_metadata"] = metadata_tweaks
# Process file using langflow service
result = await self.langflow_file_service.upload_and_ingest_file(

10
src/services/auth_service.py
View file

@ -308,6 +308,16 @@ class AuthService:
global_vars["OWNER_NAME"] = str(f"\"{owner_name}\"")
if user_info.get("email"):
global_vars["OWNER_EMAIL"] = user_info.get("email")
# Add provider credentials to MCP servers using utility function
from config.settings import get_openrag_config
from utils.langflow_headers import build_mcp_global_vars_from_config
config = get_openrag_config()
provider_vars = build_mcp_global_vars_from_config(config)
# Merge provider credentials with user info
global_vars.update(provider_vars)
# Run in background to avoid delaying login flow
task = asyncio.create_task(

40
src/services/chat_service.py
View file

@ -60,11 +60,22 @@ class ChatService:
"LANGFLOW_URL and LANGFLOW_CHAT_FLOW_ID environment variables are required"
)
# Prepare extra headers for JWT authentication
# Prepare extra headers for JWT authentication and embedding model
extra_headers = {}
if jwt_token:
extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
# Pass the selected embedding model as a global variable
from config.settings import get_openrag_config
from utils.langflow_headers import add_provider_credentials_to_headers
config = get_openrag_config()
embedding_model = config.knowledge.embedding_model
extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
# Add provider credentials to headers
add_provider_credentials_to_headers(extra_headers, config)
logger.debug(f"[LF] Extra headers {extra_headers}")
# Get context variables for filters, limit, and threshold
from auth_context import (
get_score_threshold,
@ -169,11 +180,22 @@ class ChatService:
"LANGFLOW_URL and NUDGES_FLOW_ID environment variables are required"
)
# Prepare extra headers for JWT authentication
# Prepare extra headers for JWT authentication and embedding model
extra_headers = {}
if jwt_token:
extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
# Pass the selected embedding model as a global variable
from config.settings import get_openrag_config
from utils.langflow_headers import add_provider_credentials_to_headers
config = get_openrag_config()
embedding_model = config.knowledge.embedding_model
extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
# Add provider credentials to headers
add_provider_credentials_to_headers(extra_headers, config)
# Build the complete filter expression like the chat service does
filter_expression = {}
has_user_filters = False
@ -287,10 +309,22 @@ class ChatService:
document_prompt = f"I'm uploading a document called '{filename}'. Here is its content:\n\n{document_content}\n\nPlease confirm you've received this document and are ready to answer questions about it."
if endpoint == "langflow":
# Prepare extra headers for JWT authentication
# Prepare extra headers for JWT authentication and embedding model
extra_headers = {}
if jwt_token:
extra_headers["X-LANGFLOW-GLOBAL-VAR-JWT"] = jwt_token
# Pass the selected embedding model as a global variable
from config.settings import get_openrag_config
from utils.langflow_headers import add_provider_credentials_to_headers
config = get_openrag_config()
embedding_model = config.knowledge.embedding_model
extra_headers["X-LANGFLOW-GLOBAL-VAR-SELECTED_EMBEDDING_MODEL"] = embedding_model
# Add provider credentials to headers
add_provider_credentials_to_headers(extra_headers, config)
# Ensure the Langflow client exists; try lazy init if needed
langflow_client = await clients.ensure_langflow_client()
if not langflow_client:

19
src/services/langflow_file_service.py
View file

@ -94,7 +94,7 @@ class LangflowFileService:
# Pass JWT token via tweaks using the x-langflow-global-var- pattern
if jwt_token:
# Using the global variable pattern that Langflow expects for OpenSearch components
tweaks["OpenSearchHybrid-Ve6bS"] = {"jwt_token": jwt_token}
tweaks["OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4"] = {"jwt_token": jwt_token}
logger.debug("[LF] Added JWT token to tweaks for OpenSearch components")
else:
logger.warning("[LF] No JWT token provided")
@ -112,9 +112,9 @@ class LangflowFileService:
logger.info(f"[LF] Metadata tweaks {metadata_tweaks}")
# if metadata_tweaks:
# # Initialize the OpenSearch component tweaks if not already present
# if "OpenSearchHybrid-Ve6bS" not in tweaks:
# tweaks["OpenSearchHybrid-Ve6bS"] = {}
# tweaks["OpenSearchHybrid-Ve6bS"]["docs_metadata"] = metadata_tweaks
# if "OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4" not in tweaks:
# tweaks["OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4"] = {}
# tweaks["OpenSearchVectorStoreComponentMultimodalMultiEmbedding-By9U4"]["docs_metadata"] = metadata_tweaks
# logger.debug(
# "[LF] Added metadata to tweaks", metadata_count=len(metadata_tweaks)
# )
@ -140,6 +140,13 @@ class LangflowFileService:
filename = str(file_tuples[0][0]) if file_tuples and len(file_tuples) > 0 else ""
mimetype = str(file_tuples[0][2]) if file_tuples and len(file_tuples) > 0 and len(file_tuples[0]) > 2 else ""
# Get the current embedding model and provider credentials from config
from config.settings import get_openrag_config
from utils.langflow_headers import add_provider_credentials_to_headers
config = get_openrag_config()
embedding_model = config.knowledge.embedding_model
headers={
"X-Langflow-Global-Var-JWT": str(jwt_token),
"X-Langflow-Global-Var-OWNER": str(owner),
@ -149,7 +156,11 @@ class LangflowFileService:
"X-Langflow-Global-Var-FILENAME": filename,
"X-Langflow-Global-Var-MIMETYPE": mimetype,
"X-Langflow-Global-Var-FILESIZE": str(file_size_bytes),
"X-Langflow-Global-Var-SELECTED_EMBEDDING_MODEL": str(embedding_model),
}
# Add provider credentials as global variables for ingestion
add_provider_credentials_to_headers(headers, config)
logger.info(f"[LF] Headers {headers}")
logger.info(f"[LF] Payload {payload}")
resp = await clients.langflow_request(

71
src/utils/langflow_headers.py Normal file
View file

@ -0,0 +1,71 @@
"""Utility functions for building Langflow request headers."""
from typing import Dict
from utils.container_utils import transform_localhost_url
def add_provider_credentials_to_headers(headers: Dict[str, str], config) -> None:
"""Add provider credentials to headers as Langflow global variables.
Args:
headers: Dictionary of headers to add credentials to
config: OpenRAGConfig object containing provider configurations
"""
# Add OpenAI credentials
if config.providers.openai.api_key:
headers["X-LANGFLOW-GLOBAL-VAR-OPENAI_API_KEY"] = str(config.providers.openai.api_key)
# Add Anthropic credentials
if config.providers.anthropic.api_key:
headers["X-LANGFLOW-GLOBAL-VAR-ANTHROPIC_API_KEY"] = str(config.providers.anthropic.api_key)
# Add WatsonX credentials
if config.providers.watsonx.api_key:
headers["X-LANGFLOW-GLOBAL-VAR-WATSONX_API_KEY"] = str(config.providers.watsonx.api_key)
if config.providers.watsonx.project_id:
headers["X-LANGFLOW-GLOBAL-VAR-WATSONX_PROJECT_ID"] = str(config.providers.watsonx.project_id)
# Add Ollama endpoint (with localhost transformation)
if config.providers.ollama.endpoint:
ollama_endpoint = transform_localhost_url(config.providers.ollama.endpoint)
headers["X-LANGFLOW-GLOBAL-VAR-OLLAMA_BASE_URL"] = str(ollama_endpoint)
def build_mcp_global_vars_from_config(config) -> Dict[str, str]:
"""Build MCP global variables dictionary from OpenRAG configuration.
Args:
config: OpenRAGConfig object containing provider configurations
Returns:
Dictionary of global variables for MCP servers (without X-Langflow-Global-Var prefix)
"""
global_vars = {}
# Add OpenAI credentials
if config.providers.openai.api_key:
global_vars["OPENAI_API_KEY"] = config.providers.openai.api_key
# Add Anthropic credentials
if config.providers.anthropic.api_key:
global_vars["ANTHROPIC_API_KEY"] = config.providers.anthropic.api_key
# Add WatsonX credentials
if config.providers.watsonx.api_key:
global_vars["WATSONX_API_KEY"] = config.providers.watsonx.api_key
if config.providers.watsonx.project_id:
global_vars["WATSONX_PROJECT_ID"] = config.providers.watsonx.project_id
# Add Ollama endpoint (with localhost transformation)
if config.providers.ollama.endpoint:
ollama_endpoint = transform_localhost_url(config.providers.ollama.endpoint)
global_vars["OLLAMA_BASE_URL"] = ollama_endpoint
# Add selected embedding model
if config.knowledge.embedding_model:
global_vars["SELECTED_EMBEDDING_MODEL"] = config.knowledge.embedding_model
return global_vars