Merge pull request #338 from langflow-ai/tui-optional-openai-key

Tui optional OpenAI key
This commit is contained in:
Sebastián Estévez 2025-10-31 15:54:33 -04:00 committed by GitHub
commit a35235eb59
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GPG key ID: B5690EEEBB952194
6 changed files with 169 additions and 11 deletions

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@ -2,10 +2,12 @@
# Provides easy commands for development workflow
# Load variables from .env if present so `make` commands pick them up
# Strip quotes from values to avoid issues with tools that don't handle them like python-dotenv does
ifneq (,$(wildcard .env))
include .env
# Export all simple KEY=VALUE pairs to the environment for child processes
export $(shell sed -n 's/^\([A-Za-z_][A-Za-z0-9_]*\)=.*/\1/p' .env)
# Strip single quotes from all exported variables
$(foreach var,$(shell sed -n 's/^\([A-Za-z_][A-Za-z0-9_]*\)=.*/\1/p' .env),$(eval $(var):=$(shell echo $($(var)) | sed "s/^'//;s/'$$//")))
endif
.PHONY: help dev dev-cpu dev-local infra stop clean build logs shell-backend shell-frontend install \

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@ -279,7 +279,8 @@ class AppClients:
self.opensearch = None
self.langflow_client = None
self.langflow_http_client = None
self.patched_async_client = None
self._patched_async_client = None # Private attribute
self._client_init_lock = __import__('threading').Lock() # Lock for thread-safe initialization
self.converter = None
async def initialize(self):
@ -318,8 +319,15 @@ class AppClients:
"No Langflow client initialized yet, will attempt later on first use"
)
# Initialize patched OpenAI client
self.patched_async_client = patch_openai_with_mcp(AsyncOpenAI())
# Initialize patched OpenAI client if API key is available
# This allows the app to start even if OPENAI_API_KEY is not set yet
# (e.g., when it will be provided during onboarding)
# The property will handle lazy initialization with probe when first accessed
openai_key = os.getenv("OPENAI_API_KEY")
if openai_key:
logger.info("OpenAI API key found in environment - will be initialized lazily on first use with HTTP/2 probe")
else:
logger.info("OpenAI API key not found in environment - will be initialized on first use if needed")
# Initialize document converter
self.converter = create_document_converter(ocr_engine=DOCLING_OCR_ENGINE)
@ -350,6 +358,145 @@ class AppClients:
self.langflow_client = None
return self.langflow_client
@property
def patched_async_client(self):
"""
Property that ensures OpenAI client is initialized on first access.
This allows lazy initialization so the app can start without an API key.
Note: The client is a long-lived singleton that should be closed via cleanup().
Thread-safe via lock to prevent concurrent initialization attempts.
"""
# Quick check without lock
if self._patched_async_client is not None:
return self._patched_async_client
# Use lock to ensure only one thread initializes
with self._client_init_lock:
# Double-check after acquiring lock
if self._patched_async_client is not None:
return self._patched_async_client
# Try to initialize the client on-demand
# First check if OPENAI_API_KEY is in environment
openai_key = os.getenv("OPENAI_API_KEY")
if not openai_key:
# Try to get from config (in case it was set during onboarding)
try:
config = get_openrag_config()
if config and config.provider and config.provider.api_key:
openai_key = config.provider.api_key
# Set it in environment so AsyncOpenAI can pick it up
os.environ["OPENAI_API_KEY"] = openai_key
logger.info("Loaded OpenAI API key from config file")
except Exception as e:
logger.debug("Could not load OpenAI key from config", error=str(e))
# Try to initialize the client - AsyncOpenAI() will read from environment
# We'll try HTTP/2 first with a probe, then fall back to HTTP/1.1 if it times out
import asyncio
import concurrent.futures
import threading
async def probe_and_initialize():
# Try HTTP/2 first (default)
client_http2 = patch_openai_with_mcp(AsyncOpenAI())
logger.info("Probing OpenAI client with HTTP/2...")
try:
# Probe with a small embedding and short timeout
await asyncio.wait_for(
client_http2.embeddings.create(
model='text-embedding-3-small',
input=['test']
),
timeout=5.0
)
logger.info("OpenAI client initialized with HTTP/2 (probe successful)")
return client_http2
except (asyncio.TimeoutError, Exception) as probe_error:
logger.warning("HTTP/2 probe failed, falling back to HTTP/1.1", error=str(probe_error))
# Close the HTTP/2 client
try:
await client_http2.close()
except Exception:
pass
# Fall back to HTTP/1.1 with explicit timeout settings
http_client = httpx.AsyncClient(
http2=False,
timeout=httpx.Timeout(60.0, connect=10.0)
)
client_http1 = patch_openai_with_mcp(
AsyncOpenAI(http_client=http_client)
)
logger.info("OpenAI client initialized with HTTP/1.1 (fallback)")
return client_http1
def run_probe_in_thread():
"""Run the async probe in a new thread with its own event loop"""
loop = asyncio.new_event_loop()
asyncio.set_event_loop(loop)
try:
return loop.run_until_complete(probe_and_initialize())
finally:
loop.close()
try:
# Run the probe in a separate thread with its own event loop
with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
future = executor.submit(run_probe_in_thread)
self._patched_async_client = future.result(timeout=15)
logger.info("Successfully initialized OpenAI client")
except Exception as e:
logger.error(f"Failed to initialize OpenAI client: {e.__class__.__name__}: {str(e)}")
raise ValueError(f"Failed to initialize OpenAI client: {str(e)}. Please complete onboarding or set OPENAI_API_KEY environment variable.")
return self._patched_async_client
async def cleanup(self):
"""Cleanup resources - should be called on application shutdown"""
# Close AsyncOpenAI client if it was created
if self._patched_async_client is not None:
try:
await self._patched_async_client.close()
logger.info("Closed AsyncOpenAI client")
except Exception as e:
logger.error("Failed to close AsyncOpenAI client", error=str(e))
finally:
self._patched_async_client = None
# Close Langflow HTTP client if it exists
if self.langflow_http_client is not None:
try:
await self.langflow_http_client.aclose()
logger.info("Closed Langflow HTTP client")
except Exception as e:
logger.error("Failed to close Langflow HTTP client", error=str(e))
finally:
self.langflow_http_client = None
# Close OpenSearch client if it exists
if self.opensearch is not None:
try:
await self.opensearch.close()
logger.info("Closed OpenSearch client")
except Exception as e:
logger.error("Failed to close OpenSearch client", error=str(e))
finally:
self.opensearch = None
# Close Langflow client if it exists (also an AsyncOpenAI client)
if self.langflow_client is not None:
try:
await self.langflow_client.close()
logger.info("Closed Langflow client")
except Exception as e:
logger.error("Failed to close Langflow client", error=str(e))
finally:
self.langflow_client = None
async def langflow_request(self, method: str, endpoint: str, **kwargs):
"""Central method for all Langflow API requests"""
api_key = await generate_langflow_api_key()

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@ -21,7 +21,7 @@ class ConnectorService:
task_service=None,
session_manager=None,
):
self.openai_client = patched_async_client
self.clients = patched_async_client # Store the clients object to access the property
self.process_pool = process_pool
self.embed_model = embed_model
self.index_name = index_name

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@ -470,7 +470,7 @@ async def initialize_services():
session_manager=session_manager,
)
openrag_connector_service = ConnectorService(
patched_async_client=clients.patched_async_client,
patched_async_client=clients, # Pass the clients object itself
process_pool=process_pool,
embed_model=get_embedding_model(),
index_name=INDEX_NAME,
@ -1108,6 +1108,8 @@ async def create_app():
@app.on_event("shutdown")
async def shutdown_event():
await cleanup_subscriptions_proper(services)
# Cleanup async clients
await clients.cleanup()
return app

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@ -170,8 +170,9 @@ class EnvManager:
"""
self.config.validation_errors.clear()
# Always validate OpenAI API key
if not validate_openai_api_key(self.config.openai_api_key):
# OpenAI API key is now optional (can be provided during onboarding)
# Only validate format if a key is provided
if self.config.openai_api_key and not validate_openai_api_key(self.config.openai_api_key):
self.config.validation_errors["openai_api_key"] = (
"Invalid OpenAI API key format (should start with sk-)"
)
@ -268,7 +269,9 @@ class EnvManager:
f.write(f"LANGFLOW_URL_INGEST_FLOW_ID={self._quote_env_value(self.config.langflow_url_ingest_flow_id)}\n")
f.write(f"NUDGES_FLOW_ID={self._quote_env_value(self.config.nudges_flow_id)}\n")
f.write(f"OPENSEARCH_PASSWORD={self._quote_env_value(self.config.opensearch_password)}\n")
f.write(f"OPENAI_API_KEY={self._quote_env_value(self.config.openai_api_key)}\n")
# Only write OpenAI API key if provided (can be set during onboarding instead)
if self.config.openai_api_key:
f.write(f"OPENAI_API_KEY={self._quote_env_value(self.config.openai_api_key)}\n")
f.write(
f"OPENRAG_DOCUMENTS_PATHS={self._quote_env_value(self.config.openrag_documents_paths)}\n"
)
@ -345,7 +348,7 @@ class EnvManager:
def get_no_auth_setup_fields(self) -> List[tuple[str, str, str, bool]]:
"""Get fields required for no-auth setup mode. Returns (field_name, display_name, placeholder, can_generate)."""
return [
("openai_api_key", "OpenAI API Key", "sk-...", False),
("openai_api_key", "OpenAI API Key", "sk-... or leave empty", False),
(
"opensearch_password",
"OpenSearch Password",

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@ -203,12 +203,16 @@ class ConfigScreen(Screen):
yield Static(" ")
# OpenAI API Key
yield Label("OpenAI API Key *")
yield Label("OpenAI API Key")
# Where to create OpenAI keys (helper above the box)
yield Static(
Text("Get a key: https://platform.openai.com/api-keys", style="dim"),
classes="helper-text",
)
yield Static(
Text("Can also be provided during onboarding", style="dim italic"),
classes="helper-text",
)
current_value = getattr(self.env_manager.config, "openai_api_key", "")
with Horizontal(id="openai-key-row"):
input_widget = Input(