Merge pull request #338 from langflow-ai/tui-optional-openai-key
Tui optional OpenAI key
This commit is contained in:
commit
a35235eb59
6 changed files with 169 additions and 11 deletions
4
Makefile
4
Makefile
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@ -2,10 +2,12 @@
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# Provides easy commands for development workflow
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# Load variables from .env if present so `make` commands pick them up
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# Strip quotes from values to avoid issues with tools that don't handle them like python-dotenv does
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ifneq (,$(wildcard .env))
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include .env
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# Export all simple KEY=VALUE pairs to the environment for child processes
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export $(shell sed -n 's/^\([A-Za-z_][A-Za-z0-9_]*\)=.*/\1/p' .env)
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# Strip single quotes from all exported variables
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$(foreach var,$(shell sed -n 's/^\([A-Za-z_][A-Za-z0-9_]*\)=.*/\1/p' .env),$(eval $(var):=$(shell echo $($(var)) | sed "s/^'//;s/'$$//")))
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endif
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.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:
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self.opensearch = None
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self.langflow_client = None
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self.langflow_http_client = None
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self.patched_async_client = None
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self._patched_async_client = None # Private attribute
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self._client_init_lock = __import__('threading').Lock() # Lock for thread-safe initialization
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self.converter = None
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async def initialize(self):
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@ -318,8 +319,15 @@ class AppClients:
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"No Langflow client initialized yet, will attempt later on first use"
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)
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# Initialize patched OpenAI client
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self.patched_async_client = patch_openai_with_mcp(AsyncOpenAI())
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# Initialize patched OpenAI client if API key is available
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# This allows the app to start even if OPENAI_API_KEY is not set yet
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# (e.g., when it will be provided during onboarding)
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# The property will handle lazy initialization with probe when first accessed
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openai_key = os.getenv("OPENAI_API_KEY")
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if openai_key:
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logger.info("OpenAI API key found in environment - will be initialized lazily on first use with HTTP/2 probe")
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else:
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logger.info("OpenAI API key not found in environment - will be initialized on first use if needed")
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# Initialize document converter
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self.converter = create_document_converter(ocr_engine=DOCLING_OCR_ENGINE)
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@ -350,6 +358,145 @@ class AppClients:
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self.langflow_client = None
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return self.langflow_client
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@property
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def patched_async_client(self):
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"""
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Property that ensures OpenAI client is initialized on first access.
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This allows lazy initialization so the app can start without an API key.
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Note: The client is a long-lived singleton that should be closed via cleanup().
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Thread-safe via lock to prevent concurrent initialization attempts.
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"""
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# Quick check without lock
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if self._patched_async_client is not None:
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return self._patched_async_client
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# Use lock to ensure only one thread initializes
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with self._client_init_lock:
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# Double-check after acquiring lock
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if self._patched_async_client is not None:
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return self._patched_async_client
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# Try to initialize the client on-demand
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# First check if OPENAI_API_KEY is in environment
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openai_key = os.getenv("OPENAI_API_KEY")
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if not openai_key:
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# Try to get from config (in case it was set during onboarding)
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try:
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config = get_openrag_config()
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if config and config.provider and config.provider.api_key:
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openai_key = config.provider.api_key
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# Set it in environment so AsyncOpenAI can pick it up
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os.environ["OPENAI_API_KEY"] = openai_key
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logger.info("Loaded OpenAI API key from config file")
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except Exception as e:
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logger.debug("Could not load OpenAI key from config", error=str(e))
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# Try to initialize the client - AsyncOpenAI() will read from environment
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# We'll try HTTP/2 first with a probe, then fall back to HTTP/1.1 if it times out
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import asyncio
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import concurrent.futures
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import threading
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async def probe_and_initialize():
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# Try HTTP/2 first (default)
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client_http2 = patch_openai_with_mcp(AsyncOpenAI())
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logger.info("Probing OpenAI client with HTTP/2...")
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try:
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# Probe with a small embedding and short timeout
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await asyncio.wait_for(
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client_http2.embeddings.create(
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model='text-embedding-3-small',
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input=['test']
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),
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timeout=5.0
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)
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logger.info("OpenAI client initialized with HTTP/2 (probe successful)")
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return client_http2
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except (asyncio.TimeoutError, Exception) as probe_error:
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logger.warning("HTTP/2 probe failed, falling back to HTTP/1.1", error=str(probe_error))
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# Close the HTTP/2 client
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try:
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await client_http2.close()
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except Exception:
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pass
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# Fall back to HTTP/1.1 with explicit timeout settings
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http_client = httpx.AsyncClient(
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http2=False,
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timeout=httpx.Timeout(60.0, connect=10.0)
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)
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client_http1 = patch_openai_with_mcp(
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AsyncOpenAI(http_client=http_client)
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)
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logger.info("OpenAI client initialized with HTTP/1.1 (fallback)")
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return client_http1
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def run_probe_in_thread():
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"""Run the async probe in a new thread with its own event loop"""
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loop = asyncio.new_event_loop()
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asyncio.set_event_loop(loop)
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try:
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return loop.run_until_complete(probe_and_initialize())
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finally:
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loop.close()
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try:
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# Run the probe in a separate thread with its own event loop
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with concurrent.futures.ThreadPoolExecutor(max_workers=1) as executor:
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future = executor.submit(run_probe_in_thread)
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self._patched_async_client = future.result(timeout=15)
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logger.info("Successfully initialized OpenAI client")
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except Exception as e:
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logger.error(f"Failed to initialize OpenAI client: {e.__class__.__name__}: {str(e)}")
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raise ValueError(f"Failed to initialize OpenAI client: {str(e)}. Please complete onboarding or set OPENAI_API_KEY environment variable.")
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return self._patched_async_client
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async def cleanup(self):
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"""Cleanup resources - should be called on application shutdown"""
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# Close AsyncOpenAI client if it was created
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if self._patched_async_client is not None:
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try:
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await self._patched_async_client.close()
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logger.info("Closed AsyncOpenAI client")
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except Exception as e:
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logger.error("Failed to close AsyncOpenAI client", error=str(e))
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finally:
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self._patched_async_client = None
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# Close Langflow HTTP client if it exists
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if self.langflow_http_client is not None:
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try:
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await self.langflow_http_client.aclose()
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logger.info("Closed Langflow HTTP client")
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except Exception as e:
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logger.error("Failed to close Langflow HTTP client", error=str(e))
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finally:
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self.langflow_http_client = None
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# Close OpenSearch client if it exists
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if self.opensearch is not None:
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try:
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await self.opensearch.close()
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logger.info("Closed OpenSearch client")
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except Exception as e:
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logger.error("Failed to close OpenSearch client", error=str(e))
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finally:
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self.opensearch = None
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# Close Langflow client if it exists (also an AsyncOpenAI client)
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if self.langflow_client is not None:
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try:
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await self.langflow_client.close()
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logger.info("Closed Langflow client")
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except Exception as e:
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logger.error("Failed to close Langflow client", error=str(e))
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finally:
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self.langflow_client = None
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async def langflow_request(self, method: str, endpoint: str, **kwargs):
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"""Central method for all Langflow API requests"""
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api_key = await generate_langflow_api_key()
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@ -21,7 +21,7 @@ class ConnectorService:
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task_service=None,
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session_manager=None,
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):
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self.openai_client = patched_async_client
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self.clients = patched_async_client # Store the clients object to access the property
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self.process_pool = process_pool
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self.embed_model = embed_model
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self.index_name = index_name
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@ -470,7 +470,7 @@ async def initialize_services():
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session_manager=session_manager,
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)
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openrag_connector_service = ConnectorService(
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patched_async_client=clients.patched_async_client,
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patched_async_client=clients, # Pass the clients object itself
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process_pool=process_pool,
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embed_model=get_embedding_model(),
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index_name=INDEX_NAME,
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@ -1108,6 +1108,8 @@ async def create_app():
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@app.on_event("shutdown")
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async def shutdown_event():
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await cleanup_subscriptions_proper(services)
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# Cleanup async clients
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await clients.cleanup()
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return app
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@ -170,8 +170,9 @@ class EnvManager:
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"""
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self.config.validation_errors.clear()
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# Always validate OpenAI API key
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if not validate_openai_api_key(self.config.openai_api_key):
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# OpenAI API key is now optional (can be provided during onboarding)
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# Only validate format if a key is provided
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if self.config.openai_api_key and not validate_openai_api_key(self.config.openai_api_key):
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self.config.validation_errors["openai_api_key"] = (
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"Invalid OpenAI API key format (should start with sk-)"
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)
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@ -268,7 +269,9 @@ class EnvManager:
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f.write(f"LANGFLOW_URL_INGEST_FLOW_ID={self._quote_env_value(self.config.langflow_url_ingest_flow_id)}\n")
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f.write(f"NUDGES_FLOW_ID={self._quote_env_value(self.config.nudges_flow_id)}\n")
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f.write(f"OPENSEARCH_PASSWORD={self._quote_env_value(self.config.opensearch_password)}\n")
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f.write(f"OPENAI_API_KEY={self._quote_env_value(self.config.openai_api_key)}\n")
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# Only write OpenAI API key if provided (can be set during onboarding instead)
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if self.config.openai_api_key:
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f.write(f"OPENAI_API_KEY={self._quote_env_value(self.config.openai_api_key)}\n")
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f.write(
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f"OPENRAG_DOCUMENTS_PATHS={self._quote_env_value(self.config.openrag_documents_paths)}\n"
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)
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@ -345,7 +348,7 @@ class EnvManager:
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def get_no_auth_setup_fields(self) -> List[tuple[str, str, str, bool]]:
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"""Get fields required for no-auth setup mode. Returns (field_name, display_name, placeholder, can_generate)."""
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return [
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("openai_api_key", "OpenAI API Key", "sk-...", False),
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("openai_api_key", "OpenAI API Key", "sk-... or leave empty", False),
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(
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"opensearch_password",
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"OpenSearch Password",
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@ -203,12 +203,16 @@ class ConfigScreen(Screen):
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yield Static(" ")
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# OpenAI API Key
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yield Label("OpenAI API Key *")
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yield Label("OpenAI API Key")
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# Where to create OpenAI keys (helper above the box)
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yield Static(
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Text("Get a key: https://platform.openai.com/api-keys", style="dim"),
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classes="helper-text",
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)
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yield Static(
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Text("Can also be provided during onboarding", style="dim italic"),
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classes="helper-text",
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)
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current_value = getattr(self.env_manager.config, "openai_api_key", "")
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with Horizontal(id="openai-key-row"):
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input_widget = Input(
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