import faulthandler import importlib.util import json import logging import os import platform import sys import threading from contextlib import asynccontextmanager from functools import partial from pathlib import Path from typing import Optional import uvicorn # Enable Python fault handler to get stack traces on segfaults faulthandler.enable() # Import memory tracking (if available) try: from letta.monitoring import RequestSizeMonitoringMiddleware, get_memory_tracker, identify_upload_endpoints MEMORY_TRACKING_ENABLED = True except ImportError: MEMORY_TRACKING_ENABLED = False from fastapi import FastAPI, Request from fastapi.exceptions import RequestValidationError from fastapi.responses import JSONResponse from marshmallow import ValidationError from sqlalchemy.exc import IntegrityError, OperationalError from starlette.middleware.cors import CORSMiddleware from letta.__init__ import __version__ as letta_version from letta.agents.exceptions import IncompatibleAgentType from letta.constants import ADMIN_PREFIX, API_PREFIX, OPENAI_API_PREFIX from letta.errors import ( AgentExportIdMappingError, AgentExportProcessingError, AgentFileImportError, AgentNotFoundForExportError, BedrockPermissionError, HandleNotFoundError, LettaAgentNotFoundError, LettaExpiredError, LettaInvalidArgumentError, LettaInvalidMCPSchemaError, LettaMCPConnectionError, LettaMCPTimeoutError, LettaServiceUnavailableError, LettaToolCreateError, LettaToolNameConflictError, LettaUnsupportedFileUploadError, LettaUserNotFoundError, LLMAuthenticationError, LLMError, LLMProviderOverloaded, LLMRateLimitError, LLMTimeoutError, PendingApprovalError, ) from letta.helpers.pinecone_utils import get_pinecone_indices, should_use_pinecone, upsert_pinecone_indices from letta.jobs.scheduler import start_scheduler_with_leader_election from letta.log import get_logger from letta.orm.errors import DatabaseTimeoutError, ForeignKeyConstraintViolationError, NoResultFound, UniqueConstraintViolationError from letta.otel.tracing import get_trace_id from letta.schemas.letta_message import create_letta_message_union_schema, create_letta_ping_schema from letta.schemas.letta_message_content import ( create_letta_assistant_message_content_union_schema, create_letta_message_content_union_schema, create_letta_user_message_content_union_schema, ) from letta.server.constants import REST_DEFAULT_PORT from letta.server.db import db_registry from letta.server.global_exception_handler import setup_global_exception_handlers # NOTE(charles): these are extra routes that are not part of v1 but we still need to mount to pass tests from letta.server.rest_api.auth.index import setup_auth_router # TODO: probably remove right? from letta.server.rest_api.interface import StreamingServerInterface from letta.server.rest_api.middleware import CheckPasswordMiddleware, LoggingMiddleware, ProfilerContextMiddleware from letta.server.rest_api.routers.v1 import ROUTERS as v1_routes from letta.server.rest_api.routers.v1.organizations import router as organizations_router from letta.server.rest_api.routers.v1.users import router as users_router # TODO: decide on admin from letta.server.rest_api.static_files import mount_static_files from letta.server.rest_api.utils import SENTRY_ENABLED from letta.server.server import SyncServer from letta.settings import settings, telemetry_settings from letta.validators import PATH_VALIDATORS, PRIMITIVE_ID_PATTERNS if SENTRY_ENABLED: import sentry_sdk IS_WINDOWS = platform.system() == "Windows" # NOTE(charles): @ethan I had to add this to get the global as the bottom to work interface: type = StreamingServerInterface server = SyncServer(default_interface_factory=lambda: interface()) logger = get_logger(__name__) def generate_openapi_schema(app: FastAPI): # Update the OpenAPI schema if not app.openapi_schema: app.openapi_schema = app.openapi() letta_docs = app.openapi_schema.copy() letta_docs["paths"] = {k: v for k, v in letta_docs["paths"].items() if not k.startswith("/openai")} letta_docs["info"]["title"] = "Letta API" letta_docs["components"]["schemas"]["LettaMessageUnion"] = create_letta_message_union_schema() letta_docs["components"]["schemas"]["LettaMessageContentUnion"] = create_letta_message_content_union_schema() letta_docs["components"]["schemas"]["LettaAssistantMessageContentUnion"] = create_letta_assistant_message_content_union_schema() letta_docs["components"]["schemas"]["LettaUserMessageContentUnion"] = create_letta_user_message_content_union_schema() letta_docs["components"]["schemas"]["LettaPing"] = create_letta_ping_schema() # Update the app's schema with our modified version app.openapi_schema = letta_docs for name, docs in [ ( "letta", letta_docs, ), ]: if settings.cors_origins: docs["servers"] = [{"url": host} for host in settings.cors_origins] Path(f"openapi_{name}.json").write_text(json.dumps(docs, indent=2)) # middleware that only allows requests to pass through if user provides a password thats randomly generated and stored in memory def generate_password(): import secrets return secrets.token_urlsafe(16) random_password = os.getenv("LETTA_SERVER_PASSWORD") or generate_password() @asynccontextmanager async def lifespan(app_: FastAPI): """ FastAPI lifespan context manager with setup before the app starts pre-yield and on shutdown after the yield. """ worker_id = os.getpid() # Initialize memory tracking if MEMORY_TRACKING_ENABLED: logger.info(f"[Worker {worker_id}] Initializing memory tracking") # Get the global tracker instance tracker = get_memory_tracker(enable_background_monitor=True, monitor_interval=5) # Explicitly start the background monitor (won't wait for first tracked operation) await tracker.start_background_monitor() logger.info(f"[Worker {worker_id}] Memory tracking enabled - monitoring every 5s with proactive alerts") # Initialize event loop watchdog try: import asyncio from letta.monitoring.event_loop_watchdog import start_watchdog loop = asyncio.get_running_loop() start_watchdog(loop, check_interval=5.0, timeout_threshold=15.0) logger.info(f"[Worker {worker_id}] Event loop watchdog started") except Exception as e: logger.warning(f"[Worker {worker_id}] Failed to start watchdog: {e}") if telemetry_settings.profiler: try: import googlecloudprofiler googlecloudprofiler.start( service="memgpt-server", service_version=str(letta_version), verbose=3, ) logger.info("Profiler started.") except Exception as exc: logger.info("Profiler not enabled: %", exc) # logger.info(f"[Worker {worker_id}] Starting lifespan initialization") # logger.info(f"[Worker {worker_id}] Initializing database connections") # db_registry.initialize_async() # logger.info(f"[Worker {worker_id}] Database connections initialized") if should_use_pinecone(): if settings.upsert_pinecone_indices: logger.info(f"[Worker {worker_id}] Upserting pinecone indices: {get_pinecone_indices()}") await upsert_pinecone_indices() logger.info(f"[Worker {worker_id}] Upserted pinecone indices") else: logger.info(f"[Worker {worker_id}] Enabled pinecone") else: logger.info(f"[Worker {worker_id}] Disabled pinecone") logger.info(f"[Worker {worker_id}] Starting scheduler with leader election") global server await server.init_async() try: await start_scheduler_with_leader_election(server) logger.info(f"[Worker {worker_id}] Scheduler initialization completed") except Exception as e: logger.error(f"[Worker {worker_id}] Scheduler initialization failed: {e}", exc_info=True) logger.info(f"[Worker {worker_id}] Lifespan startup completed") yield # Cleanup on shutdown logger.info(f"[Worker {worker_id}] Starting lifespan shutdown") # Report memory usage before shutdown if MEMORY_TRACKING_ENABLED: logger.info(f"[Worker {worker_id}] Generating final memory report") tracker = get_memory_tracker() report = tracker.get_report() logger.info(f"[Worker {worker_id}] Memory report:\n{report}") try: from letta.jobs.scheduler import shutdown_scheduler_and_release_lock await shutdown_scheduler_and_release_lock() logger.info(f"[Worker {worker_id}] Scheduler shutdown completed") except Exception as e: logger.error(f"[Worker {worker_id}] Scheduler shutdown failed: {e}", exc_info=True) # Cleanup SQLAlchemy instrumentation if not settings.disable_tracing and settings.sqlalchemy_tracing: try: from letta.otel.sqlalchemy_instrumentation_integration import teardown_letta_db_instrumentation teardown_letta_db_instrumentation() logger.info(f"[Worker {worker_id}] SQLAlchemy instrumentation shutdown completed") except Exception as e: logger.warning(f"[Worker {worker_id}] SQLAlchemy instrumentation shutdown failed: {e}") logger.info(f"[Worker {worker_id}] Lifespan shutdown completed") def create_application() -> "FastAPI": """the application start routine""" # global server # server = SyncServer(default_interface_factory=lambda: interface()) print(f"\n[[ Letta server // v{letta_version} ]]") if SENTRY_ENABLED: sentry_sdk.init( dsn=os.getenv("SENTRY_DSN"), environment=os.getenv("LETTA_ENVIRONMENT", "undefined"), traces_sample_rate=1.0, _experiments={ "continuous_profiling_auto_start": True, }, ) if telemetry_settings.enable_datadog: try: dd_env = settings.environment or "development" print(f"▶ Initializing Datadog profiling (env={dd_env})") # Configure environment variables before importing ddtrace (must be set in environment before importing ddtrace) os.environ.setdefault("DD_ENV", dd_env) os.environ.setdefault("DD_SERVICE", telemetry_settings.datadog_service_name) os.environ.setdefault("DD_VERSION", letta_version) os.environ.setdefault("DD_AGENT_HOST", telemetry_settings.datadog_agent_host) os.environ.setdefault("DD_TRACE_AGENT_PORT", str(telemetry_settings.datadog_agent_port)) os.environ.setdefault("DD_PROFILING_ENABLED", "true") os.environ.setdefault("DD_PROFILING_MEMORY_ENABLED", str(telemetry_settings.datadog_profiling_memory_enabled).lower()) os.environ.setdefault("DD_PROFILING_HEAP_ENABLED", str(telemetry_settings.datadog_profiling_heap_enabled).lower()) from ddtrace.profiling import Profiler # Initialize and start profiler profiler = Profiler( env=dd_env, service=telemetry_settings.datadog_service_name, version=letta_version, ) profiler.start() # Log Git metadata for source code integration git_info = "" if telemetry_settings.datadog_git_commit_sha: git_info = f", commit={telemetry_settings.datadog_git_commit_sha[:8]}" if telemetry_settings.datadog_git_repository_url: git_info += f", repo={telemetry_settings.datadog_git_repository_url}" logger.info( f"Datadog profiling enabled: env={dd_env}, " f"service={telemetry_settings.datadog_service_name}, " f"agent={telemetry_settings.datadog_agent_host}:{telemetry_settings.datadog_agent_port}{git_info}" ) except Exception as e: logger.error(f"Failed to initialize Datadog profiling: {e}", exc_info=True) if SENTRY_ENABLED: sentry_sdk.capture_exception(e) # Don't fail application startup if Datadog initialization fails debug_mode = "--debug" in sys.argv app = FastAPI( swagger_ui_parameters={"docExpansion": "none"}, # openapi_tags=TAGS_METADATA, title="Letta", summary="Create LLM agents with long-term memory and custom tools 📚🦙", version=letta_version, debug=debug_mode, # if True, the stack trace will be printed in the response lifespan=lifespan, ) # === Global Exception Handlers === # Set up handlers for exceptions outside of request context (background tasks, threads, etc.) setup_global_exception_handlers() # === Exception Handlers === # TODO (cliandy): move to separate file @app.exception_handler(Exception) async def generic_error_handler(request: Request, exc: Exception): # Log with structured context request_context = { "method": request.method, "url": str(request.url), "path": request.url.path, } # Extract user context if available user_context = {} if hasattr(request.state, "user_id"): user_context["user_id"] = request.state.user_id if hasattr(request.state, "org_id"): user_context["org_id"] = request.state.org_id logger.error( f"Unhandled error: {exc.__class__.__name__}: {str(exc)}", extra={ "exception_type": exc.__class__.__name__, "exception_message": str(exc), "exception_module": exc.__class__.__module__, "request": request_context, "user": user_context, }, exc_info=True, ) if SENTRY_ENABLED: sentry_sdk.capture_exception(exc) return JSONResponse( status_code=500, content={ "detail": "An unknown error occurred", # Only include error details in debug/development mode # "debug_info": str(exc) if settings.debug else None }, ) # Reasoning for this handler is the default path validation logic returns a pretty gnarly error message # because of the uuid4 pattern. This handler rewrites the error message to be more user-friendly and less intimidating. @app.exception_handler(RequestValidationError) async def custom_request_validation_handler(request: Request, exc: RequestValidationError): """Generalize path `_id` validation messages and include example IDs. - Rewrites string pattern/length mismatches to "primitive-{uuid4}" - Preserves stringified `detail` and includes `trace_id` - Adds top-level `examples` from `PATH_VALIDATORS` for offending params """ errors = exc.errors() examples_set: set[str] = set() content = {"trace_id": get_trace_id() or ""} for err in errors: fastapi_error_loc = err.get("loc", []) # only rewrite path param validation errors (should expand in future) if len(fastapi_error_loc) != 2 or fastapi_error_loc[0] != "path": continue # re-write the error message parameter_name = fastapi_error_loc[1] err_type = err.get("type") if ( err_type in {"string_pattern_mismatch", "string_too_short", "string_too_long"} and isinstance(parameter_name, str) and parameter_name.endswith("_id") ): primitive = parameter_name[:-3] validator = PATH_VALIDATORS.get(primitive) if validator: # simplify default error message err["msg"] = f"String should match pattern '{primitive}-{{uuid4}}'" # rewrite as string_pattern_mismatch even if the input length is too short or too long (more intuitive for user) if err_type in {"string_too_short", "string_too_long"}: # FYI: the pattern is the same as the pattern inthe validator object but for some reason the validator object # doesn't let you access it directly (unless you call into pydantic layer) err["ctx"] = {"pattern": PRIMITIVE_ID_PATTERNS[primitive].pattern} err["type"] = "string_pattern_mismatch" # collect examples for top-level examples field (prevents duplicates and allows for multiple examples for multiple primitives) # e.g. if there are 2 malformed agent ids, the examples field will contain 2 examples for the agent primitive # e.g. if there is a malformed agent id and malformed folder id, the examples field will contain both examples, for both the agent and folder primitives try: exs = getattr(validator, "examples", None) if exs: for ex in exs: examples_set.add(ex) else: examples_set.add(f"{primitive}-123e4567-e89b-42d3-8456-426614174000") except Exception: examples_set.add(f"{primitive}-123e4567-e89b-42d3-8456-426614174000") # Preserve current API contract: stringified list of errors content["detail"] = repr(errors) if examples_set: content["examples"] = sorted(examples_set) return JSONResponse(status_code=422, content=content) async def error_handler_with_code(request: Request, exc: Exception, code: int, detail: str | None = None): logger.error(f"{type(exc).__name__}", exc_info=exc) if not detail: detail = str(exc) return JSONResponse( status_code=code, content={"detail": detail}, ) _error_handler_400 = partial(error_handler_with_code, code=400) _error_handler_404 = partial(error_handler_with_code, code=404) _error_handler_404_agent = partial(_error_handler_404, detail="Agent not found") _error_handler_404_user = partial(_error_handler_404, detail="User not found") _error_handler_408 = partial(error_handler_with_code, code=408) _error_handler_409 = partial(error_handler_with_code, code=409) _error_handler_410 = partial(error_handler_with_code, code=410) _error_handler_415 = partial(error_handler_with_code, code=415) _error_handler_422 = partial(error_handler_with_code, code=422) _error_handler_500 = partial(error_handler_with_code, code=500) _error_handler_503 = partial(error_handler_with_code, code=503) # 400 Bad Request errors app.add_exception_handler(LettaInvalidArgumentError, _error_handler_400) app.add_exception_handler(LettaToolCreateError, _error_handler_400) app.add_exception_handler(LettaToolNameConflictError, _error_handler_400) app.add_exception_handler(AgentFileImportError, _error_handler_400) app.add_exception_handler(ValueError, _error_handler_400) # 404 Not Found errors app.add_exception_handler(NoResultFound, _error_handler_404) app.add_exception_handler(LettaAgentNotFoundError, _error_handler_404_agent) app.add_exception_handler(LettaUserNotFoundError, _error_handler_404_user) app.add_exception_handler(AgentNotFoundForExportError, _error_handler_404) app.add_exception_handler(HandleNotFoundError, _error_handler_404) # 410 Expired errors app.add_exception_handler(LettaExpiredError, _error_handler_410) # 408 Timeout errors app.add_exception_handler(LettaMCPTimeoutError, _error_handler_408) app.add_exception_handler(LettaInvalidMCPSchemaError, _error_handler_400) # 409 Conflict errors app.add_exception_handler(ForeignKeyConstraintViolationError, _error_handler_409) app.add_exception_handler(UniqueConstraintViolationError, _error_handler_409) app.add_exception_handler(IntegrityError, _error_handler_409) app.add_exception_handler(PendingApprovalError, _error_handler_409) # 415 Unsupported Media Type errors app.add_exception_handler(LettaUnsupportedFileUploadError, _error_handler_415) # 422 Validation errors app.add_exception_handler(ValidationError, _error_handler_422) # 500 Internal Server errors app.add_exception_handler(AgentExportIdMappingError, _error_handler_500) app.add_exception_handler(AgentExportProcessingError, _error_handler_500) # 503 Service Unavailable errors app.add_exception_handler(OperationalError, _error_handler_503) app.add_exception_handler(LettaServiceUnavailableError, _error_handler_503) app.add_exception_handler(LLMProviderOverloaded, _error_handler_503) @app.exception_handler(IncompatibleAgentType) async def handle_incompatible_agent_type(request: Request, exc: IncompatibleAgentType): logger.error("Incompatible agent types. Expected: %s, Actual: %s", exc.expected_type, exc.actual_type) if SENTRY_ENABLED: sentry_sdk.capture_exception(exc) return JSONResponse( status_code=400, content={ "detail": str(exc), "expected_type": exc.expected_type, "actual_type": exc.actual_type, }, ) @app.exception_handler(DatabaseTimeoutError) async def database_timeout_error_handler(request: Request, exc: DatabaseTimeoutError): logger.error(f"Timeout occurred: {exc}. Original exception: {exc.original_exception}") if SENTRY_ENABLED: sentry_sdk.capture_exception(exc) return JSONResponse( status_code=503, content={"detail": "The database is temporarily unavailable. Please try again later."}, ) @app.exception_handler(BedrockPermissionError) async def bedrock_permission_error_handler(request, exc: BedrockPermissionError): logger.error("Bedrock permission denied.") return JSONResponse( status_code=403, content={ "error": { "type": "bedrock_permission_denied", "message": "Unable to access the required AI model. Please check your Bedrock permissions or contact support.", "detail": {str(exc)}, } }, ) @app.exception_handler(LLMTimeoutError) async def llm_timeout_error_handler(request: Request, exc: LLMTimeoutError): return JSONResponse( status_code=504, content={ "error": { "type": "llm_timeout", "message": "The LLM request timed out. Please try again.", "detail": str(exc), } }, ) @app.exception_handler(LLMRateLimitError) async def llm_rate_limit_error_handler(request: Request, exc: LLMRateLimitError): return JSONResponse( status_code=429, content={ "error": { "type": "llm_rate_limit", "message": "Rate limit exceeded for LLM model provider. Please wait before making another request.", "detail": str(exc), } }, ) @app.exception_handler(LLMAuthenticationError) async def llm_auth_error_handler(request: Request, exc: LLMAuthenticationError): return JSONResponse( status_code=401, content={ "error": { "type": "llm_authentication", "message": "Authentication failed with the LLM model provider.", "detail": str(exc), } }, ) @app.exception_handler(LettaMCPConnectionError) async def mcp_connection_error_handler(request: Request, exc: LettaMCPConnectionError): return JSONResponse( status_code=502, content={ "error": { "type": "mcp_connection_error", "message": "Failed to connect to MCP server.", "detail": str(exc), } }, ) @app.exception_handler(LLMError) async def llm_error_handler(request: Request, exc: LLMError): return JSONResponse( status_code=502, content={ "error": { "type": "llm_error", "message": "An error occurred with the LLM request.", "detail": str(exc), } }, ) settings.cors_origins.append("https://app.letta.com") if (os.getenv("LETTA_SERVER_SECURE") == "true") or "--secure" in sys.argv: print(f"▶ Using secure mode with password: {random_password}") app.add_middleware(CheckPasswordMiddleware, password=random_password) # Add reverse proxy middleware to handle X-Forwarded-* headers # app.add_middleware(ReverseProxyMiddleware, base_path=settings.server_base_path) if telemetry_settings.profiler: app.add_middleware(ProfilerContextMiddleware) # Add unified logging middleware - enriches log context and logs exceptions app.add_middleware(LoggingMiddleware) # Add request size monitoring middleware to detect large uploads if MEMORY_TRACKING_ENABLED: app.add_middleware(RequestSizeMonitoringMiddleware) logger.info("Request size monitoring middleware enabled") # Identify potential upload endpoints identify_upload_endpoints(app) app.add_middleware( CORSMiddleware, allow_origins=settings.cors_origins, allow_credentials=True, allow_methods=["*"], allow_headers=["*"], ) # Set up OpenTelemetry tracing otlp_endpoint = settings.otel_exporter_otlp_endpoint if otlp_endpoint and not settings.disable_tracing: print(f"▶ Using OTLP tracing with endpoint: {otlp_endpoint}") env_name_suffix = os.getenv("ENV_NAME") service_name = f"letta-server-{env_name_suffix.lower()}" if env_name_suffix else "letta-server" from letta.otel.metrics import setup_metrics from letta.otel.tracing import setup_tracing setup_tracing( endpoint=otlp_endpoint, app=app, service_name=service_name, ) setup_metrics(endpoint=otlp_endpoint, app=app, service_name=service_name) # Set up SQLAlchemy synchronous operation instrumentation if settings.sqlalchemy_tracing: from letta.otel.sqlalchemy_instrumentation_integration import setup_letta_db_instrumentation try: setup_letta_db_instrumentation( enable_joined_monitoring=True, # Monitor joined loading operations sql_truncate_length=1500, # Longer SQL statements for debugging ) print("▶ SQLAlchemy synchronous operation instrumentation enabled") except Exception as e: logger.warning(f"Failed to setup SQLAlchemy instrumentation: {e}") # Don't fail startup if instrumentation fails # Ensure our validation handler overrides tracing's handler when tracing is enabled app.add_exception_handler(RequestValidationError, custom_request_validation_handler) for route in v1_routes: app.include_router(route, prefix=API_PREFIX) # this gives undocumented routes for "latest" and bare api calls. # we should always tie this to the newest version of the api. # app.include_router(route, prefix="", include_in_schema=False) app.include_router(route, prefix="/latest", include_in_schema=False) # NOTE: ethan these are the extra routes # TODO(ethan) remove # admin/users app.include_router(users_router, prefix=ADMIN_PREFIX) app.include_router(organizations_router, prefix=ADMIN_PREFIX) # /api/auth endpoints app.include_router(setup_auth_router(server, interface, random_password), prefix=API_PREFIX) # / static files mount_static_files(app) no_generation = "--no-generation" in sys.argv # Generate OpenAPI schema after all routes are mounted if not no_generation: generate_openapi_schema(app) return app app = create_application() def start_server( port: Optional[int] = None, host: Optional[str] = None, debug: bool = False, reload: bool = False, ): """Convenience method to start the server from within Python""" if debug: from letta.server.server import logger as server_logger # Set the logging level server_logger.setLevel(logging.DEBUG) # Create a StreamHandler stream_handler = logging.StreamHandler() # Set the formatter (optional) formatter = logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s") stream_handler.setFormatter(formatter) # Add the handler to the logger server_logger.addHandler(stream_handler) # Experimental UV Loop Support try: if settings.use_uvloop: print("Running server asyncio loop on uvloop...") import asyncio import uvloop asyncio.set_event_loop_policy(uvloop.EventLoopPolicy()) except: pass if (os.getenv("LOCAL_HTTPS") == "true") or "--localhttps" in sys.argv: print(f"▶ Server running at: https://{host or 'localhost'}:{port or REST_DEFAULT_PORT}") print("▶ View using ADE at: https://app.letta.com/development-servers/local/dashboard\n") if importlib.util.find_spec("granian") is not None and settings.use_granian: from granian import Granian # Experimental Granian engine Granian( target="letta.server.rest_api.app:app", # factory=True, interface="asgi", address=host or "127.0.0.1", # Note granian address must be an ip address port=port or REST_DEFAULT_PORT, workers=settings.uvicorn_workers, # runtime_blocking_threads= # runtime_threads= reload=reload or settings.uvicorn_reload, reload_paths=["letta/"], reload_ignore_worker_failure=True, reload_tick=4000, # set to 4s to prevent crashing on weird state # log_level="info" ssl_keyfile="certs/localhost-key.pem", ssl_cert="certs/localhost.pem", ).serve() else: uvicorn.run( "letta.server.rest_api.app:app", host=host or "localhost", port=port or REST_DEFAULT_PORT, workers=settings.uvicorn_workers, reload=reload or settings.uvicorn_reload, timeout_keep_alive=settings.uvicorn_timeout_keep_alive, ssl_keyfile="certs/localhost-key.pem", ssl_certfile="certs/localhost.pem", ) else: if IS_WINDOWS: # Windows doesn't those the fancy unicode characters print(f"Server running at: http://{host or 'localhost'}:{port or REST_DEFAULT_PORT}") print("View using ADE at: https://app.letta.com/development-servers/local/dashboard\n") else: print(f"▶ Server running at: http://{host or 'localhost'}:{port or REST_DEFAULT_PORT}") print("▶ View using ADE at: https://app.letta.com/development-servers/local/dashboard\n") if importlib.util.find_spec("granian") is not None and settings.use_granian: # Experimental Granian engine from granian import Granian Granian( target="letta.server.rest_api.app:app", # factory=True, interface="asgi", address=host or "127.0.0.1", # Note granian address must be an ip address port=port or REST_DEFAULT_PORT, workers=settings.uvicorn_workers, # runtime_blocking_threads= # runtime_threads= reload=reload or settings.uvicorn_reload, reload_paths=["letta/"], reload_ignore_worker_failure=True, reload_tick=4000, # set to 4s to prevent crashing on weird state # log_level="info" ).serve() else: uvicorn.run( "letta.server.rest_api.app:app", host=host or "localhost", port=port or REST_DEFAULT_PORT, workers=settings.uvicorn_workers, reload=reload or settings.uvicorn_reload, timeout_keep_alive=settings.uvicorn_timeout_keep_alive, )