feat: add profiling and structured logging (#5690)
* test dd build * dd agent in cluster * quick poc * refactor and add logging * remove tracing etc. * add changes to otel logging config * refactor to accept my feedback * finishing touches
This commit is contained in:
Kian Jones
178
letta/log.py
178
letta/log.py
@@ -1,14 +1,136 @@
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import json
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import logging
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import traceback
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from datetime import datetime, timezone
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from logging.config import dictConfig
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from pathlib import Path
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from sys import stdout
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from typing import Optional
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from typing import Any, Optional
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from letta.settings import settings
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from letta.settings import log_settings, settings, telemetry_settings
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selected_log_level = logging.DEBUG if settings.debug else logging.INFO
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class JSONFormatter(logging.Formatter):
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"""
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Custom JSON formatter for structured logging with Datadog integration.
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Outputs logs in JSON format with fields compatible with Datadog log ingestion.
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Automatically includes trace correlation fields when Datadog tracing is enabled.
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Usage:
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Enable JSON logging by setting the environment variable:
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LETTA_LOGGING_JSON_LOGGING=true
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Add custom structured fields to logs using the 'extra' parameter:
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logger.info("User action", extra={"user_id": "123", "action": "login"})
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These fields will be automatically included in the JSON output and
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indexed by Datadog for filtering and analysis.
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Output format:
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{
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"timestamp": "2025-10-23T18:34:24.931739+00:00",
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"level": "INFO",
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"logger": "Letta.module",
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"message": "Log message",
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"module": "module_name",
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"function": "function_name",
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"line": 123,
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"dd.trace_id": "1234567890", # Added when Datadog tracing is enabled
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"dd.span_id": "9876543210", # Added when Datadog tracing is enabled
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"custom_field": "custom_value" # Any extra fields you provide
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}
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"""
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def format(self, record: logging.LogRecord) -> str:
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"""Format log record as JSON with Datadog-compatible fields."""
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# Base log structure
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log_data: dict[str, Any] = {
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"timestamp": datetime.fromtimestamp(record.created, tz=timezone.utc).isoformat(),
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"level": record.levelname,
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"logger": record.name,
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"message": record.getMessage(),
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"module": record.module,
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"function": record.funcName,
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"line": record.lineno,
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}
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# Add Datadog trace correlation if available
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# ddtrace automatically injects these attributes when logging is patched
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if hasattr(record, "dd.trace_id"):
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log_data["dd.trace_id"] = getattr(record, "dd.trace_id")
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if hasattr(record, "dd.span_id"):
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log_data["dd.span_id"] = getattr(record, "dd.span_id")
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if hasattr(record, "dd.service"):
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log_data["dd.service"] = getattr(record, "dd.service")
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if hasattr(record, "dd.env"):
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log_data["dd.env"] = getattr(record, "dd.env")
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if hasattr(record, "dd.version"):
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log_data["dd.version"] = getattr(record, "dd.version")
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# Add exception info if present
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if record.exc_info:
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log_data["exception"] = {
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"type": record.exc_info[0].__name__ if record.exc_info[0] else None,
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"message": str(record.exc_info[1]) if record.exc_info[1] else None,
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"stacktrace": "".join(traceback.format_exception(*record.exc_info)),
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}
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# Add any extra fields from the log record
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# These are custom fields passed via logging.info("msg", extra={...})
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for key, value in record.__dict__.items():
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if key not in [
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"name",
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"msg",
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"args",
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"created",
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"filename",
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"funcName",
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"levelname",
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"levelno",
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"lineno",
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"module",
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"msecs",
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"message",
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"pathname",
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"process",
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"processName",
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"relativeCreated",
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"thread",
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"threadName",
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"exc_info",
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"exc_text",
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"stack_info",
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"dd_env",
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"dd_service",
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] and not key.startswith("dd."):
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log_data[key] = value
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return json.dumps(log_data, default=str)
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class DatadogEnvFilter(logging.Filter):
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"""
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Logging filter that adds Datadog-specific attributes to log records.
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This enables log-trace correlation by injecting environment and service metadata
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that Datadog can use to link logs with traces and other telemetry data.
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"""
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def filter(self, record: logging.LogRecord) -> bool:
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"""Add Datadog attributes to log record if Datadog is enabled."""
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if telemetry_settings.enable_datadog:
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record.dd_env = telemetry_settings.datadog_env
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record.dd_service = "letta-server"
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else:
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# Provide defaults to prevent attribute errors if filter is applied incorrectly
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record.dd_env = ""
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record.dd_service = ""
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return True
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def _setup_logfile() -> "Path":
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"""ensure the logger filepath is in place
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@@ -20,28 +142,65 @@ def _setup_logfile() -> "Path":
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return logfile
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# TODO: production logging should be much less invasive
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# Determine which formatter to use based on configuration
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def _get_console_formatter() -> str:
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"""Determine the appropriate console formatter based on settings."""
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if log_settings.json_logging:
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return "json"
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elif telemetry_settings.enable_datadog:
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return "datadog"
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else:
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return "no_datetime"
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def _get_file_formatter() -> str:
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"""Determine the appropriate file formatter based on settings."""
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if log_settings.json_logging:
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return "json"
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elif telemetry_settings.enable_datadog:
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return "datadog"
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else:
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return "standard"
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# Logging configuration with optional Datadog integration and JSON support
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DEVELOPMENT_LOGGING = {
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"version": 1,
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"disable_existing_loggers": False, # Allow capturing from all loggers
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"formatters": {
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"standard": {"format": "%(asctime)s - %(name)s - %(levelname)s - %(message)s"},
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"no_datetime": {"format": "%(name)s - %(levelname)s - %(message)s"},
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"datadog": {
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# Datadog-compatible format with key=value pairs for better parsing
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# ddtrace's log injection will add dd.trace_id, dd.span_id automatically when logging is patched
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"format": "%(asctime)s - %(name)s - %(levelname)s - [dd.env=%(dd_env)s dd.service=%(dd_service)s] - %(message)s"
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},
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"json": {
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# JSON formatter for structured logging with full Datadog integration
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"()": JSONFormatter,
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},
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},
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"filters": {
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"datadog_env": {
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"()": DatadogEnvFilter,
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},
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},
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"handlers": {
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"console": {
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"level": selected_log_level,
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"class": "logging.StreamHandler",
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"stream": stdout,
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"formatter": "no_datetime",
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"formatter": _get_console_formatter(),
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"filters": ["datadog_env"] if telemetry_settings.enable_datadog and not log_settings.json_logging else [],
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},
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"file": {
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"level": "DEBUG",
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"class": "logging.handlers.RotatingFileHandler",
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"filename": _setup_logfile(),
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"maxBytes": 1024**2 * 10,
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"backupCount": 3,
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"formatter": "standard",
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"maxBytes": 1024**2 * 10, # 10 MB per file
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"backupCount": 3, # Keep 3 backup files
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"formatter": _get_file_formatter(),
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"filters": ["datadog_env"] if telemetry_settings.enable_datadog and not log_settings.json_logging else [],
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},
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},
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"root": { # Root logger handles all logs
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@@ -58,6 +217,11 @@ DEVELOPMENT_LOGGING = {
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"handlers": ["console"],
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"propagate": True,
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},
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# Reduce noise from ddtrace internal logging
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"ddtrace": {
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"level": "WARNING",
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"propagate": True,
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},
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},
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}
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@@ -204,6 +204,49 @@ def create_application() -> "FastAPI":
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},
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)
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if telemetry_settings.enable_datadog:
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try:
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dd_env = settings.environment or "development"
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print(f"▶ Initializing Datadog profiling (env={dd_env})")
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# Configure environment variables before importing ddtrace (must be set in environment before importing ddtrace)
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os.environ.setdefault("DD_ENV", dd_env)
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os.environ.setdefault("DD_SERVICE", telemetry_settings.datadog_service_name)
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os.environ.setdefault("DD_VERSION", letta_version)
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os.environ.setdefault("DD_AGENT_HOST", telemetry_settings.datadog_agent_host)
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os.environ.setdefault("DD_TRACE_AGENT_PORT", str(telemetry_settings.datadog_agent_port))
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os.environ.setdefault("DD_PROFILING_ENABLED", "true")
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os.environ.setdefault("DD_PROFILING_MEMORY_ENABLED", str(telemetry_settings.datadog_profiling_memory_enabled).lower())
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os.environ.setdefault("DD_PROFILING_HEAP_ENABLED", str(telemetry_settings.datadog_profiling_heap_enabled).lower())
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from ddtrace.profiling import Profiler
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# Initialize and start profiler
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profiler = Profiler(
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env=dd_env,
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service=telemetry_settings.datadog_service_name,
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version=letta_version,
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)
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profiler.start()
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# Log Git metadata for source code integration
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git_info = ""
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if telemetry_settings.datadog_git_commit_sha:
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git_info = f", commit={telemetry_settings.datadog_git_commit_sha[:8]}"
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if telemetry_settings.datadog_git_repository_url:
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git_info += f", repo={telemetry_settings.datadog_git_repository_url}"
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logger.info(
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f"Datadog profiling enabled: env={dd_env}, "
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f"service={telemetry_settings.datadog_service_name}, "
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f"agent={telemetry_settings.datadog_agent_host}:{telemetry_settings.datadog_agent_port}{git_info}"
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)
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except Exception as e:
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logger.error(f"Failed to initialize Datadog profiling: {e}", exc_info=True)
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if SENTRY_ENABLED:
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sentry_sdk.capture_exception(e)
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# Don't fail application startup if Datadog initialization fails
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debug_mode = "--debug" in sys.argv
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app = FastAPI(
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swagger_ui_parameters={"docExpansion": "none"},
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@@ -379,15 +379,52 @@ class TestSettings(Settings):
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class LogSettings(BaseSettings):
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model_config = SettingsConfigDict(env_prefix="letta_logging_", extra="ignore")
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debug: bool | None = Field(False, description="Enable debugging for logging")
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json_logging: bool = Field(False, description="Enable json logging instead of text logging")
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json_logging: bool = Field(
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False,
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description="Enable structured JSON logging (recommended).",
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)
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log_level: str | None = Field("WARNING", description="Logging level")
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letta_log_path: Path | None = Field(Path.home() / ".letta" / "logs" / "Letta.log")
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verbose_telemetry_logging: bool = Field(False)
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class TelemetrySettings(BaseSettings):
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"""Configuration for telemetry and observability integrations."""
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model_config = SettingsConfigDict(env_prefix="letta_telemetry_", extra="ignore")
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profiler: bool | None = Field(False, description="Enable use of the profiler.")
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# Google Cloud Profiler
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profiler: bool | None = Field(False, description="Enable Google Cloud Profiler.")
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# Datadog APM and Profiling
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enable_datadog: bool | None = Field(False, description="Enable Datadog profiling. Environment is pulled from settings.environment.")
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datadog_agent_host: str = Field(
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default="localhost",
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description="Datadog agent hostname or IP address. Use service name for Kubernetes (e.g., 'datadog-cluster-agent').",
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)
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datadog_agent_port: int = Field(default=8126, ge=1, le=65535, description="Datadog trace agent port (typically 8126 for traces).")
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datadog_service_name: str = Field(default="letta-server", description="Service name for Datadog profiling.")
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datadog_profiling_memory_enabled: bool = Field(default=True, description="Enable memory profiling in Datadog.")
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datadog_profiling_heap_enabled: bool = Field(default=True, description="Enable heap profiling in Datadog.")
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# Datadog Source Code Integration (optional, tightly coupled with profiling)
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# These settings link profiling data and traces to specific Git commits,
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# enabling code navigation directly from Datadog UI to GitHub/GitLab.
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datadog_git_repository_url: str | None = Field(
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default=None,
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validation_alias=AliasChoices("DD_GIT_REPOSITORY_URL", "datadog_git_repository_url"),
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description="Git repository URL (e.g., 'https://github.com/org/repo'). Set at build time.",
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)
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datadog_git_commit_sha: str | None = Field(
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default=None,
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validation_alias=AliasChoices("DD_GIT_COMMIT_SHA", "datadog_git_commit_sha"),
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description="Git commit SHA for the deployed code. Set at build time with 'git rev-parse HEAD'.",
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)
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datadog_main_package: str = Field(
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default="letta",
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validation_alias=AliasChoices("DD_MAIN_PACKAGE", "datadog_main_package"),
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description="Primary Python package name for source code linking. Datadog uses this setting to determine which code is 'yours' vs. third-party dependencies.",
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)
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# singleton
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@@ -8,15 +8,15 @@ receivers:
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filelog:
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include:
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- /root/.letta/logs/Letta.log
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multiline:
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line_start_pattern: ^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3}
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operators:
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# Extract timestamp and other fields
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- type: regex_parser
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regex: '^(?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\s+.*'
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# Parse JSON logs
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- type: json_parser
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parse_from: body
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parse_to: attributes
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- type: time_parser
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parse_from: attributes.timestamp
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layout: '%Y-%m-%d %H:%M:%S,%L'
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layout_type: gotime
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layout: '2006-01-02T15:04:05.999999Z07:00'
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processors:
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memory_limiter:
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|
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@@ -8,15 +8,15 @@ receivers:
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filelog:
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include:
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- /root/.letta/logs/Letta.log
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multiline:
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line_start_pattern: ^\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3}
|
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operators:
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# Extract timestamp and other fields
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- type: regex_parser
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regex: '^(?P<timestamp>\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2},\d{3})\s+.*'
|
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# Parse JSON logs
|
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- type: json_parser
|
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parse_from: body
|
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parse_to: attributes
|
||||
- type: time_parser
|
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parse_from: attributes.timestamp
|
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layout: '%Y-%m-%d %H:%M:%S,%L'
|
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layout_type: gotime
|
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layout: '2006-01-02T15:04:05.999999Z07:00'
|
||||
|
||||
processors:
|
||||
memory_limiter:
|
||||
|
||||
@@ -89,7 +89,10 @@ pinecone = ["pinecone[asyncio]>=7.3.0"]
|
||||
sqlite = ["aiosqlite>=0.21.0", "sqlite-vec>=0.1.7a2"]
|
||||
|
||||
# ====== Server ======
|
||||
experimental = ["uvloop>=0.21.0", "granian[uvloop,reload]>=2.3.2", "google-cloud-profiler>=4.1.0"]
|
||||
experimental = [
|
||||
"uvloop>=0.21.0",
|
||||
"granian[uvloop,reload]>=2.3.2",
|
||||
]
|
||||
server = [
|
||||
"websockets",
|
||||
"fastapi>=0.115.6",
|
||||
@@ -144,6 +147,10 @@ desktop = [
|
||||
"magika>=0.6.2",
|
||||
#"pgserver>=0.1.4",
|
||||
]
|
||||
profiling = [
|
||||
"ddtrace>=2.18.2",
|
||||
"google-cloud-profiler>=4.1.0",
|
||||
]
|
||||
|
||||
[build-system]
|
||||
requires = ["hatchling"]
|
||||
|
||||
104
uv.lock
generated
104
uv.lock
generated
@@ -518,6 +518,15 @@ wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/7e/c1/ec214e9c94000d1c1974ec67ced1c970c148aa6b8d8373066123fc3dbf06/Brotli-1.1.0-cp313-cp313-win_amd64.whl", hash = "sha256:9011560a466d2eb3f5a6e4929cf4a09be405c64154e12df0dd72713f6500e32b", size = 358517, upload-time = "2024-10-18T12:32:54.066Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "bytecode"
|
||||
version = "0.17.0"
|
||||
source = { registry = "https://pypi.org/simple" }
|
||||
sdist = { url = "https://files.pythonhosted.org/packages/98/c4/4818b392104bd426171fc2ce9c79c8edb4019ba6505747626d0f7107766c/bytecode-0.17.0.tar.gz", hash = "sha256:0c37efa5bd158b1b873f530cceea2c645611d55bd2dc2a4758b09f185749b6fd", size = 105863, upload-time = "2025-09-03T19:55:45.703Z" }
|
||||
wheels = [
|
||||
{ url = "https://files.pythonhosted.org/packages/ce/80/379e685099841f8501a19fb58b496512ef432331fed38276c3938ab09d8e/bytecode-0.17.0-py3-none-any.whl", hash = "sha256:64fb10cde1db7ef5cc39bd414ecebd54ba3b40e1c4cf8121ca5e72f170916ff8", size = 43045, upload-time = "2025-09-03T19:55:43.879Z" },
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "cachetools"
|
||||
version = "5.5.2"
|
||||
@@ -888,6 +897,55 @@ wheels = [
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sdist = { url = "https://files.pythonhosted.org/packages/8e/5a/6f9b49d67ea91376305fdb8bbf2877c746d756e45fd8fb7d2e32d6dad19b/google_api_python_client-2.185.0.tar.gz", hash = "sha256:aa1b338e4bb0f141c2df26743f6b46b11f38705aacd775b61971cbc51da089c3", size = 13885609, upload-time = "2025-10-17T15:00:35.623Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/42/d4/2568d5d907582cc145f3ffede43879746fd4b331308088a0fc57f7ecdbca/google_api_python_client-2.179.0-py3-none-any.whl", hash = "sha256:79ab5039d70c59dab874fd18333fca90fb469be51c96113cb133e5fc1f0b2a79", size = 13955142, upload-time = "2025-08-13T18:45:25.944Z" },
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{ url = "https://files.pythonhosted.org/packages/fa/28/be3b17bd6a190c8c2ec9e4fb65d43e6ecd7b7a1bb19ccc1d9ab4f687a58c/google_api_python_client-2.185.0-py3-none-any.whl", hash = "sha256:00fe173a4b346d2397fbe0d37ac15368170dfbed91a0395a66ef2558e22b93fc", size = 14453595, upload-time = "2025-10-17T15:00:33.176Z" },
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||||
]
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||||
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||||
[[package]]
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||||
@@ -1771,14 +1838,14 @@ wheels = [
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||||
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||||
[[package]]
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||||
name = "httplib2"
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||||
version = "0.22.0"
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||||
version = "0.31.0"
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||||
source = { registry = "https://pypi.org/simple" }
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dependencies = [
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{ name = "pyparsing" },
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]
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sdist = { url = "https://files.pythonhosted.org/packages/3d/ad/2371116b22d616c194aa25ec410c9c6c37f23599dcd590502b74db197584/httplib2-0.22.0.tar.gz", hash = "sha256:d7a10bc5ef5ab08322488bde8c726eeee5c8618723fdb399597ec58f3d82df81", size = 351116, upload-time = "2023-03-21T22:29:37.214Z" }
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sdist = { url = "https://files.pythonhosted.org/packages/52/77/6653db69c1f7ecfe5e3f9726fdadc981794656fcd7d98c4209fecfea9993/httplib2-0.31.0.tar.gz", hash = "sha256:ac7ab497c50975147d4f7b1ade44becc7df2f8954d42b38b3d69c515f531135c", size = 250759, upload-time = "2025-09-11T12:16:03.403Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/a8/6c/d2fbdaaa5959339d53ba38e94c123e4e84b8fbc4b84beb0e70d7c1608486/httplib2-0.22.0-py3-none-any.whl", hash = "sha256:14ae0a53c1ba8f3d37e9e27cf37eabb0fb9980f435ba405d546948b009dd64dc", size = 96854, upload-time = "2023-03-21T22:29:35.683Z" },
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{ url = "https://files.pythonhosted.org/packages/8c/a2/0d269db0f6163be503775dc8b6a6fa15820cc9fdc866f6ba608d86b721f2/httplib2-0.31.0-py3-none-any.whl", hash = "sha256:b9cd78abea9b4e43a7714c6e0f8b6b8561a6fc1e95d5dbd367f5bf0ef35f5d24", size = 91148, upload-time = "2025-09-11T12:16:01.803Z" },
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]
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[[package]]
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@@ -2308,6 +2375,15 @@ wheels = [
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{ url = "https://files.pythonhosted.org/packages/a8/73/91a506e17bb1bc6d20c2c04cf7b459dc58951bfbfe7f97f2c952646b4500/langsmith-0.4.18-py3-none-any.whl", hash = "sha256:ad63154f503678356aadf5b999f40393b4bbd332aee2d04cde3e431c61f2e1c2", size = 376444, upload-time = "2025-08-26T17:00:03.564Z" },
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]
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|
||||
[[package]]
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||||
name = "legacy-cgi"
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version = "2.6.3"
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source = { registry = "https://pypi.org/simple" }
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sdist = { url = "https://files.pythonhosted.org/packages/a6/ed/300cabc9693209d5a03e2ebc5eb5c4171b51607c08ed84a2b71c9015e0f3/legacy_cgi-2.6.3.tar.gz", hash = "sha256:4c119d6cb8e9d8b6ad7cc0ddad880552c62df4029622835d06dfd18f438a8154", size = 24401, upload-time = "2025-03-27T00:48:56.957Z" }
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wheels = [
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{ url = "https://files.pythonhosted.org/packages/5a/33/68c6c38193684537757e0d50a7ccb4f4656e5c2f7cd2be737a9d4a1bff71/legacy_cgi-2.6.3-py3-none-any.whl", hash = "sha256:6df2ea5ae14c71ef6f097f8b6372b44f6685283dc018535a75c924564183cdab", size = 19851, upload-time = "2025-03-27T00:48:55.366Z" },
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]
|
||||
|
||||
[[package]]
|
||||
name = "letta"
|
||||
version = "0.12.1"
|
||||
@@ -2413,7 +2489,6 @@ dev = [
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||||
{ name = "pytest-order" },
|
||||
]
|
||||
experimental = [
|
||||
{ name = "google-cloud-profiler" },
|
||||
{ name = "granian", extra = ["reload", "uvloop"] },
|
||||
{ name = "uvloop" },
|
||||
]
|
||||
@@ -2438,6 +2513,10 @@ postgres = [
|
||||
{ name = "psycopg2" },
|
||||
{ name = "psycopg2-binary" },
|
||||
]
|
||||
profiling = [
|
||||
{ name = "ddtrace" },
|
||||
{ name = "google-cloud-profiler" },
|
||||
]
|
||||
redis = [
|
||||
{ name = "redis" },
|
||||
]
|
||||
@@ -2468,6 +2547,7 @@ requires-dist = [
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||||
{ name = "certifi", specifier = ">=2025.6.15" },
|
||||
{ name = "colorama", specifier = ">=0.4.6" },
|
||||
{ name = "datamodel-code-generator", extras = ["http"], specifier = ">=0.25.0" },
|
||||
{ name = "ddtrace", marker = "extra == 'profiling'", specifier = ">=2.18.2" },
|
||||
{ name = "demjson3", specifier = ">=3.0.6" },
|
||||
{ name = "docker", marker = "extra == 'desktop'", specifier = ">=7.1.0" },
|
||||
{ name = "docker", marker = "extra == 'external-tools'", specifier = ">=7.1.0" },
|
||||
@@ -2478,7 +2558,7 @@ requires-dist = [
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||||
{ name = "faker", specifier = ">=36.1.0" },
|
||||
{ name = "fastapi", marker = "extra == 'desktop'", specifier = ">=0.115.6" },
|
||||
{ name = "fastapi", marker = "extra == 'server'", specifier = ">=0.115.6" },
|
||||
{ name = "google-cloud-profiler", marker = "extra == 'experimental'", specifier = ">=4.1.0" },
|
||||
{ name = "google-cloud-profiler", marker = "extra == 'profiling'", specifier = ">=4.1.0" },
|
||||
{ name = "google-genai", specifier = ">=1.15.0" },
|
||||
{ name = "granian", extras = ["uvloop", "reload"], marker = "extra == 'experimental'", specifier = ">=2.3.2" },
|
||||
{ name = "grpcio", specifier = ">=1.68.1" },
|
||||
@@ -2564,7 +2644,7 @@ requires-dist = [
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||||
{ name = "wikipedia", marker = "extra == 'desktop'", specifier = ">=1.4.0" },
|
||||
{ name = "wikipedia", marker = "extra == 'external-tools'", specifier = ">=1.4.0" },
|
||||
]
|
||||
provides-extras = ["postgres", "redis", "pinecone", "sqlite", "experimental", "server", "bedrock", "dev", "cloud-tool-sandbox", "modal", "external-tools", "desktop"]
|
||||
provides-extras = ["postgres", "redis", "pinecone", "sqlite", "experimental", "server", "bedrock", "dev", "cloud-tool-sandbox", "modal", "external-tools", "desktop", "profiling"]
|
||||
|
||||
[[package]]
|
||||
name = "letta-client"
|
||||
|
||||
Reference in New Issue
Block a user