Improvement for MLChain 0.1.9

mlchain/__init__.py

@@ -1,14 +1,26 @@
 # Parameters of MLchain
-__version__ = "0.1.8rc1"
+__version__ = "0.1.9"
 HOST = "https://www.api.mlchain.ml"
 WEB_HOST = HOST
 API_ADDRESS = HOST
 MODEL_ID = None
+import ssl
+
+try:
+    _create_unverified_https_context = ssl._create_unverified_context
+except AttributeError:
+    # Legacy Python that doesn't verify HTTPS certificates by default
+    pass
+else:
+    # Handle target environment that doesn't support HTTPS verification
+    ssl._create_default_https_context = _create_unverified_https_context
+
 from os import environ
 
 environ['OBJC_DISABLE_INITIALIZE_FORK_SAFETY'] = 'YES'
 from mlchain.base.log import logger
 from .context import mlchain_context
 
 from .base.exceptions import *
-from .config import mlconfig
+from .config import mlconfig
+

mlchain/base/exceptions.py

@@ -1,17 +1,22 @@
+import os 
 import traceback
-from .log import logger
-
+from .log import logger, sentry_ignore_logger
+from sentry_sdk import capture_exception
+import logging 
+from sentry_sdk import add_breadcrumb
+import re 
 
 class MlChainError(Exception):
     """Base class for all exceptions."""
 
     def __init__(self, msg, code='exception', status_code=500):
+        super(MlChainError, self).__init__(msg)
         self.msg = msg
+        self.message = msg
         self.code = code
         self.status_code = status_code
-        logger.error("[{0}]: {1}".format(code, msg))
-        logger.debug(traceback.format_exc())
-
+        sentry_ignore_logger.error("[{0}]: {1}".format(code, msg))
+        sentry_ignore_logger.debug(traceback.format_exc())
 
 class MLChainAssertionError(MlChainError):
     def __init__(self, msg, code="assertion", status_code=422):
@@ -26,3 +31,11 @@ def __init__(self, msg, code="serialization", status_code=422):
 class MLChainUnauthorized(MlChainError):
     def __init__(self, msg, code="unauthorized", status_code=401):
         MlChainError.__init__(self, msg, code, status_code)
+
+class MLChainConnectionError(MlChainError):
+    def __init__(self, msg, code="connection_error", status_code=500):
+        MlChainError.__init__(self, msg, code, status_code)
+
+class MLChainTimeoutError(MlChainError):
+    def __init__(self, msg, code="timeout", status_code=500):
+        MlChainError.__init__(self, msg, code, status_code)

mlchain/base/gunicorn_config.py

@@ -0,0 +1,4 @@
+from mlchain.config import init_sentry
+
+def post_worker_init(worker):
+    init_sentry()

mlchain/base/log.py

@@ -4,17 +4,28 @@
 """
 from contextlib import contextmanager
 import re
+import traceback
 from traceback import StackSummary, extract_tb
 import os
 import sys
 import logging
-import traceback
+
+# Sentry integration
+from sentry_sdk.integrations.logging import LoggingIntegration
+from sentry_sdk.integrations.logging import ignore_logger
+
+sentry_logging = LoggingIntegration(
+    level=logging.INFO,        # Capture info and above as breadcrumbs
+    event_level=logging.ERROR  # Send errors as events
+)
+ignore_logger("mlchain-server")
+sentry_ignore_logger = logging.getLogger("mlchain-server")
+# End sentry integration 
 
 
 def get_color(n):
     return '\x1b[3{0}m'.format(n)
 
-
 class MultiLine(logging.Formatter):
     def __init__(self, fmt=None, datefmt=None, style='%', newline=None):
         logging.Formatter.__init__(self, fmt, datefmt, style)
@@ -60,7 +71,7 @@ def except_handler():
     sys.excepthook = sys.__excepthook__
 
 
-def format_exc(name='mlchain', tb=None, exception=None):
+def format_exc(name='mlchain', tb=None, exception=None, return_str=True):
     if exception is None:
         formatted_lines = traceback.format_exc().splitlines()
     else:
@@ -78,4 +89,7 @@ def format_exc(name='mlchain', tb=None, exception=None):
     output = []
     for x in formatted_lines:
         output.append(x)
-    return "\n".join(output) + "\n"
+
+    if return_str:
+        return "\n".join(output)
+    return output

mlchain/base/serve_model.py

@@ -311,7 +311,7 @@ def call_function(self, function_name_, id_=None, *args, **kwargs):
         function_name, uid = function_name_, id_
         if function_name is None:
             raise AssertionError("You need to specify the function name (API name)")
-        mlchain_context['context_id'] = uid
+
         if isinstance(function_name, str):
             if len(function_name) == 0:
                 if hasattr(self.model, '__call__') and callable(getattr(self.model, '__call__')):
@@ -339,7 +339,7 @@ async def call_async_function(self, function_name_, id_=None, *args, **kwargs):
         function_name, uid = function_name_, id_
         if function_name is None:
             raise MLChainAssertionError("You need to specify the function name (API name)")
-        mlchain_context['context_id'] = uid
+
         if isinstance(function_name, str):
             if len(function_name) == 0:
                 if hasattr(self.model, '__call__') and callable(getattr(self.model, '__call__')):

mlchain/base/wrapper.py

@@ -23,6 +23,9 @@ def load_config(self):
         for key, value in config.items():
             self.cfg.set(key.lower(), value)
 
+        from mlchain.base.gunicorn_config import post_worker_init
+        self.cfg.set("post_worker_init", post_worker_init)
+
     def load(self):
         return self.application
 

mlchain/cli/init.py

@@ -1,18 +1,20 @@
-import os
 import click
-from mlchain import logger
+import os
 
 root_path = os.path.dirname(__file__)
 
-
 @click.command("init", short_help="Init base config to run server.")
-@click.argument('file', nargs=1, required=False, default='mlconfig.yaml')
-def init_command(file):
-    if file is None:
-        file = 'mlconfig.yaml'  # pragma: no cover
-    if os.path.exists(file):
-        logger.warning("File {} exists. Please change name file".format(file))
-    else:
-        with open(file, 'wb') as fp:
-            with open(os.path.join(root_path, 'config.yaml'), 'rb') as fr:
-                fp.write(fr.read())
+def init_command():
+    def create_file(file): 
+        with open(file, 'wb') as f:
+            f.write(open(os.path.join(root_path, file), 'rb').read())
+
+    ALL_INIT_FILES = ['mlconfig.yaml', 'mlchain_server.py']
+    for file in ALL_INIT_FILES:
+        if os.path.exists(file): 
+            if click.confirm('File {0} is exist, Do you want to force update?'.format(file)):
+                create_file(file)
+        else: 
+            create_file(file)
+
+    click.secho('Mlchain initalization is done!', blink=True, bold=True)

mlchain/cli/mlchain_server.py

@@ -0,0 +1,20 @@
+"""
+THE BASE MLCHAIN SERVER 
+"""
+# Import mlchain 
+from mlchain.base import ServeModel
+from mlchain import mlconfig 
+
+
+# IMPORT YOUR CLASS HERE - YOU ONLY CARE THIS
+from main import Test # Import your class here 
+
+model = Test() # Init your class first 
+# END YOUR WORK HERE
+
+
+# Wrap your class by mlchain ServeModel
+serve_model = ServeModel(model)
+
+# THEN GO TO CONSOLE: 
+# mlchain run -c mlconfig.yaml 

mlchain/cli/mlconfig.yaml

@@ -0,0 +1,54 @@
+# Service Config 
+name: mlchain-server     # Name of service
+version: '0.0.1'         # Version of service 
+entry_file: mlchain_server.py    # Python file contains object ServeModel
+
+# Host and Port Config
+host: 0.0.0.0            # Host of service
+port: 8001               # Port service
+
+# Server config 
+server: flask            # Option flask or quart or grpc
+wrapper: None            # Option None or gunicorn or hypercorn
+cors: true               # Auto enable CORS
+static_folder:           # static folder for TemplateResponse
+static_url_path:         # static url path for TemplateResponse
+template_folder:         # template folder for TemplateResponse
+
+# Gunicorn config - Use gunicorn for general case
+gunicorn: 
+  timeout: 200            # The requests will be maximum 200 seconds in default, then when the requests is done, the worker will be restarted 
+  keepalive: 3            # Keep requests alive when inactive with client in 3 seconds default
+  max_requests: 0         # Maximum serving requests until workers restart to handle over memory in Python 
+  workers: 1              # Number of duplicate workers
+  threads: 1              # Number of simultaneous threads in workers
+  worker_class: 'gthread' # Worker class gthread is fit with all case. Can use 'uvicorn.workers.UvicornWorker' which be higher performance sometimes 
+
+# Hypercorn config - Use hypercorn for async server with Quart 
+hypercorn: 
+  timeout: 200            # The requests will be maximum 200 seconds in default, then when the requests is done, the worker will be restarted 
+  keepalive: 3            # Keep requests alive when inactive with client in 3 seconds default
+  threads: 50             # Number of simultaneous threads in workers. Default: 50. Remember that some models can not call simultaneous, so you can use @non_thread() decorator to the function.
+  worker_class: 'uvloop'  # Worker class uvloop is fit with all case. 
+
+bind:
+  - 'unix:/tmp/gunicorn.sock' # Using sock to make gunicorn faster 
+
+# Sentry logging, Sentry will be run when the worker is already initialized
+sentry: 
+  dsn: None                 # URI Sentry of the project or export SENTRY_DSN
+  traces_sample_rate: 0.1   # Default log 0.1 
+  sample_rate: 1.0          # Default 1.0
+  drop_modules: True        # Drop python requirements to lower the size of log 
+
+# Mlconfig - Use these mode and config or env to adaptive your code 
+# You can import mlconfig and use as variable. Ex: mlconfig.debug 
+mode: 
+  default: default          # The default mode
+  env:
+    default:                # All variable in default mode will be existed in other mode 
+      test: "Hello"
+    dev:                    # Development mode 
+      debug: True
+    prod:                   # Production mode 
+      debug: False