Copilot commented on code in PR #277:
URL:
https://github.com/apache/incubator-hugegraph-ai/pull/277#discussion_r2154314451
##########
hugegraph-llm/src/hugegraph_llm/config/models/base_config.py:
##########
@@ -18,118 +18,139 @@
import os
-from dotenv import dotenv_values, set_key
from pydantic_settings import BaseSettings
+import yaml
from hugegraph_llm.utils.log import log
dir_name = os.path.dirname
-env_path = os.path.join(os.getcwd(), ".env") # Load .env from the current
working directory
-
+yaml_path = os.path.join(os.getcwd(), "config.yaml")
class BaseConfig(BaseSettings):
class Config:
- env_file = env_path
+ yaml_file = yaml_path
case_sensitive = False
- extra = 'ignore' # ignore extra fields to avoid ValidationError
+ extra = 'ignore' # Ignore extra fields to avoid ValidationError
env_ignore_empty = True
- def generate_env(self):
- if os.path.exists(env_path):
- log.info("%s already exists, do you want to override with the
default configuration? (y/n)", env_path)
- update = input()
- if update.lower() != "y":
- return
- self.update_env()
- else:
- config_dict = self.model_dump()
- config_dict = {k.upper(): v for k, v in config_dict.items()}
- with open(env_path, "w", encoding="utf-8") as f:
- for k, v in config_dict.items():
- if v is None:
- f.write(f"{k}=\n")
- else:
- f.write(f"{k}={v}\n")
- log.info("Generate %s successfully!", env_path)
-
- def update_env(self):
+ def generate_yaml(self):
+ # Generate a YAML file based on the current configuration
config_dict = self.model_dump()
config_dict = {k.upper(): v for k, v in config_dict.items()}
- env_config = dotenv_values(f"{env_path}")
-
- # dotenv_values make None to '', while pydantic make None to None
- # dotenv_values make integer to string, while pydantic make integer to
integer
+ current_class_name = self.__class__.__name__
+ yaml_data = {}
+ yaml_section_data = {}
for k, v in config_dict.items():
- if k in env_config:
- if not (env_config[k] or v):
- continue
- if env_config[k] == str(v):
- continue
- log.info("Update %s: %s=%s", env_path, k, v)
- set_key(env_path, k, v if v else "", quote_mode="never")
-
- def check_env(self):
- """Synchronize configs between .env file and object.
+ yaml_section_data[k] = v
+ yaml_data[current_class_name] = yaml_section_data
+ with open(yaml_path, "w", encoding="utf-8") as f:
+ yaml.dump(yaml_data, f, sort_keys=False)
+ log.info("Generate %s successfully!", yaml_path)
+
+ def update_configs(self):
+ """Update the configurations of subclasses to the config.yaml files."""
+ config_dict = self.model_dump()
+ config_dict = {k.upper(): v for k, v in config_dict.items()}
+
+ try:
+ current_class_name = self.__class__.__name__
+ with open(yaml_path, "r", encoding="utf-8") as f:
+ content = f.read()
+ yaml_config = yaml.safe_load(content) if content.strip() else
{}
+ for k, v in config_dict.items():
+ if k in yaml_config[current_class_name]:
+ yaml_config[current_class_name][k] = v
+ with open(yaml_path, "w", encoding="utf-8") as f:
+ yaml.dump(yaml_config, f)
+ except yaml.YAMLError as e:
+ log.error("Error parsing YAML from %s: %s", yaml_path, e)
+ except Exception as e:
+ log.error("Error loading %s: %s", yaml_path, e)
+
- This method performs two steps:
- 1. Updates object attributes from .env file values when they differ
- 2. Adds missing configuration items to the .env file
+ def check_yaml_configs(self):
+ """
+ Synchronize configs between config.yaml file and object.
+ Updates object attributes from config.yaml and adds missing items to
config.yaml.
"""
+ object_config_dict = {k.upper(): v for k, v in
self.model_dump().items()}
try:
- # Read the.env file and prepare object config
- env_config = dotenv_values(env_path)
- config_dict = {k.upper(): v for k, v in self.model_dump().items()}
+ current_class_name = self.__class__.__name__
+ # Read the yaml.config file and prepare object config
+ with open(yaml_path, "r", encoding="utf-8") as f:
+ content = f.read()
+ if not content.strip():
+ yaml_file_config = {current_class_name: {}}
+ else:
+ yaml_file_config = yaml.safe_load(content)
+ if not isinstance(yaml_file_config, dict):
+ log.error("Invalid YAML content in %s. Expected a
dictionary.", yaml_path)
+ yaml_file_config = {current_class_name: {}} # Reset to
a safe state
+ elif current_class_name not in yaml_file_config:
+ yaml_file_config[current_class_name] = {}
+
+ # Step 1: Update the object from yaml.config
+ if yaml_file_config.get(current_class_name):
+ self._sync_yaml_to_object(yaml_file_config, object_config_dict)
+
+ # Step 2: Add missing onfig items from object to yaml.config
Review Comment:
There is a minor typo in the comment ('onfig' should be 'config') – please
correct it for clarity.
```suggestion
# Step 2: Add missing config items from object to yaml.config
```
##########
hugegraph-llm/src/hugegraph_llm/config/models/base_config.py:
##########
@@ -18,118 +18,139 @@
import os
-from dotenv import dotenv_values, set_key
from pydantic_settings import BaseSettings
+import yaml
from hugegraph_llm.utils.log import log
dir_name = os.path.dirname
-env_path = os.path.join(os.getcwd(), ".env") # Load .env from the current
working directory
-
+yaml_path = os.path.join(os.getcwd(), "config.yaml")
class BaseConfig(BaseSettings):
class Config:
- env_file = env_path
+ yaml_file = yaml_path
case_sensitive = False
- extra = 'ignore' # ignore extra fields to avoid ValidationError
+ extra = 'ignore' # Ignore extra fields to avoid ValidationError
env_ignore_empty = True
- def generate_env(self):
- if os.path.exists(env_path):
- log.info("%s already exists, do you want to override with the
default configuration? (y/n)", env_path)
- update = input()
- if update.lower() != "y":
- return
- self.update_env()
- else:
- config_dict = self.model_dump()
- config_dict = {k.upper(): v for k, v in config_dict.items()}
- with open(env_path, "w", encoding="utf-8") as f:
- for k, v in config_dict.items():
- if v is None:
- f.write(f"{k}=\n")
- else:
- f.write(f"{k}={v}\n")
- log.info("Generate %s successfully!", env_path)
-
- def update_env(self):
+ def generate_yaml(self):
+ # Generate a YAML file based on the current configuration
config_dict = self.model_dump()
config_dict = {k.upper(): v for k, v in config_dict.items()}
- env_config = dotenv_values(f"{env_path}")
-
- # dotenv_values make None to '', while pydantic make None to None
- # dotenv_values make integer to string, while pydantic make integer to
integer
+ current_class_name = self.__class__.__name__
+ yaml_data = {}
+ yaml_section_data = {}
for k, v in config_dict.items():
- if k in env_config:
- if not (env_config[k] or v):
- continue
- if env_config[k] == str(v):
- continue
- log.info("Update %s: %s=%s", env_path, k, v)
- set_key(env_path, k, v if v else "", quote_mode="never")
-
- def check_env(self):
- """Synchronize configs between .env file and object.
+ yaml_section_data[k] = v
+ yaml_data[current_class_name] = yaml_section_data
+ with open(yaml_path, "w", encoding="utf-8") as f:
+ yaml.dump(yaml_data, f, sort_keys=False)
+ log.info("Generate %s successfully!", yaml_path)
+
+ def update_configs(self):
+ """Update the configurations of subclasses to the config.yaml files."""
+ config_dict = self.model_dump()
+ config_dict = {k.upper(): v for k, v in config_dict.items()}
+
+ try:
+ current_class_name = self.__class__.__name__
+ with open(yaml_path, "r", encoding="utf-8") as f:
+ content = f.read()
+ yaml_config = yaml.safe_load(content) if content.strip() else
{}
Review Comment:
Before iterating over the YAML config section, ensure that
current_class_name exists as a key in yaml_config. Consider initializing
yaml_config[current_class_name] to an empty dict if it does not exist to
prevent potential KeyError.
```suggestion
yaml_config = yaml.safe_load(content) if content.strip()
else {}
current_class_name = self.__class__.__name__
if current_class_name not in yaml_config:
yaml_config[current_class_name] = {}
```
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