[1/n] Add load_json and load_yaml methods to AIConfigRuntime

python/src/aiconfig/Config.py

@@ -53,14 +53,17 @@
 ModelParserRegistry.register_model_parser(
  DefaultAnyscaleEndpointParser("AnyscaleEndpoint")
 )
-ModelParserRegistry.register_model_parser(GeminiModelParser("gemini-pro"), ["gemini-pro"])
+ModelParserRegistry.register_model_parser(
+ GeminiModelParser("gemini-pro"), ["gemini-pro"]
+)
 ModelParserRegistry.register_model_parser(ClaudeBedrockModelParser())
 ModelParserRegistry.register_model_parser(HuggingFaceTextGenerationParser())
 for model in gpt_models_extra:
  ModelParserRegistry.register_model_parser(DefaultOpenAIParser(model))
 ModelParserRegistry.register_model_parser(PaLMChatParser())
 ModelParserRegistry.register_model_parser(PaLMTextParser())
 
+
 class AIConfigRuntime(AIConfig):
  # A mapping of model names to their respective parsers
 
@@ -116,14 +119,37 @@ def load(cls, config_filepath: str) -> "AIConfigRuntime":
  else:
  data = file.read()
 
- # load the file as bytes and let pydantic handle the parsing
- # validated_data = AIConfig.model_validate_json(file.read())
- aiconfigruntime = cls.model_validate_json(data)
- update_model_parser_registry_with_config_runtime(aiconfigruntime)
-
+ config_runtime = cls.load_json(data)
  # set the file path. This is used when saving the config
- aiconfigruntime.file_path = config_filepath
- return aiconfigruntime
+ config_runtime.file_path = config_filepath
+ return config_runtime
+
+ @classmethod
+ def load_json(cls, config_json: str) -> "AIConfigRuntime":
+ """
+ Constructs AIConfigRuntime from provided JSON and returns it.
+
+ Args:
+ config_json (str): The JSON representing the AIConfig.
+ """
+
+ config_runtime = cls.model_validate_json(config_json)
+ update_model_parser_registry_with_config_runtime(config_runtime)
+
+ return config_runtime
+
+ @classmethod
+ def load_yaml(cls, config_yaml: str) -> "AIConfigRuntime":
+ """
+ Constructs AIConfigRuntime from provided YAML and returns it.
+
+ Args:
+ config_yaml (str): The YAML representing the AIConfig.
+ """
+
+ yaml_data = yaml.safe_load(config_yaml)
+ config_json = json.dumps(yaml_data)
+ return cls.load_json(config_json)
 
  @classmethod
  def load_from_workbook(cls, workbook_id: str) -> "AIConfigRuntime":

typescript/lib/config.ts

@@ -114,11 +114,25 @@ export class AIConfigRuntime implements AIConfig {
  return config;
  }
 
+ /**
+ * Loads an AIConfig from a YAML string.
+ * @param aiConfigYAML YAML string to load the AIConfig from.
+ */
+ public static loadYAML(aiConfigYAML: string) {
+ const aiConfigObj = yaml.load(aiConfigYAML);
+ return this.loadJSON(aiConfigObj);
+ }
+
  /**
  * Loads an AIConfig from a JSON object.
  * @param aiConfigObj JSON object to load the AIConfig from.
  */
  public static loadJSON(aiConfigObj: any) {
+ if (typeof aiConfigObj === "string") {
+ // Parse the string as JSON
+ aiConfigObj = JSON.parse(aiConfigObj);
+ }
+
  // TODO: saqadri - validate that the type satisfies AIConfig interface
  const aiConfig = new AIConfigRuntime(
  aiConfigObj.name,