Supported SFT for openai

lazyllm/module/onlineChatModule/openaiModule.py

@@ -1,5 +1,6 @@
 import json
 import os
+import uuid
 import requests
 from typing import Tuple, List
 from urllib.parse import urljoin
@@ -87,10 +88,10 @@ def _update_kw(self, data, normal_config):
         current_train_data = self.default_train_data.copy()
         current_train_data.update(data)
 
-        current_train_data["hyper_parameters"]["n_epochs"] = normal_config["num_epochs"]
-        current_train_data["hyper_parameters"]["learning_rate_multiplier"] = str(normal_config["learning_rate"])
-        current_train_data["hyper_parameters"]["batch_size"] = normal_config["batch_size"]
-        current_train_data["suffix"] = normal_config["finetune_model_name"]
+        current_train_data["hyperparameters"]["n_epochs"] = normal_config["num_epochs"]
+        current_train_data["hyperparameters"]["learning_rate_multiplier"] = str(normal_config["learning_rate"])
+        current_train_data["hyperparameters"]["batch_size"] = normal_config["batch_size"]
+        current_train_data["suffix"] = str(uuid.uuid4())[:7]
 
         return current_train_data
 
@@ -150,8 +151,7 @@ def _get_finetuned_model_names(self) -> Tuple[List[Tuple[str, str]], List[Tuple[
         model_data = self._query_finetuned_jobs()
         res = list()
         for model in model_data['data']:
-            status = 'Done'if 'successful' in model['message'] else 'Failed'
-            res.append([model['id'], model['fine_tuned_model'], status])
+            res.append([model['id'], model['fine_tuned_model'], self._status_mapping(model['status'])])
         return res
 
     def _status_mapping(self, status):

lazyllm/tools/train_service/client.py

@@ -253,7 +253,7 @@ def train(self, train_config, token, source):
         Args:
         - train_config (dict): Configuration parameters for the training task.
         - token (str): API-Key provided by the supplier, used for authentication.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - tuple: A tuple containing the Job-ID and its status if the training starts successfully.
@@ -284,7 +284,7 @@ def get_all_trained_models(self, token, source):
 
         Args:
         - token (str): API-Key provided by the supplier, used for authentication.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - list of lists: Each sublist contains [job_id, model_name, status] for each trained model.
@@ -307,7 +307,7 @@ def get_training_status(self, token, job_id, source):
         Args:
         - token (str): API-Key provided by the supplier, used for authentication.
         - job_id (str): The unique identifier of the training job to query.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - str: A string representing the current status of the training task. This could be one of:
@@ -332,7 +332,7 @@ def cancel_training(self, token, job_id, source):
         Args:
         - token (str): API-Key provided by the supplier, used for authentication.
         - job_id (str): The unique identifier of the training job to be cancelled.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - bool or str: Returns True if the training task was successfully cancelled. If the cancellation fails,
@@ -360,7 +360,7 @@ def get_training_log(self, token, job_id, source, target_path=None):
         Args:
         - token (str): API-Key provided by the supplier, used for authentication.
         - job_id (str): The unique identifier of the training job for which to retrieve the log.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
         - target_path (str, optional): The path where the log file should be saved. If not provided,
             the log will be saved to a temporary directory.
 
@@ -389,7 +389,7 @@ def get_training_cost(self, token, job_id, source):
         Args:
         - token (str): API-Key provided by the supplier, used for authentication.
         - job_id (str): The unique identifier of the traning job for which to retrieve the token consumption.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - int or str: The number of tokens consumed by the traning task if the query is successful.
@@ -413,7 +413,7 @@ def validate_api_key(self, token, source):
 
         Args:
         - token (str): API-Key provided by the user, used for authentication.
-        - source (str): Specifies the supplier. Supported suppliers are 'glm' and 'qwen'.
+        - source (str): Specifies the supplier. Supported suppliers are 'openai', 'glm' and 'qwen'.
 
         Returns:
         - bool: True if the API key is valid, False otherwise.