Add base_url_config args.

openlrc/chatbot.py

@@ -134,7 +134,7 @@ def message(self, messages_list: Union[List[Dict], List[List[Dict]]],
 @_register_chatbot
 class GPTBot(ChatBot):
     def __init__(self, model='gpt-3.5-turbo-0125', temperature=1, top_p=1, retry=8, max_async=16, json_mode=False,
-                 fee_limit=0.05, proxy=None):
+                 fee_limit=0.05, proxy=None, base_url_config=None):
         # Pricing for 1M tokens, info from https://openai.com/pricing
         pricing = {
             'gpt-3.5-turbo-0125': (0.5, 1.5),
@@ -145,9 +145,11 @@ def __init__(self, model='gpt-3.5-turbo-0125', temperature=1, top_p=1, retry=8,
 
         super().__init__(pricing, temperature, top_p, retry, max_async, fee_limit)
 
-        self.async_client = AsyncGPTClient(api_key=os.environ['OPENAI_API_KEY'], http_client=httpx.AsyncClient(
-            proxies=proxy,
-        ))
+        self.async_client = AsyncGPTClient(
+            api_key=os.environ['OPENAI_API_KEY'],
+            http_client=httpx.AsyncClient(proxies=proxy),
+            base_url=base_url_config['openai'] if base_url_config else None
+        )
 
         self.model = model
         self.temperature = temperature
@@ -215,7 +217,7 @@ async def _create_achat(self, messages: List[Dict], output_checker: Callable = l
 @_register_chatbot
 class ClaudeBot(ChatBot):
     def __init__(self, model='claude-3-sonnet-20240229', temperature=1, top_p=1, retry=8, max_async=16, fee_limit=0.2,
-                 proxy=None):
+                 proxy=None, base_url_config=None):
         # Pricing for 1M tokens, info from https://docs.anthropic.com/claude/docs/models-overview#model-comparison
         pricing = {
             'claude-3-opus-20240229': (15, 75),
@@ -225,9 +227,13 @@ def __init__(self, model='claude-3-sonnet-20240229', temperature=1, top_p=1, ret
 
         super().__init__(pricing, temperature, top_p, retry, max_async, fee_limit)
 
-        self.async_client = AsyncAnthropic(api_key=os.environ['ANTHROPIC_API_KEY'], http_client=httpx.AsyncClient(
-            proxies=proxy,
-        ))
+        self.async_client = AsyncAnthropic(
+            api_key=os.environ['ANTHROPIC_API_KEY'],
+            http_client=httpx.AsyncClient(
+                proxies=proxy
+            ),
+            base_url=base_url_config['anthropic'] if base_url_config else None
+        )
 
         self.model = model
         self.retry = retry

openlrc/openlrc.py

@@ -41,17 +41,21 @@ class LRCer:
         asr_options: Parameters for whisper model.
         vad_options: Parameters for VAD model.
         proxy: Proxy for openai requests. e.g. 'http://127.0.0.1:7890'
+        base_url_config: Base URL dict for OpenAI & Anthropic.
+            e.g. {'openai': 'https://openai.justsong.cn/', 'anthropic': 'https://api.g4f.icu'}
+            Default: ``None``
     """
 
     def __init__(self, whisper_model='large-v3', compute_type='float16', chatbot_model: str = 'gpt-3.5-turbo',
                  fee_limit=0.1, consumer_thread=4, asr_options=None, vad_options=None, preprocess_options=None,
-                 proxy=None):
+                 proxy=None, base_url_config=None):
         self.chatbot_model = chatbot_model
         self.fee_limit = fee_limit
         self.api_fee = 0  # Can be updated in different thread, operation should be thread-safe
         self.from_video = set()
         self.context: Context = Context()
         self.proxy = proxy
+        self.base_url_config = base_url_config
 
         self._lock = Lock()
         self.exception = None
@@ -180,7 +184,7 @@ def _translate(self, audio_name, prompter, target_lang, transcribed_opt_sub, tra
         if not translated_path.exists():
             # Translate the transcribed json
             translator = LLMTranslator(chatbot_model=self.chatbot_model, prompter=prompter, fee_limit=self.fee_limit,
-                                       proxy=self.proxy)
+                                       proxy=self.proxy, base_url_config=self.base_url_config)
             context = self.context
 
             target_texts = translator.translate(

openlrc/translate.py

@@ -26,7 +26,7 @@ def translate(self, texts: Union[str, List[str]], src_lang, target_lang):
 
 class LLMTranslator(Translator):
     def __init__(self, chatbot_model: str = 'gpt-3.5-turbo', prompter: str = 'base_trans', fee_limit=0.1,
-                 chunk_size=30, intercept_line=None, proxy=None):
+                 chunk_size=30, intercept_line=None, proxy=None, base_url_config=None):
         """
         Args:
             chatbot_model: Chatbot instance. Choices can be found using `LLMTranslator().list_chatbots()`.
@@ -35,6 +35,8 @@ def __init__(self, chatbot_model: str = 'gpt-3.5-turbo', prompter: str = 'base_t
             chunk_size (int): Use a small chunk size (<20) for speed (more asynchronous calls) and to enhance translation
                               stability (keeping audio timeline consistency).
             intercept_line (int): Intercepted text line number.
+            proxy (str): Proxy server. e.g. http://127.0.0.1:7890
+            base_url_config (dict): Base URL configuration for the chatbot API.
         """
         if prompter not in prompter_map:
             raise ValueError(f'Prompter {prompter} not found.')
@@ -43,7 +45,8 @@ def __init__(self, chatbot_model: str = 'gpt-3.5-turbo', prompter: str = 'base_t
             raise ValueError(f'Chatbot {chatbot_model} not supported.')
 
         chatbot_category = chatbot_map[model2chatbot[chatbot_model]]
-        self.chatbot = chatbot_category(model=chatbot_model, fee_limit=fee_limit, proxy=proxy, temperature=0.7)
+        self.chatbot = chatbot_category(model=chatbot_model, fee_limit=fee_limit, proxy=proxy, temperature=0.7,
+                                        base_url_config=base_url_config)
 
         self.prompter = prompter
         self.fee_limit = fee_limit