让新增的参数们真正有用

ChuanhuChatbot.py

@@ -221,7 +221,7 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
                             value="",
                             lines=1,
                         )
-                        user = gr.Textbox(
+                        user_identifier_txt = gr.Textbox(
                             show_label=True,
                             placeholder=f"用于定位滥用行为",
                             label="用户名",
@@ -379,8 +379,16 @@ with gr.Blocks(css=customCSS, theme=small_and_beautiful_theme) as demo:
     downloadFile.change(**load_history_from_file_args)
 
     # Advanced
-    top_p_slider.change(current_model.value.set_top_p, [top_p_slider], None)
     temperature_slider.change(current_model.value.set_temperature, [temperature_slider], None)
+    top_p_slider.change(current_model.value.set_top_p, [top_p_slider], None)
+    n_choices_slider.change(current_model.value.set_n_choices, [n_choices_slider], None)
+    stop_sequence_txt.change(current_model.value.set_stop_sequence, [stop_sequence_txt], None)
+    max_tokens_slider.change(current_model.value.set_max_tokens, [max_tokens_slider], None)
+    presence_penalty_slider.change(current_model.value.set_presence_penalty, [presence_penalty_slider], None)
+    frequency_penalty_slider.change(current_model.value.set_frequency_penalty, [frequency_penalty_slider], None)
+    logit_bias_txt.change(current_model.value.set_logit_bias, [logit_bias_txt], None)
+    user_identifier_txt.change(current_model.value.set_user_identifier, [user_identifier_txt], None)
+
     default_btn.click(
         reset_default, [], [apihostTxt, proxyTxt, status_display], show_progress=True
     )

modules/base_model.py

@@ -67,16 +67,12 @@ class BaseLLMModel:
         self.temperature = temperature
         self.top_p = top_p
         self.n_choices = n_choices
-        self.stop = stop
-        self.max_generation_token = (
-            max_generation_token
-            if max_generation_token is not None
-            else self.token_upper_limit
-        )
+        self.stop_sequence = stop
+        self.max_generation_token = None
         self.presence_penalty = presence_penalty
         self.frequency_penalty = frequency_penalty
         self.logit_bias = logit_bias
-        self.user = user
+        self.user_identifier = user
 
     def get_answer_stream_iter(self):
         """stream predict, need to be implemented
@@ -367,6 +363,36 @@ class BaseLLMModel:
     def set_top_p(self, new_top_p):
         self.top_p = new_top_p
 
+    def set_n_choices(self, new_n_choices):
+        self.n_choices = new_n_choices
+
+    def set_stop_sequence(self, new_stop_sequence: str):
+        new_stop_sequence = new_stop_sequence.split(",")
+        self.stop_sequence = new_stop_sequence
+
+    def set_max_tokens(self, new_max_tokens):
+        self.max_generation_token = new_max_tokens
+
+    def set_presence_penalty(self, new_presence_penalty):
+        self.presence_penalty = new_presence_penalty
+
+    def set_frequency_penalty(self, new_frequency_penalty):
+        self.frequency_penalty = new_frequency_penalty
+
+    def set_logit_bias(self, logit_bias):
+        logit_bias = logit_bias.split()
+        bias_map = {}
+        encoding = tiktoken.get_encoding("cl100k_base")
+        for line in logit_bias:
+            word, bias_amount = line.split(":")
+            if word:
+                for token in encoding.encode(word):
+                    bias_map[token] = float(bias_amount)
+        self.logit_bias = bias_map
+
+    def set_user_identifier(self, new_user_identifier):
+        self.user_identifier = new_user_identifier
+
     def set_system_prompt(self, new_system_prompt):
         self.system_prompt = new_system_prompt
 

modules/models.py

@@ -103,9 +103,6 @@ class OpenAIClient(BaseLLMModel):
         system_prompt = self.system_prompt
         history = self.history
         logging.debug(colorama.Fore.YELLOW + f"{history}" + colorama.Fore.RESET)
-        temperature = self.temperature
-        top_p = self.top_p
-        selected_model = self.model_name
         headers = {
             "Content-Type": "application/json",
             "Authorization": f"Bearer {openai_api_key}",
@@ -115,16 +112,25 @@ class OpenAIClient(BaseLLMModel):
             history = [construct_system(system_prompt), *history]
 
         payload = {
-            "model": selected_model,
-            "messages": history,  # [{"role": "user", "content": f"{inputs}"}],
-            "temperature": temperature,  # 1.0,
-            "top_p": top_p,  # 1.0,
-            "n": 1,
+            "model": self.model_name,
+            "messages": history,
+            "temperature": self.temperature,
+            "top_p": self.top_p,
+            "n": self.n_choices,
             "stream": stream,
-            "presence_penalty": 0,
-            "frequency_penalty": 0,
-            "max_tokens": self.max_generation_token,
+            "presence_penalty": self.presence_penalty,
+            "frequency_penalty": self.frequency_penalty,
         }
+
+        if self.max_generation_token is not None:
+            payload["max_tokens"] = self.max_generation_token
+        if self.stop_sequence is not None:
+            payload["stop"] = self.stop_sequence
+        if self.logit_bias is not None:
+            payload["logit_bias"] = self.logit_bias
+        if self.user_identifier is not None:
+            payload["user"] = self.user_identifier
+
         if stream:
             timeout = TIMEOUT_STREAMING
         else: