feat: 从配置文件加载保存的参数

ChuanhuChatbot.py

@@ -499,14 +499,12 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
             model_name=MODELS[DEFAULT_MODEL], access_key=my_api_key)[0]
         current_model.set_user_identifier(user_name)
         if not hide_history_when_not_logged_in or user_name:
-            filename, system_prompt, chatbot = current_model.auto_load()
+            loaded_stuff = current_model.auto_load()
         else:
-            system_prompt = gr.update()
-            filename = gr.update()
-            chatbot = gr.Chatbot.update(label=MODELS[DEFAULT_MODEL])
-        return user_info, user_name, current_model, toggle_like_btn_visibility(DEFAULT_MODEL), filename, system_prompt, chatbot, init_history_list(user_name)
+            loaded_stuff = [gr.update(), gr.update(), gr.Chatbot.update(label=MODELS[DEFAULT_MODEL]), current_model.single_turn, current_model.temperature, current_model.top_p, current_model.n_choices, current_model.stop_sequence, current_model.token_upper_limit, current_model.max_generation_token, current_model.presence_penalty, current_model.frequency_penalty, current_model.logit_bias, current_model.user_identifier]
+        return user_info, user_name, current_model, toggle_like_btn_visibility(DEFAULT_MODEL), *loaded_stuff, init_history_list(user_name)
     demo.load(create_greeting, inputs=None, outputs=[
-              user_info, user_name, current_model, like_dislike_area, saveFileName, systemPromptTxt, chatbot, historySelectList], api_name="load")
+              user_info, user_name, current_model, like_dislike_area, saveFileName, systemPromptTxt, chatbot, single_turn_checkbox, temperature_slider, top_p_slider, n_choices_slider, stop_sequence_txt, max_context_length_slider, max_generation_slider, presence_penalty_slider, frequency_penalty_slider, logit_bias_txt, user_identifier_txt, historySelectList], api_name="load")
     chatgpt_predict_args = dict(
         fn=predict,
         inputs=[
@@ -550,7 +548,7 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
     load_history_from_file_args = dict(
         fn=load_chat_history,
         inputs=[current_model, historySelectList],
-        outputs=[saveFileName, systemPromptTxt, chatbot]
+        outputs=[saveFileName, systemPromptTxt, chatbot, single_turn_checkbox, temperature_slider, top_p_slider, n_choices_slider, stop_sequence_txt, max_context_length_slider, max_generation_slider, presence_penalty_slider, frequency_penalty_slider, logit_bias_txt, user_identifier_txt],
     )
 
     refresh_history_args = dict(
@@ -587,7 +585,7 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
     emptyBtn.click(
         reset,
         inputs=[current_model, retain_system_prompt_checkbox],
-        outputs=[chatbot, status_display, historySelectList, systemPromptTxt],
+        outputs=[chatbot, status_display, historySelectList, systemPromptTxt, single_turn_checkbox, temperature_slider, top_p_slider, n_choices_slider, stop_sequence_txt, max_context_length_slider, max_generation_slider, presence_penalty_slider, frequency_penalty_slider, logit_bias_txt, user_identifier_txt],
         show_progress=True,
         _js='(a,b)=>{return clearChatbot(a,b);}',
     )
@@ -693,7 +691,7 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
     )
     historySelectList.input(**load_history_from_file_args)
     uploadFileBtn.upload(upload_chat_history, [current_model, uploadFileBtn], [
-                        saveFileName, systemPromptTxt, chatbot]).then(**refresh_history_args)
+                        saveFileName, systemPromptTxt, chatbot, single_turn_checkbox, temperature_slider, top_p_slider, n_choices_slider, stop_sequence_txt, max_context_length_slider, max_generation_slider, presence_penalty_slider, frequency_penalty_slider, logit_bias_txt, user_identifier_txt]).then(**refresh_history_args)
     historyDownloadBtn.click(None, [
                              user_name, historySelectList], None, _js='(a,b)=>{return downloadHistory(a,b,".json");}')
     historyMarkdownDownloadBtn.click(None, [
@@ -725,24 +723,24 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
         cancel_all_jobs, [], [openai_train_status], show_progress=True)
 
     # Advanced
-    max_context_length_slider.change(
+    max_context_length_slider.input(
         set_token_upper_limit, [current_model, max_context_length_slider], None)
-    temperature_slider.change(
+    temperature_slider.input(
         set_temperature, [current_model, temperature_slider], None)
-    top_p_slider.change(set_top_p, [current_model, top_p_slider], None)
-    n_choices_slider.change(
+    top_p_slider.input(set_top_p, [current_model, top_p_slider], None)
+    n_choices_slider.input(
         set_n_choices, [current_model, n_choices_slider], None)
-    stop_sequence_txt.change(
+    stop_sequence_txt.input(
         set_stop_sequence, [current_model, stop_sequence_txt], None)
-    max_generation_slider.change(
+    max_generation_slider.input(
         set_max_tokens, [current_model, max_generation_slider], None)
-    presence_penalty_slider.change(
+    presence_penalty_slider.input(
         set_presence_penalty, [current_model, presence_penalty_slider], None)
-    frequency_penalty_slider.change(
+    frequency_penalty_slider.input(
         set_frequency_penalty, [current_model, frequency_penalty_slider], None)
-    logit_bias_txt.change(
+    logit_bias_txt.input(
         set_logit_bias, [current_model, logit_bias_txt], None)
-    user_identifier_txt.change(set_user_identifier, [
+    user_identifier_txt.input(set_user_identifier, [
                                current_model, user_identifier_txt], None)
 
     default_btn.click(
@@ -784,7 +782,7 @@ with gr.Blocks(theme=small_and_beautiful_theme) as demo:
     historySelectBtn.click(  # This is an experimental feature... Not actually used.
         fn=load_chat_history,
         inputs=[current_model, historySelectList],
-        outputs=[saveFileName, systemPromptTxt, chatbot],
+        outputs=[saveFileName, systemPromptTxt, chatbot, single_turn_checkbox, temperature_slider, top_p_slider, n_choices_slider, stop_sequence_txt, max_context_length_slider, max_generation_slider, presence_penalty_slider, frequency_penalty_slider, logit_bias_txt, user_identifier_txt],
         _js='(a,b)=>{return bgSelectHistory(a,b);}'
     )
 

modules/models/OpenAI.py

@@ -32,6 +32,7 @@ class OpenAIClient(BaseLLMModel):
             system_prompt=system_prompt,
             user=user_name
         )
+        logging.info(f"TEMPERATURE: {self.temperature}")
         self.api_key = api_key
         self.need_api_key = True
         self._refresh_header()

modules/models/base_model.py

@@ -214,6 +214,7 @@ class BaseLLMModel:
         frequency_penalty=0,
         logit_bias=None,
         user="",
+        single_turn=False,
     ) -> None:
         self.history = []
         self.all_token_counts = []
@@ -230,10 +231,21 @@ class BaseLLMModel:
         self.system_prompt = system_prompt
         self.api_key = None
         self.need_api_key = False
-        self.single_turn = False
         self.history_file_path = get_first_history_name(user)
         self.user_name = user
 
+        self.default_single_turn = single_turn
+        self.default_temperature = temperature
+        self.default_top_p = top_p
+        self.default_n_choices = n_choices
+        self.default_stop_sequence = stop
+        self.default_max_generation_token = max_generation_token
+        self.default_presence_penalty = presence_penalty
+        self.default_frequency_penalty = frequency_penalty
+        self.default_logit_bias = logit_bias
+        self.default_user_identifier = user
+
+        self.single_turn = single_turn
         self.temperature = temperature
         self.top_p = top_p
         self.n_choices = n_choices
@@ -251,7 +263,9 @@ class BaseLLMModel:
         Conversations are stored in self.history, with the most recent question in OpenAI format.
         Should return a generator that yields the next word (str) in the answer.
         """
-        logging.warning("Stream prediction is not implemented. Using at once prediction instead.")
+        logging.warning(
+            "Stream prediction is not implemented. Using at once prediction instead."
+        )
         response, _ = self.get_answer_at_once()
         yield response
 
@@ -749,11 +763,34 @@ class BaseLLMModel:
         history_name = self.history_file_path[:-5]
         choices = [history_name] + get_history_names(self.user_name)
         system_prompt = self.system_prompt if remain_system_prompt else ""
+
+        self.single_turn = self.default_single_turn
+        self.temperature = self.default_temperature
+        self.top_p = self.default_top_p
+        self.n_choices = self.default_n_choices
+        self.stop_sequence = self.default_stop_sequence
+        self.max_generation_token = self.default_max_generation_token
+        self.presence_penalty = self.default_presence_penalty
+        self.frequency_penalty = self.default_frequency_penalty
+        self.logit_bias = self.default_logit_bias
+        self.user_identifier = self.default_user_identifier
+
         return (
             [],
             self.token_message([0]),
             gr.Radio.update(choices=choices, value=history_name),
             system_prompt,
+            self.single_turn,
+            self.temperature,
+            self.top_p,
+            self.n_choices,
+            self.stop_sequence,
+            self.token_upper_limit,
+            self.max_generation_token,
+            self.presence_penalty,
+            self.frequency_penalty,
+            self.logit_bias,
+            self.user_identifier,
         )
 
     def delete_first_conversation(self):
@@ -877,30 +914,67 @@ class BaseLLMModel:
                 pass
             if len(saved_json["chatbot"]) < len(saved_json["history"]) // 2:
                 logging.info("Trimming corrupted history...")
-                saved_json["history"] = saved_json["history"][-len(saved_json["chatbot"]) :]
+                saved_json["history"] = saved_json["history"][
+                    -len(saved_json["chatbot"]) :
+                ]
                 logging.info(f"Trimmed history: {saved_json['history']}")
             logging.debug(f"{self.user_name} 加载对话历史完毕")
             self.history = saved_json["history"]
-            self.single_turn = saved_json.get("single_turn", False)
-            self.temperature = saved_json.get("temperature", 1.0)
-            self.top_p = saved_json.get("top_p", None)
-            self.n_choices = saved_json.get("n_choices", 1)
-            self.stop_sequence = saved_json.get("stop_sequence", None)
-            self.max_generation_token = saved_json.get("max_generation_token", None)
-            self.presence_penalty = saved_json.get("presence_penalty", 0)
-            self.frequency_penalty = saved_json.get("frequency_penalty", 0)
-            self.logit_bias = saved_json.get("logit_bias", None)
+            self.single_turn = saved_json.get("single_turn", self.single_turn)
+            self.temperature = saved_json.get("temperature", self.temperature)
+            self.top_p = saved_json.get("top_p", self.top_p)
+            self.n_choices = saved_json.get("n_choices", self.n_choices)
+            self.stop_sequence = saved_json.get("stop_sequence", self.stop_sequence)
+            self.token_upper_limit = saved_json.get(
+                "token_upper_limit", self.token_upper_limit
+            )
+            self.max_generation_token = saved_json.get(
+                "max_generation_token", self.max_generation_token
+            )
+            self.presence_penalty = saved_json.get(
+                "presence_penalty", self.presence_penalty
+            )
+            self.frequency_penalty = saved_json.get(
+                "frequency_penalty", self.frequency_penalty
+            )
+            self.logit_bias = saved_json.get("logit_bias", self.logit_bias)
             self.user_identifier = saved_json.get("user_identifier", self.user_name)
-            self.metadata = saved_json.get("metadata", {})
+            self.metadata = saved_json.get("metadata", self.metadata)
             return (
-                os.path.basename(self.history_file_path),
+                os.path.basename(self.history_file_path)[:-5],
                 saved_json["system"],
                 saved_json["chatbot"],
+                self.single_turn,
+                self.temperature,
+                self.top_p,
+                self.n_choices,
+                self.stop_sequence,
+                self.token_upper_limit,
+                self.max_generation_token,
+                self.presence_penalty,
+                self.frequency_penalty,
+                self.logit_bias,
+                self.user_identifier,
             )
         except:
             # 没有对话历史或者对话历史解析失败
             logging.info(f"没有找到对话历史记录 {self.history_file_path}")
-            return self.history_file_path, "", []
+            return (
+                os.path.basename(self.history_file_path),
+                "",
+                [],
+                self.single_turn,
+                self.temperature,
+                self.top_p,
+                self.n_choices,
+                self.stop_sequence,
+                self.token_upper_limit,
+                self.max_generation_token,
+                self.presence_penalty,
+                self.frequency_penalty,
+                self.logit_bias,
+                self.user_identifier,
+            )
 
     def delete_chat_history(self, filename):
         if filename == "CANCELED":
@@ -910,9 +984,7 @@ class BaseLLMModel:
         if not filename.endswith(".json"):
             filename += ".json"
         if filename == os.path.basename(filename):
-            history_file_path = os.path.join(
-                HISTORY_DIR, self.user_name, filename
-            )
+            history_file_path = os.path.join(HISTORY_DIR, self.user_name, filename)
         else:
             history_file_path = filename
         md_history_file_path = history_file_path[:-5] + ".md"
@@ -934,9 +1006,7 @@ class BaseLLMModel:
             self.history_file_path = new_auto_history_filename(self.user_name)
         else:
             self.history_file_path = filepath
-        filename, system_prompt, chatbot = self.load_chat_history()
-        filename = filename[:-5]
-        return filename, system_prompt, chatbot
+        return self.load_chat_history()
 
     def like(self):
         """like the last response, implement if needed"""

modules/utils.py

@@ -389,6 +389,7 @@ def save_file(filename, model, chatbot):
         "top_p": model.top_p,
         "n_choices": model.n_choices,
         "stop_sequence": model.stop_sequence,
+        "token_upper_limit": model.token_upper_limit,
         "max_generation_token": model.max_generation_token,
         "presence_penalty": model.presence_penalty,
         "frequency_penalty": model.frequency_penalty,