加入中止回答的功能

ChuanhuChatbot.py

@@ -5,10 +5,10 @@
 
 import gradio as gr
 
-from utils import *
-from presets import *
-from overwrites import *
-from chat_func import *
+from modules.utils import *
+from modules.presets import *
+from modules.overwrites import *
+from modules.chat_func import *
 
 logging.basicConfig(
     level=logging.DEBUG,
@@ -54,7 +54,7 @@
 gr.Chatbot.postprocess = postprocess
 PromptHelper.compact_text_chunks = compact_text_chunks
 
-with open("custom.css", "r", encoding="utf-8") as f:
+with open("assets/custom.css", "r", encoding="utf-8") as f:
     customCSS = f.read()
 
 with gr.Blocks(
@@ -124,8 +124,7 @@
     token_count = gr.State([])
     promptTemplates = gr.State(load_template(get_template_names(plain=True)[0], mode=2))
     user_api_key = gr.State(my_api_key)
-    TRUECOMSTANT = gr.State(True)
-    FALSECONSTANT = gr.State(False)
+    outputing = gr.State(False)
     topic = gr.State("未命名对话历史记录")
 
     with gr.Row():
@@ -275,12 +274,9 @@
 
     gr.Markdown(description)
 
-    keyTxt.submit(submit_key, keyTxt, [user_api_key, status_display])
-    keyTxt.change(submit_key, keyTxt, [user_api_key, status_display])
-    # Chatbot
-    user_input.submit(
-        predict,
-        [
+    chatgpt_predict_args = dict(
+        fn=predict,
+        inputs=[
             user_api_key,
             systemPromptTxt,
             history,
@@ -294,40 +290,45 @@
             use_websearch_checkbox,
             index_files,
         ],
-        [chatbot, history, status_display, token_count],
+        outputs=[chatbot, history, status_display, token_count],
         show_progress=True,
     )
-    user_input.submit(reset_textbox, [], [user_input])
 
-    # submitBtn.click(return_cancel_btn, [], [submitBtn, cancelBtn])
-    submitBtn.click(
-        predict,
-        [
-            user_api_key,
-            systemPromptTxt,
-            history,
-            user_input,
-            chatbot,
-            token_count,
-            top_p,
-            temperature,
-            use_streaming_checkbox,
-            model_select_dropdown,
-            use_websearch_checkbox,
-            index_files,
-        ],
-        [chatbot, history, status_display, token_count],
-        show_progress=True,
+    start_outputing_args = dict(
+        fn=start_outputing, inputs=[], outputs=[submitBtn, cancelBtn], show_progress=True
+    )
+
+    end_outputing_args = dict(
+        fn=end_outputing, inputs=[], outputs=[submitBtn, cancelBtn]
+    )
+
+    reset_textbox_args = dict(
+        fn=reset_textbox, inputs=[], outputs=[user_input], show_progress=True
+    )
+
+    keyTxt.submit(submit_key, keyTxt, [user_api_key, status_display])
+    keyTxt.change(submit_key, keyTxt, [user_api_key, status_display])
+    # Chatbot
+    cancelBtn.click(cancel_outputing, [], [])
+
+    user_input.submit(**start_outputing_args).then(
+        **chatgpt_predict_args
+    ).then(**reset_textbox_args).then(
+        **end_outputing_args
+    )
+    submitBtn.click(**start_outputing_args).then(
+        **chatgpt_predict_args
+    ).then(**reset_textbox_args).then(
+        **end_outputing_args
     )
-    submitBtn.click(reset_textbox, [], [user_input])
 
     emptyBtn.click(
         reset_state,
         outputs=[chatbot, history, token_count, status_display],
         show_progress=True,
-    )
+    ).then(**reset_textbox_args)
 
-    retryBtn.click(
+    retryBtn.click(**start_outputing_args).then(
         retry,
         [
             user_api_key,
@@ -342,7 +343,7 @@
         ],
         [chatbot, history, status_display, token_count],
         show_progress=True,
-    )
+    ).then(**end_outputing_args)
 
     delLastBtn.click(
         delete_last_conversation,
@@ -441,17 +442,31 @@
     if dockerflag:
         if authflag:
             demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
-                server_name="0.0.0.0", server_port=7860, auth=(username, password),
-                favicon_path="./assets/favicon.png"
+                server_name="0.0.0.0",
+                server_port=7860,
+                auth=(username, password),
+                favicon_path="./assets/favicon.png",
             )
         else:
-            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=7860, share=False, favicon_path="./assets/favicon.png")
+            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
+                server_name="0.0.0.0",
+                server_port=7860,
+                share=False,
+                favicon_path="./assets/favicon.png",
+            )
     # if not running in Docker
     else:
         if authflag:
-            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(share=False, auth=(username, password), favicon_path="./assets/favicon.png", inbrowser=True)
+            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
+                share=False,
+                auth=(username, password),
+                favicon_path="./assets/favicon.png",
+                inbrowser=True,
+            )
         else:
-            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(share=False, favicon_path="./assets/favicon.ico", inbrowser=True)  # 改为 share=True 可以创建公开分享链接
+            demo.queue(concurrency_count=CONCURRENT_COUNT).launch(
+                share=False, favicon_path="./assets/favicon.ico", inbrowser=True
+            )  # 改为 share=True 可以创建公开分享链接
         # demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=7860, share=False) # 可自定义端口
         # demo.queue(concurrency_count=CONCURRENT_COUNT).launch(server_name="0.0.0.0", server_port=7860,auth=("在这里填写用户名", "在这里填写密码")) # 可设置用户名与密码
         # demo.queue(concurrency_count=CONCURRENT_COUNT).launch(auth=("在这里填写用户名", "在这里填写密码")) # 适合Nginx反向代理

chat_func.py → modules/chat_func.py

@@ -14,9 +14,10 @@
 import asyncio
 import aiohttp
 
-from presets import *
-from llama_func import *
-from utils import *
+from modules.presets import *
+from modules.llama_func import *
+from modules.utils import *
+import modules.shared as shared
 
 # logging.basicConfig(level=logging.INFO, format="%(asctime)s [%(levelname)s] [%(filename)s:%(lineno)d] %(message)s")
 
@@ -29,7 +30,6 @@ class DataframeData(TypedDict):
 
 
 initial_prompt = "You are a helpful assistant."
-API_URL = "https://api.openai.com/v1/chat/completions"
 HISTORY_DIR = "history"
 TEMPLATES_DIR = "templates"
 
@@ -65,16 +65,18 @@ def get_response(
     # 如果存在代理设置，使用它们
     proxies = {}
     if http_proxy:
-        logging.info(f"Using HTTP proxy: {http_proxy}")
+        logging.info(f"使用 HTTP 代理: {http_proxy}")
         proxies["http"] = http_proxy
     if https_proxy:
-        logging.info(f"Using HTTPS proxy: {https_proxy}")
+        logging.info(f"使用 HTTPS 代理: {https_proxy}")
         proxies["https"] = https_proxy
 
     # 如果有代理，使用代理发送请求，否则使用默认设置发送请求
+    if shared.state.api_url != API_URL:
+        logging.info(f"使用自定义API URL: {shared.state.api_url}")
     if proxies:
         response = requests.post(
-            API_URL,
+            shared.state.api_url,
             headers=headers,
             json=payload,
             stream=True,
@@ -83,7 +85,7 @@ def get_response(
         )
     else:
         response = requests.post(
-            API_URL,
+            shared.state.api_url,
             headers=headers,
             json=payload,
             stream=True,
@@ -268,10 +270,10 @@ def predict(
     if files:
         msg = "构建索引中……（这可能需要比较久的时间）"
         logging.info(msg)
-        yield chatbot, history, msg, all_token_counts
+        yield chatbot+[(inputs, "")], history, msg, all_token_counts
         index = construct_index(openai_api_key, file_src=files)
         msg = "索引构建完成，获取回答中……"
-        yield chatbot, history, msg, all_token_counts
+        yield chatbot+[(inputs, "")], history, msg, all_token_counts
         history, chatbot, status_text = chat_ai(openai_api_key, index, inputs, history, chatbot)
         yield chatbot, history, status_text, all_token_counts
         return
@@ -306,10 +308,15 @@ def predict(
             all_token_counts.append(0)
         else:
             history[-2] = construct_user(inputs)
-        yield chatbot, history, status_text, all_token_counts
+        yield chatbot+[(inputs, "")], history, status_text, all_token_counts
+        return
+    elif len(inputs.strip()) == 0:
+        status_text = standard_error_msg + no_input_msg
+        logging.info(status_text)
+        yield chatbot+[(inputs, "")], history, status_text, all_token_counts
         return
 
-    yield chatbot, history, "开始生成回答……", all_token_counts
+    yield chatbot+[(inputs, "")], history, "开始生成回答……", all_token_counts
 
     if stream:
         logging.info("使用流式传输")
@@ -327,6 +334,9 @@ def predict(
             display_append=link_references
         )
         for chatbot, history, status_text, all_token_counts in iter:
+            if shared.state.interrupted:
+                shared.state.recover()
+                return
             yield chatbot, history, status_text, all_token_counts
     else:
         logging.info("不使用流式传输")

llama_func.py → modules/llama_func.py

@@ -14,8 +14,8 @@
 import colorama
 
 
-from presets import *
-from utils import *
+from modules.presets import *
+from modules.utils import *
 
 
 def get_documents(file_src):

overwrites.py → modules/overwrites.py

@@ -5,8 +5,8 @@
 from typing import List, Tuple
 import mdtex2html
 
-from presets import *
-from llama_func import *
+from modules.presets import *
+from modules.llama_func import *
 
 
 def compact_text_chunks(self, prompt: Prompt, text_chunks: List[str]) -> List[str]:
@@ -51,5 +51,5 @@ def template_response(*args, **kwargs):
         return res
 
     gr.routes.templates.TemplateResponse = template_response
-     
+
 GradioTemplateResponseOriginal = gr.routes.templates.TemplateResponse

presets.py → modules/presets.py

@@ -14,9 +14,10 @@
 proxy_error_prompt = "代理错误，无法获取对话。"  # 代理错误
 ssl_error_prompt = "SSL错误，无法获取对话。"  # SSL 错误
 no_apikey_msg = "API key长度不是51位，请检查是否输入正确。"  # API key 长度不足 51 位
+no_input_msg = "请输入对话内容。"  # 未输入对话内容
 
 max_token_streaming = 3500  # 流式对话时的最大 token 数
-timeout_streaming = 30  # 流式对话时的超时时间
+timeout_streaming = 5  # 流式对话时的超时时间
 max_token_all = 3500  # 非流式对话时的最大 token 数
 timeout_all = 200  # 非流式对话时的超时时间
 enable_streaming_option = True  # 是否启用选择选择是否实时显示回答的勾选框

modules/shared.py

@@ -0,0 +1,24 @@
+from modules.presets import API_URL
+
+class State:
+    interrupted = False
+    api_url = API_URL
+
+    def interrupt(self):
+        self.interrupted = True
+
+    def recover(self):
+        self.interrupted = False
+
+    def set_api_url(self, api_url):
+        self.api_url = api_url
+
+    def reset_api_url(self):
+        self.api_url = API_URL
+        return self.api_url
+
+    def reset_all(self):
+        self.interrupted = False
+        self.api_url = API_URL
+
+state = State()