为GPT4做准备。加入模型选择功能。

ChuanhuChatbot.py

@@ -51,10 +51,12 @@ with gr.Blocks(css=customCSS) as demo:
 
     gr.HTML(title)
     with gr.Row():
-        with gr.Column(scale=4):
-            keyTxt = gr.Textbox(show_label=False, placeholder=f"在这里输入你的OpenAI API-key...",value=my_api_key, type="password", visible=not HIDE_MY_KEY).style(container=False)
-        with gr.Column(scale=1):
-            use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
+        with gr.Column():
+            keyTxt = gr.Textbox(show_label=True, placeholder=f"在这里输入你的OpenAI API-key...",value=my_api_key, type="password", visible=not HIDE_MY_KEY, label="API-Key")
+        with gr.Column():
+            with gr.Row():
+                model_select_dropdown = gr.Dropdown(label="选择模型", choices=MODELS, multiselect=False, value=MODELS[0])
+                use_streaming_checkbox = gr.Checkbox(label="实时传输回答", value=True, visible=enable_streaming_option)
     chatbot = gr.Chatbot()  # .style(color_map=("#1D51EE", "#585A5B"))
     with gr.Row():
         with gr.Column(scale=12):
@@ -108,20 +110,20 @@ with gr.Blocks(css=customCSS) as demo:
     gr.Markdown(description)
 
 
-    user_input.submit(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
+    user_input.submit(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
     user_input.submit(reset_textbox, [], [user_input])
 
-    submitBtn.click(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
+    submitBtn.click(predict, [keyTxt, systemPromptTxt, history, user_input, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
     submitBtn.click(reset_textbox, [], [user_input])
 
     emptyBtn.click(reset_state, outputs=[chatbot, history, token_count, status_display], show_progress=True)
 
-    retryBtn.click(retry, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
+    retryBtn.click(retry, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
 
-    delLastBtn.click(delete_last_conversation, [chatbot, history, token_count, use_streaming_checkbox], [
+    delLastBtn.click(delete_last_conversation, [chatbot, history, token_count, use_streaming_checkbox, model_select_dropdown], [
                      chatbot, history, token_count, status_display], show_progress=True)
 
-    reduceTokenBtn.click(reduce_token_size, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox], [chatbot, history, status_display, token_count], show_progress=True)
+    reduceTokenBtn.click(reduce_token_size, [keyTxt, systemPromptTxt, history, chatbot, token_count, top_p, temperature, use_streaming_checkbox, model_select_dropdown], [chatbot, history, status_display, token_count], show_progress=True)
 
     saveHistoryBtn.click(save_chat_history, [
                   saveFileName, systemPromptTxt, history, chatbot], None, show_progress=True)

Dockerfile 2

@@ -0,0 +1,14 @@
+FROM python:3.9 as builder
+RUN apt-get update && apt-get install -y build-essential
+COPY requirements.txt .
+RUN pip install --user -r requirements.txt
+
+FROM python:3.9
+MAINTAINER iskoldt
+COPY --from=builder /root/.local /root/.local
+ENV PATH=/root/.local/bin:$PATH
+COPY . /app
+WORKDIR /app
+ENV my_api_key empty
+ENV dockerrun yes
+CMD ["python3", "-u", "ChuanhuChatbot.py", "2>&1", "|", "tee", "/var/log/application.log"]

presets.py

@@ -32,6 +32,7 @@ pre code {
 """
 
 summarize_prompt = "请总结以上对话，不超过100字。" # 总结对话时的 prompt
+MODELS = ["gpt-3.5-turbo"] # 可选的模型
 
 # 错误信息
 standard_error_msg = "☹️发生了错误：" # 错误信息的标准前缀

requirements 2.txt

@@ -0,0 +1 @@
+git+https://github.com/GaiZhenbiao/gradio.git

utils.py

@@ -99,7 +99,7 @@ def construct_assistant(text):
 def construct_token_message(token, stream=False):
     return f"Token 计数: {token}"
 
-def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream):
+def get_response(openai_api_key, system_prompt, history, temperature, top_p, stream, selected_model):
     headers = {
         "Content-Type": "application/json",
         "Authorization": f"Bearer {openai_api_key}"
@@ -108,7 +108,7 @@ def get_response(openai_api_key, system_prompt, history, temperature, top_p, str
     history = [construct_system(system_prompt), *history]
 
     payload = {
-        "model": "gpt-3.5-turbo",
+        "model": selected_model,
         "messages": history,  # [{"role": "user", "content": f"{inputs}"}],
         "temperature": temperature,  # 1.0,
         "top_p": top_p,  # 1.0,
@@ -124,7 +124,7 @@ def get_response(openai_api_key, system_prompt, history, temperature, top_p, str
     response = requests.post(API_URL, headers=headers, json=payload, stream=True, timeout=timeout)
     return response
 
-def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature):
+def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
     def get_return_value():
         return chatbot, history, status_text, all_token_counts
 
@@ -145,7 +145,7 @@ def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_
     print(f"输入token计数: {user_token_count}")
     yield get_return_value()
     try:
-        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True)
+        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, True, selected_model)
     except requests.exceptions.ConnectTimeout:
         status_text = standard_error_msg + connection_timeout_prompt + error_retrieve_prompt
         yield get_return_value()
@@ -192,14 +192,14 @@ def stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_
                 yield get_return_value()
 
 
-def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature):
+def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model):
     print("一次性回答模式")
     history.append(construct_user(inputs))
     history.append(construct_assistant(""))
     chatbot.append((parse_text(inputs), ""))
     all_token_counts.append(count_token(inputs))
     try:
-        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False)
+        response = get_response(openai_api_key, system_prompt, history, temperature, top_p, False, selected_model)
     except requests.exceptions.ConnectTimeout:
         status_text = standard_error_msg + error_retrieve_prompt
         return chatbot, history, status_text, all_token_counts
@@ -218,7 +218,7 @@ def predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_tok
     return chatbot, history, status_text, all_token_counts
 
 
-def predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, stream=False, should_check_token_count = True):  # repetition_penalty, top_k
+def predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, stream=False, selected_model = MODELS[0], should_check_token_count = True):  # repetition_penalty, top_k
     print("输入为：" +colorama.Fore.BLUE + f"{inputs}" + colorama.Style.RESET_ALL)
     if len(openai_api_key) != 51:
         status_text = standard_error_msg + no_apikey_msg
@@ -232,12 +232,12 @@ def predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_c
     yield chatbot, history, "开始生成回答……", all_token_counts
     if stream:
         print("使用流式传输")
-        iter = stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature)
+        iter = stream_predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model)
         for chatbot, history, status_text, all_token_counts in iter:
             yield chatbot, history, status_text, all_token_counts
     else:
         print("不使用流式传输")
-        chatbot, history, status_text, all_token_counts = predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature)
+        chatbot, history, status_text, all_token_counts = predict_all(openai_api_key, system_prompt, history, inputs, chatbot, all_token_counts, top_p, temperature, selected_model)
         yield chatbot, history, status_text, all_token_counts
     print(f"传输完毕。当前token计数为{all_token_counts}")
     if len(history) > 1 and history[-1]['content'] != inputs:
@@ -254,7 +254,7 @@ def predict(openai_api_key, system_prompt, history, inputs, chatbot, all_token_c
             yield chatbot, history, status_text, all_token_counts
 
 
-def retry(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False):
+def retry(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, selected_model = MODELS[0]):
     print("重试中……")
     if len(history) == 0:
         yield chatbot, history, f"{standard_error_msg}上下文是空的", token_count
@@ -262,15 +262,15 @@ def retry(openai_api_key, system_prompt, history, chatbot, token_count, top_p, t
     history.pop()
     inputs = history.pop()["content"]
     token_count.pop()
-    iter = predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream)
+    iter = predict(openai_api_key, system_prompt, history, inputs, chatbot, token_count, top_p, temperature, stream=stream, selected_model=selected_model)
     print("重试完毕")
     for x in iter:
         yield x
 
 
-def reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, hidden=False):
+def reduce_token_size(openai_api_key, system_prompt, history, chatbot, token_count, top_p, temperature, stream=False, hidden=False, selected_model = MODELS[0]):
     print("开始减少token数量……")
-    iter = predict(openai_api_key, system_prompt, history, summarize_prompt, chatbot, token_count, top_p, temperature, stream=stream, should_check_token_count=False)
+    iter = predict(openai_api_key, system_prompt, history, summarize_prompt, chatbot, token_count, top_p, temperature, stream=stream, selected_model = selected_model, should_check_token_count=False)
     for chatbot, history, status_text, previous_token_count in iter:
         history = history[-2:]
         token_count = previous_token_count[-1:]