From e359fff0405c4cb865b809b4ecfc0a95a54d2512 Mon Sep 17 00:00:00 2001
From: binary-husky <qingxu.fu@outlook.com>
Date: Thu, 15 Feb 2024 00:02:24 +0800
Subject: [PATCH] Fix response message bug in bridge_qianfan.py,
 bridge_qwen.py, and bridge_skylark2.py

---
 request_llms/bridge_qianfan.py  | 12 ++++--------
 request_llms/bridge_qwen.py     |  1 +
 request_llms/bridge_skylark2.py |  1 +
 request_llms/bridge_spark.py    |  5 +++--
 4 files changed, 9 insertions(+), 10 deletions(-)

diff --git a/request_llms/bridge_qianfan.py b/request_llms/bridge_qianfan.py
index a806e0d..0f02457 100644
--- a/request_llms/bridge_qianfan.py
+++ b/request_llms/bridge_qianfan.py
@@ -146,21 +146,17 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     yield from update_ui(chatbot=chatbot, history=history)
     # 开始接收回复
     try:
+        response = f"[Local Message] 等待{model_name}响应中 ..."
         for response in generate_from_baidu_qianfan(inputs, llm_kwargs, history, system_prompt):
             chatbot[-1] = (inputs, response)
             yield from update_ui(chatbot=chatbot, history=history)
+        history.extend([inputs, response])
+        yield from update_ui(chatbot=chatbot, history=history)
     except ConnectionAbortedError as e:
         from .bridge_all import model_info
         if len(history) >= 2: history[-1] = ""; history[-2] = "" # 清除当前溢出的输入：history[-2] 是本次输入, history[-1] 是本次输出
-        history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'], 
+        history = clip_history(inputs=inputs, history=history, tokenizer=model_info[llm_kwargs['llm_model']]['tokenizer'],
                     max_token_limit=(model_info[llm_kwargs['llm_model']]['max_token'])) # history至少释放二分之一
         chatbot[-1] = (chatbot[-1][0], "[Local Message] Reduce the length. 本次输入过长, 或历史数据过长. 历史缓存数据已部分释放, 您可以请再次尝试. (若再次失败则更可能是因为输入过长.)")
         yield from update_ui(chatbot=chatbot, history=history, msg="异常") # 刷新界面
         return
-    
-    # 总结输出
-    response = f"[Local Message] {model_name}响应异常 ..."
-    if response == f"[Local Message] 等待{model_name}响应中 ...":
-        response = f"[Local Message] {model_name}响应异常 ..."
-    history.extend([inputs, response])
-    yield from update_ui(chatbot=chatbot, history=history)
\ No newline at end of file
diff --git a/request_llms/bridge_qwen.py b/request_llms/bridge_qwen.py
index 18877b9..808c2c7 100644
--- a/request_llms/bridge_qwen.py
+++ b/request_llms/bridge_qwen.py
@@ -51,6 +51,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     # 开始接收回复
     from .com_qwenapi import QwenRequestInstance
     sri = QwenRequestInstance()
+    response = f"[Local Message] 等待{model_name}响应中 ..."
     for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
         chatbot[-1] = (inputs, response)
         yield from update_ui(chatbot=chatbot, history=history)
diff --git a/request_llms/bridge_skylark2.py b/request_llms/bridge_skylark2.py
index 8f10b83..1a8edcb 100644
--- a/request_llms/bridge_skylark2.py
+++ b/request_llms/bridge_skylark2.py
@@ -56,6 +56,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
     # 开始接收回复
     from .com_skylark2api import YUNQUERequestInstance
     sri = YUNQUERequestInstance()
+    response = f"[Local Message] 等待{model_name}响应中 ..."
     for response in sri.generate(inputs, llm_kwargs, history, system_prompt):
         chatbot[-1] = (inputs, response)
         yield from update_ui(chatbot=chatbot, history=history)
diff --git a/request_llms/bridge_spark.py b/request_llms/bridge_spark.py
index 1fe31ce..8449494 100644
--- a/request_llms/bridge_spark.py
+++ b/request_llms/bridge_spark.py
@@ -9,7 +9,7 @@ model_name = '星火认知大模型'
 
 def validate_key():
     XFYUN_APPID = get_conf('XFYUN_APPID')
-    if XFYUN_APPID == '00000000' or XFYUN_APPID == '': 
+    if XFYUN_APPID == '00000000' or XFYUN_APPID == '':
         return False
     return True
 
@@ -49,9 +49,10 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
         from core_functional import handle_core_functionality
         inputs, history = handle_core_functionality(additional_fn, inputs, history, chatbot)
 
-    # 开始接收回复    
+    # 开始接收回复
     from .com_sparkapi import SparkRequestInstance
     sri = SparkRequestInstance()
+    response = f"[Local Message] 等待{model_name}响应中 ..."
     for response in sri.generate(inputs, llm_kwargs, history, system_prompt, use_image_api=True):
         chatbot[-1] = (inputs, response)
         yield from update_ui(chatbot=chatbot, history=history)