合并master修改

2023-04-23 10:04:32 +08:00
parent 3f4e4ba261 95f8b2824a
commit 94df191060
16 changed files with 435 additions and 59 deletions
--- a/request_llm/README.md
+++ b/request_llm/README.md
@ -1,4 +1,4 @@
-# 如何使用其他大语言模型（v3.0分支测试中）
+# 如何使用其他大语言模型

 ## ChatGLM

@ -15,7 +15,7 @@ LLM_MODEL = "chatglm"


 ---
-## Text-Generation-UI (TGUI)
+## Text-Generation-UI (TGUI，调试中，暂不可用)

 ### 1. 部署TGUI
 ``` sh
--- a/request_llm/bridge_all.py
+++ b/request_llm/bridge_all.py
@ -1,16 +1,17 @@

 """
-    该文件中主要包含2个函数
+    该文件中主要包含2个函数，是所有LLM的通用接口，它们会继续向下调用更底层的LLM模型，处理多模型并行等细节

-    不具备多线程能力的函数：
-    1. predict: 正常对话时使用，具备完备的交互功能，不可多线程
+    不具备多线程能力的函数：正常对话时使用，具备完备的交互功能，不可多线程
+    1. predict(...)

-    具备多线程调用能力的函数
-    2. predict_no_ui_long_connection：在实验过程中发现调用predict_no_ui处理长文档时，和openai的连接容易断掉，这个函数用stream的方式解决这个问题，同样支持多线程
+    具备多线程调用能力的函数：在函数插件中被调用，灵活而简洁
+    2. predict_no_ui_long_connection(...)
 """
 import tiktoken
-from functools import wraps, lru_cache
+from functools import lru_cache
 from concurrent.futures import ThreadPoolExecutor
+from toolbox import get_conf

 from request_llm.bridge_chatgpt import predict_no_ui_long_connection as chatgpt_noui
 from request_llm.bridge_chatgpt import predict as chatgpt_ui
@ -42,18 +43,37 @@ class LazyloadTiktoken(object):
    def decode(self, *args, **kwargs):
        encoder = self.get_encoder(self.model) 
        return encoder.decode(*args, **kwargs)
-    
+
+# Endpoint 重定向
+API_URL_REDIRECT, = get_conf("API_URL_REDIRECT")
+openai_endpoint = "https://api.openai.com/v1/chat/completions"
+api2d_endpoint = "https://openai.api2d.net/v1/chat/completions"
+# 兼容旧版的配置
+try:
+    API_URL, = get_conf("API_URL")
+    if API_URL != "https://api.openai.com/v1/chat/completions": 
+        openai_endpoint = API_URL
+        print("警告！API_URL配置选项将被弃用，请更换为API_URL_REDIRECT配置")
+except:
+    pass
+# 新版配置
+if openai_endpoint in API_URL_REDIRECT: openai_endpoint = API_URL_REDIRECT[openai_endpoint]
+if api2d_endpoint in API_URL_REDIRECT: api2d_endpoint = API_URL_REDIRECT[api2d_endpoint]
+
+
+# 获取tokenizer
 tokenizer_gpt35 = LazyloadTiktoken("gpt-3.5-turbo")
 tokenizer_gpt4 = LazyloadTiktoken("gpt-4")
 get_token_num_gpt35 = lambda txt: len(tokenizer_gpt35.encode(txt, disallowed_special=()))
 get_token_num_gpt4 = lambda txt: len(tokenizer_gpt4.encode(txt, disallowed_special=()))

+
 model_info = {
    # openai
    "gpt-3.5-turbo": {
        "fn_with_ui": chatgpt_ui,
        "fn_without_ui": chatgpt_noui,
-        "endpoint": "https://api.openai.com/v1/chat/completions",
+        "endpoint": openai_endpoint,
        "max_token": 4096,
        "tokenizer": tokenizer_gpt35,
        "token_cnt": get_token_num_gpt35,
@ -62,7 +82,7 @@ model_info = {
    "gpt-4": {
        "fn_with_ui": chatgpt_ui,
        "fn_without_ui": chatgpt_noui,
-        "endpoint": "https://api.openai.com/v1/chat/completions",
+        "endpoint": openai_endpoint,
        "max_token": 8192,
        "tokenizer": tokenizer_gpt4,
        "token_cnt": get_token_num_gpt4,
@ -72,7 +92,7 @@ model_info = {
    "api2d-gpt-3.5-turbo": {
        "fn_with_ui": chatgpt_ui,
        "fn_without_ui": chatgpt_noui,
-        "endpoint": "https://openai.api2d.net/v1/chat/completions",
+        "endpoint": api2d_endpoint,
        "max_token": 4096,
        "tokenizer": tokenizer_gpt35,
        "token_cnt": get_token_num_gpt35,
@ -81,7 +101,7 @@ model_info = {
    "api2d-gpt-4": {
        "fn_with_ui": chatgpt_ui,
        "fn_without_ui": chatgpt_noui,
-        "endpoint": "https://openai.api2d.net/v1/chat/completions",
+        "endpoint": api2d_endpoint,
        "max_token": 8192,
        "tokenizer": tokenizer_gpt4,
        "token_cnt": get_token_num_gpt4,
@ -190,7 +210,7 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history, sys_prompt, obser
            return_string_collect.append( f"【{str(models[i])} 说】: <font color=\"{colors[i]}\"> {future.result()} </font>" )

        window_mutex[-1] = False # stop mutex thread
-        res = '<br/>\n\n---\n\n'.join(return_string_collect)
+        res = '<br/><br/>\n\n---\n\n'.join(return_string_collect)
        return res


--- a/request_llm/bridge_chatglm.py
+++ b/request_llm/bridge_chatglm.py
@ -92,8 +92,8 @@ def predict_no_ui_long_connection(inputs, llm_kwargs, history=[], sys_prompt="",

    # chatglm 没有 sys_prompt 接口，因此把prompt加入 history
    history_feedin = []
+    history_feedin.append(["What can I do?", sys_prompt])
    for i in range(len(history)//2):
-        history_feedin.append(["What can I do?", sys_prompt] )
        history_feedin.append([history[2*i], history[2*i+1]] )

    watch_dog_patience = 5 # 看门狗 (watchdog) 的耐心, 设置5秒即可
@ -131,10 +131,13 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
        inputs = core_functional[additional_fn]["Prefix"] + inputs + core_functional[additional_fn]["Suffix"]

    history_feedin = []
+    history_feedin.append(["What can I do?", system_prompt] )
    for i in range(len(history)//2):
-        history_feedin.append(["What can I do?", system_prompt] )
        history_feedin.append([history[2*i], history[2*i+1]] )

    for response in glm_handle.stream_chat(query=inputs, history=history_feedin, max_length=llm_kwargs['max_length'], top_p=llm_kwargs['top_p'], temperature=llm_kwargs['temperature']):
        chatbot[-1] = (inputs, response)
-        yield from update_ui(chatbot=chatbot, history=history)
+        yield from update_ui(chatbot=chatbot, history=history)
+
+    history.extend([inputs, response])
+    yield from update_ui(chatbot=chatbot, history=history)
--- a/request_llm/bridge_chatgpt.py
+++ b/request_llm/bridge_chatgpt.py
@ -21,7 +21,7 @@ import importlib

 # config_private.py放自己的秘密如API和代理网址
 # 读取时首先看是否存在私密的config_private配置文件（不受git管控），如果有，则覆盖原config文件
-from toolbox import get_conf, update_ui, is_any_api_key, select_api_key
+from toolbox import get_conf, update_ui, is_any_api_key, select_api_key, what_keys
 proxies, API_KEY, TIMEOUT_SECONDS, MAX_RETRY = \
    get_conf('proxies', 'API_KEY', 'TIMEOUT_SECONDS', 'MAX_RETRY')

@ -118,7 +118,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
    """
    if is_any_api_key(inputs):
        chatbot._cookies['api_key'] = inputs
-        chatbot.append(("输入已识别为openai的api_key", "api_key已导入"))
+        chatbot.append(("输入已识别为openai的api_key", what_keys(inputs)))
        yield from update_ui(chatbot=chatbot, history=history, msg="api_key已导入") # 刷新界面
        return
    elif not is_any_api_key(chatbot._cookies['api_key']):
@ -141,7 +141,7 @@ def predict(inputs, llm_kwargs, plugin_kwargs, chatbot, history=[], system_promp
    try:
        headers, payload = generate_payload(inputs, llm_kwargs, history, system_prompt, stream)
    except RuntimeError as e:
-        chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。")
+        chatbot[-1] = (inputs, f"您提供的api-key不满足要求，不包含任何可用于{llm_kwargs['llm_model']}的api-key。您可能选择了错误的模型或请求源。")
        yield from update_ui(chatbot=chatbot, history=history, msg="api-key不满足要求") # 刷新界面
        return