feat: 使用tiktoken计算tokens数

README.md

@@ -242,7 +242,7 @@ cd QChatGPT
 2. 安装依赖
 
 ```bash
-pip3 install requests yiri-mirai openai colorlog func_timeout dulwich Pillow nakuru-project-idk
+pip3 install requests yiri-mirai openai colorlog func_timeout dulwich Pillow nakuru-project-idk CallingGPT tiktoken
 ```
 
 3. 运行一次主程序，生成配置文件

main.py

@@ -47,7 +47,7 @@ def init_db():
 
 def ensure_dependencies():
     import pkg.utils.pkgmgr as pkgmgr
-    pkgmgr.run_pip(["install", "openai", "Pillow", "nakuru-project-idk", "CallingGPT", "--upgrade",
+    pkgmgr.run_pip(["install", "openai", "Pillow", "nakuru-project-idk", "CallingGPT", "tiktoken", "--upgrade",
                     "-i", "https://pypi.tuna.tsinghua.edu.cn/simple",
                     "--trusted-host", "pypi.tuna.tsinghua.edu.cn"])
 

pkg/openai/api/chat_completion.py

@@ -93,10 +93,10 @@ class ChatCompletionRequest(RequestBase):
             if 'function_call' in choice0['message']:
                 self.pending_func_call = choice0['message']['function_call']
 
-                self.append_message(
+                # self.append_message(
-                    role="assistant",
+                #     role="assistant",
-                    content="function call: "+json.dumps(self.pending_func_call, ensure_ascii=False)
+                #     content="function call: "+json.dumps(self.pending_func_call, ensure_ascii=False)
-                )
+                # )
 
                 return {
                     "id": resp["id"],

pkg/openai/modelmgr.py

@@ -7,6 +7,7 @@ Completion - text-davinci-003 等模型
 """
 import openai, logging, threading, asyncio
 import openai.error as aiE
+import tiktoken
 
 from pkg.openai.api.model import RequestBase
 from pkg.openai.api.completion import CompletionRequest
@@ -49,3 +50,70 @@ def select_request_cls(model_name: str, messages: list, args: dict) -> RequestBa
     elif model_name in COMPLETION_MODELS:
         return CompletionRequest(model_name, messages, **args)
     raise ValueError("不支持模型[{}]，请检查配置文件".format(model_name))
+
+
+def count_chat_completion_tokens(messages: list, model: str) -> int:
+    """Return the number of tokens used by a list of messages."""
+    try:
+        encoding = tiktoken.encoding_for_model(model)
+    except KeyError:
+        print("Warning: model not found. Using cl100k_base encoding.")
+        encoding = tiktoken.get_encoding("cl100k_base")
+    if model in {
+        "gpt-3.5-turbo-0613",
+        "gpt-3.5-turbo-16k-0613",
+        "gpt-4-0314",
+        "gpt-4-32k-0314",
+        "gpt-4-0613",
+        "gpt-4-32k-0613",
+        }:
+        tokens_per_message = 3
+        tokens_per_name = 1
+    elif model == "gpt-3.5-turbo-0301":
+        tokens_per_message = 4  # every message follows <|start|>{role/name}\n{content}<|end|>\n
+        tokens_per_name = -1  # if there's a name, the role is omitted
+    elif "gpt-3.5-turbo" in model:
+        # print("Warning: gpt-3.5-turbo may update over time. Returning num tokens assuming gpt-3.5-turbo-0613.")
+        return count_chat_completion_tokens(messages, model="gpt-3.5-turbo-0613")
+    elif "gpt-4" in model:
+        # print("Warning: gpt-4 may update over time. Returning num tokens assuming gpt-4-0613.")
+        return count_chat_completion_tokens(messages, model="gpt-4-0613")
+    else:
+        raise NotImplementedError(
+            f"""count_chat_completion_tokens() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens."""
+        )
+    num_tokens = 0
+    for message in messages:
+        num_tokens += tokens_per_message
+        for key, value in message.items():
+            num_tokens += len(encoding.encode(value))
+            if key == "name":
+                num_tokens += tokens_per_name
+    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
+    return num_tokens
+
+
+def count_completion_tokens(messages: list, model: str) -> int:
+
+    try:
+        encoding = tiktoken.encoding_for_model(model)
+    except KeyError:
+        print("Warning: model not found. Using cl100k_base encoding.")
+        encoding = tiktoken.get_encoding("cl100k_base")
+
+    text = ""
+
+    for message in messages:
+        text += message['role'] + message['content'] + "\n"
+
+    text += "assistant: "
+
+    return len(encoding.encode(text))
+
+
+def count_tokens(messages: list, model: str):
+    if model in CHAT_COMPLETION_MODELS:
+        return count_chat_completion_tokens(messages, model)
+    elif model in COMPLETION_MODELS:
+        return count_completion_tokens(messages, model)
+    raise ValueError("不支持模型[{}]，请检查配置文件".format(model))

pkg/openai/session.py

@@ -16,6 +16,8 @@ import pkg.utils.context
 import pkg.plugin.host as plugin_host
 import pkg.plugin.models as plugin_models
 
+from pkg.openai.modelmgr import count_tokens
+
 # 运行时保存的所有session
 sessions = {}
 
@@ -107,9 +109,6 @@ class Session:
     prompt = []
     """使用list来保存会话中的回合"""
 
-    token_counts = []
-    """每个回合的token数量"""
-
     default_prompt = []
     """本session的默认prompt"""
 
@@ -215,12 +214,7 @@ class Session:
         config = pkg.utils.context.get_config()
         max_length = config.prompt_submit_length
 
-        prompts, counts = self.cut_out(text, max_length)
+        prompts, _ = self.cut_out(text, max_length)
-
-        # 计算请求前的prompt数量
-        total_token_before_query = 0
-        for token_count in counts:
-            total_token_before_query += token_count
 
         res_text = ""
 
@@ -281,8 +275,8 @@ class Session:
         self.prompt += pending_msgs
 
         # 向token_counts中添加本回合的token数量
-        self.token_counts.append(total_tokens-total_token_before_query)
+        # self.token_counts.append(total_tokens-total_token_before_query)
-        logging.debug("本回合使用token: {}, session counts: {}".format(total_tokens-total_token_before_query, self.token_counts))
+        # logging.debug("本回合使用token: {}, session counts: {}".format(total_tokens-total_token_before_query, self.token_counts))
 
         if self.just_switched_to_exist_session:
             self.just_switched_to_exist_session = False
@@ -319,24 +313,19 @@ class Session:
 
         # 包装目前的对话回合内容
         changable_prompts = []
-        changable_counts = []
-        # 倒着来, 遍历prompt的步长为2, 遍历tokens_counts的步长为1
-        changable_index = len(self.prompt) - 1
-        token_count_index = len(self.token_counts) - 1
 
-        packed_tokens = 0
+        use_model = pkg.utils.context.get_config().completion_api_params['model']
 
-        while changable_index >= 0 and token_count_index >= 0:
+        ptr = len(self.prompt) - 1
-            if packed_tokens + self.token_counts[token_count_index] > max_tokens:
+
+        # 直接从后向前扫描拼接，不管是否是整回合
+        while ptr >= 0:
+            if count_tokens(self.prompt[ptr:ptr+1]+changable_prompts, use_model) > max_tokens:
                 break
 
-            changable_prompts.insert(0, self.prompt[changable_index])
+            changable_prompts.insert(0, self.prompt[ptr])
-            changable_prompts.insert(0, self.prompt[changable_index - 1])
-            changable_counts.insert(0, self.token_counts[token_count_index])
-            packed_tokens += self.token_counts[token_count_index]
 
-            changable_index -= 2
+            ptr -= 1
-            token_count_index -= 1
 
         # 将default_prompt和changable_prompts合并
         result_prompt = self.default_prompt + changable_prompts
@@ -349,12 +338,9 @@ class Session:
             }
         )
 
-        logging.debug('cut_out: {}\nchangable section tokens: {}\npacked counts: {}\nsession counts: {}'.format(json.dumps(result_prompt, ensure_ascii=False, indent=4),
+        logging.debug("cut_out: {}".format(json.dumps(result_prompt, ensure_ascii=False, indent=4)))
-                                                                             packed_tokens,
-                                                                             changable_counts,
-                                                                             self.token_counts))
 
-        return result_prompt, changable_counts
+        return result_prompt, count_tokens(changable_prompts, use_model)
 
     # 持久化session
     def persistence(self):

requirements.txt

@@ -2,10 +2,11 @@ requests~=2.31.0
 openai~=0.27.8
 dulwich~=0.21.5
 colorlog~=6.6.0
-yiri-mirai~=0.2.7
+yiri-mirai
 websockets
 urllib3~=1.26.10
 func_timeout~=4.3.5
 Pillow
 nakuru-project-idk
 CallingGPT
+tiktoken