增加对GLM-4大模型的支持

[smartrui]

调用方法： export BASE_URL="https://open.bigmodel.cn/api/paas/v4/"
export OPENAI_API_KEY="XXXXXXXXXXXXXXXXXXXX"
python run.py --task "[Develop a snake game]" --name "[snamer03]" --model=GLM_4

错误日志： ... Note that we must ONLY discuss the product modality and do not discuss anything else! Once we all have expressed our opinion(s) and agree with the results of the discussion unanimously, any of us must actively terminate the discussion by replying with only one line, which starts with a single word , followed by our final product modality without any other words, e.g., " PowerPoint".

Traceback (most recent call last): File "/Users/rui/anaconda3/envs/ChatDev_conda_env/lib/python3.9/site-packages/tenacity/init.py", line 382, in call result = fn(*args, *kwargs) File "/Users/rui/workbrench/ChatDev/camel/utils.py", line 157, in wrapper return func(self, args, kwargs) File "/Users/rui/workbrench/ChatDev/camel/agents/chat_agent.py", line 239, in step response = self.model_backend.run(messages=openai_messages) File "/Users/rui/workbrench/ChatDev/camel/model_backend.py", line 68, in run encoding = tiktoken.encoding_for_model(self.model_type.value) File "/Users/rui/anaconda3/envs/ChatDev_conda_env/lib/python3.9/site-packages/tiktoken/model.py", line 70, in encoding_for_model raise KeyError( KeyError: 'Could not automatically map glm-4 to a tokeniser. Please use tiktok.get_encoding to explicitly get the tokeniser you expect.'**

The above exception was the direct cause of the following exception:

Traceback (most recent call last): File "/Users/rui/workbrench/ChatDev/run.py", line 135, in chat_chain.execute_chain() File "/Users/rui/workbrench/ChatDev/chatdev/chat_chain.py", line 168, in execute_chain self.execute_step(phase_item) File "/Users/rui/workbrench/ChatDev/chatdev/chat_chain.py", line 138, in execute_step self.chat_env = self.phases[phase].execute(self.chat_env, File "/Users/rui/workbrench/ChatDev/chatdev/phase.py", line 295, in execute self.chatting(chat_env=chat_env, File "/Users/rui/workbrench/ChatDev/chatdev/utils.py", line 79, in wrapper return func(*args, *kwargs) File "/Users/rui/workbrench/ChatDev/chatdev/phase.py", line 133, in chatting assistant_response, user_response = role_play_session.step(input_user_msg, chat_turn_limit == 1) File "/Users/rui/workbrench/ChatDev/camel/agents/role_playing.py", line 247, in step assistant_response = self.assistant_agent.step(user_msg_rst) File "/Users/rui/anaconda3/envs/ChatDev_conda_env/lib/python3.9/site-packages/tenacity/init.py", line 289, in wrapped_f return self(f, args, **kw) File "/Users/rui/anaconda3/envs/ChatDev_conda_env/lib/python3.9/site-packages/tenacity/init.py", line 379, in call do = self.iter(retry_state=retry_state) File "/Users/rui/anaconda3/envs/ChatDev_conda_env/lib/python3.9/site-packages/tenacity/init.py", line 326, in iter raise retry_exc from fut.exception() tenacity.RetryError: RetryError[<Future at 0x119747fd0 state=finished raised KeyError>]

代码定位： /site-packages/tiktoken/model.py MODEL_TO_ENCODING: dict[str, str] = {

chat

"gpt-4": "cl100k_base",
"gpt-3.5-turbo": "cl100k_base",
# text
"text-davinci-003": "p50k_base",
"text-davinci-002": "p50k_base",
"text-davinci-001": "r50k_base",
"text-curie-001": "r50k_base",
"text-babbage-001": "r50k_base",
"text-ada-001": "r50k_base",
"davinci": "r50k_base",
"curie": "r50k_base",
"babbage": "r50k_base",
"ada": "r50k_base",
# code
"code-davinci-002": "p50k_base",
"code-davinci-001": "p50k_base",
"code-cushman-002": "p50k_base",
"code-cushman-001": "p50k_base",
"davinci-codex": "p50k_base",
"cushman-codex": "p50k_base",
# edit
"text-davinci-edit-001": "p50k_edit",
"code-davinci-edit-001": "p50k_edit",
# embeddings
"text-embedding-ada-002": "cl100k_base",
# old embeddings
"text-similarity-davinci-001": "r50k_base",
"text-similarity-curie-001": "r50k_base",
"text-similarity-babbage-001": "r50k_base",
"text-similarity-ada-001": "r50k_base",
"text-search-davinci-doc-001": "r50k_base",
"text-search-curie-doc-001": "r50k_base",
"text-search-babbage-doc-001": "r50k_base",
"text-search-ada-doc-001": "r50k_base",
"code-search-babbage-code-001": "r50k_base",
"code-search-ada-code-001": "r50k_base",
# open source
"gpt2": "gpt2",

}

def encoding_for_model(model_name: str) -> Encoding: """Returns the encoding used by a model.""" encoding_name = None if model_name in MODEL_TO_ENCODING: encoding_name = MODEL_TO_ENCODING[model_name] else:

Check if the model matches a known prefix

    # Prefix matching avoids needing library updates for every model version release
    # Note that this can match on non-existent models (e.g., gpt-3.5-turbo-FAKE)
    for model_prefix, model_encoding_name in MODEL_PREFIX_TO_ENCODING.items():
        if model_name.startswith(model_prefix):
            return get_encoding(model_encoding_name)

if encoding_name is None:
    raise KeyError(
        f"Could not automatically map {model_name} to a tokeniser. "
        "Please use `tiktok.get_encoding` to explicitly get the tokeniser you expect."
    ) from None

return get_encoding(encoding_name)