ValueError: too many values to unpack (expected 2)
Labels: name: area: memory, name: auto:bug

### System Info

langchain:0.0.353
platform:windows10
python:3.10

I am a beginner in Langchain. I am a I want to use ConversationTokenBufferMemory to manually save the context, but an error occurred. My code is as follows
`import os
from lc.api_key import OPENAI_API_KEY
os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY

from langchain.chains import ConversationChain
from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationTokenBufferMemory

llm = ChatOpenAI(temperature=0.0)
memory = ConversationTokenBufferMemory(
    llm=llm,
    max_token_limit=100
)
memory.save_context(inputs={"input": "how about AI?"}, outputs={"output": "Amazing!"})
memory.save_context({"input": "what is space?"}, {"output": "just like a stage."})
memory.save_context({"input": "what can i do?"}, {"output": "workers of the world, unite!"})
print(memory.load_memory_variables())
chain = ConversationChain(
    llm=llm,
    memory=memory,
    verbose=True
)
print(chain.predict(input="what is 1+1?"))
print(chain.predict(input="what is my name?"))
print(chain.predict(input="what can i do?"))`
---------------------------------
---------------------------------
The problem is that the code is executed to memory.save_ Context, an error will be reported.The stack information is as follows:

memory.save_context(inputs={"input": "how about AI?"}, outputs={"output": "Amazing!"})
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain\memory\token_buffer.py", line 54, in save_context
    curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain_community\chat_models\openai.py", line 610, in get_num_tokens_from_messages
    model, encoding = self._get_encoding_model()
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain_community\chat_models\openai.py", line 588, in _get_encoding_model
    encoding = tiktoken_.encoding_for_model(model)
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\model.py", line 97, in encoding_for_model
    return get_encoding(encoding_name_for_model(model_name))
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\registry.py", line 73, in get_encoding
    enc = Encoding(**constructor())
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken_ext\openai_public.py", line 64, in cl100k_base
    mergeable_ranks = load_tiktoken_bpe(
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\load.py", line 117, in load_tiktoken_bpe
    return {
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\load.py", line 117, in <dictcomp>
    return {
ValueError: too many values to unpack (expected 2)

### Who can help?

_No response_

### Information

- [ ] The official example notebooks/scripts
- [X] My own modified scripts

### Related Components

- [ ] LLMs/Chat Models
- [ ] Embedding Models
- [ ] Prompts / Prompt Templates / Prompt Selectors
- [ ] Output Parsers
- [ ] Document Loaders
- [ ] Vector Stores / Retrievers
- [X] Memory
- [ ] Agents / Agent Executors
- [ ] Tools / Toolkits
- [ ] Chains
- [ ] Callbacks/Tracing
- [ ] Async

### Reproduction

import os
from lc.api_key import OPENAI_API_KEY
os.environ['OPENAI_API_KEY'] = OPENAI_API_KEY

from langchain.chains import ConversationChain
from langchain.chat_models import ChatOpenAI
from langchain.memory import ConversationTokenBufferMemory

llm = ChatOpenAI(temperature=0.0)
memory = ConversationTokenBufferMemory(
    llm=llm,
    max_token_limit=100
)
memory.save_context(inputs={"input": "how about AI?"}, outputs={"output": "Amazing!"})
memory.save_context({"input": "what is space?"}, {"output": "just like a stage."})
memory.save_context({"input": "what can i do?"}, {"output": "workers of the world, unite!"})
print(memory.load_memory_variables())
chain = ConversationChain(
    llm=llm,
    memory=memory,
    verbose=True
)
print(chain.predict(input="what is 1+1?"))
print(chain.predict(input="what is my name?"))
print(chain.predict(input="what can i do?"))

### Expected behavior

Traceback (most recent call last):
  File "E:\Project\pythonProject\langChain\lc\memory\ConversationTokenBufferMemoryUseCaseScript.py", line 14, in <module>
    memory.save_context(inputs={"input": "how about AI?"}, outputs={"output": "Amazing!"})
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain\memory\token_buffer.py", line 54, in save_context
    curr_buffer_length = self.llm.get_num_tokens_from_messages(buffer)
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain_community\chat_models\openai.py", line 610, in get_num_tokens_from_messages
    model, encoding = self._get_encoding_model()
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\langchain_community\chat_models\openai.py", line 588, in _get_encoding_model
    encoding = tiktoken_.encoding_for_model(model)
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\model.py", line 97, in encoding_for_model
    return get_encoding(encoding_name_for_model(model_name))
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\registry.py", line 73, in get_encoding
    enc = Encoding(**constructor())
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken_ext\openai_public.py", line 64, in cl100k_base
    mergeable_ranks = load_tiktoken_bpe(
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\load.py", line 124, in load_tiktoken_bpe
    return {
  File "E:\Project\pythonProject\langChain\venv\lib\site-packages\tiktoken\load.py", line 124, in <dictcomp>
    return {
ValueError: too many values to unpack (expected 2)

Process finished with exit code 1