Replacing the correct code with GPT-4 will result in an error
Labels: name: auto:bug, name: auto:question, name: area: models

### Issue you'd like to raise.

**my code：**

from langchain.document_loaders import PyPDFLoader, TextLoader, PyMuPDFLoader
from langchain.chat_models import ChatOpenAI

from langchain.chains import QAGenerationChain
from langchain.prompts.prompt import PromptTemplate

loader_pdf = PyMuPDFLoader("/Users/11.pdf")

doc_pdf = loader_pdf.load()

llm = ChatOpenAI(temperature=0.1,model_name="gpt-3.5-turbo-16k")
templ = """You are a smart assistant designed to help high school teachers come up with reading comprehension questions.
Given a piece of text, you must come up with a question and answer pair that can be used to test a student's reading comprehension abilities.
When coming up with this question/answer pair, you must respond in the following format in Chinese:
```
{{
    "question": "$YOUR_QUESTION_HERE",
    "answer": "$THE_ANSWER_HERE"
}}
```

Everything between the ``` must be valid json.

Please come up with a question/answer pair, in the specified JSON format, for the following text:
----------------
{text}"""

prompt = PromptTemplate.from_template(templ)
chain = QAGenerationChain.from_llm(llm=llm, prompt=prompt)

doc_ = ''
for i in doc_pdf:
    doc_ += i.page_content

print(doc_)
qa_pdf = chain.run(doc_)


This code can run correctly and have results.
But when “model_name='gpt-4' ”, an error is reported.
What is it???

**the error：**
---------------------------------------------------------------------------
JSONDecodeError                           Traceback (most recent call last)
Cell In[22], line 1
----> 1 qa_pdf = chain.run(doc_)

File ~/anaconda3/envs/langchain-py311/lib/python3.11/site-packages/langchain/chains/base.py:505, in Chain.run(self, callbacks, tags, metadata, *args, **kwargs)
    503     if len(args) != 1:
    504         raise ValueError("`run` supports only one positional argument.")
--> 505     return self(args[0], callbacks=callbacks, tags=tags, metadata=metadata)[
    506         _output_key
    507     ]
    509 if kwargs and not args:
    510     return self(kwargs, callbacks=callbacks, tags=tags, metadata=metadata)[
    511         _output_key
    512     ]

File ~/anaconda3/envs/langchain-py311/lib/python3.11/site-packages/langchain/chains/base.py:310, in Chain.__call__(self, inputs, return_only_outputs, callbacks, tags, metadata, run_name, include_run_info)
    308 except BaseException as e:
    309     run_manager.on_chain_error(e)
--> 310     raise e
    311 run_manager.on_chain_end(outputs)
    312 final_outputs: Dict[str, Any] = self.prep_outputs(
    313     inputs, outputs, return_only_outputs
    314 )

File ~/anaconda3/envs/langchain-py311/lib/python3.11/site-packages/langchain/chains/base.py:304, in Chain.__call__(self, inputs, return_only_outputs, callbacks, tags, metadata, run_name, include_run_info)
    297 run_manager = callback_manager.on_chain_start(
    298     dumpd(self),
    299     inputs,
    300     name=run_name,
    301 )
    302 try:
    303     outputs = (
--> 304         self._call(inputs, run_manager=run_manager)
    305         if new_arg_supported
    306         else self._call(inputs)
    307     )
    308 except BaseException as e:
    309     run_manager.on_chain_error(e)

File ~/anaconda3/envs/langchain-py311/lib/python3.11/site-packages/langchain/chains/qa_generation/base.py:75, in QAGenerationChain._call(self, inputs, run_manager)
     71 docs = self.text_splitter.create_documents([inputs[self.input_key]])
     72 results = self.llm_chain.generate(
     73     [{"text": d.page_content} for d in docs], run_manager=run_manager
     74 )
---> 75 print(results)
     76 qa = [json.loads(res[0].text) for res in results.generations]
     77 return {self.output_key: qa}

File ~/anaconda3/envs/langchain-py311/lib/python3.11/site-packages/langchain/chains/qa_generation/base.py:75, in <listcomp>(.0)
     71 docs = self.text_splitter.create_documents([inputs[self.input_key]])
     72 results = self.llm_chain.generate(
     73     [{"text": d.page_content} for d in docs], run_manager=run_manager
     74 )
---> 75 print(results)
     76 qa = [json.loads(res[0].text) for res in results.generations]
     77 return {self.output_key: qa}

File ~/anaconda3/envs/langchain-py311/lib/python3.11/json/__init__.py:346, in loads(s, cls, object_hook, parse_float, parse_int, parse_constant, object_pairs_hook, **kw)
    341     s = s.decode(detect_encoding(s), 'surrogatepass')
    343 if (cls is None and object_hook is None and
    344         parse_int is None and parse_float is None and
    345         parse_constant is None and object_pairs_hook is None and not kw):
--> 346     return _default_decoder.decode(s)
    347 if cls is None:
    348     cls = JSONDecoder

File ~/anaconda3/envs/langchain-py311/lib/python3.11/json/decoder.py:337, in JSONDecoder.decode(self, s, _w)
    332 def decode(self, s, _w=WHITESPACE.match):
    333     """Return the Python representation of ``s`` (a ``str`` instance
    334     containing a JSON document).
    335 
    336     """
--> 337     obj, end = self.raw_decode(s, idx=_w(s, 0).end())
    338     end = _w(s, end).end()
    339     if end != len(s):

File ~/anaconda3/envs/langchain-py311/lib/python3.11/json/decoder.py:355, in JSONDecoder.raw_decode(self, s, idx)
    353     obj, end = self.scan_once(s, idx)
    354 except StopIteration as err:
--> 355     raise JSONDecodeError("Expecting value", s, err.value) from None
    356 return obj, end

JSONDecodeError: Expecting value: line 1 column 1 (char 0)

### Suggestion:

_No response_