Update README.md

[3coins]

Updated instructions to set api keys in the notebook cell.

[bjornjorgensen]

The reason for this PR #330 was that %env OPENAI_API_KEY='sk don't work. I'm using a docker build from jupyter/docker-stack but os.environ["OPENAI_API_KEY"]='sk works.

This is the error I get

---------------------------------------------------------------------------
AuthenticationError                       Traceback (most recent call last)
Cell In[4], line 1
----> 1 get_ipython().run_cell_magic('ai', 'chatgpt -f code', 'A program that asks me for my name and then greets me by my name, in Norwegian\n')

File /opt/conda/lib/python3.11/site-packages/IPython/core/interactiveshell.py:2478, in InteractiveShell.run_cell_magic(self, magic_name, line, cell)
   2476 with self.builtin_trap:
   2477     args = (magic_arg_s, cell)
-> 2478     result = fn(*args, **kwargs)
   2480 # The code below prevents the output from being displayed
   2481 # when using magics with decodator @output_can_be_silenced
   2482 # when the last Python token in the expression is a ';'.
   2483 if getattr(fn, magic.MAGIC_OUTPUT_CAN_BE_SILENCED, False):

File /opt/conda/lib/python3.11/site-packages/jupyter_ai_magics/magics.py:590, in AiMagics.ai(self, line, cell)
    587 ip = get_ipython()
    588 prompt = prompt.format_map(FormatDict(ip.user_ns))
--> 590 return self.run_ai_cell(args, prompt)

File /opt/conda/lib/python3.11/site-packages/jupyter_ai_magics/magics.py:532, in AiMagics.run_ai_cell(self, args, prompt)
    529 prompt = prompt.format_map(FormatDict(ip.user_ns))
    531 # generate output from model via provider
--> 532 result = provider.generate([prompt])
    533 output = result.generations[0][0].text
    535 # if openai-chat, append exchange to transcript

File /opt/conda/lib/python3.11/site-packages/langchain/llms/base.py:227, in BaseLLM.generate(self, prompts, stop, callbacks, tags, **kwargs)
    221         raise ValueError(
    222             "Asked to cache, but no cache found at `langchain.cache`."
    223         )
    224     run_managers = callback_manager.on_llm_start(
    225         dumpd(self), prompts, invocation_params=params, options=options
    226     )
--> 227     output = self._generate_helper(
    228         prompts, stop, run_managers, bool(new_arg_supported), **kwargs
    229     )
    230     return output
    231 if len(missing_prompts) > 0:

File /opt/conda/lib/python3.11/site-packages/langchain/llms/base.py:178, in BaseLLM._generate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    176     for run_manager in run_managers:
    177         run_manager.on_llm_error(e)
--> 178     raise e
    179 flattened_outputs = output.flatten()
    180 for manager, flattened_output in zip(run_managers, flattened_outputs):

File /opt/conda/lib/python3.11/site-packages/langchain/llms/base.py:165, in BaseLLM._generate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs)
    155 def _generate_helper(
    156     self,
    157     prompts: List[str],
   (...)
    161     **kwargs: Any,
    162 ) -> LLMResult:
    163     try:
    164         output = (
--> 165             self._generate(
    166                 prompts,
    167                 stop=stop,
    168                 # TODO: support multiple run managers
    169                 run_manager=run_managers[0] if run_managers else None,
    170                 **kwargs,
    171             )
    172             if new_arg_supported
    173             else self._generate(prompts, stop=stop)
    174         )
    175     except (KeyboardInterrupt, Exception) as e:
    176         for run_manager in run_managers:

File /opt/conda/lib/python3.11/site-packages/langchain/llms/openai.py:822, in OpenAIChat._generate(self, prompts, stop, run_manager, **kwargs)
    818     return LLMResult(
    819         generations=[[Generation(text=response)]],
    820     )
    821 else:
--> 822     full_response = completion_with_retry(self, messages=messages, **params)
    823     llm_output = {
    824         "token_usage": full_response["usage"],
    825         "model_name": self.model_name,
    826     }
    827     return LLMResult(
    828         generations=[
    829             [Generation(text=full_response["choices"][0]["message"]["content"])]
    830         ],
    831         llm_output=llm_output,
    832     )

File /opt/conda/lib/python3.11/site-packages/langchain/llms/openai.py:106, in completion_with_retry(llm, **kwargs)
    102 @retry_decorator
    103 def _completion_with_retry(**kwargs: Any) -> Any:
    104     return llm.client.create(**kwargs)
--> 106 return _completion_with_retry(**kwargs)

File /opt/conda/lib/python3.11/site-packages/tenacity/__init__.py:289, in BaseRetrying.wraps.<locals>.wrapped_f(*args, **kw)
    287 @functools.wraps(f)
    288 def wrapped_f(*args: t.Any, **kw: t.Any) -> t.Any:
--> 289     return self(f, *args, **kw)

File /opt/conda/lib/python3.11/site-packages/tenacity/__init__.py:379, in Retrying.__call__(self, fn, *args, **kwargs)
    377 retry_state = RetryCallState(retry_object=self, fn=fn, args=args, kwargs=kwargs)
    378 while True:
--> 379     do = self.iter(retry_state=retry_state)
    380     if isinstance(do, DoAttempt):
    381         try:

File /opt/conda/lib/python3.11/site-packages/tenacity/__init__.py:314, in BaseRetrying.iter(self, retry_state)
    312 is_explicit_retry = fut.failed and isinstance(fut.exception(), TryAgain)
    313 if not (is_explicit_retry or self.retry(retry_state)):
--> 314     return fut.result()
    316 if self.after is not None:
    317     self.after(retry_state)

File /opt/conda/lib/python3.11/concurrent/futures/_base.py:449, in Future.result(self, timeout)
    447     raise CancelledError()
    448 elif self._state == FINISHED:
--> 449     return self.__get_result()
    451 self._condition.wait(timeout)
    453 if self._state in [CANCELLED, CANCELLED_AND_NOTIFIED]:

File /opt/conda/lib/python3.11/concurrent/futures/_base.py:401, in Future.__get_result(self)
    399 if self._exception:
    400     try:
--> 401         raise self._exception
    402     finally:
    403         # Break a reference cycle with the exception in self._exception
    404         self = None

File /opt/conda/lib/python3.11/site-packages/tenacity/__init__.py:382, in Retrying.__call__(self, fn, *args, **kwargs)
    380 if isinstance(do, DoAttempt):
    381     try:
--> 382         result = fn(*args, **kwargs)
    383     except BaseException:  # noqa: B902
    384         retry_state.set_exception(sys.exc_info())  # type: ignore[arg-type]

File /opt/conda/lib/python3.11/site-packages/langchain/llms/openai.py:104, in completion_with_retry.<locals>._completion_with_retry(**kwargs)
    102 @retry_decorator
    103 def _completion_with_retry(**kwargs: Any) -> Any:
--> 104     return llm.client.create(**kwargs)

File /opt/conda/lib/python3.11/site-packages/openai/api_resources/chat_completion.py:25, in ChatCompletion.create(cls, *args, **kwargs)
     23 while True:
     24     try:
---> 25         return super().create(*args, **kwargs)
     26     except TryAgain as e:
     27         if timeout is not None and time.time() > start + timeout:

File /opt/conda/lib/python3.11/site-packages/openai/api_resources/abstract/engine_api_resource.py:153, in EngineAPIResource.create(cls, api_key, api_base, api_type, request_id, api_version, organization, **params)
    127 @classmethod
    128 def create(
    129     cls,
   (...)
    136     **params,
    137 ):
    138     (
    139         deployment_id,
    140         engine,
   (...)
    150         api_key, api_base, api_type, api_version, organization, **params
    151     )
--> 153     response, _, api_key = requestor.request(
    154         "post",
    155         url,
    156         params=params,
    157         headers=headers,
    158         stream=stream,
    159         request_id=request_id,
    160         request_timeout=request_timeout,
    161     )
    163     if stream:
    164         # must be an iterator
    165         assert not isinstance(response, OpenAIResponse)

File /opt/conda/lib/python3.11/site-packages/openai/api_requestor.py:298, in APIRequestor.request(self, method, url, params, headers, files, stream, request_id, request_timeout)
    277 def request(
    278     self,
    279     method,
   (...)
    286     request_timeout: Optional[Union[float, Tuple[float, float]]] = None,
    287 ) -> Tuple[Union[OpenAIResponse, Iterator[OpenAIResponse]], bool, str]:
    288     result = self.request_raw(
    289         method.lower(),
    290         url,
   (...)
    296         request_timeout=request_timeout,
    297     )
--> 298     resp, got_stream = self._interpret_response(result, stream)
    299     return resp, got_stream, self.api_key

File /opt/conda/lib/python3.11/site-packages/openai/api_requestor.py:700, in APIRequestor._interpret_response(self, result, stream)
    692     return (
    693         self._interpret_response_line(
    694             line, result.status_code, result.headers, stream=True
    695         )
    696         for line in parse_stream(result.iter_lines())
    697     ), True
    698 else:
    699     return (
--> 700         self._interpret_response_line(
    701             result.content.decode("utf-8"),
    702             result.status_code,
    703             result.headers,
    704             stream=False,
    705         ),
    706         False,
    707     )

File /opt/conda/lib/python3.11/site-packages/openai/api_requestor.py:763, in APIRequestor._interpret_response_line(self, rbody, rcode, rheaders, stream)
    761 stream_error = stream and "error" in resp.data
    762 if stream_error or not 200 <= rcode < 300:
--> 763     raise self.handle_error_response(
    764         rbody, rcode, resp.data, rheaders, stream_error=stream_error
    765     )
    766 return resp

AuthenticationError: Incorrect API key provided: 'sk-UDSc*****************************************Wz7'. You can find your API key at https://platform.openai.com/account/api-keys.

[bjornjorgensen]

oh.. if I use os.environ then I need 'KEY', but if I use %env then its without ' '
%env works now.