chapter 3 - Using Hugging Face

[amscosta]

Hi, The following code snippet from Chapter 3 : from langchain.llms import HuggingFaceHub llm = HuggingFaceHub( model_kwargs={"temperature": 0.5, "max_length": 64}, repo_id="google/flan-t5-xxl" ) prompt = "In which country is Tokyo?" completion = llm(prompt) print(completion)

Is giving:

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ValueError Traceback (most recent call last) Cell In[6], line 2 1 prompt = "In which country is Tokyo?" ----> 2 completion = llm(prompt) 3 print(completion)

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\base.py:825, in BaseLLM.call(self, prompt, stop, callbacks, tags, metadata, **kwargs) 818 if not isinstance(prompt, str): 819 raise ValueError( 820 "Argument prompt is expected to be a string. Instead found " 821 f"{type(prompt)}. If you want to run the LLM on multiple prompts, use " 822 "generate instead." 823 ) 824 return ( --> 825 self.generate( 826 [prompt], 827 stop=stop, 828 callbacks=callbacks, 829 tags=tags, 830 metadata=metadata, 831 **kwargs, 832 ) 833 .generations[0][0] 834 .text 835 )

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\base.py:621, in BaseLLM.generate(self, prompts, stop, callbacks, tags, metadata, **kwargs) 612 raise ValueError( 613 "Asked to cache, but no cache found at langchain.cache." 614 ) 615 run_managers = [ 616 callback_manager.on_llm_start( 617 dumpd(self), [prompt], invocation_params=params, options=options 618 )[0] 619 for callback_manager, prompt in zip(callback_managers, prompts) 620 ] --> 621 output = self._generate_helper( 622 prompts, stop, run_managers, bool(new_arg_supported), **kwargs 623 ) 624 return output 625 if len(missing_prompts) > 0:

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\base.py:523, in BaseLLM._generate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs) 521 for run_manager in run_managers: 522 run_manager.on_llm_error(e) --> 523 raise e 524 flattened_outputs = output.flatten() 525 for manager, flattened_output in zip(run_managers, flattened_outputs):

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\base.py:510, in BaseLLM._generate_helper(self, prompts, stop, run_managers, new_arg_supported, **kwargs) 500 def _generate_helper( 501 self, 502 prompts: List[str], (...) 506 **kwargs: Any, 507 ) -> LLMResult: 508 try: 509 output = ( --> 510 self._generate( 511 prompts, 512 stop=stop, 513 # TODO: support multiple run managers 514 run_manager=run_managers[0] if run_managers else None, 515 **kwargs, 516 ) 517 if new_arg_supported 518 else self._generate(prompts, stop=stop) 519 ) 520 except (KeyboardInterrupt, Exception) as e: 521 for run_manager in run_managers:

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\base.py:1000, in LLM._generate(self, prompts, stop, run_manager, **kwargs) 997 new_arg_supported = inspect.signature(self._call).parameters.get("run_manager") 998 for prompt in prompts: 999 text = ( -> 1000 self._call(prompt, stop=stop, run_manager=run_manager, **kwargs) 1001 if new_arg_supported 1002 else self._call(prompt, stop=stop, **kwargs) 1003 ) 1004 generations.append([Generation(text=text)]) 1005 return LLMResult(generations=generations)

File D:\generative_ai_with_langchain\pyenv\Lib\site-packages\langchain\llms\huggingface_hub.py:112, in HuggingFaceHub._call(self, prompt, stop, run_manager, **kwargs) 110 response = self.client(inputs=prompt, params=params) 111 if "error" in response: --> 112 raise ValueError(f"Error raised by inference API: {response['error']}") 113 if self.client.task == "text-generation": 114 # Text generation return includes the starter text. 115 text = response[0]["generated_text"][len(prompt) :]

ValueError: Error raised by inference API: Service Unavailable