---------------------------------------------------------------------------
ValueError                                Traceback (most recent call last)
Cell In[10], line 22
     19 qa = RetrievalQA.from_chain_type(llm=llm, chain_type="stuff", retriever=docsearch, return_source_documents=False)
     21 q = input("input your query:")
---> 22 result = qa.run(query=q)
     24 print(result["result"])
     25 #print(result["source_documents"])

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:261, in Chain.run(self, callbacks, *args, **kwargs)
    258     return self(args[0], callbacks=callbacks)[self.output_keys[0]]
    260 if kwargs and not args:
--> 261     return self(kwargs, callbacks=callbacks)[self.output_keys[0]]
    263 if not kwargs and not args:
    264     raise ValueError(
    265         "`run` supported with either positional arguments or keyword arguments,"
    266         " but none were provided."
    267     )

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:147, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)
--> 147     raise e
    148 run_manager.on_chain_end(outputs)
    149 final_outputs: Dict[str, Any] = self.prep_outputs(
    150     inputs, outputs, return_only_outputs
    151 )

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:141, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    135 run_manager = callback_manager.on_chain_start(
    136     dumpd(self),
    137     inputs,
    138 )
    139 try:
    140     outputs = (
--> 141         self._call(inputs, run_manager=run_manager)
    142         if new_arg_supported
    143         else self._call(inputs)
    144     )
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)

File /opt/conda/lib/python3.10/site-packages/langchain/chains/retrieval_qa/base.py:120, in BaseRetrievalQA._call(self, inputs, run_manager)
    117 question = inputs[self.input_key]
    119 docs = self._get_docs(question)
--> 120 answer = self.combine_documents_chain.run(
    121     input_documents=docs, question=question, callbacks=_run_manager.get_child()
    122 )
    124 if self.return_source_documents:
    125     return {self.output_key: answer, "source_documents": docs}

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:261, in Chain.run(self, callbacks, *args, **kwargs)
    258     return self(args[0], callbacks=callbacks)[self.output_keys[0]]
    260 if kwargs and not args:
--> 261     return self(kwargs, callbacks=callbacks)[self.output_keys[0]]
    263 if not kwargs and not args:
    264     raise ValueError(
    265         "`run` supported with either positional arguments or keyword arguments,"
    266         " but none were provided."
    267     )

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:147, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)
--> 147     raise e
    148 run_manager.on_chain_end(outputs)
    149 final_outputs: Dict[str, Any] = self.prep_outputs(
    150     inputs, outputs, return_only_outputs
    151 )

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:141, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    135 run_manager = callback_manager.on_chain_start(
    136     dumpd(self),
    137     inputs,
    138 )
    139 try:
    140     outputs = (
--> 141         self._call(inputs, run_manager=run_manager)
    142         if new_arg_supported
    143         else self._call(inputs)
    144     )
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)

File /opt/conda/lib/python3.10/site-packages/langchain/chains/combine_documents/base.py:84, in BaseCombineDocumentsChain._call(self, inputs, run_manager)
     82 # Other keys are assumed to be needed for LLM prediction
     83 other_keys = {k: v for k, v in inputs.items() if k != self.input_key}
---> 84 output, extra_return_dict = self.combine_docs(
     85     docs, callbacks=_run_manager.get_child(), **other_keys
     86 )
     87 extra_return_dict[self.output_key] = output
     88 return extra_return_dict

File /opt/conda/lib/python3.10/site-packages/langchain/chains/combine_documents/stuff.py:87, in StuffDocumentsChain.combine_docs(self, docs, callbacks, **kwargs)
     85 inputs = self._get_inputs(docs, **kwargs)
     86 # Call predict on the LLM.
---> 87 return self.llm_chain.predict(callbacks=callbacks, **inputs), {}

File /opt/conda/lib/python3.10/site-packages/langchain/chains/llm.py:218, in LLMChain.predict(self, callbacks, **kwargs)
    203 def predict(self, callbacks: Callbacks = None, **kwargs: Any) -> str:
    204     """Format prompt with kwargs and pass to LLM.
    205
    206     Args:
   (...)
    216             completion = llm.predict(adjective="funny")
    217     """
--> 218     return self(kwargs, callbacks=callbacks)[self.output_key]

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:147, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)
--> 147     raise e
    148 run_manager.on_chain_end(outputs)
    149 final_outputs: Dict[str, Any] = self.prep_outputs(
    150     inputs, outputs, return_only_outputs
    151 )

File /opt/conda/lib/python3.10/site-packages/langchain/chains/base.py:141, in Chain.__call__(self, inputs, return_only_outputs, callbacks, include_run_info)
    135 run_manager = callback_manager.on_chain_start(
    136     dumpd(self),
    137     inputs,
    138 )
    139 try:
    140     outputs = (
--> 141         self._call(inputs, run_manager=run_manager)
    142         if new_arg_supported
    143         else self._call(inputs)
    144     )
    145 except (KeyboardInterrupt, Exception) as e:
    146     run_manager.on_chain_error(e)

File /opt/conda/lib/python3.10/site-packages/langchain/chains/llm.py:74, in LLMChain._call(self, inputs, run_manager)
     69 def _call(
     70     self,
     71     inputs: Dict[str, Any],
     72     run_manager: Optional[CallbackManagerForChainRun] = None,
     73 ) -> Dict[str, str]:
---> 74     response = self.generate([inputs], run_manager=run_manager)
     75     return self.create_outputs(response)[0]

File /opt/conda/lib/python3.10/site-packages/langchain/chains/llm.py:84, in LLMChain.generate(self, input_list, run_manager)
     82 """Generate LLM result from inputs."""
     83 prompts, stop = self.prep_prompts(input_list, run_manager=run_manager)
---> 84 return self.llm.generate_prompt(
     85     prompts, stop, callbacks=run_manager.get_child() if run_manager else None
     86 )

File /opt/conda/lib/python3.10/site-packages/langchain/llms/base.py:139, in BaseLLM.generate_prompt(self, prompts, stop, callbacks, **kwargs)
    131 def generate_prompt(
    132     self,
    133     prompts: List[PromptValue],
   (...)
    136     **kwargs: Any,
    137 ) -> LLMResult:
    138     prompt_strings = [p.to_string() for p in prompts]
--> 139     return self.generate(prompt_strings, stop=stop, callbacks=callbacks, **kwargs)

File /opt/conda/lib/python3.10/site-packages/langchain/llms/base.py:203, in BaseLLM.generate(self, prompts, stop, callbacks, **kwargs)
    201 except (KeyboardInterrupt, Exception) as e:
    202     run_manager.on_llm_error(e)
--> 203     raise e
    204 run_manager.on_llm_end(output)
    205 if run_manager:

File /opt/conda/lib/python3.10/site-packages/langchain/llms/base.py:195, in BaseLLM.generate(self, prompts, stop, callbacks, **kwargs)
    190 run_manager = callback_manager.on_llm_start(
    191     dumpd(self), prompts, invocation_params=params, options=options
    192 )
    193 try:
    194     output = (
--> 195         self._generate(
    196             prompts, stop=stop, run_manager=run_manager, **kwargs
    197         )
    198         if new_arg_supported
    199         else self._generate(prompts, stop=stop, **kwargs)
    200     )
    201 except (KeyboardInterrupt, Exception) as e:
    202     run_manager.on_llm_error(e)

File /opt/conda/lib/python3.10/site-packages/langchain/llms/base.py:493, in LLM._generate(self, prompts, stop, run_manager, **kwargs)
    490 new_arg_supported = inspect.signature(self._call).parameters.get("run_manager")
    491 for prompt in prompts:
    492     text = (
--> 493         self._call(prompt, stop=stop, run_manager=run_manager, **kwargs)
    494         if new_arg_supported
    495         else self._call(prompt, stop=stop, **kwargs)
    496     )
    497     generations.append([Generation(text=text)])
    498 return LLMResult(generations=generations)

File /opt/conda/lib/python3.10/site-packages/langchain/llms/huggingface_hub.py:114, in HuggingFaceHub._call(self, prompt, stop, run_manager, **kwargs)
    112 response = self.client(inputs=prompt, params=params)
    113 if "error" in response:
--> 114     raise ValueError(f"Error raised by inference API: {response['error']}")
    115 if self.client.task == "text-generation":
    116     # Text generation return includes the starter text.
    117     text = response[0]["generated_text"][len(prompt) :]

ValueError: Error raised by inference API: Pipeline cannot infer suitable model classes from lucas0/empath-llama-7b