Opiniones sobre Explore Generative AI with the Vertex AI Gemini API: Lab de desafío
2708 opiniones
Manan S. · Se revisó hace 3 meses
Muhammad H. · Se revisó hace 3 meses
It never marks my progress as successful even though I have done this five times now and get the right results.
Joey G. · Se revisó hace 3 meses
Ajay S. · Se revisó hace 3 meses
_MultiThreadedRendezvous Traceback (most recent call last) File ~/.local/lib/python3.10/site-packages/google/api_core/grpc_helpers.py:170, in _wrap_stream_errors.<locals>.error_remapped_callable(*args, **kwargs) 169 prefetch_first = getattr(callable_, "_prefetch_first_result_", True) --> 170 return _StreamingResponseIterator( 171 result, prefetch_first_result=prefetch_first 172 ) 173 except grpc.RpcError as exc: File ~/.local/lib/python3.10/site-packages/google/api_core/grpc_helpers.py:92, in _StreamingResponseIterator.__init__(self, wrapped, prefetch_first_result) 91 if prefetch_first_result: ---> 92 self._stored_first_result = next(self._wrapped) 93 except TypeError: 94 # It is possible the wrapped method isn't an iterable (a grpc.Call 95 # for instance). If this happens don't store the first result. File /opt/conda/lib/python3.10/site-packages/grpc/_channel.py:543, in _Rendezvous.__next__(self) 542 def __next__(self): --> 543 return self._next() File /opt/conda/lib/python3.10/site-packages/grpc/_channel.py:969, in _MultiThreadedRendezvous._next(self) 968 elif self._state.code is not None: --> 969 raise self _MultiThreadedRendezvous: <_MultiThreadedRendezvous of RPC that terminated with: status = StatusCode.INTERNAL details = "Internal error encountered." debug_error_string = "UNKNOWN:Error received from peer ipv4:74.125.133.95:443 {created_time:"2024-08-03T03:36:26.704724959+00:00", grpc_status:13, grpc_message:"Internal error encountered."}" > The above exception was the direct cause of the following exception: InternalServerError Traceback (most recent call last) Cell In[27], line 23 20 print_multimodal_prompt(contents) 22 print("\n-------Response--------") ---> 23 for response in responses: 24 print(response.text, end="") File ~/.local/lib/python3.10/site-packages/vertexai/generative_models/_generative_models.py:719, in _GenerativeModel._generate_content_streaming(self, contents, generation_config, safety_settings, tools, tool_config) 694 """Generates content. 695 696 Args: (...) 710 A stream of GenerationResponse objects 711 """ 712 request = self._prepare_request( 713 contents=contents, 714 generation_config=generation_config, (...) 717 tool_config=tool_config, 718 ) --> 719 response_stream = self._prediction_client.stream_generate_content( 720 request=request 721 ) 722 for chunk in response_stream: 723 yield self._parse_response(chunk) File ~/.local/lib/python3.10/site-packages/google/cloud/aiplatform_v1beta1/services/prediction_service/client.py:2412, in PredictionServiceClient.stream_generate_content(self, request, model, contents, retry, timeout, metadata) 2409 self._validate_universe_domain() 2411 # Send the request. -> 2412 response = rpc( 2413 request, 2414 retry=retry, 2415 timeout=timeout, 2416 metadata=metadata, 2417 ) 2419 # Done; return the response. 2420 return response File ~/.local/lib/python3.10/site-packages/google/api_core/gapic_v1/method.py:131, in _GapicCallable.__call__(self, timeout, retry, compression, *args, **kwargs) 128 if self._compression is not None: 129 kwargs["compression"] = compression --> 131 return wrapped_func(*args, **kwargs) File ~/.local/lib/python3.10/site-packages/google/api_core/grpc_helpers.py:174, in _wrap_stream_errors.<locals>.error_remapped_callable(*args, **kwargs) 170 return _StreamingResponseIterator( 171 result, prefetch_first_result=prefetch_first 172 ) 173 except grpc.RpcError as exc: --> 174 raise exceptions.from_grpc_error(exc) from exc InternalServerError: 500 Internal error encountered.
José Gustavo F. · Se revisó hace 3 meses
Pranav P. · Se revisó hace 3 meses
Questions are too vague and the correct answers that should be printed out are not immediately checked for scoring
SEOKKEUN O. · Se revisó hace 3 meses
difficult
裕貴 片. · Se revisó hace 3 meses
Jason B. · Se revisó hace 3 meses
Monde M. · Se revisó hace 3 meses
Task 3 is not working , giving 500 error
rakesh B. · Se revisó hace 3 meses
AVINASH G. · Se revisó hace 3 meses
First attempt: Lab failed to create project Second attempt: Repeated "Server 500" errors at last step - unable to resolve with kernel/server restarts or different models - server running in europe-west4a Third attempt: same internal 500 server error but this time in us-west1-c.
Ben M. · Se revisó hace 3 meses
First attempt: Lab failed to create project Second attempt: Repeated "Server 500" errors at last step - unable to resolve with kernel/server restarts or different models - server running in europe-west4a
Ben M. · Se revisó hace 3 meses
Sirasanagandla V. · Se revisó hace 3 meses
Reeshna A. · Se revisó hace 3 meses
Jay F. · Se revisó hace 3 meses
Jivithan M. · Se revisó hace 3 meses
Issue with the task completion. Update: Issue with the last task resolved.
Sukumar S. · Se revisó hace 3 meses
Rohit C. · Se revisó hace 3 meses
Instructions are very unclear (e.g. choose the correct model, but there are multiple models for every task). Checkpoints take a long time to verify progress and will fail if the format of the prints is not 100% matching expectations, so it would be useful to know exactly which format is expected. I ran out of time because, even though I was able to describe video contents by replacing code in the notebook cell, the checkpoint never validated my progress. Also, there was a problem with the GCP project. For more than half the lab, all calls to gemini with video input would fail with a 500 (even in the console with an example prompt from the prompt garden). That made me lose a lot of time for nothing. The idea behind the lab is interesting, but the expected print format needs to be clear and resources need to work.
Giulia M. · Se revisó hace 3 meses
Theo H. · Se revisó hace 3 meses
Johnson O. · Se revisó hace 3 meses
Instructions are very unclear (e.g. choose the correct model, but there are multiple models for every task). Checkpoints take a long time to verify progress and will fail if the format of the prints is not 100% matching expectations, so it would be useful to know exactly which format is expected. I ran out of time because, even though I was able to describe video contents by replacing code in the notebook cell, the checkpoint never validated my progress. Also, there was a problem with the GCP project. For more than half the lab, all calls to gemini with video input would fail with a 500 (even in the console with an example prompt from the prompt garden). That made me lose a lot of time for nothing. The idea behind the lab is interesting, but the expected print format needs to be clear and resources need to work.
Giulia M. · Se revisó hace 3 meses
Anshu K. · Se revisó hace 3 meses
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