This guide describes common errors and their solutions.

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↔️ Galileo API Errors

Find solutions to errors with the Galileo API below.

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400: Bad Request

  • Message: Missing required field: 'model_id'
  • Interpretation: A required field in the request body is missing or malformed.
  • Troubleshooting:
    • Validate your JSON payload structure.
    • Review the API documentation for required fields.

Example (missing field):

{
  "dataset": "review_data"
}

Fix:

{
  "model_id": "bert-v1",
  "dataset": "review_data"
}

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401: Unauthorized

  • Message: Authentication credentials were not provided.
  • Interpretation: The request was made without a valid API key.
  • Troubleshooting:
    • Ensure the Authorization header is set.
    • Visit your Galileo account settings to confirm the API key is valid and not expired.

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403: Forbidden

  • Message: You do not have permission to access this resource.
  • Interpretation: The API key is valid, but access to the specified resource is denied.
  • Troubleshooting:
    • Double-check your project, workspace, or dataset permissions.
    • Visit your Galileo account settings to confirm your API key has the correct scope.

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404: Not Found

  • Message: Project ID 'xyz' not found.
  • Interpretation: The specified resource doesn’t exist.
  • Troubleshooting:
    • Verify the resource ID exists in your Galileo Console.
    • Double-check for typos in the endpoint or parameter.

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405: Method Not Allowed

  • Message: POST method not supported for this endpoint.
  • Interpretation: The wrong HTTP method was used.
  • Troubleshooting:
    • Consult the API documentation to confirm the correct method (GET, POST, PUT, DELETE).

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422: Unprocessable Entity

  • Message: Field 'logits' must be an array of floats matching number of classes.
  • Interpretation: The data format is incorrect even though the syntax is valid.
  • Troubleshooting:
    • Ensure arrays like logits, tokens, or labels match expected dimensions.
    • Refer to the model type’s required input structure.

Example (incorrect logits dimensions):

{
  "model_id": "bert-v1",
  "dataset": "reviews",
  "inputs": ["This movie was amazing!"],
  "logits": [[1.2, 0.8]], // ❌ Only 2 values, should be 3
  "labels": [2]
}

Fix:

{
  "model_id": "bert-v1",
  "dataset": "reviews",
  "inputs": ["This movie was amazing!"],
  "logits": [[1.2, 0.8, -0.3]], // ✅ 3 values
  "labels": [2]
}

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501: Not Implemented

  • Message: This endpoint is not available.
  • Interpretation: The endpoint exists but is not supported or publicly accessible.
  • Troubleshooting:
    • Do not use undocumented endpoints.
    • Contact support if access to the endpoint is expected.

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📁 Galileo SDK Errors

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Missing or Invalid API Key

  • Error Message: ValueError: No API key found. Please set your GALILEO_API_KEY.
  • Interpretation: The SDK cannot authenticate with the Galileo API.
  • Troubleshooting:
    • Set your API key using an environment variable: 
      export GALILEO_API_KEY="your-api-key"
    • Or programmatically: 
      import galileo
galileo.set_api_key("your-api-key")

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Invalid Input Shape

  • Error Message: ValueError: Inputs and logits must have the same batch size.
  • Interpretation: The arrays passed to log_model_outputs() are mismatched.
  • Troubleshooting:
    • Ensure the number of entries in inputs, logits, and labels is the same.

Example (incorrect):

inputs = ["text1", "text2"]
logits = [[0.1, 0.9]]  # Only one set of logits
labels = [1, 0]
galileo.log_model_outputs(inputs=inputs, logits=logits, labels=labels)

Fix:

logits = [[0.1, 0.9], [0.8, 0.2]]  # Now matches batch size

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Unsupported Model Type

  • Error Message: UnsupportedModelTypeError: Model type 'regression' is not supported.
  • Interpretation: The SDK currently supports a limited set of model types.
  • Troubleshooting:

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Token Mismatch Error

  • Error Message: ValueError: Token offsets do not match number of tokens.
  • Interpretation: The offsets passed during token classification are misaligned.
  • Troubleshooting:
    • Validate token offset array lengths match token arrays.
    • Use the Galileo Tokenizer helpers when possible.

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Dataset Not Found

  • Error Message: DatasetNotFoundError: Dataset 'reviews_v2' not found.
  • Interpretation: The specified dataset was not found in the project or workspace.
  • Troubleshooting:
    • Confirm dataset name and project association in the Galileo Console.
    • Run galileo.get_datasets() to verify available datasets.

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Experiment Creation Failed

  • Error Message: ExperimentError: Cannot create experiment. Missing metadata.
  • Interpretation: Required metadata fields were not logged before calling create_experiment().
  • Troubleshooting:
    • Ensure you’ve logged inputs, outputs, and model predictions.
    • Call log_model_outputs() before create_experiment().

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Network or Timeout Issues

  • Error Message: requests.exceptions.ConnectionError
  • Interpretation: SDK could not connect to the Galileo API.
  • Troubleshooting:
    • Check your internet connection.
    • Retry after a few moments.
    • Ensure the API base URL is not overridden or misconfigured.

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🖥️ Galileo Console Errors

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Access Denied

  • Error Message: You do not have permission to view this project.
  • Interpretation: Your account lacks access to a resource within a workspace or project.
  • Troubleshooting:
    • Ask your admin to verify your permissions.
    • Ensure you’re logged into the correct workspace.

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Project Not Found

  • Error Message: Project does not exist or has been deleted.
  • Interpretation: The requested project ID or slug is invalid.
  • Troubleshooting:
    • Refresh the Console and check your project list.
    • Ask a teammate to verify the project is still active.

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Dataset Load Failed

  • Error Message: Failed to load dataset. Please try again.
  • Interpretation: The dataset may not have been logged properly, or it failed to sync.
  • Troubleshooting:
    • Verify that the dataset was successfully logged via SDK or API.
    • Try refreshing the browser or logging out and back in.
    • If persistent, check SDK logs for any upload errors.

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Experiment Failed to Run

  • Error Message: Unable to create experiment. Check that all required data is available.
  • Interpretation: The backend did not receive sufficient input data.
  • Troubleshooting:
    • Ensure model inputs, outputs, and predictions were logged.
    • Confirm the correct dataset is selected.
    • Re-run log_model_outputs() before retrying in the Console.

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Visualization Error

  • Error Message: Visualization failed to render.
  • Interpretation: The plot component encountered unexpected data or rendering issues.
  • Troubleshooting:
    • Try changing filters, date range, or toggling options.
    • If you uploaded custom metadata, ensure it follows the schema.
    • Try a different browser or clear cache.

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File Upload Failed

  • Error Message: File type not supported. or Upload failed. Please retry.
  • Interpretation: Invalid file type or temporary server-side issue.
  • Troubleshooting:
    • Check that the file format is supported (e.g., CSV, JSONL).
    • Rename the file and try again.
    • If issue persists, contact support.

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Export Unavailable

  • Error Message: Export failed. No records available for download.
  • Interpretation: Attempting to export an empty or invalid dataset or experiment.
  • Troubleshooting:
    • Ensure filters are not excluding all records.
    • Re-run the experiment to regenerate results.

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General Tips

  • Refresh the Console often when data changes.
  • Use the latest version of a modern browser (Chrome, Edge, Firefox).
  • Ensure cookies and local storage are enabled for session persistence.

If issues persist, contact support at support@rungalileo.io with your request payload and full error message.