Problem: Amazon Bedrock Error - "ValidationException: Invalid input payload" When Calling InvokeModel

Problem: Amazon Bedrock Error - "ValidationException: Invalid input payload" When Calling InvokeModel

Problem:

When using the InvokeModel API in Amazon Bedrock, you may encounter this error message:

$ aws bedrock-runtime invoke-model \
    --model-id anthropic.claude-v2 \
    --body '{"prompt": "Hello, world!"}' \
    --region us-east-1

# Error:
# An error occurred (ValidationException) when calling the 
# InvokeModel operation: Invalid input payload

Issue:

This error occurs when the JSON payload sent to the model does not match the expected format or contains invalid data. Common causes include:

• Malformed JSON – The payload may have incorrect syntax, missing brackets, or improperly formatted data.
• Incorrect Parameter Names – Bedrock models require specific parameter names that differ between providers.
• Exceeding Token Limits – The input prompt may be too long, exceeding model constraints.
• Missing Required Fields – Some models require extra metadata fields that are not included.
• Incorrect Data Types – Some fields may need to be formatted as arrays, strings, or objects in a specific way.

Fix: Validate and Correct the Input Payload 

# Step 1: Check JSON Formatting
# Use jq to validate JSON structure
echo '{"prompt": "Hello, world!"}' | jq .

# Expected Output:
# {
#   "prompt": "Hello, world!"
# }

# If an error occurs:
# - Fix any missing or extra brackets, commas, or quotation marks in 
#   the JSON structure.
# - Ensure the JSON is enclosed in single quotes to prevent shell 
#   parsing issues.

# Step 2: Verify Parameter Names
# Ensure correct structure based on model requirements.
# Example for Anthropic Claude:
echo '{
  "prompt": "Hello, world!",
  "max_tokens": 256
}' | jq .

# Expected Output:
# {
#   "prompt": "Hello, world!",
#   "max_tokens": 256
# }

# If an error occurs:
# - Check Amazon Bedrock’s documentation for the correct parameters 
#   for your model.
# - Ensure correct spelling and case sensitivity.

# Step 3: Ensure Token Limits Are Not Exceeded
# Reduce input size if needed.
echo '{
  "prompt": "Hello, world!",
  "max_tokens": 200
}' | jq .

# If the model returns an error like:
# "ValidationException: Exceeded max token limit"
# - Reduce `max_tokens` further.
# - If using a long prompt, shorten the input text.

# Step 4: Confirm Required Fields
# Some models require extra metadata fields.
echo '{
  "prompt": "Hello, world!",
  "max_tokens": 256,
  "stop_sequences": ["\n\n"]
}' | jq .

# If an error occurs:
# - Ensure `stop_sequences` or any required fields match the expected format.
# - Check the model's documentation for mandatory parameters.

# Step 5: Retry the API Call with the Corrected Payload
aws bedrock-runtime invoke-model \
    --model-id anthropic.claude-v2 \
    --body '{"prompt": "Hello, world!", "max_tokens": 256}' \
    --region us-east-1

# Expected Output (Example for a Successful Call):
# {
#   "completion": "Hello! How can I assist you today?",
#   "stop_reason": "end_of_text",
#   "usage": {
#     "input_tokens": 3,
#     "output_tokens": 7
#   }
# }

# If an error persists:
# - Double-check that `model-id` is correct and available in the 
#   specified region.
# - Run `aws bedrock list-foundation-models --region us-east-1` to 
#   confirm the model is supported.
# - Ensure AWS permissions allow invoking models.

Need AWS Expertise?

If you're looking for guidance on Amazon Bedrock or any cloud challenges, feel free to reach out! We'd love to help you tackle your Bedrock projects. 🚀

Email us at: info@pacificw.com

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