[bedrock] Error: ValidationException: A conversation must start with a user message. Try again with a conversation that starts with a user message.

[luckylhb90]

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Dify version

0.10.2

Cloud or Self Hosted

Self Hosted (Source)

Steps to reproduce

1. When we use sonnet3.5 with memory enabled, this error is always reported when we call it.

[bedrock] Error: ValidationException: A conversation must start with a user message. Try again with a conversation that starts with a user message.

2. I analyzed the code and guessed that it might have something to do with checking tokens here. For the other models, I didn't think there was a problem, but for sonnet, if we removed a prompt, it would cause this error.

3. I try to modify the configuration of the model, but again I get input token overrun issues.
   context_size: 20000000

Is there any relevant experience you can provide for our reference?

✔️ Expected Behavior

Even if the memory function is enabled, users will not be affected.

❌ Actual Behavior

Always get the following error：

[dosubot]

I found a similar unsolved discussion that might be relevant to your issue: Error using large language model ^[1].

Regarding your issue, it seems that the error "A conversation must start with a user message" is related to how the conversation is initiated in the Dify platform. To start a conversation with a user message, you need to ensure that the initial message in the conversation is from the user. This can be done using the create_chat_message method from the ChatClient class, where you specify the query as the user's message and leave the conversation_id empty to start a new conversation ^[2].

Additionally, the token_buffer_memory.py script is responsible for managing the conversation history while respecting token limits. It retrieves and formats past messages, ensuring that the total number of tokens does not exceed a specified limit. If the token count exceeds the limit, it prunes messages from the start of the list ^[3].

For the 'Claude 3.5 Sonnet' model, the default max_tokens is set to 8192. If you're encountering input token overrun issues, you might need to adjust this parameter to prevent exceeding the token limit ^[4].

Ensure that your initial user message is correctly formatted and that the token limits are configured appropriately to avoid these errors.

To continue talking to Dosu, mention @dosu.

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[crazywoola]

Can you try it in the latest version?

[luckylhb90]

Can you try it in the latest version?

We're upgrading, too. Let me test it.