langgenius / langgenius/dify-plugin-daemon

PluginInvokeError: {"args":{},"error_type":"APIError","message":"if content is list. item must be dict and key[type] should in dict"}

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#661 2 comments 1 reaction 0 assignees View on GitHub

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bug
Dominant language
Go
Stars
459
Forks
313
Avg merge
5h 17m
Merged PRs (30d)
5

Description

Self Checks
  • I have read the Contributing Guide and Language Policy.
  • This is only for bug report, if you would like to ask a question, please head to Discussions.
  • I have searched for existing issues search for existing issues, including closed ones.
  • I confirm that I am using English to submit this report, otherwise it will be closed.
  • 【中文用户 & Non English User】请使用英语提交,否则会被关闭 :)
  • Please do not modify this template :) and fill in all the required fields.
Dify version

1.13.2

Cloud or Self Hosted

Self Hosted (Docker)

Steps to reproduce
Image

In chatflow workflow, use the document extractor to extract Excel data and enter LLM error:

req_id: d608032dde PluginInvokeError: {"args":{},"error_type":"APIError","message":"if content is list. item must be dict and key[type] should in dict"}

But there is no error in the same steps on the cloud

✔️ Expected Behavior
Image
❌ Actual Behavior

No response

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start by reproducing the document extractor workflow with Excel input in the self-hosted Docker setup, then compare it with the cloud behavior and trace the plugin invocation producing the APIError. Done means the same workflow no longer returns the reported content-list error in self-hosted use, with the relevant regression coverage added if an existing test location is found.

Written by the indexing model from the issue text.

Assessment

Tech stack
docker, go
Domain
api, backend
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Quiet
Clarity
Needs clarification
Newbie friendliness
35/100

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