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run agents in workflow show error #8857
Closed
opened 2026-02-21 18:28:11 -05:00 by yindo
·
25 comments
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main
codex/strengthen-tool-provider-types
yanli/refactor-sandbox-and-e2b
0721-happy-path-smoke
feat/ws-proxy-support
chore/support-preview-mode-fe
gareth/esq1-170-rbac-for-agent
deploy/saas
linw/snp-549-reauth-after-accepting-invitation
0721-document-detail
feat/hitl-im-dev
deploy/enterprise
fix/empty-dataset-list-tip
feat/ce-telemetry-dev
0720-documents-tasks
deploy/agent
release/e-1.11.4
fix/cus-1422-enterprise-api-timeout
hotfix/cus-1422-enterprise-api-timeout
perf/optimize-markdown-renderer
feat/fix-undefined-answer-preview
hotfix/1.15.0-fix.15
dependabot/uv/dify-agent/pillow-12.3.0
0720-crawl-selection
0720-crawl-preview
0720-source-connections
0720-create-knowledge
0720-new-rag-contracts
laipz8200/human-input-loop-iteration
0720-new-rag-list
codex/migrate-knowledge-fs
hotfix/1.15.0-fix.14
lts/1.13.x
deploy/workflow-archive-catalog-discovery
dependabot/uv/api/pydantic-09001a97e5
laipz8200/completion-workflow-entry
dependabot/uv/api/lts/1.13.x/python-packages-6c2bf7110c
dependabot/uv/api/storage-4219cfbece
dependabot/uv/api/lts/1.13.x/dev-6fc4f8b90c
dependabot/uv/api/llm-46e0cee538
dependabot/uv/api/lts/1.13.x/vdb-72526f7860
dependabot/uv/api/opentelemetry-b8005594e1
dependabot/uv/api/lts/1.13.x/storage-4310e8b8d8
dependabot/uv/api/lts/1.13.x/database-c0fba9b420
dependabot/uv/api/lts/1.13.x/llm-5ce1d68736
dependabot/uv/api/lts/1.13.x/pydantic-09001a97e5
dependabot/uv/api/lts/1.13.x/opentelemetry-b8005594e1
dependabot/uv/api/google-68de7a6be5
dependabot/github_actions/lts/1.13.x/github-actions-dependencies-1a36b91cf1
dependabot/uv/api/lts/1.13.x/google-c93828e58f
dependabot/uv/api/lts/1.13.x/flask-1086fc46af
0717-knowledge-fs-contract
feat/secret-scrub-persistence
feat/llm-ft-timeout
feat/appdeploy-selected-workflow-dsl
0715-new-rag
laipz8200/llm-environment-variables
release/ee-1.15.0-hotfix
laipz8200/chore-remove-feature-preview-root-env
dependabot/go_modules/dify-agent-runtime/golang.org/x/net-0.55.0
hotfix/1.15.0-fix.12
hotfix/1.15.0-fix.12-cherrypick
hotfix/1.15.0-fix.13
build/invite-seats-precheck
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laipz8200/workflow-persistence-mixed-mode
hotfix/1.15.0-fix.10
zhangxin/eng-558-licensed-seats-1.15
fix/wta-1307-effect-suspense-read
feat/cli-skills-agents
0713-vp-lint
deploy/dev
fix/agent-roster-answer-completion-main
feat/pay-by-invoice
codex/run-external-e2e-main-ci
agent/remove-sandbox-bind-mounts
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hotfix/1.15.0-fix.9
hotfix/1.15.0-fix.8
build/test-archive-export
linw/restore-agent-message-delta-feat
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codex/pr-38227-session-types
codex/pr-38227-session-scope-split
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codex/review-pr-38480
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copilot/fix-web-full-stack-e2e-job
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laipz8200/scope-segment-route-lookup
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codex/upgrade-orpc-v2-beta
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worktree-token-expired-error-code
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codex/agent-v2-state-graph
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build/fix/workflow-error-hanging
work/dify-2585-agent-drafts-pr
fix/dify-2574-soul-files-kv
fix/dify-2554-debug-conversation-per-user
hotfix/1.14.2-fix.11
feat/openapi-rbac
test/cli-e2e-error-body-contract
build/optimize-clean-messages-eligible-apps
zhaohao1004/optimize-clean-messages-cursor
gh-readonly-queue/main/pr-37592-c71f03f5902031b7c02e61af3aff5c2dee6f7d85
build/optimize-clean-messages-cursor
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hotfix/1.14.2-fix.7
hotfix/1.14.2-fix.6
codex/page-title-updates
feat/agent-mention-stable-ids
fix/guard-workspace-with-defualt-roles
build/pr-37227-free-plan-workflow-run-cleanup
feat/cli-e2e-test-suite
feat/ui-start-node
feat/hitl-file-in-body
copilot/dify-team-question-agent-node
fix/wta-438-device-sso-redirect-origin
hotfix/1.14.2-fix.5
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codex/local-app-list-tag-filter
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hotfix/1.14.2-fix.3
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codex/snp-406-pointer-position-ref
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build/feat/model-type-migration-script
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copilot/research-retrieval-attachment-consumption
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build/1.14.1-fix.1-langfuse
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bug1
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e-0156
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0.15.1-admin-apis
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fix/switch-strategy-clean-param
fix/chore-fix
opik-monitoring
provider-gpustack
feat/mecab-japanese-keywords
feat/retry-single-step-debug
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fix/remove-the-retry-index-field
fix/11839
feat/node-execution-retry
feat/support-extractor-tools-update-wip
feat/update-tidb-batchget-endpoint
fix/iteration-thread-pool-error
feat/support-multi-token-count
feat/parent-child-retrieval-api
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build/add-dependabot
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fix/9772-internal-server-error-when-custom-disclaimer-longer-than-64-characters
alert-autofix-89
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build/switch-to-pnpm
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fix/external-knowledge-retrieval-issues
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fix/db-lock-timeout
feat/new-tooltip
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fix/extra-table-tracing-app-config
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bai
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1.13.3
1.13.2
1.13.1
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Reference: langgenius/dify#8857
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Originally created by @yulin12341 on GitHub (Mar 2, 2025).
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Dify version
1.0.0
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Self Hosted (Docker)
Steps to reproduce
when I run workflow with agents, it shows below error:
Run failed: Failed to transform agent message: PluginInvokeError: {"args":{},"error_type":"ValidationError","message":"1 validation error for FunctionCallingParams\nmodel.entity\n Input should be a valid dictionary or instance of AIModelEntity [type=model_type, input_value=None, input_type=NoneType]\n For further information visit https://errors.pydantic.dev/2.8/v/model_type"}
✔️ Expected Behavior
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❌ Actual Behavior
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@dosubot[bot] commented on GitHub (Mar 2, 2025):
Hello, @yulin12341! I'm here to help you with any bugs, questions, or contributions. Let's work together to solve the issue you're facing.
I found a similar unsolved discussion that might be relevant to your issue: Agent node in workflow run status fails, which was last updated on February 28, 2025 [1].
Regarding the error you're encountering, it seems to be related to a
ValidationErrorin theFunctionCallingParams. This error typically occurs when the input is not a valid dictionary or instance ofAIModelEntity. To resolve this, ensure that themodelparameter in your workflow configuration is correctly defined as a validAIModelEntity. This includes specifying the model identifier and ensuring that all required fields are correctly populated [2].To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@yulin12341 commented on GitHub (Mar 2, 2025):
My configuration is very simple, but can't run the agents in workflow, please help to check the below configuration:
@dosubot[bot] commented on GitHub (Mar 2, 2025):
The error you're encountering is related to the
FunctionCallingParams\model.entityfield, which needs to be a valid dictionary or an instance ofAIModelEntity. Here are a few steps to help resolve this issue:Ensure Correct Model Configuration: Verify that the
modelfield in your configuration is correctly defined as an instance ofAIModelEntity. This includes specifying the model identifier, such as "doubao-pro-128k", and ensuring all required fields are populated correctly. The required fields for anAIModelEntityincludemodel,model_type, andmodel_properties[1].Check the
FunctionCallingParams: Make sure that themodelparameter in theFunctionCallingParamsis defined using theAgentModelConfigclass. This ensures that the model parameter is correctly configured to avoid validation errors [2].Review the Tool List: Ensure that the tools listed, such as the "TIME" calculator, are compatible with the selected model and correctly configured. Although specific details about the "doubao-pro-128k" model and the "TIME" calculator tool are not available, ensuring compatibility and correct configuration is crucial.
Validate the YAML Configuration: If you're using a
function_calling.yamlfile, double-check the syntax and ensure all parameters are correctly defined, includingmodel,tools,query, andmax_iterations.By following these steps, you should be able to resolve the validation error and successfully run the agents in your workflow.
To continue talking to Dosu, mention @dosu.
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@yulin12341 commented on GitHub (Mar 2, 2025):
below is my configuration, it's very simple! should not be wrong with the configuration.
app:
description: ''
icon: 🤖
icon_background: '#FFEAD5'
mode: advanced-chat
name: 测试chatflow
use_icon_as_answer_icon: false
dependencies: []
kind: app
version: 0.1.5
workflow:
conversation_variables: []
environment_variables: []
features:
file_upload:
allowed_file_extensions:
- .JPG
- .JPEG
- .PNG
- .GIF
- .WEBP
- .SVG
allowed_file_types:
- image
allowed_file_upload_methods:
- local_file
- remote_url
enabled: false
fileUploadConfig:
audio_file_size_limit: 50
batch_count_limit: 5
file_size_limit: 15
image_file_size_limit: 10
video_file_size_limit: 100
workflow_file_upload_limit: 10
image:
enabled: false
number_limits: 3
transfer_methods:
- local_file
- remote_url
number_limits: 3
opening_statement: ''
retriever_resource:
enabled: true
sensitive_word_avoidance:
enabled: false
speech_to_text:
enabled: false
suggested_questions: []
suggested_questions_after_answer:
enabled: false
text_to_speech:
enabled: false
language: ''
voice: ''
graph:
edges:
- data:
isInIteration: false
sourceType: start
targetType: agent
id: 1740845799739-source-1740926418820-target
source: '1740845799739'
sourceHandle: source
target: '1740926418820'
targetHandle: target
type: custom
zIndex: 0
- data:
isInIteration: false
sourceType: agent
targetType: answer
id: 1740926418820-source-answer-target
source: '1740926418820'
sourceHandle: source
target: answer
targetHandle: target
type: custom
zIndex: 0
nodes:
- data:
desc: ''
selected: false
title: 开始
type: start
variables: []
height: 54
id: '1740845799739'
position:
x: 78.94444628236204
y: 282
positionAbsolute:
x: 78.94444628236204
y: 282
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
answer: '{{#llm.text#}}'
desc: ''
selected: false
title: 直接回复
type: answer
variables: []
height: 103
id: answer
position:
x: 775.2667318004308
y: 176.67212346540285
positionAbsolute:
x: 775.2667318004308
y: 176.67212346540285
selected: false
sourcePosition: right
targetPosition: left
type: custom
width: 244
- data:
agent_parameters:
instruction:
type: constant
value: you are a risk manager.
model:
type: constant
value:
completion_params: {}
mode: chat
model: doubao-pro-128k
model_type: llm
provider: langgenius/volcengine_maas/volcengine_maas
type: model-selector
query:
type: constant
value: '{{#sys.query#}}'
tools:
type: constant
value:
- enabled: true
extra:
description: ''
parameters:
day:
auto: 1
value: null
month:
auto: 1
value: null
year:
auto: 1
value: null
provider_name: time
schemas:
- auto_generate: null
default: null
form: llm
human_description:
en_US: Year
ja_JP: Year
pt_BR: Year
zh_Hans: 年
label:
en_US: Year
ja_JP: Year
pt_BR: Year
zh_Hans: 年
llm_description: null
max: null
min: null
name: year
options: []
placeholder: null
precision: null
required: true
scope: null
template: null
type: number
- auto_generate: null
default: null
form: llm
human_description:
en_US: Month
ja_JP: Month
pt_BR: Month
zh_Hans: 月
label:
en_US: Month
ja_JP: Month
pt_BR: Month
zh_Hans: 月
llm_description: null
max: null
min: null
name: month
options: []
placeholder: null
precision: null
required: true
scope: null
template: null
type: number
- auto_generate: null
default: null
form: llm
human_description:
en_US: day
ja_JP: day
pt_BR: day
zh_Hans: 日
label:
en_US: day
ja_JP: day
pt_BR: day
zh_Hans: 日
llm_description: null
max: null
min: null
name: day
options: []
placeholder: null
precision: null
required: true
scope: null
template: null
type: number
settings: {}
tool_label: 星期几计算器
tool_name: weekday
type: builtin
agent_strategy_label: FunctionCalling
agent_strategy_name: function_calling
agent_strategy_provider_name: langgenius/agent/agent
desc: ''
output_schema: null
plugin_unique_identifier: langgenius/agent:0.0.8@6dd1206901fa166f1a631fb3f0f8eb08f9e7cf54043b7fe45fcb011218cad7a2
selected: false
title: Agent
type: agent
height: 198
id: '1740926418820'
position:
x: 467.23918844161807
y: 369.6523832785868
positionAbsolute:
x: 467.23918844161807
y: 369.6523832785868
selected: true
sourcePosition: right
targetPosition: left
type: custom
width: 244
viewport:
x: 114.77436976154002
y: -47.14612545816931
zoom: 0.9253044280378528
@wl102 commented on GitHub (Mar 3, 2025):
I got error with function calling agent:
Failed to transform agent message: PluginInvokeError: {"args":{},"error_type":"ValidationError","message":"1 validation error for LogMessage\nmetadata.start_at.[key]\n Input should be 'started_at', 'finished_at', 'elapsed_time', 'total_price', 'total_tokens', 'provider' or 'currency' [type=enum, input_value='start_at', input_type=str]\n For further information visit https://errors.pydantic.dev/2.8/v/enum"}
@yulin12341 commented on GitHub (Mar 3, 2025):
@dosu
@dosubot[bot] commented on GitHub (Mar 3, 2025):
The error you're encountering is related to the
model.entityfield in theFunctionCallingParams, which needs to be a valid dictionary or an instance ofAIModelEntity. Here are some steps to help resolve this issue:Verify Model Configuration: Ensure that the
modelfield in your configuration is correctly defined as an instance ofAIModelEntity. This includes specifying the model identifier, such as "doubao-pro-128k", and ensuring all required fields are populated correctly. The required fields for anAIModelEntityincludemodel,model_type, andmodel_properties[1].Check
FunctionCallingParamsStructure: Make sure that themodelparameter in theFunctionCallingParamsis defined using theAgentModelConfigclass. This ensures that the model parameter is correctly configured to avoid validation errors [2].Review the Configuration: Double-check the configuration to ensure that all parameters are correctly defined, including
model,tools,query, andmax_iterations. Ensure that themodelfield is not missing any required attributes.By following these steps, you should be able to resolve the validation error and successfully run the agents in your workflow.
To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@yulin12341 commented on GitHub (Mar 3, 2025):
@dosu Hello, I'm a bit confused. I used the interface for configuration. Where exactly do I configure this AIModelEntity information?
@dosubot[bot] commented on GitHub (Mar 3, 2025):
To configure the
AIModelEntityinformation in Dify, you need to go to Settings --> Model Providers in the Dify interface. Here, you can add and configure the language model you intend to use. Make sure to specify the model identifier, model type, and model properties correctly. This setup is crucial for ensuring that themodelparameter in your workflow is correctly defined as an instance ofAIModelEntity[1].To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@yulin12341 commented on GitHub (Mar 3, 2025):
@dosu Hello, please take a look at the two screenshots I've attached. The first one is the model configuration, which I configured using Volcengine. I am certain that the configuration information is correct. Additionally, as you can see from my second screenshot, there are no issues when calling within a single agent, indicating that the model configuration is correct. Moreover, the doubao model I'm using does support function calls.
@dosubot[bot] commented on GitHub (Mar 3, 2025):
The issue you're facing with the
FunctionCallingParams\model.entityvalidation error might be due to a mismatch in how the model is configured in the workflow compared to the single agent setup. Here are a few things to check:Model Configuration Consistency: Ensure that the model configuration in the workflow matches exactly with the configuration used in the single agent setup. This includes verifying that all fields such as
model,model_type, andproviderare identical.Required Parameters: Double-check that all required parameters for the
doubao-pro-128kmodel are provided in the workflow configuration. Missing parameters can lead to validation errors [1].Tool Configuration: Ensure that the tools used in the workflow are correctly enabled and configured. The validation error can occur if the tools are not properly set up or if required tools are missing [1].
FunctionCallingParams Validation: Make sure that the
FunctionCallingParamsare correctly defined, including themodel,tools, andqueryfields. Themodelfield should be a valid instance ofAIModelEntity, and all necessary attributes should be populated [2].By ensuring these configurations are consistent and complete, you should be able to resolve the validation error in the workflow.
To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@yulin12341 commented on GitHub (Mar 3, 2025):
@dosu please help to look at the screenshot I've attached. The agent information I configured in the workflow is as shown in the screenshot, and it's just a very simple test workflow. The model configured inside the agent is the one I defined, consistent with the model configuration. The tool simply calls the 'weekday' built-in tool, which seems to be one of the simplest workflows with an agent that could be defined for use. However, it keeps showing an error.
@dosubot[bot] commented on GitHub (Mar 3, 2025):
The error you're encountering might be due to a few potential issues in the configuration of the
AIModelEntityor theFunctionCallingParams. Here are some steps to help resolve this:Verify Model Configuration: Ensure that the model configuration in the workflow is consistent with the single agent setup. This includes checking that the
model,model_type, andproviderfields are correctly defined and match the configuration used in the single agent setup.Check Required Fields: Make sure all required fields for the
AIModelEntityare correctly populated. This includes fields likemodel,model_type, andmodel_properties. Themodel_propertiesshould include necessary attributes likemodeand any other specific properties required by the model type [1].Tool Configuration: Since you're using the 'weekday' built-in tool, ensure that all required parameters (
year,month,day) are correctly set up in the workflow. These parameters should be provided in the correct format and should not be null [2].FunctionCallingParams Validation: Double-check the
FunctionCallingParamsto ensure that themodelfield is a valid instance ofAIModelEntityand that all necessary attributes are included. This includes ensuring that themodelparameter is correctly defined using theAgentModelConfigclass [3].By ensuring these configurations are consistent and complete, you should be able to resolve the validation error in the workflow.
To continue talking to Dosu, mention @dosu.
Help Dosu learn! Give it feedback: Great Response | Irrelevant Answer | Incorrect Sources | Too Verbose | Hallucination | Bug Report | Other
@Bestwo2024 commented on GitHub (Mar 4, 2025):
换模型就好了,用deepseek模型可以不报错
@yulin12341 commented on GitHub (Mar 9, 2025):
@Bestwo2024 为啥换模型就好了,其它模型不能支持么?
@NullUserSIe commented on GitHub (Mar 10, 2025):
I can not understand, either. What i've tried for the agent node specified FunctionCalling:
There is quite some weird problems inside FunctionCalling. Or else, just show us What the provider and model is supposed to be supporting FuncionCalling in a list.
NOTE: All of these happened when using Dify Cloud which might be with Network Issues when accessing from China.
@HamaWhiteGG commented on GitHub (Mar 13, 2025):
After debugging, it was determined that the error requires modifying the dependency code within the plugin.
Modify the
__init__.pyfile in the directoryvolumes/plugin_daemon/cwd/langgenius/agent-0.0.9@f16916b704a20067317dbe9030f62aa28f0832021a3ef6d4ce699504074c5e13/.venv/lib64/python3.12/site-packages/dify_plugin/interfaces/agent, and set the default value ofentityin theAgentModelConfigclass toNone.Before modification:
After modification:
To restart the docker-plugin_daemon-1 container after modifying the code, you can use the following command:
Verification result:
@dosubot[bot] commented on GitHub (Apr 13, 2025):
Hi, @yulin12341. I'm Dosu, and I'm helping the Dify team manage their backlog. I'm marking this issue as stale.
Issue Summary
PluginInvokeErrordue to aValidationErrorinFunctionCallingParams.model.entityfield not being a valid dictionary orAIModelEntity.AgentModelConfigclass to set theentityfield's default toNone.Next Steps
Thank you for your understanding and contribution!
@user905 commented on GitHub (Apr 17, 2025):
@dosu - This is still an issue, it is not stale. This is after testing an Agent in a basic chatflow
@Nov1c444 commented on GitHub (Apr 18, 2025):
Could you please provider your agent plugin's version? Maybe update the plugin's version could solve the issues
@dosubot[bot] commented on GitHub (Apr 18, 2025):
The issue with certain models not supporting FunctionCalling in Dify can be attributed to specific requirements and compatibility issues. Here are some key points to consider:
Model Requirements: For a model to support FunctionCalling in Dify, it must have Vision multimodal support and the Function Call parameter enabled. Additionally, compatibility with the Agent plugin is necessary, as not all models that work in workflows are supported in Agent nodes [1][2].
Known Model Issues: Some models, like those from PPIO, currently do not support Function Call as Agent Mode due to the lack of Function Calling capability in their API. This feature is under development [3]. Additionally, using models like gpt-4o-mini may result in inconsistent function call outputs due to the model's decision-making behavior [4].
Provider and Model Compatibility: If you encounter issues with specific models, consider switching to models from different providers that are known to be compatible with FunctionCalling. For example, using the DeepSeek model resolved the issue for another user [3].
Configuration Adjustments: If you are experiencing validation errors related to
AIModelEntity, ensure that the model configuration is correctly defined with all required fields populated. You may also need to modify theAgentModelConfigclass to set theentityattribute toNoneby default, as suggested in previous debugging steps [5][6].By ensuring that the models meet these requirements and making necessary configuration adjustments, you should be able to resolve the issues with FunctionCalling in Dify.
To continue talking to Dosu, mention @dosu.
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@user905 commented on GitHub (Apr 18, 2025):
@Nov1c444 - We're using GPT-4o on Azure OpenAI, v0.0.14, which is the latest.
@user905 commented on GitHub (Apr 18, 2025):
It appears that upgrading to v1.2.0 resolves the issue.
@Nov1c444 commented on GitHub (Apr 20, 2025):
You could upgrade the agent plugin's version, the latest version is 0.0.14.
@user905 commented on GitHub (Apr 21, 2025):
Thanks. Did this as well, but can't say whether it resolved the issue. I'd already found a fix. See higher up in the chain.