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What is Arize

Enterprise-grade LLM observability, online & offline evaluation, monitoring, and experimentation—powered by OpenTelemetry. Purpose-built for LLM & agent-driven applications.
For more details, please refer to Arize.

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How to Configure Arize

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1. Register/Login to Arize

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2. Get your Arize API Key

Retrieve your Arize API Key from the user menu at the top-right. Click on API Key, then on the API Key to copy it: Arize API Key

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3. Integrating Arize with Dify

Configure Arize in the Dify application. Open the application you need to monitor, open Monitoring in the side menu, and select Tracing app performance on the page. Tracing app performance After clicking configure, paste the API Key, Space ID and project name created in Arize into the configuration and save. Configure Arize Once successfully saved, you can view the monitoring status on the current page. Configure Arize

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Monitoring Data List

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Workflow/Chatflow Trace Information

Used to track workflows and chatflows
WorkflowArize Trace
workflow_app_log_id/workflow_run_idid
user_session_id- placed in metadata
workflow_name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
Model token consumptionusage_metadata
metadatametadata
errorerror
[workflow]tags
”conversation_id/none for workflow”conversation_id in metadata
Workflow Trace Info
  • workflow_id - Unique identifier of the workflow
  • conversation_id - Conversation ID
  • workflow_run_id - ID of the current run
  • tenant_id - Tenant ID
  • elapsed_time - Time taken for the current run
  • status - Run status
  • version - Workflow version
  • total_tokens - Total tokens used in the current run
  • file_list - List of processed files
  • triggered_from - Source that triggered the current run
  • workflow_run_inputs - Input data for the current run
  • workflow_run_outputs - Output data for the current run
  • error - Errors encountered during the current run
  • query - Query used during the run
  • workflow_app_log_id - Workflow application log ID
  • message_id - Associated message ID
  • start_time - Start time of the run
  • end_time - End time of the run
  • workflow node executions - Information about workflow node executions
  • Metadata
    • workflow_id - Unique identifier of the workflow
    • conversation_id - Conversation ID
    • workflow_run_id - ID of the current run
    • tenant_id - Tenant ID
    • elapsed_time - Time taken for the current run
    • status - Run status
    • version - Workflow version
    • total_tokens - Total tokens used in the current run
    • file_list - List of processed files
    • triggered_from - Source that triggered the current run

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Message Trace Information

Used to track LLM-related conversations
ChatArize LLM
message_idid
user_session_id- placed in metadata
”llm”name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
Model token consumptionusage_metadata
metadatametadata
[“message”, conversation_mode]tags
conversation_idconversation_id in metadata
Message Trace Info
  • message_id - Message ID
  • message_data - Message data
  • user_session_id - User session ID
  • conversation_model - Conversation mode
  • message_tokens - Number of tokens in the message
  • answer_tokens - Number of tokens in the answer
  • total_tokens - Total number of tokens in the message and answer
  • error - Error information
  • inputs - Input data
  • outputs - Output data
  • file_list - List of processed files
  • start_time - Start time
  • end_time - End time
  • message_file_data - File data associated with the message
  • conversation_mode - Conversation mode
  • Metadata
    • conversation_id - Conversation ID
    • ls_provider - Model provider
    • ls_model_name - Model ID
    • status - Message status
    • from_end_user_id - ID of the sending user
    • from_account_id - ID of the sending account
    • agent_based - Whether the message is agent-based
    • workflow_run_id - Workflow run ID
    • from_source - Message source

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Moderation Trace Information

Used to track conversation moderation
ModerationArize Tool
user_id- placed in metadata
“moderation”name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
metadatametadata
[“moderation”]tags
Moderation Trace Info
  • message_id - Message ID
  • user_id: User ID
  • workflow_app_log_id - Workflow application log ID
  • inputs - Moderation input data
  • message_data - Message data
  • flagged - Whether the content is flagged for attention
  • action - Specific actions taken
  • preset_response - Preset response
  • start_time - Moderation start time
  • end_time - Moderation end time
  • Metadata
    • message_id - Message ID
    • action - Specific actions taken
    • preset_response - Preset response

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Suggested Question Trace Information

Used to track suggested questions
Suggested QuestionArize LLM
user_id- placed in metadata
”suggested_question”name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
metadatametadata
[“suggested_question”]tags
Message Trace Info
  • message_id - Message ID
  • message_data - Message data
  • inputs - Input content
  • outputs - Output content
  • start_time - Start time
  • end_time - End time
  • total_tokens - Number of tokens
  • status - Message status
  • error - Error information
  • from_account_id - ID of the sending account
  • agent_based - Whether the message is agent-based
  • from_source - Message source
  • model_provider - Model provider
  • model_id - Model ID
  • suggested_question - Suggested question
  • level - Status level
  • status_message - Status message
  • Metadata
    • message_id - Message ID
    • ls_provider - Model provider
    • ls_model_name - Model ID
    • status - Message status
    • from_end_user_id - ID of the sending user
    • from_account_id - ID of the sending account
    • workflow_run_id - Workflow run ID
    • from_source - Message source

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Dataset Retrieval Trace Information

Used to track knowledge base retrieval
Dataset RetrievalArize Retriever
user_id- placed in metadata
”dataset_retrieval”name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
metadatametadata
[“dataset_retrieval”]tags
message_idparent_run_id
Dataset Retrieval Trace Info
  • message_id - Message ID
  • inputs - Input content
  • documents - Document data
  • start_time - Start time
  • end_time - End time
  • message_data - Message data
  • Metadata
    • message_id - Message ID
    • ls_provider - Model provider
    • ls_model_name - Model ID
    • status - Message status
    • from_end_user_id - ID of the sending user
    • from_account_id - ID of the sending account
    • agent_based - Whether the message is agent-based
    • workflow_run_id - Workflow run ID
    • from_source - Message source

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Tool Trace Information

Used to track tool invocation
ToolArize Tool
user_id- placed in metadata
tool_namename
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
metadatametadata
[“tool”, tool_name]tags

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Tool Trace Info

  • message_id - Message ID
  • tool_name - Tool name
  • start_time - Start time
  • end_time - End time
  • tool_inputs - Tool inputs
  • tool_outputs - Tool outputs
  • message_data - Message data
  • error - Error information, if any
  • inputs - Inputs for the message
  • outputs - Outputs of the message
  • tool_config - Tool configuration
  • time_cost - Time cost
  • tool_parameters - Tool parameters
  • file_url - URL of the associated file
  • Metadata
    • message_id - Message ID
    • tool_name - Tool name
    • tool_inputs - Tool inputs
    • tool_outputs - Tool outputs
    • tool_config - Tool configuration
    • time_cost - Time cost
    • error - Error information, if any
    • tool_parameters - Tool parameters
    • message_file_id - Message file ID
    • created_by_role - Role of the creator
    • created_user_id - User ID of the creator
Generate Name Trace Information Used to track conversation title generation
Generate NameArize Tool
user_id- placed in metadata
”generate_conversation_name”name
start_timestart_time
end_timeend_time
inputsinputs
outputsoutputs
metadatametadata
[“generate_name”]tags
Generate Name Trace Info
  • conversation_id - Conversation ID
  • inputs - Input data
  • outputs - Generated conversation name
  • start_time - Start time
  • end_time - End time
  • tenant_id - Tenant ID
  • Metadata
    • conversation_id - Conversation ID
    • tenant_id - Tenant ID
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