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What is Opik

Opik is an open-source platform designed for evaluating, testing, and monitoring large language model (LLM) applications. Developed by Comet, it aims to facilitate more intuitive collaboration, testing, and monitoring of LLM-based applications.

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How to Configure Opik

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1. Register/Login to Opik

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2. Get your Opik API Key

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

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3. Integrating Opik with Dify

Configure Opik 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.

After clicking configure, paste the API Key and project name created in Opik into the configuration and save.

Once successfully saved, you can view the monitoring status on the current page.

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Viewing Monitoring Data in Opik

Once configured, you can debug or use the Dify application as usual. All usage history can be monitored in Opik.

When you switch to Opik, you can view detailed operation logs of Dify applications in the dashboard.

Detailed LLM operation logs through Opik will help you optimize the performance of your Dify application.

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Monitoring Data List

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Workflow/Chatflow Trace Information

Used to track workflows and chatflows

Workflow	Opik Trace
workflow_app_log_id/workflow_run_id	id
user_session_id	- placed in metadata
workflow_	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
Model token consumption	usage_metadata
metadata	metadata
error	error
[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

Chat	Opik LLM
message_id	id
user_session_id	- placed in metadata
”llm”	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
Model token consumption	usage_metadata
metadata	metadata
[“message”, conversation_mode]	tags
conversation_id	conversation_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

Moderation	Opik Tool
user_id	- placed in metadata
“moderation”	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
metadata	metadata
[“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 Question	Opik LLM
user_id	- placed in metadata
”suggested_question”	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
metadata	metadata
[“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 Retrieval	Opik Retriever
user_id	- placed in metadata
”dataset_retrieval”	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
metadata	metadata
[“dataset_retrieval”]	tags
message_id	parent_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

Tool	Opik Tool
user_id	- placed in metadata
tool_name	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
metadata	metadata
[“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 Name	Opik Tool
user_id	- placed in metadata
”generate_conversation_name”	name
start_time	start_time
end_time	end_time
inputs	inputs
outputs	outputs
metadata	metadata
[“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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