> ## Documentation Index > Fetch the complete documentation index at: https://docs.galileo.ai/llms.txt > Use this file to discover all available pages before exploring further. # Metrics Testing Available Columns ## OpenAPI ````yaml https://api.galileo.ai/public/v2/openapi.json post /v2/projects/{project_id}/metrics-testing/available_columns openapi: 3.1.0 info: title: FastAPI version: 0.1.0 servers: - url: https://api.galileo.ai description: Galileo Public APIs - galileo-v2 security: [] paths: /v2/projects/{project_id}/metrics-testing/available_columns: post: tags: - trace summary: Metrics Testing Available Columns operationId: >- metrics_testing_available_columns_v2_projects__project_id__metrics_testing_available_columns_post parameters: - name: project_id in: path required: true schema: type: string format: uuid4 title: Project Id requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/MetricsTestingAvailableColumnsRequest' responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/LogRecordsAvailableColumnsResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' security: - APIKeyHeader: [] - OAuth2PasswordBearer: [] - HTTPBasic: [] components: schemas: MetricsTestingAvailableColumnsRequest: properties: log_stream_id: anyOf: - type: string format: uuid4 - type: 'null' title: Log Stream Id description: Log stream id associated with the traces. experiment_id: anyOf: - type: string format: uuid4 - type: 'null' title: Experiment Id description: Experiment id associated with the traces. metrics_testing_id: anyOf: - type: string format: uuid4 - type: 'null' title: Metrics Testing Id description: Metrics testing id associated with the traces. name: type: string title: Name description: Name of the metric that we are testing. output_type: $ref: '#/components/schemas/OutputTypeEnum' description: >- Output type of the metrics testing table. If not provided, all columns are returned. default: boolean cot_enabled: type: boolean title: Cot Enabled description: >- Whether the metrics testing table is using chain of thought (CoT) enabled scorers. If True, the columns will be generated for CoT enabled scorers. default: false metric_key: type: string title: Metric Key description: >- The metric key to use for column generation (e.g., 'generated_scorer_validation' or 'registered_scorer_validation'). default: generated_scorer_validation required_scorers: anyOf: - items: type: string type: array - type: 'null' title: Required Scorers description: >- List of required scorer names for composite scorers. Columns will be generated for these scorers. score_type: anyOf: - type: string - type: 'null' title: Score Type description: >- The score type for registered scorers (e.g., 'bool', 'int', 'float', 'str'). Used to determine the correct data_type for the column. Provided by validation result. type: object required: - name title: MetricsTestingAvailableColumnsRequest description: Request to get the available columns for the metrics testing table. LogRecordsAvailableColumnsResponse: properties: columns: items: $ref: '#/components/schemas/LogRecordsColumnInfo' type: array title: Columns type: object title: LogRecordsAvailableColumnsResponse examples: - columns: - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: text description: Input to the trace or span. filter_type: text filterable: true group_label: Standard id: input is_empty: false is_optional: false label: Input multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: text description: Output of the trace or span. filter_type: text filterable: true group_label: Standard id: output is_empty: false is_optional: false label: Output multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: text description: Name of the trace, span or session. filter_type: text filterable: true group_label: Standard id: name is_empty: false is_optional: false label: Name multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: timestamp description: Timestamp of the trace or span's creation. filter_type: date filterable: true group_label: Standard id: created_at is_empty: false is_optional: false label: Created multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: string_list description: Tags associated with this trace or span. filter_type: collection filterable: true group_label: Standard id: tags is_empty: false is_optional: false label: Tags multi_valued: true sortable: false - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: integer description: >- Status code of the trace or span. Used for logging failure or error states. filter_type: number filterable: true group_label: Standard id: status_code is_empty: false is_optional: true label: Status Code multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: text description: A user-provided session, trace or span ID. filter_type: text filterable: true group_label: Standard id: external_id is_empty: false is_optional: true label: External Id multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: text description: Input to the dataset associated with this trace filter_type: text filterable: true group_label: Standard id: dataset_input is_empty: false is_optional: false label: Dataset Input multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: text description: Output from the dataset associated with this trace filter_type: text filterable: true group_label: Standard id: dataset_output is_empty: false is_optional: false label: Dataset Output multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm - session category: standard data_type: uuid description: Galileo ID of the session, trace or span filter_type: id filterable: true group_label: Standard id: id is_empty: false is_optional: false label: ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: uuid description: >- Galileo ID of the session containing the trace (or the same value as id for a trace) filter_type: id filterable: true group_label: Standard id: session_id is_empty: false is_optional: false label: Session ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: uuid description: Galileo ID of the project associated with this trace or span filter_type: id filterable: true group_label: Standard id: project_id is_empty: false is_optional: false label: Project ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: uuid description: >- Galileo ID of the run (log stream or experiment) associated with this trace or span filter_type: id filterable: true group_label: Standard id: run_id is_empty: false is_optional: false label: Run ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: timestamp description: Timestamp of the session or trace or span's last update filter_type: date filterable: true group_label: Standard id: updated_at is_empty: false is_optional: true label: Last Updated multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: boolean description: Whether or not this trace or span has child spans filter_type: boolean filterable: true group_label: Standard id: has_children is_empty: false is_optional: true label: Has Children multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - trace - llm category: standard data_type: boolean description: Whether the parent trace is complete or not filter_type: boolean filterable: true group_label: Standard id: is_complete is_empty: false is_optional: false label: Is Complete multi_valued: false sortable: true - allowed_values: - tool - workflow - control - agent - retriever - trace - llm - session applicable_types: - tool - workflow - control - agent - retriever - llm category: standard data_type: text description: Type of the trace, span or session. filter_type: text filterable: true group_label: Standard id: type is_empty: false is_optional: false label: Type multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - llm category: standard data_type: uuid description: >- Galileo ID of the trace containing the span (or the same value as id for a trace) filter_type: id filterable: true group_label: Standard id: trace_id is_empty: false is_optional: false label: Trace ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - llm category: standard data_type: uuid description: Galileo ID of the parent of this span filter_type: id filterable: true group_label: Standard id: parent_id is_empty: false is_optional: false label: Parent ID multi_valued: false sortable: true - applicable_types: - tool - workflow - control - agent - retriever - llm category: standard data_type: integer description: Topological step number of the span. filter_type: number filterable: true group_label: Standard id: step_number is_empty: false is_optional: true label: Step Number multi_valued: false sortable: true - allowed_values: - judge - planner - react - default - router - classifier - reflection - supervisor applicable_types: - agent category: standard data_type: text description: Agent type. filter_type: text filterable: true group_label: Standard id: agent_type is_empty: false is_optional: false label: Agent Type multi_valued: false sortable: true - applicable_types: - llm category: standard data_type: text description: List of available tools passed to the LLM on invocation. filter_type: text filterable: true group_label: Standard id: tools is_empty: false is_optional: false label: Tools multi_valued: false sortable: true - applicable_types: - llm category: standard data_type: text description: Model used for this span. filter_type: text filterable: true group_label: Standard id: model is_empty: false is_optional: true label: Model multi_valued: false sortable: true - applicable_types: - llm category: standard data_type: floating_point description: Temperature used for generation. filter_type: number filterable: true group_label: Standard id: temperature is_empty: false is_optional: true label: Temperature multi_valued: false sortable: true - applicable_types: - llm category: standard data_type: text description: Reason for finishing. filter_type: text filterable: true group_label: Standard id: finish_reason is_empty: false is_optional: true label: Finish Reason multi_valued: false sortable: true - applicable_types: - tool category: standard data_type: text description: ID of the tool call. filter_type: text filterable: true group_label: Standard id: tool_call_id is_empty: false is_optional: true label: Tool Call Id multi_valued: false sortable: true - applicable_types: - control category: standard data_type: integer description: Identifier of the control definition that produced this span. filter_type: number filterable: true group_label: Standard id: control_id is_empty: false is_optional: true label: Control Id multi_valued: false sortable: true - applicable_types: - control category: standard data_type: text description: Normalized agent name associated with this control execution. filter_type: text filterable: true group_label: Standard id: agent_name is_empty: false is_optional: true label: Agent Name multi_valued: false sortable: true - allowed_values: - pre - post applicable_types: - control category: standard data_type: text description: >- Execution stage where the control ran, typically 'pre' or 'post'. filter_type: text filterable: true group_label: Standard id: check_stage is_empty: false is_optional: true label: Check Stage multi_valued: false sortable: true - allowed_values: - tool_call - llm_call applicable_types: - control category: standard data_type: text description: >- Parent execution type the control applied to, for example 'llm_call' or 'tool_call'. filter_type: text filterable: true group_label: Standard id: applies_to is_empty: false is_optional: true label: Applies To multi_valued: false sortable: true - applicable_types: - control category: standard data_type: text description: >- Representative evaluator name for this control span. For composite controls, this is the primary evaluator chosen for observability identity. filter_type: text filterable: true group_label: Standard id: evaluator_name is_empty: false is_optional: true label: Evaluator Name multi_valued: false sortable: true - applicable_types: - control category: standard data_type: text description: >- Representative selector path for this control span. For composite controls, this is the primary selector path chosen for observability identity. filter_type: text filterable: true group_label: Standard id: selector_path is_empty: false is_optional: true label: Selector Path multi_valued: false sortable: true - applicable_types: [] category: metric data_type: floating_point data_unit: percentage description: >- Measures the presence and severity of harmful, offensive, or abusive language in the model's response filter_type: number filterable: true group_label: Safety Metrics id: metrics/toxicity is_empty: false is_optional: false label: Output Toxicity (SLM) multi_valued: false roll_up_method: average sortable: true threshold: buckets: - 0.5 - 0.8 display_value_levels: - Low - Medium - High inverted: true - applicable_types: [] category: metric data_type: floating_point description: >- BLEU is a case-sensitive measurement of the difference between an model generation and target generation at the sentence-level. filter_type: number filterable: true group_label: Output Quality id: metrics/bleu is_empty: false is_optional: false label: BLEU - DEPRECATED multi_valued: false sortable: true HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError OutputTypeEnum: type: string enum: - boolean - categorical - count - discrete - freeform - percentage - multilabel - retrieved_chunk_list_boolean - boolean_multilabel title: OutputTypeEnum description: Enumeration of output types. LogRecordsColumnInfo: properties: id: type: string title: Id description: Column id. Must be universally unique. label: anyOf: - type: string - type: 'null' title: Label description: Display label of the column in the UI. category: $ref: '#/components/schemas/ColumnCategory' description: Category of the column. description: anyOf: - type: string - type: 'null' title: Description description: Description of the column. group_label: anyOf: - type: string - type: 'null' title: Group Label description: Display label of the column group. data_type: anyOf: - $ref: '#/components/schemas/DataType' - type: 'null' description: >- Data type of the column. This is used to determine how to format the data on the UI. data_unit: anyOf: - $ref: '#/components/schemas/DataUnit' - type: 'null' description: Data unit of the column (optional). multi_valued: type: boolean title: Multi Valued description: Whether the column is multi-valued. default: false allowed_values: anyOf: - items: {} type: array uniqueItems: true - type: 'null' title: Allowed Values description: Allowed values for this column. sortable: type: boolean title: Sortable description: Whether the column is sortable. filterable: type: boolean title: Filterable description: Whether the column is filterable. is_empty: type: boolean title: Is Empty description: Indicates whether the column is empty and should be hidden. default: false applicable_types: items: $ref: '#/components/schemas/StepType' type: array uniqueItems: true title: Applicable Types description: List of types applicable for this column. is_optional: type: boolean title: Is Optional description: Whether the column is optional. default: false roll_up_method: anyOf: - type: string - type: 'null' title: Roll Up Method description: >- Default roll-up aggregation method for this metric (e.g., 'sum', 'average'). metric_key_alias: anyOf: - type: string - type: 'null' title: Metric Key Alias description: >- Alternate metric key for this column. When scorer UUIDs are used as column IDs, this holds the legacy metric_name string for dual-key ClickHouse query fallback. scorer_config: anyOf: - $ref: '#/components/schemas/ScorerConfig' - type: 'null' description: 'For metric columns only: Scorer config that produced the metric.' scorer_id: anyOf: - type: string format: uuid4 - type: 'null' title: Scorer Id description: >- For metric columns only: Scorer id that produced the metric. This is deprecated and will be removed in future versions. insight_type: anyOf: - $ref: '#/components/schemas/InsightType' - type: 'null' description: Insight type. filter_type: anyOf: - $ref: '#/components/schemas/LogRecordsFilterType' - type: 'null' description: Filter type. threshold: anyOf: - $ref: '#/components/schemas/MetricThreshold' - type: 'null' description: Thresholds for the column, if this is a metrics column. label_color: anyOf: - type: string enum: - positive - negative - type: 'null' title: Label Color description: >- Type of label color for the column, if this is a multilabel metric column. type: object required: - id - category - data_type title: LogRecordsColumnInfo ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError ColumnCategory: type: string enum: - standard - metric - user_metadata - metric_status - dataset_metadata - dataset - feedback - tags title: ColumnCategory DataType: type: string enum: - uuid - text - integer - floating_point - boolean - timestamp - string_list - tag - dataset - prompt - playground - rank - category_count - score_rating_aggregate - star_rating_aggregate - thumb_rating_aggregate - tags_rating_aggregate - text_rating_aggregate - annotation_agreement - fully_annotated title: DataType DataUnit: type: string enum: - percentage - nano_seconds - milli_seconds - dollars - count_and_total title: DataUnit StepType: type: string enum: - llm - retriever - tool - workflow - agent - control - trace - session title: StepType ScorerConfig: properties: model_name: anyOf: - type: string - type: 'null' title: Model Name num_judges: anyOf: - type: integer - type: 'null' title: Num Judges filters: anyOf: - items: oneOf: - $ref: '#/components/schemas/NodeNameFilter' - $ref: '#/components/schemas/MetadataFilter' - $ref: '#/components/schemas/ModalityFilter' discriminator: propertyName: name mapping: metadata: $ref: '#/components/schemas/MetadataFilter' modality: $ref: '#/components/schemas/ModalityFilter' node_name: $ref: '#/components/schemas/NodeNameFilter' type: array - type: 'null' title: Filters description: List of filters to apply to the scorer. scoreable_node_types: anyOf: - items: type: string type: array - type: 'null' title: Scoreable Node Types description: >- List of node types that can be scored by this scorer. Defaults to llm/chat. cot_enabled: anyOf: - type: boolean - type: 'null' title: Cot Enabled description: >- Whether to enable chain of thought for this scorer. Defaults to False for llm scorers. output_type: anyOf: - $ref: '#/components/schemas/OutputTypeEnum' - type: 'null' description: >- What type of output to use for model-based scorers (boolean, categorical, etc.). input_type: anyOf: - $ref: '#/components/schemas/InputTypeEnum' - type: 'null' description: >- What type of input to use for model-based scorers (sessions_normalized, trace_io_only, etc..). id: type: string format: uuid4 title: Id name: anyOf: - type: string - type: 'null' title: Name scorer_type: $ref: '#/components/schemas/ScorerTypes' model_type: anyOf: - $ref: '#/components/schemas/ModelType' - type: 'null' description: >- Type of model to use for this scorer. slm maps to luna, and llm maps to plus scorer_version: anyOf: - $ref: '#/components/schemas/BaseScorerVersionDB' - type: 'null' description: >- ScorerVersion to use for this scorer. If not provided, the latest version will be used. multimodal_capabilities: anyOf: - items: $ref: '#/components/schemas/MultimodalCapability' type: array - type: 'null' title: Multimodal Capabilities description: >- Multimodal capabilities which this scorer can utilize in its evaluation. roll_up_method: anyOf: - $ref: '#/components/schemas/RollUpMethodDisplayOptions' - type: 'null' score_type: anyOf: - type: string - type: 'null' title: Score Type description: Return type of code scorers (e.g., 'bool', 'int', 'float', 'str'). type: object required: - id - scorer_type title: ScorerConfig description: Used for configuring a scorer for a scorer job. InsightType: type: string enum: - vertical_bar - horizontal_bar title: InsightType LogRecordsFilterType: type: string enum: - id - date - number - boolean - text - collection - fully_annotated title: LogRecordsFilterType MetricThreshold: properties: inverted: type: boolean title: Inverted description: >- Whether the column should be inverted for thresholds, i.e. if True, lower is better. default: false buckets: items: anyOf: - type: integer - type: number type: array title: Buckets description: >- Threshold buckets for the column. If the column is a metric, these are the thresholds for the column. display_value_levels: items: type: string type: array title: Display Value Levels description: >- Ordered list of strings that raw values get transformed to for displaying. type: object title: MetricThreshold description: |- Threshold configuration for metrics. Defines how metric values are bucketed and displayed, including whether lower or higher values are considered better. NodeNameFilter: properties: name: type: string const: node_name title: Name default: node_name operator: type: string enum: - eq - ne - contains - one_of - not_in title: Operator value: anyOf: - type: string - items: type: string type: array title: Value case_sensitive: type: boolean title: Case Sensitive default: true type: object required: - operator - value title: NodeNameFilter description: Filters on node names in scorer jobs. MetadataFilter: properties: name: type: string const: metadata title: Name default: metadata operator: type: string enum: - one_of - not_in - eq - ne title: Operator key: type: string title: Key value: anyOf: - type: string - items: type: string type: array title: Value type: object required: - operator - key - value title: MetadataFilter description: Filters on metadata key-value pairs in scorer jobs. ModalityFilter: properties: name: type: string const: modality title: Name default: modality operator: type: string enum: - eq - ne - one_of - not_in title: Operator value: anyOf: - type: string description: >- Single enum value - specific options depend on the concrete enum type used example: ENUM_VALUE - items: type: string example: ENUM_VALUE type: array description: Array of enum values example: - ENUM_VALUE_1 - ENUM_VALUE_2 title: Value type: object required: - operator - value title: ModalityFilter description: |- Filters on content modalities in scorer jobs. Matches if at least one of the specified modalities is present. InputTypeEnum: type: string enum: - basic - llm_spans - retriever_spans - sessions_normalized - sessions_trace_io_only - tool_spans - trace_input_only - trace_io_only - trace_normalized - trace_output_only - agent_spans - workflow_spans title: InputTypeEnum description: Enumeration of input types. ScorerTypes: type: string enum: - llm - code - luna - preset title: ScorerTypes ModelType: type: string enum: - slm - llm - code title: ModelType BaseScorerVersionDB: properties: id: type: string format: uuid4 title: Id version: type: integer title: Version scorer_id: type: string format: uuid4 title: Scorer Id generated_scorer: anyOf: - $ref: '#/components/schemas/BaseGeneratedScorerDB' - type: 'null' registered_scorer: anyOf: - $ref: '#/components/schemas/BaseRegisteredScorerDB' - type: 'null' finetuned_scorer: anyOf: - $ref: '#/components/schemas/BaseFinetunedScorerDB' - type: 'null' model_name: anyOf: - type: string - type: 'null' title: Model Name num_judges: anyOf: - type: integer - type: 'null' title: Num Judges scoreable_node_types: anyOf: - items: type: string type: array - type: 'null' title: Scoreable Node Types description: >- List of node types that can be scored by this scorer. Defaults to llm/chat. cot_enabled: anyOf: - type: boolean - type: 'null' title: Cot Enabled description: >- Whether to enable chain of thought for this scorer. Defaults to False for llm scorers. output_type: anyOf: - $ref: '#/components/schemas/OutputTypeEnum' - type: 'null' description: >- What type of output to use for model-based scorers (sessions_normalized, trace_io_only, etc.). input_type: anyOf: - $ref: '#/components/schemas/InputTypeEnum' - type: 'null' description: >- What type of input to use for model-based scorers (sessions_normalized, trace_io_only, etc.). type: object required: - id - version - scorer_id title: BaseScorerVersionDB description: Scorer version from the scorer_versions table. MultimodalCapability: type: string enum: - vision - audio title: MultimodalCapability RollUpMethodDisplayOptions: type: string enum: - average - sum - max - min - category_count - percentage_true - percentage_false title: RollUpMethodDisplayOptions description: >- Display options for roll up methods when showing rolled up metrics in the UI. Separates display intent from computation methods. The computation methods (NumericRollUpMethod, CategoricalRollUpMethod) control what aggregations are available. This enum controls how the UI displays the selected roll-up value for a scorer. BaseGeneratedScorerDB: properties: id: type: string format: uuid4 title: Id name: type: string title: Name instructions: anyOf: - type: string - type: 'null' title: Instructions chain_poll_template: $ref: '#/components/schemas/ChainPollTemplate' user_prompt: anyOf: - type: string - type: 'null' title: User Prompt type: object required: - id - name - chain_poll_template title: BaseGeneratedScorerDB BaseRegisteredScorerDB: properties: id: type: string format: uuid4 title: Id name: type: string title: Name score_type: anyOf: - type: string - type: 'null' title: Score Type type: object required: - id - name title: BaseRegisteredScorerDB BaseFinetunedScorerDB: properties: id: type: string format: uuid4 title: Id name: type: string title: Name lora_task_id: type: integer title: Lora Task Id lora_weights_path: anyOf: - type: string - type: 'null' title: Lora Weights Path prompt: type: string title: Prompt luna_input_type: anyOf: - $ref: '#/components/schemas/LunaInputTypeEnum' - type: 'null' luna_output_type: anyOf: - $ref: '#/components/schemas/LunaOutputTypeEnum' - type: 'null' class_name_to_vocab_ix: anyOf: - additionalProperties: items: type: integer type: array uniqueItems: true type: object - additionalProperties: type: integer type: object - type: 'null' title: Class Name To Vocab Ix executor: anyOf: - $ref: '#/components/schemas/ScorerName' - type: 'null' description: >- Executor pipeline. Defaults to finetuned scorer pipeline but can run custom galileo score pipelines. type: object required: - id - name - lora_task_id - prompt title: BaseFinetunedScorerDB ChainPollTemplate: properties: metric_system_prompt: anyOf: - type: string - type: 'null' title: Metric System Prompt description: System prompt for the metric. metric_description: anyOf: - type: string - type: 'null' title: Metric Description description: Description of what the metric should do. value_field_name: type: string title: Value Field Name description: Field name to look for in the chainpoll response, for the rating. default: rating explanation_field_name: type: string title: Explanation Field Name description: >- Field name to look for in the chainpoll response, for the explanation. default: explanation template: type: string title: Template description: Chainpoll prompt template. metric_few_shot_examples: items: $ref: '#/components/schemas/FewShotExample' type: array title: Metric Few Shot Examples description: Few-shot examples for the metric. response_schema: anyOf: - additionalProperties: true type: object - type: 'null' title: Response Schema description: Response schema for the output type: object required: - template title: ChainPollTemplate description: |- Template for a chainpoll metric prompt, containing all the info necessary to send a chainpoll prompt. LunaInputTypeEnum: type: string enum: - span - trace_object - trace_input_output_only title: LunaInputTypeEnum LunaOutputTypeEnum: type: string enum: - float - string - string_list - bool_list title: LunaOutputTypeEnum ScorerName: type: string enum: - action_completion_luna - action_advancement_luna - agentic_session_success - agentic_session_success - agentic_workflow_success - agentic_workflow_success - agent_efficiency - agent_flow - bleu - chunk_attribution_utilization_luna - chunk_attribution_utilization - chunk_relevance - chunk_relevance_luna - context_precision - precision_at_k - completeness_luna - completeness - context_adherence - context_adherence_luna - context_relevance - context_relevance_luna - conversation_quality - correctness - ground_truth_adherence - visual_fidelity - visual_quality - input_pii - input_pii_gpt - input_sexist - input_sexist - input_sexist_luna - input_sexist_luna - input_tone - input_tone_gpt - input_toxicity - input_toxicity_luna - instruction_adherence - output_pii - output_pii_gpt - output_sexist - output_sexist - output_sexist_luna - output_sexist_luna - output_tone - output_tone_gpt - output_toxicity - output_toxicity_luna - prompt_injection - prompt_injection_luna - prompt_perplexity - rouge - reasoning_coherence - sql_efficiency - sql_adherence - sql_injection - sql_correctness - tool_error_rate - tool_error_rate_luna - tool_selection_quality - tool_selection_quality_luna - uncertainty - user_intent_change - interruption_detection title: ScorerName FewShotExample: properties: generation_prompt_and_response: type: string title: Generation Prompt And Response evaluating_response: type: string title: Evaluating Response type: object required: - generation_prompt_and_response - evaluating_response title: FewShotExample description: Few-shot example for a chainpoll metric prompt. securitySchemes: APIKeyHeader: type: apiKey in: header name: Galileo-API-Key OAuth2PasswordBearer: type: oauth2 flows: password: scopes: {} tokenUrl: https://api.galileo.ai/login HTTPBasic: type: http scheme: basic ````