Galileo Technologies Project Settings API

openapi: 3.2.0
info:
  title: Galileo API Server Project Settings API
  version: 0.0.0+orbit
servers:
- url: https://api.galileo.ai
  description: Galileo API Server - galileo-v2
tags:
- name: Project Settings
paths:
  /projects/{project_id}/settings:
    put:
      tags:
      - Project Settings
      summary: Update Project Settings
      description: Update project settings after checking permissions for the fields that changed.
      operationId: update_project_settings_projects__project_id__settings_put
      security:
      - APIKeyHeader: []
      - ClassicAPIKeyHeader: []
      - OAuth2PasswordBearer: []
      - HTTPBasic: []
      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/GenAIProjectSettingsUpdate'
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/ProjectSettingsDB'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
    get:
      tags:
      - Project Settings
      summary: Get Settings
      operationId: get_settings_projects__project_id__settings_get
      security:
      - APIKeyHeader: []
      - ClassicAPIKeyHeader: []
      - OAuth2PasswordBearer: []
      - HTTPBasic: []
      parameters:
      - name: project_id
        in: path
        required: true
        schema:
          type: string
          format: uuid4
          title: Project Id
      responses:
        '200':
          description: Successful Response
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/GenAIProjectSettings'
        '422':
          description: Validation Error
          content:
            application/json:
              schema:
                $ref: '#/components/schemas/HTTPValidationError'
components:
  schemas:
    MetricWeightUpdate:
      properties:
        weight:
          type: number
          title: Weight
          default: 0.5
      type: object
      title: MetricWeightUpdate
    MetricDescriptions:
      type: string
      enum:
      - 'Measures whether the LLM''s response is supported by (or baked in) the context provided. '
      - Checks whether a response is supported by text and image context. PDF files are not yet supported.
      - Measures whether the LLM's response is supported by the provided context, including images and documents.
      - Measures whether the LLM's response is supported by the provided context, including audio.
      - Measures how well the LLM follows the system instructions provided in the prompt.
      - Measures how well the LLM follows system instructions provided in the prompt.
      - Measures how well the LLM follows system instructions provided in the prompt.
      - Measures how well the workflow's response aligns with the ground truth provided.
      - Measures how well the workflow's response aligns with ground truth that includes images or documents.
      - Measures how well the workflow's response aligns with ground truth that includes audio.
      - Detects whether the model selected the right Tool with the right arguments.
      - Detects whether the model selected the right Tool with the right arguments.
      - Detects whether the model selected the right Tool with the right arguments.
      - Detects whether the Tool executed successfully (i.e. without errors).
      - Measures whether the retrieved context has enough information to answer the user's query.
      - Measures the potential presence of factual errors or inconsistencies in the model's response.
      - Detects whether model output concretely violates one or more applicable configured output-policy rules.
      - Measures the potential presence of factual errors or inconsistencies in the model's response, including image or document content.
      - Measures the potential presence of factual errors or inconsistencies in the model's response, including audio content.
      - Classifies the sentiment of the user's input into one of joy, love, fear, surprise, sadness, anger, annoyance, confusion or neutral.
      - Measures how 'sexist' a user's input might be perceived ranging in the values of 0-1 (1 being more sexist).
      - Scores text and images in the user's input for sexism. PDF files are not yet supported.
      - Measures how sexist image or document input content might be perceived, ranging from 0 to 1.
      - Measures how sexist audio input content might be perceived, ranging from 0 to 1.
      - Measures the presence and severity of harmful, offensive, or abusive language
      - Scores text and images in the user's input for toxicity. PDF files are not yet supported.
      - Measures the presence and severity of harmful, offensive, or abusive content in image or document inputs.
      - Measures the presence and severity of harmful, offensive, or abusive content in audio inputs.
      - Tracks the presence of personal identifiable information in the user's input
      - Detects personally identifiable information in text and images in the user's input. PDF files are not yet supported.
      - Tracks the presence of personal identifiable information in the user's image or document input
      - Tracks the presence of personal identifiable information in the user's audio input
      - Classifies the sentiment in the model's response into one of joy, love, fear, surprise, sadness, anger, annoyance, confusion or neutral.
      - Measures how 'sexist' a response might be perceived ranging in the values of 0-1 (1 being more sexist).
      - Scores text and images in the model's response for sexism. PDF files are not yet supported.
      - Measures how 'sexist' a response might be perceived ranging in the values of 0-1 (1 being more sexist).
      - Measures how 'sexist' a response might be perceived ranging in the values of 0-1 (1 being more sexist).
      - Measures the presence and severity of harmful, offensive, or abusive language in the model's response
      - Scores text and images in the model's response for toxicity. PDF files are not yet supported.
      - Measures the presence and severity of harmful, offensive, or abusive content in the model's image or document responses.
      - Measures the presence and severity of harmful, offensive, or abusive content in the model's audio responses.
      - Tracks the presence of personal identifiable information in the LLM's responses
      - Detects personally identifiable information in text and images in the model's response. PDF files are not yet supported.
      - Tracks the presence of personal identifiable information in the LLM's image or document responses
      - Tracks the presence of personal identifiable information in the LLM's audio responses
      - Measures the presence of prompt injection attacks in inputs to the LLM.
      - Detects prompt injection attempts in text and image inputs. PDF files are not yet supported.
      - Measures the presence of prompt injection attacks in inputs to the LLM.
      - Measures the presence of prompt injection attacks in inputs to the LLM.
      - Precision of top-K retrieved chunks, measuring the proportion of relevant chunks among the first K results.
      - Measures which documents or chunks retrieved were used by the model to generate a response.
      - Measures how much of the text in the retrieved chunks was used by the model to compose its response.
      - Evaluates whether each retrieved chunk is relevant to the query.
      - Position-weighted relevance score that accounts for the order of retrieved chunks.
      - A response-level metric measuring 'out of all the information in the context pertinent to the question, how much was covered in the answer?'
      - Cost of executing the run and does not include any costs incurred for metric calculation.
      - Cost of all the metrics that call the OpenAI API.
      - Detects whether the user successfully accomplished or advanced towards their goal.
      - Detects whether the user successfully accomplished all of their goals.
      - Detects whether the user successfully accomplished all of their goals in a session that includes images or documents.
      - Detects whether the user successfully accomplished all of their goals in a session that includes audio.
      - Detects whether the agent followed the most efficient path to accomplish the user's goal.
      - Measures the correctness and coherence of an agentic trajectory by validating it against user-specified natural language tests.
      - Measures the correctness and coherence of an agentic trajectory by validating it against user-specified natural language tests.
      - Measures the correctness and coherence of an agentic trajectory by validating it against user-specified natural language tests.
      - Assesses whether a chatbot interaction left the user feeling satisfied and positive, or frustrated and dissatisfied, based on tone, engagement, and overall experience.
      - Assesses whether a chatbot interaction that includes images or documents left the user feeling satisfied and positive, or frustrated and dissatisfied, based on tone, engagement, and overall experience.
      - Assesses whether a chatbot interaction that includes audio left the user feeling satisfied and positive, or frustrated and dissatisfied, based on tone, engagement, and overall experience.
      - Detects a significant shift in the user's primary conversational goal or workflow during a session, relative to their initial stated intent.
      - Detects a significant shift in the user's primary conversational goal or workflow during a session that includes images or documents.
      - Detects a significant shift in the user's primary conversational goal or workflow during a session that includes audio.
      - Evaluates whether the SQL query semantically adheres to the natural language query.
      - 'Evaluates the SQL query on two independent binary dimensions: syntactic correctness and schematic adherence.'
      - Evaluates whether the SQL query is structurally efficient and free of common performance anti-patterns.
      - Detects SQL injection risks and other security exploits in the query.
      - Measures the coherence of the reasoning process by evaluating the consistency and logical flow of the reasoning steps.
      - Measures the coherence of the reasoning process by evaluating the consistency and logical flow of reasoning steps with image or document context.
      - Measures the coherence of the reasoning process by evaluating the consistency and logical flow of reasoning steps with audio context.
      - Determines whether the input image / PDF is of sufficient quality to complete the given task.
      - Evaluates whether the generated image / PDF complies with the provided rules.
      - Identifies barge-ins by the user or the LLM in an audio conversation.
      title: MetricDescriptions
    AlertsConfiguration:
      properties:
        emails:
          items:
            type: string
            format: email
          type: array
          title: Emails
        webhooks:
          items:
            $ref: '#/components/schemas/Webhook'
          type: array
          title: Webhooks
      type: object
      title: AlertsConfiguration
    MetricWeight:
      properties:
        label:
          anyOf:
          - type: string
          - type: 'null'
          title: Label
        group_label:
          anyOf:
          - $ref: '#/components/schemas/GroupLabel'
          - type: 'null'
        description:
          anyOf:
          - $ref: '#/components/schemas/MetricDescriptions'
          - type: 'null'
        weight:
          type: number
          title: Weight
          default: 0.5
      type: object
      title: MetricWeight
    Webhook:
      properties:
        url:
          type: string
          maxLength: 2083
          minLength: 1
          format: uri
          title: Url
        status:
          $ref: '#/components/schemas/WebhookStatus'
          default: untested
        notes:
          type: string
          maxLength: 255
          title: Notes
          default: ''
      type: object
      required:
      - url
      title: Webhook
    GenAIProjectSettings:
      properties:
        metric_weights_configuration:
          anyOf:
          - additionalProperties:
              $ref: '#/components/schemas/MetricWeight'
            type: object
          - type: 'null'
          title: Metric Weights Configuration
        alerts_configuration:
          anyOf:
          - $ref: '#/components/schemas/AlertsConfiguration'
          - type: 'null'
        rate_limit_configuration:
          anyOf:
          - $ref: '#/components/schemas/RateLimitConfiguration'
          - type: 'null'
      type: object
      title: GenAIProjectSettings
    ProjectSettingsDB:
      properties:
        metric_weights_configuration:
          anyOf:
          - additionalProperties:
              $ref: '#/components/schemas/MetricWeight'
            type: object
          - type: 'null'
          title: Metric Weights Configuration
        alerts_configuration:
          anyOf:
          - $ref: '#/components/schemas/AlertsConfiguration'
          - type: 'null'
        rate_limit_configuration:
          anyOf:
          - $ref: '#/components/schemas/RateLimitConfiguration'
          - type: 'null'
        project_id:
          type: string
          format: uuid4
          title: Project Id
        id:
          type: string
          format: uuid4
          title: Id
        created_at:
          type: string
          format: date-time
          title: Created At
        updated_at:
          type: string
          format: date-time
          title: Updated At
      type: object
      required:
      - project_id
      - id
      - created_at
      - updated_at
      title: ProjectSettingsDB
    GroupLabel:
      type: string
      enum:
      - Input Quality
      - Output Quality
      - Configuration
      - LLM Parameters
      - RAG Quality
      - RAG Parameters
      - Generic Parameters
      - Safety Metrics
      - Protect
      - System Metrics
      - Rating Summary
      - Annotation Agreement
      - Custom Metrics
      - Security
      - Dataset
      - Agent Quality
      - Text to SQL Metrics
      title: GroupLabel
      description: Group labels for prompt rows.
    ValidationError:
      properties:
        loc:
          items:
            anyOf:
            - type: string
            - type: integer
          type: array
          title: Location
        msg:
          type: string
          title: Message
        type:
          type: string
          title: Error Type
        input:
          title: Input
        ctx:
          type: object
          title: Context
      type: object
      required:
      - loc
      - msg
      - type
      title: ValidationError
    HTTPValidationError:
      properties:
        detail:
          items:
            $ref: '#/components/schemas/ValidationError'
          type: array
          title: Detail
      type: object
      title: HTTPValidationError
    RateLimitConfiguration:
      properties:
        spans_per_minute:
          type: integer
          maximum: 1000000000.0
          minimum: 0.0
          title: Spans Per Minute
          description: Spans per minute this project may ingest. 0 means unlimited (exempt from the global default).
        burst:
          type: integer
          maximum: 1000000000.0
          minimum: 0.0
          title: Burst
          description: Total burst capacity in spans, not an allowance on top of spans_per_minute. The most this project may ingest at one moment, and the cap on the spans one request may carry.
      type: object
      required:
      - spans_per_minute
      - burst
      title: RateLimitConfiguration
      description: 'Per-project ingestion rate limit: spans/minute plus a burst allowance.


        All-or-nothing: an override wholly replaces the global default, so both fields are

        required. ``spans_per_minute = 0`` means unlimited (exempt from the global default),

        not "reject everything".'
    GenAIProjectSettingsUpdate:
      properties:
        metric_weights_configuration:
          anyOf:
          - additionalProperties:
              $ref: '#/components/schemas/MetricWeightUpdate'
            type: object
          - type: 'null'
          title: Metric Weights Configuration
        alerts_configuration:
          anyOf:
          - $ref: '#/components/schemas/AlertsConfiguration'
          - type: 'null'
        rate_limit_configuration:
          anyOf:
          - $ref: '#/components/schemas/RateLimitConfiguration'
          - type: 'null'
      type: object
      title: GenAIProjectSettingsUpdate
    WebhookStatus:
      type: string
      enum:
      - active
      - untested
      - failed
      - paused
      title: WebhookStatus
  securitySchemes:
    APIKeyHeader:
      type: apiKey
      in: header
      name: Splunk-AO-API-Key
    ClassicAPIKeyHeader:
      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
x-provenance:
  method: harvested
  publisher: Galileo Technologies
  source: https://api.galileo.ai/openapi.json
  note: split by refine-openapis from the provider's own published document, verified by fetch (openapi/_original/*.fetch.json);
    stamped by stamp-openapi-provenance.py (roadmap#793)