Deployments SDK Reference

Deployments

Deployments are unavailable in workspaces created on or after November 10, 2026. Workspaces created before that date keep their Deployments.

Invoke a Deployment

Invoke a deployment with a given payload

from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY"),
) as orq:

    res = orq.deployments.invoke(key="<key>", stream=False, identity={
        "id": "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
        "display_name": "Jane Doe",
        "email": "jane.doe@example.com",
        "metadata": [
            {
                "department": "Engineering",
                "role": "Senior Developer",
            },
        ],
        "logo_url": "https://example.com/avatars/jane-doe.jpg",
        "tags": [
            "hr",
            "engineering",
        ],
    }, documents=[
        {
            "text": "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
            "metadata": {
                "file_name": "refund_policy.pdf",
                "file_type": "application/pdf",
                "page_number": 1,
            },
        },
        {
            "text": "Premium members receive free shipping on all orders over $50.",
            "metadata": {
                "file_name": "membership_benefits.md",
                "file_type": "text/markdown",
            },
        },
    ])

    assert res is not None

    # Handle response
    print(res)

import { Orq } from "@orq-ai/node";

const orq = new Orq({
  apiKey: process.env["ORQ_API_KEY"] ?? "",
});

async function run() {
  const result = await orq.deployments.invoke({
    key: "<key>",
    identity: {
      id: "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
      displayName: "Jane Doe",
      email: "jane.doe@example.com",
      metadata: [
        {
          "department": "Engineering",
          "role": "Senior Developer",
        },
      ],
      logoUrl: "https://example.com/avatars/jane-doe.jpg",
      tags: [
        "hr",
        "engineering",
      ],
    },
    documents: [
      {
        text: "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
        metadata: {
          fileName: "refund_policy.pdf",
          fileType: "application/pdf",
          pageNumber: 1,
        },
      },
      {
        text: "Premium members receive free shipping on all orders over $50.",
        metadata: {
          fileName: "membership_benefits.md",
          fileType: "text/markdown",
        },
      },
    ],
  });

  console.log(result);
}

run();

Show Parameters

{
    "key": str,  # required
    "stream": Optional[bool],
    "inputs": Dict[str, Any],  # optional
    "context": Dict[str, Any],  # optional
    "prefix_messages": List[Union[SystemMessage, DeveloperMessage, UserMessage, AssistantMessage, ToolMessage]],  # optional
    "messages": List[Union[MessagesSystemMessage, MessagesDeveloperMessage, MessagesUserMessage, MessagesAssistantMessage, MessagesToolMessage]],  # optional
    "identity": {  # optional
        "id": str,  # required
        "display_name": Optional[str],
        "email": Optional[str],
        "metadata": List[Dict[str, Any]],  # optional
        "logo_url": Optional[str],
        "tags": List[str],  # optional
    },
    "file_ids": List[str],  # optional
    "metadata": Dict[str, Any],  # optional
    "extra_params": Dict[str, Any],  # optional
    "documents": [{  # optional
        "text": str,  # required
        "metadata": {  # optional
            "file_name": Optional[str],
            "file_type": Optional[str],
            "page_number": Optional[float],
        },
    }],
    "invoke_options": {  # optional
        "include_retrievals": Optional[bool],
        "include_usage": Optional[bool],
        "mock_response": Optional[str],
    },
    "thread": {  # optional
        "id": str,  # required
        "tags": List[str],  # optional
    },
    "knowledge_filter": Union[Dict[str, KnowledgeFilter1], KnowledgeFilterAnd, KnowledgeFilterOr],  # optional
}

{
  key: string;  // required
  stream?: boolean;
  inputs?: Record<string, any>;
  context?: Record<string, any>;
  prefixMessages?: (SystemMessage | DeveloperMessage | UserMessage | AssistantMessage | ToolMessage)[];
  messages?: (MessagesSystemMessage | MessagesDeveloperMessage | MessagesUserMessage | MessagesAssistantMessage | MessagesToolMessage)[];
  identity?: {
    id: string;  // required
    displayName?: string;
    email?: string;
    metadata?: Record<string, any>[];
    logoUrl?: string;
    tags?: string[];
  };
  fileIds?: string[];
  metadata?: Record<string, any>;
  extraParams?: Record<string, any>;
  documents?: {
    text: string;  // required
    metadata?: {
      fileName?: string;
      fileType?: string;
      pageNumber?: number;
    };
  }[];
  invokeOptions?: {
    includeRetrievals?: boolean;
    includeUsage?: boolean;
    mockResponse?: string;
  };
  thread?: {
    id: string;  // required
    tags?: string[];
  };
  knowledgeFilter?: {
    // one of: KnowledgeFilterAnd, { [k: string]: KnowledgeFilter1 }, KnowledgeFilterOr
    and: Record<string, And>[];  // required (variant-specific)
    // one of: InvokeDeploymentRequest1Eq, InvokeDeploymentRequest1Ne, Gt, Gte, Lt, Lte, InvokeDeploymentRequest1In, InvokeDeploymentRequest1Nin
    eq: string | number | boolean;  // required (variant-specific)
    ne: string | number | boolean;  // required (variant-specific)
    gt: number;  // required (variant-specific)
    gte: number;  // required (variant-specific)
    lt: number;  // required (variant-specific)
    lte: number;  // required (variant-specific)
    in: (string | number | boolean)[];  // required (variant-specific)
    nin: (string | number | boolean)[];  // required (variant-specific)
    or: Record<string, Or>[];  // required (variant-specific)
  };
}

Show Response

{
    "id": str,
    "created": str,
    "object": Literal["chat", "completion", "image"],
    "model": str,
    "provider": Literal["openai", "groq", "cohere", "azure", "aws", "google", "google-ai", "huggingface", "togetherai", "perplexity", "anthropic", "leonardoai", "fal", "nvidia", "jina", "elevenlabs", "litellm", "cerebras", "openailike", "bytedance", "mistral", "deepseek", "moonshotai", "zai", "minimax", "xai", "alibaba", "tensorix", "scaleway", "hcompany", "inception", "particle", "munito", "inceptron", "wafer", "poolside", "tencent", "nebius", "fireworks", "baseten", "reson8", "meta", "greenpt", "liquid", "typesafe", "berget", "cloudflare", "slack", "orq"],
    "is_final": bool,
    "integration_id": Optional[str],
    "telemetry": {
        "trace_id": str,
        "span_id": str,
    },
    "finalized": str,  # optional
    "system_fingerprint": Optional[str],
    "retrievals": [{  # optional
        "document": str,
        "metadata": {
            "file_name": str,
            "page_number": Nullable[float],
            "file_type": str,
            "rerank_score": Optional[float],
            "search_score": float,
        },
    }],
    "provider_response": Optional[Any],
    "usage": {  # optional
        "total_tokens": Optional[float],
        "prompt_tokens": Optional[float],
        "completion_tokens": Optional[float],
        "prompt_tokens_details": {  # optional
            "cached_tokens": Optional[float],
        },
        "completion_tokens_details": {  # optional
            "reasoning_tokens": Optional[float],
        },
    },
    "choices": [{
        "index": float,
        "message": {
            # one of: Message1, Message2, Message3
            "type": Union[Union[Literal["tool_calls"], Literal["content"]], Literal["image"]],
            "role": Literal["system", "developer", "assistant", "user", "exception", "tool", "prompt", "correction", "expected_output"],
            "content": Union[Optional[str], Nullable[str]],
            "tool_calls": [{
                "id": Optional[str],
                "index": Optional[float],
                "type": Literal["function"],
                "function": {
                    "name": str,
                    "arguments": str,
                },
            }],
            "reasoning": Optional[str],
            "reasoning_signature": Optional[str],
            "redacted_reasoning": Optional[str],
            "url": str,
        },
        "finish_reason": Optional[str],
    }],
}

{
  id: string;
  created: Date;
  object: "chat" | "completion" | "image";
  model: string;
  provider: "openai" | "groq" | "cohere" | "azure" | "aws" | "google" | "google-ai" | "huggingface" | "togetherai" | "perplexity" | "anthropic" | "leonardoai" | "fal" | "nvidia" | "jina" | "elevenlabs" | "litellm" | "cerebras" | "openailike" | "bytedance" | "mistral" | "deepseek" | "moonshotai" | "zai" | "minimax" | "xai" | "alibaba" | "tensorix" | "scaleway" | "hcompany" | "inception" | "particle" | "munito" | "inceptron" | "wafer" | "poolside" | "tencent" | "nebius" | "fireworks" | "baseten" | "reson8" | "meta" | "greenpt" | "liquid" | "typesafe" | "berget" | "cloudflare" | "slack" | "orq";
  isFinal: boolean;
  integrationId?: string;
  telemetry: {
    traceId: string;
    spanId: string;
  };
  finalized?: Date;
  systemFingerprint?: string;
  retrievals?: {
    document: string;
    metadata: {
      fileName: string;
      pageNumber: number;
      fileType: string;
      rerankScore?: number;
      searchScore: number;
    };
  }[];
  providerResponse?: any;
  usage?: {
    totalTokens?: number;
    promptTokens?: number;
    completionTokens?: number;
    promptTokensDetails?: {
      cachedTokens?: number;
    };
    completionTokensDetails?: {
      reasoningTokens?: number;
    };
  };
  choices: {
    index: number;
    message: {
      // one of: Message1, Message2, Three
      type: "tool_calls" | "content" | "image";
      role: "system" | "developer" | "assistant" | "user" | "exception" | "tool" | "prompt" | "correction" | "expected_output";
      content: string;
      toolCalls: {
        id?: string;
        index?: number;
        type: "function";
        function: {
          name: string;
          arguments: string;
        };
      }[];
      reasoning?: string;
      reasoningSignature?: string;
      redactedReasoning?: string;
      url: string;
    };
    finishReason?: string;
  }[];
}

Show Variant types

KnowledgeFilter1

{
    # one of: DeploymentStream1Eq, DeploymentStream1Ne, DeploymentStream1Gt, DeploymentStream1Gte, DeploymentStream1Lt, DeploymentStream1Lte, DeploymentStream1In, DeploymentStream1Nin
    "eq": Union[str, float, bool],
    "ne": Union[str, float, bool],
    "gt": float,
    "gte": float,
    "lt": float,
    "lte": float,
    "in_": List[Union[str, float, bool]],
    "nin": List[Union[str, float, bool]],
}

Stream a Deployment

Stream deployment generation. Only supported for completions and chat completions.

from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY"),
) as orq:

    res = orq.deployments.stream(key="<key>", identity={
        "id": "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
        "display_name": "Jane Doe",
        "email": "jane.doe@example.com",
        "metadata": [
            {
                "department": "Engineering",
                "role": "Senior Developer",
            },
        ],
        "logo_url": "https://example.com/avatars/jane-doe.jpg",
        "tags": [
            "hr",
            "engineering",
        ],
    }, documents=[
        {
            "text": "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
            "metadata": {
                "file_name": "refund_policy.pdf",
                "file_type": "application/pdf",
                "page_number": 1,
            },
        },
        {
            "text": "Premium members receive free shipping on all orders over $50.",
            "metadata": {
                "file_name": "membership_benefits.md",
                "file_type": "text/markdown",
            },
        },
    ])

    with res as event_stream:
        for event in event_stream:
            # handle event
            print(event, flush=True)

import { Orq } from "@orq-ai/node";

const orq = new Orq({
  apiKey: process.env["ORQ_API_KEY"] ?? "",
});

async function run() {
  const result = await orq.deployments.stream({
    key: "<key>",
    identity: {
      id: "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
      displayName: "Jane Doe",
      email: "jane.doe@example.com",
      metadata: [
        {
          "department": "Engineering",
          "role": "Senior Developer",
        },
      ],
      logoUrl: "https://example.com/avatars/jane-doe.jpg",
      tags: [
        "hr",
        "engineering",
      ],
    },
    documents: [
      {
        text: "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
        metadata: {
          fileName: "refund_policy.pdf",
          fileType: "application/pdf",
          pageNumber: 1,
        },
      },
      {
        text: "Premium members receive free shipping on all orders over $50.",
        metadata: {
          fileName: "membership_benefits.md",
          fileType: "text/markdown",
        },
      },
    ],
  });

  for await (const event of result) {
    console.log(event);
  }
}

run();

Show Parameters

{
    "key": str,  # required
    "inputs": Dict[str, Any],  # optional
    "context": Dict[str, Any],  # optional
    "prefix_messages": List[Union[PrefixMessagesSystemMessage, PrefixMessagesDeveloperMessage, PrefixMessagesUserMessage, PrefixMessagesAssistantMessage, PrefixMessagesToolMessage]],  # optional
    "messages": List[Union[DeploymentStreamMessagesSystemMessage, DeploymentStreamMessagesDeveloperMessage, DeploymentStreamMessagesUserMessage, DeploymentStreamMessagesAssistantMessage, DeploymentStreamMessagesToolMessage]],  # optional
    "identity": {  # optional
        "id": str,  # required
        "display_name": Optional[str],
        "email": Optional[str],
        "metadata": List[Dict[str, Any]],  # optional
        "logo_url": Optional[str],
        "tags": List[str],  # optional
    },
    "file_ids": List[str],  # optional
    "metadata": Dict[str, Any],  # optional
    "extra_params": Dict[str, Any],  # optional
    "documents": [{  # optional
        "text": str,  # required
        "metadata": {  # optional
            "file_name": Optional[str],
            "file_type": Optional[str],
            "page_number": Optional[float],
        },
    }],
    "invoke_options": {  # optional
        "include_retrievals": Optional[bool],
        "include_usage": Optional[bool],
        "mock_response": Optional[str],
    },
    "thread": {  # optional
        "id": str,  # required
        "tags": List[str],  # optional
    },
    "knowledge_filter": Union[Dict[str, KnowledgeFilter1], DeploymentStreamKnowledgeFilterAnd, DeploymentStreamKnowledgeFilterOr],  # optional
}

{
  key: string;  // required
  inputs?: Record<string, any>;
  context?: Record<string, any>;
  prefixMessages?: (SystemMessage | DeveloperMessage | UserMessage | AssistantMessage | ToolMessage)[];
  messages?: (MessagesSystemMessage | MessagesDeveloperMessage | MessagesUserMessage | MessagesAssistantMessage | MessagesToolMessage)[];
  identity?: {
    id: string;  // required
    displayName?: string;
    email?: string;
    metadata?: Record<string, any>[];
    logoUrl?: string;
    tags?: string[];
  };
  fileIds?: string[];
  metadata?: Record<string, any>;
  extraParams?: Record<string, any>;
  documents?: {
    text: string;  // required
    metadata?: {
      fileName?: string;
      fileType?: string;
      pageNumber?: number;
    };
  }[];
  invokeOptions?: {
    includeRetrievals?: boolean;
    includeUsage?: boolean;
    mockResponse?: string;
  };
  thread?: {
    id: string;  // required
    tags?: string[];
  };
  knowledgeFilter?: {
    // one of: And, { [k: string]: KnowledgeFilter1 }, Or
    and: Record<string, KnowledgeFilterAnd>[];  // required (variant-specific)
    // one of: Eq, Ne, Gt, Gte, Lt, Lte, In, Nin
    eq: string | number | boolean;  // required (variant-specific)
    ne: string | number | boolean;  // required (variant-specific)
    gt: number;  // required (variant-specific)
    gte: number;  // required (variant-specific)
    lt: number;  // required (variant-specific)
    lte: number;  // required (variant-specific)
    in: (string | number | boolean)[];  // required (variant-specific)
    nin: (string | number | boolean)[];  // required (variant-specific)
    or: Record<string, KnowledgeFilterOr>[];  // required (variant-specific)
  };
}

List Deployments

Returns a list of your deployments. The deployments are returned sorted by creation date, with the most recent deployments appearing first.

from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY"),
) as orq:

    res = orq.deployments.list(limit=10)

    # Handle response
    print(res)

import { Orq } from "@orq-ai/node";

const orq = new Orq({
  apiKey: process.env["ORQ_API_KEY"] ?? "",
});

async function run() {
  const result = await orq.deployments.list({});

  console.log(result);
}

run();

Show Parameters

{
    "limit": Optional[int],
    "starting_after": Optional[str],
    "ending_before": Optional[str],
}

{
  limit?: number;
  startingAfter?: string;
  endingBefore?: string;
}

Show Response

{
    "object": Literal["list"],
    "data": [{
        "id": str,
        "created": str,
        "updated": str,
        "key": str,
        "description": str,
        "prompt_config": {
            "tools": [{
                "display_name": Optional[str],
                "type": Literal["function"],
                "function": {
                    "name": str,
                    "description": Optional[str],
                    "strict": Optional[bool],
                    "parameters": {
                        "type": Literal["object"],
                        "properties": Dict[str, Any],
                        "required": List[str],  # optional
                        "additional_properties": Optional[Literal[False]],
                    },
                },
                "id": Optional[float],
            }],
            "model": str,
            "model_type": Literal["chat", "completion", "embedding", "image", "tts", "stt", "rerank", "ocr", "moderation", "classify", "vision"],
            "model_parameters": {
                "temperature": Optional[float],
                "max_tokens": Optional[float],
                "top_k": Optional[float],
                "top_p": Optional[float],
                "frequency_penalty": Optional[float],
                "presence_penalty": Optional[float],
                "num_images": Optional[float],
                "seed": Optional[float],
                "format_": Optional[Literal["url", "b64_json", "text", "json_object"]],
                "dimensions": Optional[str],
                "quality": Optional[str],
                "style": Optional[str],
                "response_format": {  # optional
                    # one of: DeploymentsResponseFormat1, DeploymentsResponseFormat2, DeploymentsResponseFormat3, DeploymentsResponseFormat4, DeploymentsResponseFormat5, DeploymentsResponseFormat6
                    "type": Union[Union[Literal["json_schema"], Literal["json_object"]], Literal["text"]],
                    "display_name": Optional[str],
                    "json_schema": {
                        "name": str,
                        "description": Optional[str],
                        "strict": Optional[bool],
                        "schema_": Dict[str, Any],
                    },
                },
                "cache_control": {  # optional
                    "type": Literal["ephemeral"],
                    "ttl": Optional[Literal["5m", "1h"]],
                },
                "photo_real_version": Optional[Literal["v1", "v2"]],
                "encoding_format": Optional[Literal["float", "base64"]],
                "reasoning_effort": Optional[Literal["none", "disable", "minimal", "low", "medium", "high", "xhigh", "max"]],
                "budget_tokens": Optional[float],
                "verbosity": Optional[Literal["low", "medium", "high"]],
                "thinking_level": Optional[Literal["minimal", "low", "medium", "high"]],
            },
            "provider": Literal["openai", "groq", "cohere", "azure", "aws", "google", "google-ai", "huggingface", "togetherai", "perplexity", "anthropic", "leonardoai", "fal", "nvidia", "jina", "elevenlabs", "litellm", "cerebras", "openailike", "bytedance", "mistral", "deepseek", "moonshotai", "zai", "minimax", "xai", "alibaba", "tensorix", "scaleway", "hcompany", "inception", "particle", "munito", "inceptron", "wafer", "poolside", "tencent", "nebius", "fireworks", "baseten", "reson8", "meta", "greenpt", "liquid", "typesafe", "berget", "cloudflare", "slack", "orq"],
            "messages": [{
                "role": Literal["system", "developer", "assistant", "user", "exception", "tool", "prompt", "correction", "expected_output"],
                "content": Union[str, List[DeploymentsContent2]],
                "tool_calls": [{  # optional
                    "id": Optional[str],
                    "index": Optional[float],
                    "type": Literal["function"],
                    "function": {
                        "name": str,
                        "arguments": str,
                    },
                }],
                "tool_call_id": Optional[str],
            }],
        },
        "version": str,
    }],
    "has_more": bool,
}

{
  object: "list";
  data: {
    id: string;
    created: string;
    updated: string;
    key: string;
    description: string;
    promptConfig: {
      tools: {
        displayName?: string;
        type: "function";
        function: {
          name: string;
          description?: string;
          strict?: boolean;
          parameters: {
            type: "object";
            properties: Record<string, any>;
            required?: string[];
          };
        };
        id?: number;
      }[];
      model: string;
      modelType: "chat" | "completion" | "embedding" | "image" | "tts" | "stt" | "rerank" | "ocr" | "moderation" | "classify" | "vision";
      modelParameters: {
        temperature?: number;
        maxTokens?: number;
        topK?: number;
        topP?: number;
        frequencyPenalty?: number;
        presencePenalty?: number;
        numImages?: number;
        seed?: number;
        format?: "url" | "b64_json" | "text" | "json_object";
        dimensions?: string;
        quality?: string;
        style?: string;
        responseFormat?: {
          // one of: DeploymentsResponseFormat1, DeploymentsResponseFormat2, DeploymentsResponseFormat3, DeploymentsResponseFormat4, DeploymentsResponseFormat5, DeploymentsResponseFormat6
          type: "json_schema" | "json_object" | "text";
          displayName?: string;
          jsonSchema: {
            name: string;
            description?: string;
            strict?: boolean;
            schema: Record<string, any>;
          };
        };
        cacheControl?: {
          type: "ephemeral";
          ttl?: "5m" | "1h";
        };
        photoRealVersion?: "v1" | "v2";
        encodingFormat?: "float" | "base64";
        reasoningEffort?: "none" | "disable" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
        budgetTokens?: number;
        verbosity?: "low" | "medium" | "high";
        thinkingLevel?: "minimal" | "low" | "medium" | "high";
      };
      provider: "openai" | "groq" | "cohere" | "azure" | "aws" | "google" | "google-ai" | "huggingface" | "togetherai" | "perplexity" | "anthropic" | "leonardoai" | "fal" | "nvidia" | "jina" | "elevenlabs" | "litellm" | "cerebras" | "openailike" | "bytedance" | "mistral" | "deepseek" | "moonshotai" | "zai" | "minimax" | "xai" | "alibaba" | "tensorix" | "scaleway" | "hcompany" | "inception" | "particle" | "munito" | "inceptron" | "wafer" | "poolside" | "tencent" | "nebius" | "fireworks" | "baseten" | "reson8" | "meta" | "greenpt" | "liquid" | "typesafe" | "berget" | "cloudflare" | "slack" | "orq";
      messages: {
        role: "system" | "developer" | "assistant" | "user" | "exception" | "tool" | "prompt" | "correction" | "expected_output";
        content: string | DeploymentsContent2[];
        toolCalls?: {
          id?: string;
          index?: number;
          type: "function";
          function: {
            name: string;
            arguments: string;
          };
        }[];
        toolCallId?: string;
      }[];
    };
    version: string;
  }[];
  hasMore: boolean;
}

Show Variant types

DeploymentsContent2

{
    # one of: Deployments21, Deployments22, Deployments23
    "type": Union[Union[Literal["text"], Literal["image_url"]], Literal["file"]],
    "text": str,
    "image_url": {
        "id": Optional[str],
        "url": str,
        "detail": Optional[str],
    },
    "file": {
        "file_data": Optional[str],
        "uri": Optional[str],
        "mime_type": Optional[str],
        "filename": Optional[str],
    },
}

{
  // one of: Deployments21, Deployments22, Deployments23
  type: "text" | "image_url" | "file";
  text: string;
  imageUrl: {
    id?: string;
    url: string;
    detail?: string;
  };
  file: {
    fileData?: string;
    uri?: string;
    mimeType?: string;
    filename?: string;
  };
}

List Versions

List saved versions across deployment variants, including drafts, newest first. Resolve the deployment by key or ID. Optionally filter by variant_id. Use the version _id with starting_after or ending_before to paginate.

from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY"),
) as orq:

    res = orq.deployments.list_versions(key_or_id="<id>", limit=10)

    # Handle response
    print(res)

import { Orq } from "@orq-ai/node";

const orq = new Orq({
  apiKey: process.env["ORQ_API_KEY"] ?? "",
});

async function run() {
  const result = await orq.deployments.listVersions({
    keyOrID: "<id>",
  });

  console.log(result);
}

run();

Show Parameters

{
    "key_or_id": str,  # required
    "limit": Optional[int],
    "starting_after": Optional[str],
    "ending_before": Optional[str],
    "variant_id": Optional[str],
}

{
  keyOrID: string;  // required
  limit?: number;
  startingAfter?: string;
  endingBefore?: string;
  variantId?: string;
}

Show Response

{
    "object": Literal["list"],
    "data": [{
        "id": str,
        "deployment_id": str,
        "variant_id": str,
        "prompt_config": {
            "model": str,
            "model_db_id": str,
            "model_type": Literal["chat", "completion", "embedding", "image", "tts", "stt", "rerank", "ocr", "moderation", "classify", "vision"],
            "model_parameters": {
                "temperature": Optional[float],
                "max_tokens": Optional[float],
                "top_k": Optional[float],
                "top_p": Optional[float],
                "frequency_penalty": Optional[float],
                "presence_penalty": Optional[float],
                "num_images": Optional[float],
                "seed": Optional[float],
                "format_": Optional[Literal["url", "b64_json", "text", "json_object"]],
                "dimensions": Optional[str],
                "quality": Optional[str],
                "style": Optional[str],
                "response_format": {  # optional
                    # one of: ListDeploymentVersionsResponseFormat1, ListDeploymentVersionsResponseFormat2, ListDeploymentVersionsResponseFormat3, ListDeploymentVersionsResponseFormat4, ListDeploymentVersionsResponseFormatDeployments5, ListDeploymentVersionsResponseFormatDeployments6
                    "type": Union[Union[Literal["json_schema"], Literal["json_object"]], Literal["text"]],
                    "display_name": Optional[str],
                    "json_schema": {
                        "name": str,
                        "description": Optional[str],
                        "strict": Optional[bool],
                        "schema_": Dict[str, Any],
                    },
                },
                "cache_control": {  # optional
                    "type": Literal["ephemeral"],
                    "ttl": Optional[Literal["5m", "1h"]],
                },
                "photo_real_version": Optional[Literal["v1", "v2"]],
                "encoding_format": Optional[Literal["float", "base64"]],
                "reasoning_effort": Optional[Literal["none", "disable", "minimal", "low", "medium", "high", "xhigh", "max"]],
                "budget_tokens": Optional[float],
                "verbosity": Optional[Literal["low", "medium", "high"]],
                "thinking_level": Optional[Literal["minimal", "low", "medium", "high"]],
            },
            "provider": Literal["openai", "groq", "cohere", "azure", "aws", "google", "google-ai", "huggingface", "togetherai", "perplexity", "anthropic", "leonardoai", "fal", "nvidia", "jina", "elevenlabs", "litellm", "cerebras", "openailike", "bytedance", "mistral", "deepseek", "moonshotai", "zai", "minimax", "xai", "alibaba", "tensorix", "scaleway", "hcompany", "inception", "particle", "munito", "inceptron", "wafer", "poolside", "tencent", "nebius", "fireworks", "baseten", "reson8", "meta", "greenpt", "liquid", "typesafe", "berget", "cloudflare", "slack", "orq"],
            "messages": [{
                "role": Literal["system", "developer", "assistant", "user", "exception", "tool", "prompt", "correction", "expected_output"],
                "content": Union[str, List[ListDeploymentVersionsContent2]],
                "tool_calls": [{  # optional
                    "id": Optional[str],
                    "index": Optional[float],
                    "type": Literal["function"],
                    "function": {
                        "name": str,
                        "arguments": str,
                    },
                }],
                "tool_call_id": Optional[str],
                "id": Optional[str],
            }],
            "integration_id": Optional[str],
            "version": Optional[str],
        },
        "fallbacks": [{
            "model": str,
            "model_db_id": str,
            "model_type": Literal["chat", "completion", "embedding", "image", "tts", "stt", "rerank", "ocr", "moderation", "classify", "vision"],
            "model_parameters": {
                "temperature": Optional[float],
                "max_tokens": Optional[float],
                "top_k": Optional[float],
                "top_p": Optional[float],
                "frequency_penalty": Optional[float],
                "presence_penalty": Optional[float],
                "num_images": Optional[float],
                "seed": Optional[float],
                "format_": Optional[Literal["url", "b64_json", "text", "json_object"]],
                "dimensions": Optional[str],
                "quality": Optional[str],
                "style": Optional[str],
                "response_format": {  # optional
                    # one of: ListDeploymentVersionsResponseFormatDeployments1, ListDeploymentVersionsResponseFormatDeployments2, ListDeploymentVersionsResponseFormatDeployments3, ListDeploymentVersionsResponseFormatDeployments4, ListDeploymentVersionsResponseFormat5, ListDeploymentVersionsResponseFormat6
                    "type": Union[Union[Literal["json_schema"], Literal["json_object"]], Literal["text"]],
                    "display_name": Optional[str],
                    "json_schema": {
                        "name": str,
                        "description": Optional[str],
                        "strict": Optional[bool],
                        "schema_": Dict[str, Any],
                    },
                },
                "cache_control": {  # optional
                    "type": Literal["ephemeral"],
                    "ttl": Optional[Literal["5m", "1h"]],
                },
                "photo_real_version": Optional[Literal["v1", "v2"]],
                "encoding_format": Optional[Literal["float", "base64"]],
                "reasoning_effort": Optional[Literal["none", "disable", "minimal", "low", "medium", "high", "xhigh", "max"]],
                "budget_tokens": Optional[float],
                "verbosity": Optional[Literal["low", "medium", "high"]],
                "thinking_level": Optional[Literal["minimal", "low", "medium", "high"]],
            },
            "provider": Literal["openai", "groq", "cohere", "azure", "aws", "google", "google-ai", "huggingface", "togetherai", "perplexity", "anthropic", "leonardoai", "fal", "nvidia", "jina", "elevenlabs", "litellm", "cerebras", "openailike", "bytedance", "mistral", "deepseek", "moonshotai", "zai", "minimax", "xai", "alibaba", "tensorix", "scaleway", "hcompany", "inception", "particle", "munito", "inceptron", "wafer", "poolside", "tencent", "nebius", "fireworks", "baseten", "reson8", "meta", "greenpt", "liquid", "typesafe", "berget", "cloudflare", "slack", "orq"],
            "integration_id": Optional[str],
            "version": Optional[str],
        }],
        "tools": [{
            "display_name": Optional[str],
            "type": Literal["function"],
            "function": {
                "name": str,
                "description": Optional[str],
                "strict": Optional[bool],
                "parameters": {
                    "type": Literal["object"],
                    "properties": Dict[str, Any],
                    "required": List[str],  # optional
                    "additional_properties": Optional[Literal[False]],
                },
            },
            "id": Optional[float],
        }],
        "variables": [{
            "key": str,
            "value": Optional[Any],
            "is_pii": Optional[bool],
            "description": Optional[str],
        }],
        "notes": Optional[str],
        "timestamp": str,
        "retry_count": Optional[float],
        "version": str,
        "description": str,
        "status": Literal["live", "draft", "pending", "published"],
        "user_id": Nullable[str],
        "knowledge_bases": [{  # optional
            "id": Optional[str],
            "knowledge_id": str,
            "configuration": {
                # one of: KnowledgeBaseLastUserMessage, KnowledgeBaseStaticQuery
                "type": Union[Literal["last_user_message"], Literal["query"]],
                "query": str,
            },
        }],
        "settings": {  # optional
            "guardrails": [{  # optional
                "id": str,
                "sample_rate": Optional[float],
                "execute_on": Literal["input", "output", "both"],
            }],
            "evaluators": [{  # optional
                "id": str,
                "sample_rate": Optional[float],
                "execute_on": Literal["input", "output", "both"],
            }],
            "cache": {  # optional
                # one of: Cache1, Cache2
                "enabled": Union[Literal[False], Literal[True]],
                "type": Literal["exact", "semantic"],
                "ttl": float,
            },
            "guardrail_behaviour": Optional[Literal["none", "retry", "fallback"]],
            "engine": Optional[Literal["text", "jinja", "mustache"]],
            "input_masking": Optional[bool],
            "system_masking": Optional[bool],
            "output_masking": Optional[bool],
        },
    }],
    "has_more": bool,
}

{
  object: "list";
  data: {
    id: string;
    deploymentId: string;
    variantId: string;
    promptConfig: {
      model: string;
      modelDbId: string;
      modelType: "chat" | "completion" | "embedding" | "image" | "tts" | "stt" | "rerank" | "ocr" | "moderation" | "classify" | "vision";
      modelParameters: {
        temperature?: number;
        maxTokens?: number;
        topK?: number;
        topP?: number;
        frequencyPenalty?: number;
        presencePenalty?: number;
        numImages?: number;
        seed?: number;
        format?: "url" | "b64_json" | "text" | "json_object";
        dimensions?: string;
        quality?: string;
        style?: string;
        responseFormat?: {
          // one of: ListDeploymentVersionsResponseFormat1, ListDeploymentVersionsResponseFormat2, ListDeploymentVersionsResponseFormat3, ListDeploymentVersionsResponseFormat4, ListDeploymentVersionsResponseFormatDeployments5, ListDeploymentVersionsResponseFormatDeployments6
          type: "json_schema" | "json_object" | "text";
          displayName?: string;
          jsonSchema: {
            name: string;
            description?: string;
            strict?: boolean;
            schema: Record<string, any>;
          };
        };
        cacheControl?: {
          type: "ephemeral";
          ttl?: "5m" | "1h";
        };
        photoRealVersion?: "v1" | "v2";
        encodingFormat?: "float" | "base64";
        reasoningEffort?: "none" | "disable" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
        budgetTokens?: number;
        verbosity?: "low" | "medium" | "high";
        thinkingLevel?: "minimal" | "low" | "medium" | "high";
      };
      provider: "openai" | "groq" | "cohere" | "azure" | "aws" | "google" | "google-ai" | "huggingface" | "togetherai" | "perplexity" | "anthropic" | "leonardoai" | "fal" | "nvidia" | "jina" | "elevenlabs" | "litellm" | "cerebras" | "openailike" | "bytedance" | "mistral" | "deepseek" | "moonshotai" | "zai" | "minimax" | "xai" | "alibaba" | "tensorix" | "scaleway" | "hcompany" | "inception" | "particle" | "munito" | "inceptron" | "wafer" | "poolside" | "tencent" | "nebius" | "fireworks" | "baseten" | "reson8" | "meta" | "greenpt" | "liquid" | "typesafe" | "berget" | "cloudflare" | "slack" | "orq";
      messages: {
        role: "system" | "developer" | "assistant" | "user" | "exception" | "tool" | "prompt" | "correction" | "expected_output";
        content: string | ListDeploymentVersionsContent2[];
        toolCalls?: {
          id?: string;
          index?: number;
          type: "function";
          function: {
            name: string;
            arguments: string;
          };
        }[];
        toolCallId?: string;
        id?: string;
      }[];
      integrationId?: string;
      version?: string;
    };
    fallbacks: {
      model: string;
      modelDbId: string;
      modelType: "chat" | "completion" | "embedding" | "image" | "tts" | "stt" | "rerank" | "ocr" | "moderation" | "classify" | "vision";
      modelParameters: {
        temperature?: number;
        maxTokens?: number;
        topK?: number;
        topP?: number;
        frequencyPenalty?: number;
        presencePenalty?: number;
        numImages?: number;
        seed?: number;
        format?: "url" | "b64_json" | "text" | "json_object";
        dimensions?: string;
        quality?: string;
        style?: string;
        responseFormat?: {
          // one of: ListDeploymentVersionsResponseFormatDeployments1, ListDeploymentVersionsResponseFormatDeployments2, ListDeploymentVersionsResponseFormatDeployments3, ListDeploymentVersionsResponseFormatDeployments4, ListDeploymentVersionsResponseFormat5, ListDeploymentVersionsResponseFormat6
          type: "json_schema" | "json_object" | "text";
          displayName?: string;
          jsonSchema: {
            name: string;
            description?: string;
            strict?: boolean;
            schema: Record<string, any>;
          };
        };
        cacheControl?: {
          type: "ephemeral";
          ttl?: "5m" | "1h";
        };
        photoRealVersion?: "v1" | "v2";
        encodingFormat?: "float" | "base64";
        reasoningEffort?: "none" | "disable" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
        budgetTokens?: number;
        verbosity?: "low" | "medium" | "high";
        thinkingLevel?: "minimal" | "low" | "medium" | "high";
      };
      provider: "openai" | "groq" | "cohere" | "azure" | "aws" | "google" | "google-ai" | "huggingface" | "togetherai" | "perplexity" | "anthropic" | "leonardoai" | "fal" | "nvidia" | "jina" | "elevenlabs" | "litellm" | "cerebras" | "openailike" | "bytedance" | "mistral" | "deepseek" | "moonshotai" | "zai" | "minimax" | "xai" | "alibaba" | "tensorix" | "scaleway" | "hcompany" | "inception" | "particle" | "munito" | "inceptron" | "wafer" | "poolside" | "tencent" | "nebius" | "fireworks" | "baseten" | "reson8" | "meta" | "greenpt" | "liquid" | "typesafe" | "berget" | "cloudflare" | "slack" | "orq";
      integrationId?: string;
      version?: string;
    }[];
    tools: {
      displayName?: string;
      type: "function";
      function: {
        name: string;
        description?: string;
        strict?: boolean;
        parameters: {
          type: "object";
          properties: Record<string, any>;
          required?: string[];
        };
      };
      id?: number;
    }[];
    variables: {
      key: string;
      value?: any;
      isPii?: boolean;
      description?: string;
    }[];
    notes?: string;
    timestamp: Date;
    retryCount?: number;
    version: string;
    description: string;
    status: "live" | "draft" | "pending" | "published";
    userId: string;
    knowledgeBases?: {
      id?: string;
      knowledgeId: string;
      configuration: {
        // one of: KnowledgeBaseLastUserMessage, KnowledgeBaseStaticQuery
        type: "last_user_message" | "query";
        query: string;
      };
    }[];
    settings?: {
      guardrails?: {
        id: string;
        sampleRate?: number;
        executeOn: "input" | "output" | "both";
      }[];
      evaluators?: {
        id: string;
        sampleRate?: number;
        executeOn: "input" | "output" | "both";
      }[];
      cache?: {
        // one of: Cache1, Cache2
        enabled: false | true;
        type: "exact" | "semantic";
        ttl: number;
      };
      guardrailBehaviour?: "none" | "retry" | "fallback";
      engine?: "text" | "jinja" | "mustache";
      inputMasking?: boolean;
      systemMasking?: boolean;
      outputMasking?: boolean;
    };
  }[];
  hasMore: boolean;
}

Show Variant types

ListDeploymentVersionsContent2

{
    # one of: ListDeploymentVersions21, ListDeploymentVersions22, ListDeploymentVersions23
    "type": Union[Union[Literal["text"], Literal["image_url"]], Literal["file"]],
    "text": str,
    "image_url": {
        "id": Optional[str],
        "url": str,
        "detail": Optional[str],
    },
    "file": {
        "file_data": Optional[str],
        "uri": Optional[str],
        "mime_type": Optional[str],
        "filename": Optional[str],
    },
}

{
  // one of: ListDeploymentVersions21, ListDeploymentVersions22, ListDeploymentVersions23
  type: "text" | "image_url" | "file";
  text: string;
  imageUrl: {
    id?: string;
    url: string;
    detail?: string;
  };
  file: {
    fileData?: string;
    uri?: string;
    mimeType?: string;
    filename?: string;
  };
}

Get Config

Retrieve the deployment configuration

from orq_ai_sdk import Orq
import os

with Orq(
    api_key=os.getenv("ORQ_API_KEY"),
) as orq:

    res = orq.deployments.get_config(key="<key>", identity={
        "id": "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
        "display_name": "Jane Doe",
        "email": "jane.doe@example.com",
        "metadata": [
            {
                "department": "Engineering",
                "role": "Senior Developer",
            },
        ],
        "logo_url": "https://example.com/avatars/jane-doe.jpg",
        "tags": [
            "hr",
            "engineering",
        ],
    }, documents=[
        {
            "text": "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
            "metadata": {
                "file_name": "refund_policy.pdf",
                "file_type": "application/pdf",
                "page_number": 1,
            },
        },
        {
            "text": "Premium members receive free shipping on all orders over $50.",
            "metadata": {
                "file_name": "membership_benefits.md",
                "file_type": "text/markdown",
            },
        },
    ])

    assert res is not None

    # Handle response
    print(res)

import { Orq } from "@orq-ai/node";

const orq = new Orq({
  apiKey: process.env["ORQ_API_KEY"] ?? "",
});

async function run() {
  const result = await orq.deployments.getConfig({
    key: "<key>",
    identity: {
      id: "contact_01ARZ3NDEKTSV4RRFFQ69G5FAV",
      displayName: "Jane Doe",
      email: "jane.doe@example.com",
      metadata: [
        {
          "department": "Engineering",
          "role": "Senior Developer",
        },
      ],
      logoUrl: "https://example.com/avatars/jane-doe.jpg",
      tags: [
        "hr",
        "engineering",
      ],
    },
    documents: [
      {
        text: "The refund policy allows customers to return items within 30 days of purchase for a full refund.",
        metadata: {
          fileName: "refund_policy.pdf",
          fileType: "application/pdf",
          pageNumber: 1,
        },
      },
      {
        text: "Premium members receive free shipping on all orders over $50.",
        metadata: {
          fileName: "membership_benefits.md",
          fileType: "text/markdown",
        },
      },
    ],
  });

  console.log(result);
}

run();

Show Parameters

{
    "key": str,  # required
    "inputs": Dict[str, Any],  # optional
    "context": Dict[str, Any],  # optional
    "prefix_messages": List[Union[DeploymentGetConfigPrefixMessagesSystemMessage, DeploymentGetConfigPrefixMessagesDeveloperMessage, DeploymentGetConfigPrefixMessagesUserMessage, DeploymentGetConfigPrefixMessagesAssistantMessage, DeploymentGetConfigPrefixMessagesToolMessage]],  # optional
    "messages": List[Union[DeploymentGetConfigMessagesSystemMessage, DeploymentGetConfigMessagesDeveloperMessage, DeploymentGetConfigMessagesUserMessage, DeploymentGetConfigMessagesAssistantMessage, DeploymentGetConfigMessagesToolMessage]],  # optional
    "identity": {  # optional
        "id": str,  # required
        "display_name": Optional[str],
        "email": Optional[str],
        "metadata": List[Dict[str, Any]],  # optional
        "logo_url": Optional[str],
        "tags": List[str],  # optional
    },
    "file_ids": List[str],  # optional
    "metadata": Dict[str, Any],  # optional
    "extra_params": Dict[str, Any],  # optional
    "documents": [{  # optional
        "text": str,  # required
        "metadata": {  # optional
            "file_name": Optional[str],
            "file_type": Optional[str],
            "page_number": Optional[float],
        },
    }],
    "invoke_options": {  # optional
        "include_retrievals": Optional[bool],
        "include_usage": Optional[bool],
        "mock_response": Optional[str],
    },
    "thread": {  # optional
        "id": str,  # required
        "tags": List[str],  # optional
    },
    "knowledge_filter": Union[Dict[str, DeploymentGetConfigKnowledgeFilter1], DeploymentGetConfigKnowledgeFilterAnd, DeploymentGetConfigKnowledgeFilterOr],  # optional
}

{
  key: string;  // required
  inputs?: Record<string, any>;
  context?: Record<string, any>;
  prefixMessages?: (PrefixMessagesSystemMessage | PrefixMessagesDeveloperMessage | PrefixMessagesUserMessage | PrefixMessagesAssistantMessage | PrefixMessagesToolMessage)[];
  messages?: (DeploymentGetConfigMessagesSystemMessage | DeploymentGetConfigMessagesDeveloperMessage | DeploymentGetConfigMessagesUserMessage | DeploymentGetConfigMessagesAssistantMessage | DeploymentGetConfigMessagesToolMessage)[];
  identity?: {
    id: string;  // required
    displayName?: string;
    email?: string;
    metadata?: Record<string, any>[];
    logoUrl?: string;
    tags?: string[];
  };
  fileIds?: string[];
  metadata?: Record<string, any>;
  extraParams?: Record<string, any>;
  documents?: {
    text: string;  // required
    metadata?: {
      fileName?: string;
      fileType?: string;
      pageNumber?: number;
    };
  }[];
  invokeOptions?: {
    includeRetrievals?: boolean;
    includeUsage?: boolean;
    mockResponse?: string;
  };
  thread?: {
    id: string;  // required
    tags?: string[];
  };
  knowledgeFilter?: {
    // one of: DeploymentGetConfigKnowledgeFilterAnd, { [k: string]: KnowledgeFilter1 }, DeploymentGetConfigKnowledgeFilterOr
    and: Record<string, DeploymentGetConfigKnowledgeFilterDeploymentsAnd>[];  // required (variant-specific)
    // one of: DeploymentGetConfig1Eq, DeploymentGetConfig1Ne, OneGt, OneGte, OneLt, OneLte, DeploymentGetConfig1In, DeploymentGetConfig1Nin
    eq: string | number | boolean;  // required (variant-specific)
    ne: string | number | boolean;  // required (variant-specific)
    gt: number;  // required (variant-specific)
    gte: number;  // required (variant-specific)
    lt: number;  // required (variant-specific)
    lte: number;  // required (variant-specific)
    in: (string | number | boolean)[];  // required (variant-specific)
    nin: (string | number | boolean)[];  // required (variant-specific)
    or: Record<string, DeploymentGetConfigKnowledgeFilterDeploymentsOr>[];  // required (variant-specific)
  };
}

Show Response

{
    "id": str,
    "provider": str,
    "model": str,
    "type": Optional[Literal["chat", "completion", "embedding", "image", "tts", "stt", "rerank", "ocr", "moderation", "classify", "vision"]],
    "version": str,
    "messages": [{
        "role": Literal["system", "developer", "assistant", "user", "exception", "tool", "prompt", "correction", "expected_output"],
        "content": Union[str, List[DeploymentGetConfigContentDeploymentsResponse2]],
        "tool_calls": [{  # optional
            "id": Optional[str],
            "index": Optional[float],
            "type": Literal["function"],
            "function": {
                "name": str,
                "arguments": str,
            },
        }],
        "tool_call_id": Optional[str],
    }],
    "parameters": {
        "temperature": Optional[float],
        "max_tokens": Optional[float],
        "top_k": Optional[float],
        "top_p": Optional[float],
        "frequency_penalty": Optional[float],
        "presence_penalty": Optional[float],
        "num_images": Optional[float],
        "seed": Optional[float],
        "format_": Optional[Literal["url", "b64_json", "text", "json_object"]],
        "dimensions": Optional[str],
        "quality": Optional[str],
        "style": Optional[str],
        "response_format": {  # optional
            # one of: ResponseFormat1, ResponseFormat2, ResponseFormat3, ResponseFormat4, ResponseFormat5, ResponseFormat6
            "type": Union[Union[Literal["json_schema"], Literal["json_object"]], Literal["text"]],
            "display_name": Optional[str],
            "json_schema": {
                "name": str,
                "description": Optional[str],
                "strict": Optional[bool],
                "schema_": Dict[str, Any],
            },
        },
        "cache_control": {  # optional
            "type": Literal["ephemeral"],
            "ttl": Optional[Literal["5m", "1h"]],
        },
        "photo_real_version": Optional[Literal["v1", "v2"]],
        "encoding_format": Optional[Literal["float", "base64"]],
        "reasoning_effort": Optional[Literal["none", "disable", "minimal", "low", "medium", "high", "xhigh", "max"]],
        "budget_tokens": Optional[float],
        "verbosity": Optional[Literal["low", "medium", "high"]],
        "thinking_level": Optional[Literal["minimal", "low", "medium", "high"]],
    },
    "tools": [{  # optional
        "type": Literal["function"],
        "function": {
            "name": str,
            "description": Optional[str],
            "parameters": Dict[str, Any],  # optional
        },
    }],
}

{
  id: string;
  provider: string;
  model: string;
  type?: "chat" | "completion" | "embedding" | "image" | "tts" | "stt" | "rerank" | "ocr" | "moderation" | "classify" | "vision";
  version: string;
  messages: {
    role: "system" | "developer" | "assistant" | "user" | "exception" | "tool" | "prompt" | "correction" | "expected_output";
    content: string | DeploymentGetConfigContentDeploymentsResponse2[];
    toolCalls?: {
      id?: string;
      index?: number;
      type: "function";
      function: {
        name: string;
        arguments: string;
      };
    }[];
    toolCallId?: string;
  }[];
  parameters: {
    temperature?: number;
    maxTokens?: number;
    topK?: number;
    topP?: number;
    frequencyPenalty?: number;
    presencePenalty?: number;
    numImages?: number;
    seed?: number;
    format?: "url" | "b64_json" | "text" | "json_object";
    dimensions?: string;
    quality?: string;
    style?: string;
    responseFormat?: {
      // one of: ResponseFormat1, ResponseFormat2, ResponseFormat3, ResponseFormat4, Five, Six
      type: "json_schema" | "json_object" | "text";
      displayName?: string;
      jsonSchema: {
        name: string;
        description?: string;
        strict?: boolean;
        schema: Record<string, any>;
      };
    };
    cacheControl?: {
      type: "ephemeral";
      ttl?: "5m" | "1h";
    };
    photoRealVersion?: "v1" | "v2";
    encodingFormat?: "float" | "base64";
    reasoningEffort?: "none" | "disable" | "minimal" | "low" | "medium" | "high" | "xhigh" | "max";
    budgetTokens?: number;
    verbosity?: "low" | "medium" | "high";
    thinkingLevel?: "minimal" | "low" | "medium" | "high";
  };
  tools?: {
    type: "function";
    function: {
      name: string;
      description?: string;
      parameters?: Record<string, any>;
    };
  }[];
}

Show Variant types

DeploymentGetConfigKnowledgeFilter1

{
    # one of: DeploymentGetConfig1Eq, DeploymentGetConfig1Ne, DeploymentGetConfig1Gt, DeploymentGetConfig1Gte, DeploymentGetConfig1Lt, DeploymentGetConfig1Lte, DeploymentGetConfig1In, DeploymentGetConfig1Nin
    "eq": Union[str, float, bool],
    "ne": Union[str, float, bool],
    "gt": float,
    "gte": float,
    "lt": float,
    "lte": float,
    "in_": List[Union[str, float, bool]],
    "nin": List[Union[str, float, bool]],
}

DeploymentGetConfigContentDeploymentsResponse2

{
    # one of: Two1, Two2, Two3
    "type": Union[Union[Literal["text"], Literal["image_url"]], Literal["file"]],
    "text": str,
    "image_url": {
        "id": Optional[str],
        "url": str,
        "detail": Optional[str],
    },
    "file": {
        "file_data": Optional[str],
        "uri": Optional[str],
        "mime_type": Optional[str],
        "filename": Optional[str],
    },
}

{
  // one of: Two1, Two2, Two3
  type: "text" | "image_url" | "file";
  text: string;
  imageUrl: {
    id?: string;
    url: string;
    detail?: string;
  };
  file: {
    fileData?: string;
    uri?: string;
    mimeType?: string;
    filename?: string;
  };
}

Orq SDK

Terminal & Agents

Terraform

Platform APIs

Management APIs

Deployments

Invoke a Deployment

KnowledgeFilter1

Stream a Deployment

List Deployments

DeploymentsContent2

List Versions

ListDeploymentVersionsContent2

Get Config

DeploymentGetConfigKnowledgeFilter1

DeploymentGetConfigContentDeploymentsResponse2

​Deployments

​Invoke a Deployment

​KnowledgeFilter1

​Stream a Deployment

​List Deployments

​DeploymentsContent2

​List Versions

​ListDeploymentVersionsContent2

​Get Config

​DeploymentGetConfigKnowledgeFilter1

​DeploymentGetConfigContentDeploymentsResponse2

Deployments

Invoke a Deployment

KnowledgeFilter1

Stream a Deployment

List Deployments

DeploymentsContent2

List Versions

ListDeploymentVersionsContent2

Get Config

DeploymentGetConfigKnowledgeFilter1

DeploymentGetConfigContentDeploymentsResponse2