Create Orq.ai Deployments to ship LLM use cases to production. Configure model routing, invoke them via API or SDK, and monitor calls in real time.
Deployments are unavailable in workspaces created on or after November 10, 2026. Workspaces created before that date keep their Deployments.
Deployments ship Gen AI use cases to production with Orq.ai as an AI Gateway. All calls route through the platform, providing routing, monitoring, and security in one place. Connect with a single line of code, iterate without a code release, and benefit from full observability throughout.Common use cases include customer support bots, RAG-powered document Q&A, content generation pipelines, and any LLM feature that needs reliable model routing, versioning, and production monitoring.
Create
Set up a Deployment with a key, model, and system prompt in AI Studio or via MCP.
Configure
Set the model, fallbacks, variables, knowledge base, tools, caching, and guardrails per Variant.
Routing
Route traffic across Variants by environment, context attributes, or percentage split.
Versioning
Deploy and roll back configurations without a code release.
Invoke
Call a Deployment via API or SDK and pass identity, usage tracking, and extra parameters.
Analytics
Monitor requests, filter logs by Variant, and inspect full request details.
Open Deployments in the Managed Agents section, then click Deployment.
2
Choose Deployment
Select Deployment from the entity picker.
Configure the deployment key and primary model. All settings can be changed later.
3
Configure the initial Variant
Set the deployment key (alphanumeric) and select the primary model for the first Variant. The Variant editor opens.
Use the Orq MCP server to manage deployments directly from an AI code assistant.Find an existing deployment:
Search for the "support-bot" deployment in my workspace
The assistant uses search_entities with type: "deployment" to locate deployments by name or key.Retrieve deployment configuration:
Get the full configuration of the "support-bot" deployment
The assistant uses get_deployment to return the key, description, model, messages, and variant settings.Create a deployment:
Create a customer support deployment called "support-bot" in the Default/Deployments project. Use GPT-5.6 Sol with a professional, concise system prompt.
The assistant uses create_deployment with the specified key, path, and variant (model and messages). Use list_models first to find valid model IDs.
Variants are different prompt and model configurations available behind one Deployment. A Deployment can hold any number of Variants.On creation, the Variant screen opens for model and prompt setup.
A Variant Prompt is similar to any other prompt. To learn how to configure a Prompt, see Creating a Prompt.
The Primary Model panel defines the first model queried through this Variant.RetriesIn case of failure, configure how many times a query is retried with this model.
Retries are only triggered when a retry count greater than 0 is configured in the Variant settings.When retries are enabled, Orq.ai automatically retries the model provider API call if it returns one of the following HTTP status codes:
408 Request Timeout
429 Rate Limit Exceeded
500 Internal Server Error
502 Bad Gateway
503 Service Unavailable
504 Gateway Timeout
529 Provider Overloaded
Error handling flow:
If an error code above is returned and retries are configured (retry count > 0), Orq.ai retries the Primary Model.
If all retry attempts fail (or no retries are configured) AND a Fallback Model is configured, Orq.ai routes to the Fallback Model.
If the Fallback Model also fails, the error is returned to the calling application.
Fallback ModelThe Fallback Model is triggered only if the Primary Model fails after all configured retries are exhausted. Fallback Models can have a different configuration from the Primary Model.
The Fallback Model configuration is right below the main model configuration. Configure them independently.
Multiple fallback models can be configured in a Deployment. They fall back to one another in order of configuration. Use the Add extra fallback button to declare another model.
See how fallbacks and retries work together in a production system. Read our cookbook Customer Support Chat.
API invocation behaviorWhen invoking a Deployment via the API, response timing depends on the retry and fallback configuration:
Success on first try: Response returned immediately.
Retry scenario: Response may be delayed by up to base_latency × (retry_count + 1) to account for the initial attempt plus all configured retries.
Fallback invoked: Additional latency as the Fallback Model processes the request.
All retries and fallback failed: Error returned to the calling application.
Set appropriate timeouts on API calls to account for retry and fallback latency.
Configure structured outputs to ensure consistent and reliable responses from a Deployment. Structured outputs specify the exact format the model should follow when generating a response.Two modes are available:
JSON Mode: the model automatically returns a valid JSON object for every generation.
JSON Schema: define a schema that explicitly describes the fields, types, and structure of the model output.
Once defined, a schema can be saved to the directory for reuse across multiple variants or deployments.
Set the Response Format to JSON Schema to configure structured output.
Reference dynamic values in the prompt using double braces: {{variable_name}}. Pass a key-value map to the inputs field when invoking and Orq.ai substitutes each variable before sending the prompt to the model.
Orq.ai supports three template engines. Select the Template Engine from the Variant Settings panel:
Text (default): variables use {{double_braces}} syntax.
Jinja: full templating with conditionals, loops, filters, and more.
Mustache: logic-less templating with sections.
Select a Template Engine in the Variant Settings panel.
Example: support bot that adapts by subscription tier
Jinja example
1
Prompt template
Jinja
You are a support assistant for {{company_name}}.{% if user_tier == "premium" %}{{customer_name}} is a premium customer. Greet them by name and let them know they have priority support with a 2-hour response SLA.{% else %}{{customer_name}} is on the free plan. Let them know the standard response time is 24 hours.{% endif %}
You are a support assistant for {{company_name}}.{{! Pass is_premium: true for premium customers, false for free plan }}{{# is_premium}}{{customer_name}} is a premium customer. Greet them by name with priority support and a 2-hour SLA.{{/ is_premium}}{{^ is_premium}}{{customer_name}} is on the free plan. Standard response time is 24 hours.{{/ is_premium}}
Add {{variable_name}} placeholders to the prompt and pass the corresponding values in the inputs field at invoke time. Orq.ai substitutes each key before sending the prompt to the model.
Ground a Deployment’s responses in domain-specific knowledge by adding a Knowledge Base.Open the deployment configuration, go to Knowledge Bases, then select Knowledge Base.
Knowledge Bases enable RAG (Retrieval-Augmented Generation), allowing the model to retrieve and use relevant information from documentation or data sources to provide more accurate and contextual responses.
Configuration options (via the ... menu on an attached Knowledge Base):
Last User Message: the user’s latest message is automatically used as a query to retrieve relevant chunks.
Query: a predefined query is used to retrieve chunks. Use Input Variables like {{query}} to make it dynamic at runtime.
Configure which Knowledge Base to use and how it should be queried in the deployment.
To learn more about creating and configuring Knowledge Bases, see Knowledge Bases.
Reference the Knowledge Base in the prompt using the {{knowledge_base_key}} syntax, where knowledge_base_key is the identifier of the Knowledge Base. If the Knowledge Base is not explicitly referenced in the prompt, retrieved chunks are automatically appended to the end of the system message.
Using a Knowledge Base in a prompt.
See knowledge base retrieval used end-to-end in a working deployment. Read our cookbook Multilingual FAQ Bot.
When invoking a Deployment that uses a Knowledge Base, set include_retrievals: true in invoke_options to embed the retrieval chunks in the response.
curl --location 'https://my.orq.ai/v2/deployments/invoke' \--header 'Content-Type: application/json' \--header 'Accept: application/json' \--header 'Authorization: Bearer <ORQ_API_KEY>' \--data '{ "key": "deployment-demo", "messages": [ { "role": "user", "content": "What were the total net sales in 2023?" } ], "invoke_options": { "include_retrievals": true }}'
generation = client.deployments.invoke( key="deployment-demo", messages=[ { "role": "user", "content": "What were the total net sales in 2023?" } ], invoke_options={"include_retrievals": True})print(generation.choices[0].message.content)
const deployment = await client.deployments.invoke({ key: 'deployment-demo', messages: [ { role: 'user', content: 'What were the total net sales in 2023?', }, ], invokeOptions: { includeRetrievals: true },});
Retrievals are returned in the retrievals field of the response. Each chunk includes source details and scores:
Retrieval results are embedded in the retrievals field, containing document details, file metadata, and search scores.
See knowledge base retrievals wired into a complete application. Read our cookbook Multilingual FAQ Bot.
orq deployments invoke \ --key deployment-demo \ --messages '[{"role": "user", "content": "What were the total net sales in 2023?"}]' \ --invoke-options '{"include_retrievals": true}'
See install and setup to get started with the CLI. Run orq deployments invoke --help for the full flag reference.
Tools can only be added and configured at the deployment level. Only Function tools are supported in Deployments, enabling the model to call external functions during execution.To add a Function tool, open the Tools tab in the deployment configuration and click Tool:
Create a new Tool: define a custom function directly within the deployment.
Import an existing Tool: select a previously created Function tool from the resource library.
Configure function tools the model can call during deployment execution.
To learn more about creating Function tools, see Creating Tools.
Variant generation can be cached to reduce processing time and cost. When an input is received that matches a cached entry within the Variant, the stored response is returned directly without triggering a new generation.To enable caching, open the Variant Settings tab and select Enabled in the Caching section. The cache can be manually invalidated at any time by clicking the configuration icon.
Configure the cache expiration time.
TTL (time to live) corresponds to the amount of time a cached response is stored before being invalidated. Once invalidated, a new LLM generation is triggered. Configure the TTL from the drop-down once Caching is enabled.
The cache only works when there is an exact match. Image models are not supported.
Evaluators and Guardrails are configured as separate sections in the variant settings. Both operate on the generation pipeline but with different behaviours.
Guardrails execute synchronously and can block a generation, while Evaluators run asynchronously and never block the response.
EvaluatorsClick Evaluator to add an evaluator from the Library. Configure each evaluator as:
Input evaluator: runs evaluation on the input sent to the model.
Output evaluator: runs evaluation on the output generated by the model.
Evaluators run asynchronously and never block the response.
Configure a Sample Rate (0–100%) on each evaluator to control how frequently it runs.
Evaluators do not run when using the Test panel in AI Studio. To trigger evaluators, invoke the Deployment externally via the API or SDK.
GuardrailsClick Guardrail to add a guardrail-capable evaluator from the Library.A Guardrail runs synchronously and will deny the generation if its evaluation fails, returning an error to the user. Guardrails can be configured as:
Input Guardrail: runs before the input is sent to the model.
Output Guardrail: runs after generation, before client response.
Guardrail behavior when a guardrail fails:
Behavior
Description
Retry
Triggers a new generation attempt. Use this when a transient or non-deterministic failure may resolve on retry.
Fallback
Executes the fallback model configured on the Deployment. Use this for a safe default response instead of retrying.
Guardrail behavior is configured per Deployment and applies to all guardrails attached to it.
Output Guardrails and Streaming: When a deployment is invoked with streaming enabled, output guardrails will be deactivated as they cannot be run effectively on chunks only.
See guardrails put to the test against adversarial inputs. Read Red Teaming.
Input MaskingInputs in a Variant can be flagged as PII (Personally Identifiable Information). This is recommended when processing sensitive user data such as names, email addresses, or phone numbers.To configure this, open the Security tab when editing an input and choose Personally Identifiable Information (PII) from the Privacy drop-down.
Once deployed, the input value will not be logged within Orq systems.
Flagging an input as PII removes its values from logs and traces. When opening a log or trace, the input is shown in red to indicate it was not logged. The API response itself still includes the PII value.
The API response will include the PII, but input and output logs and traces will not be logged in Orq.ai.
Output MaskingEnable output masking to hide generated outputs from logs and traces. Head to the Security tab in the Variant and enable the Output masking toggle.When Output Masking is enabled, logs and traces will not store the generated response.
A single Deployment can hold multiple Variants. Multiple Variants can handle different use cases and scenarios within one Deployment, and can be served simultaneously through Routing.To add a new Variant, select the Variant name at the top-left of the screen and choose Add variant.
Switch between Variants and add a new Variant to a Deployment at any time.
Once a Variant is ready to be deployed, configure the routing variables to control which Variant is reached. Open the Routing page by selecting Routing at the top-left of the panel.
The Routing panel maps Variants to Context field values. Each row is a Variant, each column is a Context field, and each cell is a condition that must match for that Variant to be selected. A Variant is selected only when every condition in its row matches, and the first matching row wins.
An example routing table using list, string, and boolean Context fields.
Default variant: The top Variant in the Routing table is the default. If no routing rules match, or no context values are provided, the request is routed to it.Code SnippetsRight-click on any Variant in the Routing table and select Generate Code Snippets to get ready-to-use code for that specific Variant. Snippets include the correct context environment to reach the selected Variant.
Right-click on the variant path to generate code snippets.
Context FieldsTo add a new context field, press the button at the top right of the Routing table. Set a name and type for the field: boolean, date, list, number, or string.Routing ConditionsCreate a custom routing condition for each field and Variant by entering a value in the corresponding cell. By default, the = operator is used. Click = to change the operator.
Different operators are available depending on the field type.
SimulatorRouting can be tested at any time by opening the Simulator via the Simulator icon at the top-right of the Routing panel. Enter values for all field configurations and select Simulate to see which Variant the query routes to.
Version control tracks all changes to the model and prompt configuration. A new commit is made on each deployment and history is preserved throughout. All changes can be viewed, and any prior version can be restored.
Deploying a New VersionWhen the configuration is ready, press the Deploy button on the Variant screen.
The Deploy button is enabled once there are changes to commit.
The deployment modal prompts for the new version (Major or Minor bump), a description of the changes, and whether to deploy immediately or save as a draft.Saving a Draft commits the changes on a new version without making them publicly available. They become public on the next deployment.Comparing ChangesSelect the Compare Changes button at the top-right to visualize changes between configurations in a side-by-side JSON view. Restore a previous version by selecting it in the left panel and clicking Restore.
Side-by-side visualization of two versions of the same Variant.
Click Test in the Deployment toolbar to open the Test panel. Enter values for any configured variables and submit to see the model response inline. No code required.This is useful for quickly checking prompt content and model behavior during development.
The Test panel with variable inputs and the model response.
Evaluators configured on the Deployment do not run in the Test panel. To trigger evaluators, invoke the Deployment via the API or SDK.
Use the Code Snippet button at the top-right of the Variant page to get ready-to-use integration code for Python, Node.js, and cURL. All snippets include the keys and context variables needed to reach the current Variant.
The Code Snippet button at the top-right of the Variant page.
The Code Snippet panel with all integration languages.
Code snippets per Variant are also accessible from the Routing page:
Open a Deployment and go to the Routing page.
Right-click the target Variant and select Generate Code Snippet.
Invoke a Deployment by sending a request to the /v2/deployments/invoke endpoint. Orq.ai routes the request to the correct Variant, applies all configured settings, and returns the model’s response.
curl --request POST \ --url https://my.orq.ai/v2/deployments/invoke \ --header 'Authorization: Bearer <ORQ_API_KEY>' \ --header 'Content-Type: application/json' \ --data '{ "key": "deployment-demo", "context": {"environments": "production"}, "messages": [ { "role": "user", "content": "What is the return policy for electronics?" } ] }'
generation = client.deployments.invoke( key="deployment-demo", context={"environments": "production"}, messages=[ { "role": "user", "content": "What is the return policy for electronics?", } ],)print(generation.choices[0].message.content)
const generation = await client.deployments.invoke({ key: 'deployment-demo', context: { environments: 'production' }, messages: [ { role: 'user', content: 'What is the return policy for electronics?', }, ],});console.log(generation.choices[0].message.content);
The response includes prompt_tokens, completion_tokens, and total_tokens.IdentityAssociate an identity with deployment invocations for tracking and personalization.Identity fields:
id: Unique identifier for the identity (required).
Pass context values in the invocation payload to reach a specific Variant. The Routing table decides which one receives the request, and the default Variant handles anything that matches no row.
An example routing table.
The following examples send the same user question to the Deployment above with different context values, so each one reaches a different Variant.
API & SDK
CLI
Staging
Routes to the staging Variant:
curl --request POST \ --url https://my.orq.ai/v2/deployments/invoke \ --header 'Authorization: Bearer <ORQ_API_KEY>' \ --header 'Content-Type: application/json' \ --data '{ "key": "deployment-demo", "context": {"environments": "staging"}, "messages": [ { "role": "user", "content": "What is the return policy for electronics?" } ] }'
generation = client.deployments.invoke( key="deployment-demo", context={"environments": "staging"}, messages=[ { "role": "user", "content": "What is the return policy for electronics?", } ],)print(generation.choices[0].message.content)
const generation = await client.deployments.invoke({ key: 'deployment-demo', context: { environments: 'staging' }, messages: [ { role: 'user', content: 'What is the return policy for electronics?', }, ],});console.log(generation.choices[0].message.content);
generation = client.deployments.invoke( key="deployment-demo", context={"environments": "production", "region": "eu"}, messages=[ { "role": "user", "content": "What is the return policy for electronics?", } ],)print(generation.choices[0].message.content)
const generation = await client.deployments.invoke({ key: 'deployment-demo', context: { environments: 'production', region: 'eu' }, messages: [ { role: 'user', content: 'What is the return policy for electronics?', }, ],});console.log(generation.choices[0].message.content);
No context (default)
Omits context entirely, routing to the default Variant:
curl --request POST \ --url https://my.orq.ai/v2/deployments/invoke \ --header 'Authorization: Bearer <ORQ_API_KEY>' \ --header 'Content-Type: application/json' \ --data '{ "key": "deployment-demo", "messages": [ { "role": "user", "content": "What is the return policy for electronics?" } ] }'
generation = client.deployments.invoke( key="deployment-demo", messages=[ { "role": "user", "content": "What is the return policy for electronics?", } ],)print(generation.choices[0].message.content)
const generation = await client.deployments.invoke({ key: 'deployment-demo', messages: [ { role: 'user', content: 'What is the return policy for electronics?', }, ],});console.log(generation.choices[0].message.content);
Pass each Context field as a separate --context flag.Staging:
orq deployments invoke \ --key deployment-demo \ --context environments=staging \ --messages '[{"role": "user", "content": "What is the return policy for electronics?"}]'
Production EU:
orq deployments invoke \ --key deployment-demo \ --context environments=production \ --context region=eu \ --messages '[{"role": "user", "content": "What is the return policy for electronics?"}]'
No context (default):
orq deployments invoke \ --key deployment-demo \ --messages '[{"role": "user", "content": "What is the return policy for electronics?"}]'
See install and setup to get started with the CLI. Run orq deployments invoke --help for the full flag reference.
The invoke response carries the model and provider that answered, not the Variant name. To confirm which Variant handled a request, open Logs and filter on Variant, or on Evaluation to separate Matched from Default Matched. See Analytics and Logs.
Use extra_params to pass parameters not directly exposed by the Orq.ai panel, or to override existing model configuration at runtime.Passing an unsupported parameter:
This feature is only supported with OpenAI, Anthropic, and Google Gemini models.
Embed files directly in the Invoke payload using a file type message with a standard data URI scheme: data:content/type;base64 followed by the base64-encoded file data.
See PDF inputs used to extract structured data end-to-end. Read our cookbook PDF Extraction.
Knowledge Base vs. Direct File AttachmentUse a Knowledge Base when: the information is reused across many requests and RAG (targeted chunk retrieval) is sufficient. Knowledge Bases retrieve relevant chunks but not the full document.Use direct file attachment when: the task requires full-document understanding (e.g. summarization, legal review, detailed analysis), the document is ad-hoc or session-specific, or the data is too sensitive for a shared knowledge repository.
Once a Deployment is running and receiving traffic, detailed analytics of all requests are available.Logs show requests per Variant. Filters available:
Variant: select a single Variant to filter logs.
Evaluation: Matched (a routing rule was matched) or Default Matched (no routing rule matched, default Variant was used).
Source: API, SDK, or Simulator.
Click any log line to open a detail panel showing context, requests, and parameters sent to the Deployment.
Logs overview.
HyperlinkingCopy a generation’s model configuration (prompt, model, and other settings) into another module from the detail panel:
Share
Run in Playgrounds
Create a Deployment
Add Variant to Deployment
Add to Dataset
Size limitA log holds at most 16 MB across text inputs, generations, retrievals, and embedded images. Oversized logs are discarded from the Logs view.
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Use GPT-5.6 Sol with a professional, concise system prompt.`})}),`\n`,_jsx(_components.span,{className:`line`,children:_jsx(_components.span,{})})]})})}),_jsxs(_components.p,{children:[`The assistant uses `,_jsx(_components.code,{children:`create_deployment`}),` with the specified `,_jsx(_components.code,{children:`key`}),`, `,_jsx(_components.code,{children:`path`}),`, and `,_jsx(_components.code,{children:`variant`}),` (model and messages). Use `,_jsx(_components.code,{children:`list_models`}),` first to find valid model IDs.`]})]})]}),`\n`,_jsx(Heading,{level:`2`,id:`configure-a-variant`,children:`Configure a Variant`}),`\n`,_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Variants`}),` are different prompt and model configurations available behind one Deployment. A Deployment can hold any number of Variants.`]}),`\n`,_jsxs(_components.p,{children:[`On creation, the `,_jsx(_components.strong,{children:`Variant`}),` screen opens for model and prompt setup.`]}),`\n`,_jsx(Info,{children:_jsxs(_components.p,{children:[`A Variant Prompt is similar to any other prompt. To learn how to configure a Prompt, see `,_jsx(_components.a,{href:`/ai-studio/prompts/prompts`,children:`Creating a Prompt`}),`.`]})}),`\n`,_jsx(Heading,{level:`3`,id:`primary-model-retries-and-fallback`,children:`Primary Model, Retries, and Fallback`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-2`,children:[_jsxs(_components.p,{children:[`The `,_jsx(_components.strong,{children:`Primary Model`}),` panel defines the first model queried through this Variant.`]}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Retries`})}),_jsx(_components.p,{children:`In case of failure, configure how many times a query is retried with this model.`}),_jsxs(Info,{children:[_jsx(_components.p,{children:`Retries are only triggered when a retry count greater than 0 is configured in the Variant settings.`}),_jsxs(_components.p,{children:[`When retries are enabled, `,_jsx(_components.strong,{children:`Orq.ai`}),` automatically retries the model provider API call if it returns one of the following HTTP status codes:`]}),_jsxs(_components.ul,{children:[`\n`,_jsx(_components.li,{children:`408 Request Timeout`}),`\n`,_jsx(_components.li,{children:`429 Rate Limit Exceeded`}),`\n`,_jsx(_components.li,{children:`500 Internal Server Error`}),`\n`,_jsx(_components.li,{children:`502 Bad Gateway`}),`\n`,_jsx(_components.li,{children:`503 Service Unavailable`}),`\n`,_jsx(_components.li,{children:`504 Gateway Timeout`}),`\n`,_jsx(_components.li,{children:`529 Provider Overloaded`}),`\n`]})]}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Error handling flow:`})}),_jsxs(_components.ol,{children:[`\n`,_jsxs(_components.li,{children:[`If an error code above is returned and retries are configured (retry count > 0), `,_jsx(_components.strong,{children:`Orq.ai`}),` retries the Primary Model.`]}),`\n`,_jsxs(_components.li,{children:[`If all retry attempts fail (or no retries are configured) AND a Fallback Model is configured, `,_jsx(_components.strong,{children:`Orq.ai`}),` routes to the Fallback Model.`]}),`\n`,_jsx(_components.li,{children:`If the Fallback Model also fails, the error is returned to the calling application.`}),`\n`]}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Fallback Model`})}),_jsx(_components.p,{children:`The Fallback Model is triggered only if the Primary Model fails after all configured retries are exhausted. Fallback Models can have a different configuration from the Primary Model.`}),_jsx(Frame,{caption:`The Fallback Model configuration is right below the main model configuration. 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The cache can be manually invalidated at any time by clicking the configuration icon.`]}),_jsx(Frame,{caption:`Configure the cache expiration time.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=19274aa9dca644973c478d57f446605b`,alt:`Cache settings with the Enabled toggle on and an Expires in dropdown open, showing options from 1 hour to 2 weeks.`,\"data-og-width\":`554`,width:`554`,\"data-og-height\":`469`,height:`469`,\"data-path\":`images/deployment-variant-caching.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=280\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=3b13b5aa0c0773b557ba469a162430ec 280w, https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=560\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=b0ffed57b110cc31645f97f5c8f940cc 560w, https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=840\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=ecc64dfcc12a7a38bc0353c325627c4f 840w, https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=1100\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=a920883d5671cf2323eb0dbd0628c6db 1100w, https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=1650\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=6ea0e63c7c10b775a6a24192935e0009 1650w, https://mintcdn.com/orqai/vOJWhuVD9oBrDhcx/images/deployment-variant-caching.png?w=2500\u0026fit=max\u0026auto=format\u0026n=vOJWhuVD9oBrDhcx\u0026q=85\u0026s=cc85aac5a671d9859cde0bae795369d0 2500w`})}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`TTL (time to live)`}),` corresponds to the amount of time a cached response is stored before being invalidated. Once invalidated, a new LLM generation is triggered. Configure the TTL from the drop-down once Caching is enabled.`]}),_jsx(Info,{children:_jsx(_components.p,{children:`The cache only works when there is an exact match. Image models are not supported.`})})]})}),`\n`,_jsx(Heading,{level:`3`,id:`evaluators-and-guardrails`,children:`Evaluators and Guardrails`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-8`,children:[_jsxs(_components.p,{children:[_jsx(_components.a,{href:`/ai-studio/optimize/evaluators`,children:`Evaluators`}),` and Guardrails are configured as separate sections in the variant settings. Both operate on the generation pipeline but with different behaviours.`]}),_jsx(Frame,{caption:`Guardrails execute synchronously and can block a generation, while Evaluators run asynchronously and never block the response.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=1c40c78aac37b6819e2ab2bfceaba12e`,alt:`Flow diagram showing a user query passing through Input Guardrails synchronously, then Deployment Model Generation, then Output Guardrails, with Input and Output Evaluators running asynchronously and fail paths returning an Error Response.`,\"data-og-width\":`3278`,width:`3278`,\"data-og-height\":`1779`,height:`1779`,\"data-path\":`images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=280\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=b8f666190d4bb66b59bbc717a3b3cbc2 280w, https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=560\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=da2e9140bb9fbf3935b4d59df9b6a6fd 560w, https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=840\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=15f83ba427c7beb058c188dba7bdfc5f 840w, https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=1100\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=b1c1c15f3d892a61855e8b2778088452 1100w, https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=1650\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=23a4e7ce49ab7b8b57858d57053e52cb 1650w, https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/a6be2fe5b5e1290b3d2132212a9ec6e74287d7b6cb896d86f8f4838b5a9bcf73-Guardrails_and_Evaluators_-_Deployment.png?w=2500\u0026fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=3cf9be4551983d7f3e7894a8166a23d6 2500w`})}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Evaluators`})}),_jsxs(_components.p,{children:[`Click `,_jsxs(`kbd`,{className:`key`,children:[_jsx(Icon,{icon:`circle-plus`,color:`#fff`}),` Evaluator`]}),` to add an evaluator from the Library. Configure each evaluator as:`]}),_jsxs(_components.ul,{children:[`\n`,_jsxs(_components.li,{children:[_jsx(`kbd`,{children:_jsx(Icon,{icon:`arrow-up-right`,color:`#22c55e`})}),` `,_jsx(_components.strong,{children:`Input evaluator`}),`: runs evaluation on the input sent to the model.`]}),`\n`,_jsxs(_components.li,{children:[_jsx(`kbd`,{children:_jsx(Icon,{icon:`arrow-down-left`,color:`#ef4444`})}),` `,_jsx(_components.strong,{children:`Output evaluator`}),`: runs evaluation on the output generated by the model.`]}),`\n`]}),_jsxs(_components.p,{children:[`Evaluators run `,_jsx(_components.strong,{children:`asynchronously`}),` and never block the response.`]}),_jsx(Frame,{caption:`Configure a Sample Rate (0–100%) on each evaluator to control how frequently it runs.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=2b05a024b244f5fc74171dfe78e2b71c`,alt:`Guardrails section listing input_contains_pii and output_toxicity, and Evaluators section showing HTTP Evaluator at 15%, with a Sample Rate popover displaying 15%.`,\"data-og-width\":`589`,width:`589`,\"data-og-height\":`357`,height:`357`,\"data-path\":`images/evaluator-variant.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=280\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=083a871a34415948616ae6b2fa7b5c27 280w, https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=560\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=ae90cf12fdc181203bafa474d6f5dd44 560w, https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=840\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=aef4e7b938e2bccd0d1777bac1d3032c 840w, https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=1100\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=56c803b4f86ecd78b7b74475010ea2a2 1100w, https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=1650\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=dac7fbfd34b00fb4f7632f3904696cce 1650w, https://mintcdn.com/orqai/4f-ka8j82TWkynBc/images/evaluator-variant.png?w=2500\u0026fit=max\u0026auto=format\u0026n=4f-ka8j82TWkynBc\u0026q=85\u0026s=bb4357416b8b221f39447d6722821a33 2500w`})}),_jsx(Note,{children:_jsxs(_components.p,{children:[`Evaluators do not run when using the `,_jsxs(_components.a,{href:`#test-a-deployment`,children:[_jsx(_components.strong,{children:`Test`}),` panel`]}),` in AI Studio. To trigger evaluators, invoke the Deployment externally via the `,_jsx(_components.a,{href:`#invoke-a-deployment`,children:`API or SDK`}),`.`]})}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Guardrails`})}),_jsxs(_components.p,{children:[`Click `,_jsxs(`kbd`,{className:`key`,children:[_jsx(Icon,{icon:`circle-plus`,color:`#fff`}),` Guardrail`]}),` to add a guardrail-capable evaluator from the Library.`]}),_jsxs(_components.p,{children:[`A Guardrail runs `,_jsx(_components.strong,{children:`synchronously`}),` and will `,_jsx(_components.strong,{children:`deny`}),` the generation if its evaluation fails, returning an error to the user. Guardrails can be configured as:`]}),_jsxs(_components.ul,{children:[`\n`,_jsxs(_components.li,{children:[_jsx(`kbd`,{children:_jsx(Icon,{icon:`arrow-up-right`,color:`#22c55e`})}),` `,_jsx(_components.strong,{children:`Input Guardrail`}),`: runs `,_jsx(_components.strong,{children:`before`}),` the input is sent to the model.`]}),`\n`,_jsxs(_components.li,{children:[_jsx(`kbd`,{children:_jsx(Icon,{icon:`arrow-down-left`,color:`#ef4444`})}),` `,_jsx(_components.strong,{children:`Output Guardrail`}),`: runs `,_jsx(_components.strong,{children:`after`}),` generation, before client response.`]}),`\n`]}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Guardrail behavior when a guardrail fails:`})}),_jsxs(Table,{children:[_jsx(_components.thead,{children:_jsxs(_components.tr,{children:[_jsx(_components.th,{children:`Behavior`}),_jsx(_components.th,{children:`Description`})]})}),_jsxs(_components.tbody,{children:[_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.strong,{children:`Retry`})}),_jsx(_components.td,{children:`Triggers a new generation attempt. Use this when a transient or non-deterministic failure may resolve on retry.`})]}),_jsxs(_components.tr,{children:[_jsx(_components.td,{children:_jsx(_components.strong,{children:`Fallback`})}),_jsx(_components.td,{children:`Executes the fallback model configured on the Deployment. Use this for a safe default response instead of retrying.`})]})]})]}),_jsx(_components.p,{children:`Guardrail behavior is configured per Deployment and applies to all guardrails attached to it.`}),_jsx(Warning,{children:_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Output Guardrails and Streaming`}),`: When a deployment is invoked with streaming enabled, output guardrails will be deactivated as they cannot be run effectively on chunks only.`]})}),_jsx(Callout,{icon:`hat-chef`,color:`#7ecece`,children:_jsxs(_components.p,{children:[`See guardrails put to the test against adversarial inputs. Read `,_jsx(_components.a,{href:`/ai-studio/optimize/red-teaming`,children:`Red Teaming`}),`.`]})})]})}),`\n`,_jsx(Heading,{level:`3`,id:`security-and-privacy`,children:`Security and Privacy`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-9`,children:[_jsx(_components.p,{children:_jsx(_components.strong,{children:`Input Masking`})}),_jsx(_components.p,{children:`Inputs in a Variant can be flagged as PII (Personally Identifiable Information). This is recommended when processing sensitive user data such as names, email addresses, or phone numbers.`}),_jsxs(_components.p,{children:[`To configure this, open the `,_jsx(_components.strong,{children:`Security`}),` tab when editing an input and choose `,_jsx(_components.strong,{children:`Personally Identifiable Information (PII)`}),` from the Privacy drop-down.`]}),_jsx(Frame,{caption:`Once deployed, the input value will not be logged within Orq systems.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=7b66c02cebefb3ccb499e95410e5cc34`,alt:`Variables section with a Question variable and a privacy dropdown showing None and Personally Identifiable Information (PII) options.`,\"data-og-width\":`758`,width:`758`,\"data-og-height\":`194`,height:`194`,\"data-path\":`images/variable-pii.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=280\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=d46269d179d6d54d68ac31c9991ea975 280w, https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=560\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=37e19da2b23f0abcc99d5d49751bd860 560w, https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=840\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=cfa39043c73f9e91d42f46f51f524e56 840w, https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=1100\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=f6237c6a19e74d8ee78e139ed42f7858 1100w, https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=1650\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=c3e27020b86f68850b1f8d3e0680d7ab 1650w, https://mintcdn.com/orqai/R7t6xmeUretxbcfc/images/variable-pii.png?w=2500\u0026fit=max\u0026auto=format\u0026n=R7t6xmeUretxbcfc\u0026q=85\u0026s=ef86a441d4e99470e44c466089ad4408 2500w`})}),_jsx(_components.p,{children:`Flagging an input as PII removes its values from logs and traces. When opening a log or trace, the input is shown in red to indicate it was not logged. The API response itself still includes the PII value.`}),_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/E8L3R46ivX7g9-QI/images/docs/955b175e6f005d7f112a98e54d3468acb0b72f001a150ced0ac4262128321179-iScreen_Shoter_-_Google_Chrome_-_250317122231.jpg?fit=max\u0026auto=format\u0026n=E8L3R46ivX7g9-QI\u0026q=85\u0026s=700d1089a333f51107572e98bb4a0a05`,alt:`Trace detail for gpt-5.6-sol showing a user message say hello to {name} and the assistant reply Hello, [name]! 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Head to the `,_jsx(_components.strong,{children:`Security tab`}),` in the Variant and enable the `,_jsx(_components.strong,{children:`Output masking`}),` toggle.`]}),_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/55N7ogp78VJHeSpN/images/variant-output-masking.png?fit=max\u0026auto=format\u0026n=55N7ogp78VJHeSpN\u0026q=85\u0026s=2c5239c4d02963abfc4b9a71ae3af464`,alt:`Variables section with city and date variables, and a Masking section with the Output Masking toggle enabled.`,\"data-og-width\":`545`,width:`545`,\"data-og-height\":`259`,height:`259`,\"data-path\":`images/variant-output-masking.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/55N7ogp78VJHeSpN/images/variant-output-masking.png?w=280\u0026fit=max\u0026auto=format\u0026n=55N7ogp78VJHeSpN\u0026q=85\u0026s=002e438f41ad0e8d8ad2d8a58532729c 280w, 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2500w`}),_jsx(_components.p,{children:`When Output Masking is enabled, logs and traces will not store the generated response.`}),_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/4YNqGRNpuZNyo0_T/images/output-masking-410.png?fit=max\u0026auto=format\u0026n=4YNqGRNpuZNyo0_T\u0026q=85\u0026s=51d32de03bcf8b72edd8a37c9de5b35b`,alt:`A masked output field with a striped pattern and a tooltip reading The response from the model was masked due to your deployment settings.`,\"data-og-width\":`294`,width:`294`,\"data-og-height\":`137`,height:`137`,\"data-path\":`images/output-masking-410.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/4YNqGRNpuZNyo0_T/images/output-masking-410.png?w=280\u0026fit=max\u0026auto=format\u0026n=4YNqGRNpuZNyo0_T\u0026q=85\u0026s=d3d3a886c14d0451685646cfabc5f0e5 280w, 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2500w`})]})}),`\n`,_jsx(Heading,{level:`2`,id:`add-a-variant`,children:`Add a Variant`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, 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Enter values for all field configurations and select `,_jsx(_components.strong,{children:`Simulate`}),` to see which Variant the query routes to.`]})]})}),`\n`,_jsx(Heading,{level:`2`,id:`versioning`,children:`Versioning`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-12`,children:[_jsx(_components.p,{children:`Version control tracks all changes to the model and prompt configuration. A new commit is made on each deployment and history is preserved throughout. All changes can be viewed, and any prior version can be restored.`}),_jsx(`div`,{className:`mint-max-w-md`,children:_jsx(OptimizedFrame,{src:`https://www.youtube.com/embed/5AJA-KHWu9Y`,title:`How to Use Version Control, SDK Snippets, and PII Filtering in Orq.ai Deployments`,frameborder:`0`,className:`mint-w-full mint-aspect-video mint-rounded-xl`,allow:`accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share`,allowfullscreen:true})}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Deploying a New Version`})}),_jsxs(_components.p,{children:[`When the configuration is ready, press the `,_jsx(_components.strong,{children:`Deploy`}),` button on the Variant screen.`]}),_jsx(Frame,{caption:`The Deploy button is enabled once there are changes to commit.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=5b63d03a432251cdd9bf531d6e6728b2`,alt:`Variant toolbar showing share, code snippet, history, and external link buttons alongside the Deploy button.`,\"data-og-width\":`266`,width:`266`,\"data-og-height\":`48`,height:`48`,\"data-path\":`images/deployment-code-snippet-button.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=280\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=571fea8bd40b1df60c666278458d3d98 280w, https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=560\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=bf4d481818ce31327b182a8d03b4c80c 560w, https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=840\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=fda7434071b950b3180182f73fd6dfa5 840w, https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=1100\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=32abf18a884f336a6340a91dab24d57e 1100w, https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=1650\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=99aa0256051203ae75c4569509fffbec 1650w, https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?w=2500\u0026fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=835e1c0171e4449fda43b4455d5612c1 2500w`})}),_jsx(_components.p,{children:`The deployment modal prompts for the new version (Major or Minor bump), a description of the changes, and whether to deploy immediately or save as a draft.`}),_jsxs(_components.p,{children:[_jsx(_components.strong,{children:`Saving a Draft`}),` commits the changes on a new version without making them publicly available. They become public on the next deployment.`]}),_jsx(_components.p,{children:_jsx(_components.strong,{children:`Comparing Changes`})}),_jsxs(_components.p,{children:[`Select the `,_jsx(_components.strong,{children:`Compare Changes`}),` button at the top-right to visualize changes between configurations in a side-by-side JSON view. Restore a previous version by selecting it in the left panel and clicking `,_jsx(_components.strong,{children:`Restore`}),`.`]}),_jsx(Frame,{caption:`Side-by-side visualization of two versions of the same Variant.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=f697d32cd10550b3d3f40c266fd0bcec`,alt:`Prompt template changes dialog showing a side-by-side diff between Base v1.1 and Compare v1.0 Published, highlighting a tools array added in the newer version.`,\"data-og-width\":`2950`,width:`2950`,\"data-og-height\":`1968`,height:`1968`,\"data-path\":`images/deployment-version-compare.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=280\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=157d0787b5c8555c32ebf59776cec9eb 280w, https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=560\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=aa7576667d47ab97317684eadc1f45c8 560w, https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=840\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=491322ebb2f4a364cabfb9a27d996da9 840w, https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=1100\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=7f5e985c74c4f2643cdeaeda4598a37f 1100w, https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=1650\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=79a6ff044e79619e015af7ea50ec4d20 1650w, https://mintcdn.com/orqai/MGpeNVsx2VMjZoDd/images/deployment-version-compare.png?w=2500\u0026fit=max\u0026auto=format\u0026n=MGpeNVsx2VMjZoDd\u0026q=85\u0026s=4e7d19132af9390cec636e7d824e2dc3 2500w`})})]})}),`\n`,_jsx(Heading,{level:`2`,id:`test-a-deployment`,children:`Test a Deployment`}),`\n`,_jsx(Tabs,{children:_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-13`,children:[_jsxs(_components.p,{children:[`Click `,_jsx(`kbd`,{children:`Test`}),` in the Deployment toolbar to open the Test panel. Enter values for any configured variables and submit to see the model response inline. No code required.`]}),_jsx(_components.p,{children:`This is useful for quickly checking prompt content and model behavior during development.`}),_jsx(Frame,{caption:`The Test panel with variable inputs and the model response.`,children:_jsx(`div`,{className:`mint-max-w-[70%]`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=626b2ff7c209eee43c374f7b5ceb9fea`,alt:`Test panel showing a Variables section with company_name, user_question, and tone inputs, and the model response below.`,\"data-og-width\":`589`,width:`589`,\"data-og-height\":`1164`,height:`1164`,\"data-path\":`images/deployment-test.png`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=280\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=6aa62f3a401de6e89bf678fad4a0923b 280w, https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=560\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=167fb5d6af73144254ebc3e047da74ae 560w, https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=840\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=7ebce42e62e1b755826a461374e1b302 840w, https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=1100\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=f2ab617c6363c7a579e4ece7fff7662e 1100w, https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=1650\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=cadbb26214bb9d7dab28cc2301f7b645 1650w, https://mintcdn.com/orqai/Vvtq1CVIs20Zcvqz/images/deployment-test.png?w=2500\u0026fit=max\u0026auto=format\u0026n=Vvtq1CVIs20Zcvqz\u0026q=85\u0026s=fa056452b991091f80756cd78d3f8a19 2500w`})})}),_jsx(Warning,{children:_jsxs(_components.p,{children:[`Evaluators configured on the Deployment do not run in the Test panel. To trigger evaluators, invoke the Deployment via the `,_jsx(_components.a,{href:`#invoke-a-deployment`,children:`API or SDK`}),`.`]})})]})}),`\n`,_jsx(Heading,{level:`2`,id:`invoke-a-deployment`,children:`Invoke a Deployment`}),`\n`,_jsxs(Tabs,{children:[_jsxs(Tab,{title:`AI Studio`,icon:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=ac04dd509320d58ab9701cb6d6137733`,\"data-og-width\":`100`,width:`100`,\"data-og-height\":`100`,height:`100`,\"data-path\":`images/logos/ai-studio-round.svg`,\"data-optimize\":`true`,\"data-opv\":`3`,srcset:`https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=280\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=d9df8d5b2ef07a766e62eaa0623240cd 280w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=560\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3c40989d2bc47d1ec6d05f8eb3a585dd 560w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=840\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=2c40a18399d00e68a15d7d1262484486 840w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1100\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=3e853add10f479adccee3068427de43d 1100w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=1650\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=71d1130736022278f4de6d95e7583c9b 1650w, https://mintcdn.com/orqai/My16MDKJXrKALEHC/images/logos/ai-studio-round.svg?w=2500\u0026fit=max\u0026auto=format\u0026n=My16MDKJXrKALEHC\u0026q=85\u0026s=41a312377a09cf0f6da1edb9b02b695c 2500w`,id:`ai-studio-14`,children:[_jsxs(_components.p,{children:[`Use the `,_jsx(_components.strong,{children:`Code Snippet`}),` button at the top-right of the Variant page to get ready-to-use integration code for Python, Node.js, and cURL. All snippets include the keys and context variables needed to reach the current Variant.`]}),_jsx(`div`,{className:`mint-max-w-md`,children:_jsx(OptimizedFrame,{src:`https://www.youtube.com/embed/deLu3xMxyQA`,title:`From Invocation to Insight: Running Orq.ai Deployments and Reading the Logs`,frameborder:`0`,className:`mint-w-full mint-aspect-video mint-rounded-xl`,allow:`accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture; web-share`,allowfullscreen:true})}),_jsx(Frame,{caption:`The Code Snippet button at the top-right of the Variant page.`,children:_jsx(OptimizedImage,{src:`https://mintcdn.com/orqai/aNCOui-yQmuILSqI/images/deployment-code-snippet-button.png?fit=max\u0026auto=format\u0026n=aNCOui-yQmuILSqI\u0026q=85\u0026s=5b63d03a432251cdd9bf531d6e6728b2`,alt:`Variant toolbar showing share, code snippet, history, and external link buttons alongside the Deploy 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