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Usage",id:"proxy-usage",level:2},{value:"Add model to config",id:"add-model-to-config",level:3},{value:"Start proxy",id:"start-proxy",level:3},{value:"Test",id:"test",level:3},{value:"Azure: GA vs beta realtime protocol",id:"azure-ga-vs-beta-realtime-protocol",level:2},{value:"Guardrails",id:"guardrails",level:2},{value:"Set guardrails on a key or team",id:"set-guardrails-on-a-key-or-team",level:3},{value:"Pass guardrails dynamically (easy testing)",id:"pass-guardrails-dynamically-easy-testing",level:3},{value:"Logging",id:"logging",level:2}];function I(e){let n={a:"a",code:"code",h1:"h1",h2:"h2",h3:"h3",header:"header",li:"li",p:"p",pre:"pre",strong:"strong",ul:"ul",...(0,s.R)(),...e.components};return(0,i.jsxs)(i.Fragment,{children:[(0,i.jsx)(n.header,{children:(0,i.jsx)(n.h1,{id:"realtime",children:"/realtime"})}),"\n",(0,i.jsx)(n.p,{children:"Use this to loadbalance across Azure + OpenAI + xAI and more."}),"\n",(0,i.jsx)(n.p,{children:"Supported Providers:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:"OpenAI"}),"\n",(0,i.jsx)(n.li,{children:"Azure"}),"\n",(0,i.jsxs)(n.li,{children:["xAI (",(0,i.jsx)(n.a,{href:"/docs/providers/xai_realtime",children:"see full docs"}),")"]}),"\n",(0,i.jsx)(n.li,{children:"Google AI Studio (Gemini)"}),"\n",(0,i.jsx)(n.li,{children:"Vertex AI"}),"\n",(0,i.jsxs)(n.li,{children:["Vertex AI Chirp, transcription only (",(0,i.jsx)(n.a,{href:"/docs/providers/vertex_transcription#chirp-realtime-transcription",children:"see full docs"}),")"]}),"\n",(0,i.jsx)(n.li,{children:"Bedrock"}),"\n",(0,i.jsxs)(n.li,{children:["Meta Muse Voice, transcription only (",(0,i.jsx)(n.a,{href:"/docs/providers/meta#muse-voice-realtime-transcription",children:"see full docs"}),")"]}),"\n"]}),"\n",(0,i.jsx)(n.h2,{id:"proxy-usage",children:"Proxy Usage"}),"\n",(0,i.jsx)(n.h3,{id:"add-model-to-config",children:"Add model to config"}),"\n",(0,i.jsxs)(t.A,{children:[(0,i.jsx)(r.A,{value:"openai",label:"OpenAI",children:(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-yaml",children:"model_list:\n - model_name: openai-gpt-4o-realtime-audio\n litellm_params:\n model: openai/gpt-4o-realtime-preview-2024-10-01\n api_key: os.environ/OPENAI_API_KEY\n model_info:\n mode: realtime\n"})})}),(0,i.jsx)(r.A,{value:"openai+azure",label:"OpenAI + Azure",children:(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-yaml",children:"model_list:\n - model_name: azure-gpt-4o-realtime-audio\n litellm_params:\n model: azure/gpt-4o-realtime-preview\n api_key: os.environ/AZURE_SWEDEN_API_KEY\n api_base
1: os.environ/AZURE_SWEDEN_API_BASE\n\n - model_name: azure-gpt-realtime\n litellm_params:\n model: azure/gpt-realtime\n api_key: os.environ/AZURE_API_KEY\n api_base: os.environ/AZURE_API_BASE\n model_info:\n mode: realtime\n\n - model_name: openai-gpt-4o-realtime-audio\n litellm_params:\n model: openai/gpt-4o-realtime-preview-2024-10-01\n api_key: os.environ/OPENAI_API_KEY\n"})})}),(0,i.jsxs)(r.A,{value:"xai",label:"xAI Grok Voice Agent",children:[(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-yaml",children:"model_list:\n - model_name: grok-voice-agent\n litellm_params:\n model: xai/grok-voice-latest\n api_key: os.environ/XAI_API_KEY\n model_info:\n mode: realtime\n"})}),(0,i.jsx)(n.p,{children:(0,i.jsx)(n.strong,{children:(0,i.jsx)(n.a,{href:"/docs/providers/xai_realtime",children:"See full xAI Realtime documentation \u2192"})})})]})]}),"\n",(0,i.jsx)(n.h3,{id:"start-proxy",children:"Start proxy"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"litellm --config /path/to/config.yaml \n\n# RUNNING on http://0.0.0.0:4000\n"})}),"\n",(0,i.jsx)(n.h3,{id:"test",children:"Test"}),"\n",(0,i.jsxs)(n.p,{children:["Run this script using node - ",(0,i.jsx)(n.code,{children:"node test.js"})]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-js",children:'// test.js\nconst WebSocket = require("ws");\n\nconst url = "ws://0.0.0.0:4000/v1/realtime?model=openai-gpt-4o-realtime-audio";\n// const url = "wss://my-azure-endpoint.openai.azure.com/openai/realtime?api-version=2024-10-01-preview&deployment=gpt-4o-realtime-preview";\nconst ws = new WebSocket(url, {\n headers: {\n "api-key": `sk-<your-litellm-api-key>`,\n "OpenAI-Beta": "realtime=v1",\n },\n});\n\nws.on("open", function open() {\n console.log("Connected to server.");\n ws.send(JSON.stringify({\n type: "response.create",\n response: {\n modalities: ["text"],\n instructions: "Please assist the user.",\n }\n }));\n});\n\nws.on("message", function incoming(message) {\n console.log(JSON.parse(message.toString()));\n});\n\nws.on("error", function handleError(error) {\n console.error("Error: ", error);\n});\n'})}),"\n",(0,i.jsx)(n.h2,{id:"azure-ga-vs-beta-realtime-protocol",children:"Azure: GA vs beta realtime protocol"}),"\n",(0,i.jsxs)(n.p,{children:["Azure exposes two realtime upstreams. The GA endpoint (",(0,i.jsx)(n.code,{children:"/openai/v1/realtime?model=<deployment>"}),") speaks the GA event schema (",(0,i.jsx)(n.code,{children:"session.type"}),", ",(0,i.jsx)(n.code,{children:"output_modalities"}),", nested ",(0,i.jsx)(n.code,{children:"audio"}),"), and the older beta endpoint (",(0,i.jsx)(n.code,{children:"/openai/realtime?api-version=2024-10-01-preview&deployment=<deployment>"}),") speaks the beta schema (",(0,i.jsx)(n.code,{children:"modalities"}),", ",(0,i.jsx)(n.code,{children:"voice"}),", flat audio formats). Sending a GA-shaped ",(0,i.jsx)(n.code,{children:"session.update"})," to the beta endpoint fails with ",(0,i.jsx)(n.code,{children:"Unknown parameter: 'session.type'"})]}),"\n",(0,i.jsxs)(n.p,{children:["LiteLLM picks the upstream from the client connection. A client that sends the ",(0,i.jsx)(n.code,{children:"OpenAI-Beta: realtime=v1"})," header (the openai SDK's ",(0,i.jsx)(n.code,{children:"client.beta.realtime.connect"}),") is bridged to the beta endpoint. A client without that header (the openai SDK's ",(0,i.jsx)(n.code,{children:"client.realtime.connect"}),", and most voice agent frameworks) is bridged to the GA endpoint. Transcription sessions (",(0,i.jsx)(n.code,{children:"intent=transcription"}),") always use GA"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:'from openai import AsyncOpenAI\n\nclient = AsyncOpenAI(base_url="http://0.0.0.0:4000", api_key="sk-1234")\n\nasync with client.realtime.connect(model="azure-gpt-realtime") as connection:\n await connection.session.update(\n session={"type": "realtime", "output_modalities": ["audio"], "instructions": "Please assist the user."}\n )\n async for event in connection:\n print(event.type)\n if event.type == "session.updated":\n break\n'})}),"\n",(0,i.jsxs)(n.p,{children:["To pin one protocol regardless of what the client sends, set ",(0,i.jsx)(n.code,{children:"realtime_protocol"})," on the deployment or ",(0,i.jsx)(n.code,{children:"LITELLM_AZURE_REALTIME_PROTOCOL"})," in the proxy's environment. The deployment setting wins over the environment variable, and both win over the client header. The realtime health check (",(0,i.jsx)(n.code,{children:"/health"})," on a ",(0,i.jsx)(n.code,{children:"mode: realtime"})," deployment, and the Admin UI's Test Connect) has no client header to read, so it probes the GA endpoint unless one of those pins the protocol"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-yaml",children:"model_list:\n - model_name: azure-gpt-realtime\n litellm_params:\n model: azure/gpt-realtime\n api_key: os.environ/AZURE_API_KEY\n api_base
1: os.environ/AZURE_API_BASE\n realtime_protocol: beta # or GA\n"})}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-bash",children:"export LITELLM_AZURE_REALTIME_PROTOCOL=beta # or GA\n"})}),"\n",(0,i.jsx)(n.h2,{id:"guardrails",children:"Guardrails"}),"\n",(0,i.jsxs)(n.p,{children:["You can apply ",(0,i.jsx)(n.a,{href:"https://docs.litellm.ai/docs/proxy/guardrails/quick_start",children:"LiteLLM guardrails"})," to realtime sessions."]}),"\n",(0,i.jsx)(n.h3,{id:"set-guardrails-on-a-key-or-team",children:"Set guardrails on a key or team"}),"\n",(0,i.jsx)(n.p,{children:"The easiest production setup: attach guardrails to a virtual key or team so they always apply automatically, without any client-side changes."}),"\n",(0,i.jsxs)(n.p,{children:["See ",(0,i.jsx)(n.a,{href:"https://docs.litellm.ai/docs/proxy/virtual_keys#guardrails",children:"Virtual Keys \u2192 Guardrails"})," and ",(0,i.jsx)(n.a,{href:"https://docs.litellm.ai/docs/proxy/team_budgets",children:"Teams \u2192 Guardrails"}),"."]}),"\n",(0,i.jsx)(n.h3,{id:"pass-guardrails-dynamically-easy-testing",children:"Pass guardrails dynamically (easy testing)"}),"\n",(0,i.jsxs)(n.p,{children:["Pass ",(0,i.jsx)(n.code,{children:"guardrails"})," as a query param when opening the WebSocket.\nUseful for testing guardrails without modifying key/team config."]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-js",children:'// node test.js\nconst WebSocket = require("ws");\n\nconst guardrails = ["your-guardrail-name"]; // comma-separated list\nconst url = `ws://0.0.0.0:4000/v1/realtime?model=openai-gpt-4o-realtime-audio&guardrails=${guardrails.join(",")}`;\n\nconst ws = new WebSocket(url, {\n headers: {\n "Authorization": "Bearer sk-<your-litellm-api-key>",\n },\n});\n\nws.on("open", function open() {\n console.log("Connected \u2014 guardrails active:", guardrails);\n});\n\nws.on("message", function incoming(message) {\n const data = JSON.parse(message);\n if (data.type === "error") {\n // Guardrail block is sent as an error event before the connection closes\n console.error("Guardrail error:", data.error.message);\n }\n});\n\nws.on("close", function close(code, reason) {\n console.log("Closed:", code, reason.toString());\n // code 1011 = blocked by guardrail at pre_call\n});\n'})}),"\n",(0,i.jsx)(n.p,{children:"Or with Python:"}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-python",children:'import asyncio\nimport websockets\n\nasync def main():\n url = "ws://0.0.0.0:4000/v1/realtime?model=openai-gpt-4o-realtime-audio&guardrails=your-guardrail-name"\n async with websockets.connect(\n url,\n additional_headers={"Authorization": "Bearer sk-<your-litellm-api-key>"},\n ) as ws:\n print("Connected \u2014 guardrail active")\n async for msg in ws:\n import json\n data = json.loads(msg)\n if data["type"] == "error":\n print("Guardrail blocked:", data["error"]["message"])\n break\n\nasyncio.run(main())\n'})}),"\n",(0,i.jsxs)(n.p,{children:["When a guardrail blocks the request, the proxy sends an ",(0,i.jsx)(n.code,{children:"error"})," event over the WebSocket and then closes the connection:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-json",children:'{\n "type": "error",\n "error": {\n "type": "guardrail_error",\n "message": "Guardrail blocked this request: <reason>"\n }\n}\n'})}),"\n",(0,i.jsx)(n.h2,{id:"logging",children:"Logging"}),"\n",(0,i.jsx)(n.p,{children:"To prevent requests from being dropped, by default LiteLLM just logs these event types:"}),"\n",(0,i.jsxs)(n.ul,{children:["\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"session.created"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"response.create"})}),"\n",(0,i.jsx)(n.li,{children:(0,i.jsx)(n.code,{children:"response.done"})}),"\n"]}),"\n",(0,i.jsxs)(n.p,{children:["You can override this by setting the ",(0,i.jsx)(n.code,{children:"logged_real_time_event_types"})," parameter in the config. For example:"]}),"\n",(0,i.jsx)(n.pre,{children:(0,i.jsx)(n.code,{className:"language-yaml",children:'litellm_settings:\n logged_real_time_event_types: "*" # Log all events\n ## OR ## \n logged_real_time_event_types: ["session.created", "response.create", "response.done"] # Log only these event types\n'})})]})}function b(e={}){let{wrapper:n}={...(0,s.R)(),...e.components};return n?(0,i.jsx)(n,{...e,children:(0,i.jsx)(I,{...e})}):I(e)}},5400(e,n,l){l.d(n,{A:()=>s});var a=l(74848);l(96540);var i=l(34164);function s({children:e,hidden:n,className:l}){return(0,a.jsx)("div",{role:"tabpanel",className:(0,i.A)("tabItem_Ymn6",l),hidden:n,children:e})}},53720(e,n,l){l.d(n,{A:()=>G});var a=l(74848),i=l(96540),s=l(34164),t=l(65697),r=l(56347),o=l(56650),c=l(9226),d=l(34387),g=l(10426);function I(e){return i.Children.toArray(e).filter(e=>"\n"!==e).map(e=>{if(!e||(0,i.isValidElement)(e)&&function(e){let{props:n}=e;return!!n&&"object"==typeof n&&"value"in n}(e))return e;throw Error(`Docusaurus error: Bad <Tabs>
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Line numbers count LF bytes from the start of the resource, as the search results do. Vendor segments are library code the classifier recognised; they are stored but not indexed. Bytes are shown as Latin1 characters, one per byte.