> ## Documentation Index > Fetch the complete documentation index at: https://docs.tavus.io/llms.txt > Use this file to discover all available pages before exploring further. # Get Persona > This endpoint returns a single persona by its unique identifier. ## OpenAPI ````yaml get /v2/personas/{persona_id} openapi: 3.0.3 info: title: Tavus Developer API Collection version: 1.0.0 contact: {} servers: - url: https://tavusapi.com security: - apiKey: [] tags: - name: Videos - name: Replicas - name: Conversations - name: Personas - name: Replacements - name: Transcriptions - name: Documents paths: /v2/personas/{persona_id}: parameters: - name: persona_id in: path required: true description: The unique identifier of the persona. schema: type: string example: pcb7a34da5fe get: tags: - Personas summary: Get Persona description: | This endpoint returns a single persona by its unique identifier. operationId: getPersona responses: '200': description: '' content: application/json: schema: type: object properties: data: type: array items: type: object properties: persona_id: type: string description: A unique identifier for the persona. example: pcb7a34da5fe persona_name: type: string description: A name for the persona. example: Life Coach system_prompt: type: string description: The system prompt that will be used by the llm. example: >- As a Life Coach, you are a dedicated professional who specializes in... default_replica_id: type: string example: rf4e9d9790f0 description: >- The default replica_id associated with this persona if one exists. document_ids: type: array description: >- Array of document IDs that the persona has access to. These documents will be available to the persona in all their conversations. The document_ids are returned in the response of the [Get Document](/api-reference/documents/get-document) and the [Create Document](/api-reference/documents/create-document) endpoints. items: type: string example: - d1234567890 - d2468101214 document_tags: type: array description: >- Array of document tags that the persona has access to. Documents matching these tags will be available to the persona in all their conversations. items: type: string example: - product_info - company_policies layers: type: object properties: llm: type: object properties: model: type: string description: The model name that will be used by the llm. base_url: type: string description: >- The base URL for the OpenAI compatible endpoint if you are using your own llm. example: your-base-url api_key: type: string description: >- The API key for the OpenAI compatible endpoint if you are using your own llm. example: your-api-key tools: type: array description: Optional tools to provide to your custom LLM example: - type: function function: name: get_current_weather description: >- Get the current weather in a given location parameters: type: object properties: location: type: string description: >- The city and state, e.g. San Francisco, CA unit: type: string enum: - celsius - fahrenheit required: - location headers: type: object description: >- Optional headers to provide to your custom LLM example: Authorization: Bearer your-api-key extra_body: type: object description: > Optional parameters to customize the LLM request. For Tavus-hosted models, you can pass `temperature` and `top_p`: - `temperature`: Controls randomness in the model's output. Range typically 0.0 to 2.0. Lower values make output more deterministic and focused, higher values make it more creative and varied. - `top_p`: Controls diversity via nucleus sampling. Range 0.0 to 1.0. Lower values make output more focused on high-probability tokens, higher values allow more diverse token selection. For custom LLMs, you can pass any parameters that your LLM provider supports (e.g., `temperature`, `top_p`, `frequency_penalty`, etc.). example: temperature: 0.7 top_p: 0.9 tts: type: object properties: api_key: type: string description: >- The API key for the chosen TTS provider. Only required when using private voices. example: your-api-key tts_engine: type: string description: The TTS engine that will be used. enum: - cartesia - elevenlabs external_voice_id: type: string description: >- The voice ID used for the TTS engine when you want to customize your replica's voice. Choose from Cartesia's stock voices by referring to their [Voice Catalog](https://docs.cartesia.ai/api-reference/voices/list), or if you want more options you can consider [ElevenLabs](https://elevenlabs.io/docs/api-reference/voices/get-all). example: external-voice-id voice_settings: type: object description: > Optional voice settings to customize TTS behavior. For Cartesia we support inline Cartesia SSML settings (https://docs.cartesia.ai/build-with-cartesia/sonic-3/ssml-tags). For ElevenLabs we support: speed (0.7–1.2), stability (0.0–1.0), similarity_boost (0.0–1.0), style (0.0–1.0), use_speaker_boost (boolean). See https://elevenlabs.io/docs/api-reference/voices/settings/get. example: speed: 0.5 emotion: - positivity:high - curiosity tts_emotion_control: type: boolean description: >- If true, the TTS engine will be able to control the emotion of the voice. Defaults to true. example: true default: true tts_model_name: type: string description: >- The model name that will be used by the TTS engine. Please double check this with the TTS provider you are using to ensure valid model names. example: sonic-3 perception: type: object properties: perception_model: type: string description: >- The perception model to use. `raven-1` (default and recommended) provides real-time emotional understanding from user audio, more natural and human-like interactions, plus all visual capabilities from raven-0. `raven-0` (legacy settings [here](/sections/troubleshooting#migration-from-legacy-perception-to-raven-1)) offers advanced visual perception only. `off` disables all perception. enum: - raven-1 - raven-0 - 'off' default: raven-1 example: raven-1 visual_awareness_queries: type: array description: >- Custom queries that Raven continuously monitors in the visual stream. These provide ambient visual context without requiring explicit prompting. items: type: string example: - Is the user showing an ID card? - >- Does the user appear distressed or uncomfortable? visual_tool_prompt: type: string description: >- A prompt that details how and when to use visual tools based on what Raven sees. This helps the replica understand the context of the visual tools. example: >- You have a tool to notify the system when an ID card is detected, named `notify_if_id_shown`. You MUST use this tool when a form of ID is detected. visual_tools: type: array description: >- Tools that can be triggered based on visual context, enabling automated actions in response to visual cues. items: type: object properties: name: type: string description: The name of the tool to be called. description: type: string description: >- A description of what the tool does and when it should be called. example: - type: function function: name: notify_if_id_shown description: >- Use this function when a drivers license or passport is detected in the image with high confidence. After collecting the ID, internally use final_ask() parameters: type: object properties: id_type: type: string description: best guess on what type of ID it is required: - id_type audio_awareness_queries: type: array description: >- Custom queries that Raven-1 continuously monitors in the audio stream. These provide ambient audio context such as user tone and emotional state. Only available with `raven-1`. items: type: string example: - >- Does the user sound frustrated or confused? - >- Is the user speaking quickly as if in a hurry? audio_tool_prompt: type: string description: >- A prompt that details how and when to use audio tools based on what Raven-1 hears. Only available with `raven-1`. example: >- You have a tool to escalate to a human agent when the user sounds very frustrated, named `escalate_to_human`. Use this tool when detecting sustained frustration. audio_tools: type: array description: >- Tools that can be triggered based on audio analysis, enabling automated actions in response to user tone and emotion. Only available with `raven-1`. items: type: object properties: name: type: string description: The name of the tool to be called. description: type: string description: >- A description of what the tool does and when it should be called. example: - type: function function: name: escalate_to_human description: >- Escalate the conversation to a human agent when user frustration is detected parameters: type: object properties: reason: type: string description: The reason for escalation required: - reason stt: type: object description: > **Note**: Turn-taking is now configured on the [Conversational Flow layer](/sections/conversational-video-interface/persona/conversational-flow). properties: stt_engine: type: string description: >- The STT engine that will be used. `tavus-turbo` is our lowest-latency model, but `tavus-advanced` provides higher transcription accuracy. Please note that non-English languages will default to `tavus-advanced` if not specified. enum: - tavus-turbo - tavus-advanced hotwords: type: string description: >- The hotwords that will be used for the STT engine. example: This is a hotword example created_at: type: string description: The date and time the persona was created. example: '' updated_at: type: string description: >- The date and time of when the persona was last updated. '400': description: Bad Request content: application/json: schema: type: object properties: error: type: string description: The error message. example: Invalid persona_id '401': description: UNAUTHORIZED content: application/json: schema: type: object properties: message: type: string description: The error message. example: Invalid access token security: - apiKey: [] components: securitySchemes: apiKey: type: apiKey in: header name: x-api-key ```` Built with [Mintlify](https://mintlify.com).