#Please help me!!! I am gonna implement AI agent using 11labs. It must say as voice when user send

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dire socketBOT
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AI-generated Answer for night1117123321

You have two supported ways to make an ElevenLabs agent “speak” when the user sends a text message.

Option A — Use the Conversational AI WebSocket (agent speaks back automatically)

  • Create/configure an Agent in the dashboard to choose model/voice; note its agent_id. You can also fetch/update agent config via the API.
  • Open a WebSocket to wss://api.elevenlabs.io/v1/convai/conversation?agent_id=YOUR_AGENT_ID. For private agents, obtain a signed URL from your server; never expose your API key client‑side.
  • Send the user’s text as a WebSocket message: {"type":"user_message","text":"..."}.
  • Listen for messages. The agent returns:
    • agent_response (text) and
    • audio events with base64 audio. Also read the initial conversation_initiation_metadata to get agent_output_audio_format (e.g., pcm_16000) so you can decode/play it.

Option B — If you already have your own LLM (just synthesize its text to voice)

  • Synchronous HTTP: POST /v1/text-to-speech/{voice_id} with JSON { "text": "...", "model_id": "..." } and choose output_format (e.g., mp3_44100_128). Play the resulting audio file/bytes.
  • Low‑latency streaming over HTTP: use the official Node/Python SDKs’ text-to-speech.stream to consume chunks as they are generated.
  • Real‑time via WebSocket (TTS only): connect to wss://api.elevenlabs.io/v1/text-to-speech/{voice_id}/stream-input?model_id=..., send your text frames, and write out audio chunks as they arrive. For lowest latency, the guide recommends the eleven_flash_v2_5 model and explains buffering controls like chunk_length_schedule and flush.

If you prefer a no‑code frontend

  • The web widget supports “Voice + text” mode so users can type or speak; enable this modality in the widget settings if you want text input with spoken responses. Avoid “Text only mode,” which disables voice output.

Security note

  • For browser apps, proxy any REST calls and use signed WebSocket URLs for private agents; do not ship your xi‑api‑key to the client.

If you tell me your stack (web, iOS/Android, Node/Python), I can point you to the exact snippet to connect, send {"type":"user_message"}, and play the returned audio.

dusky python
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I am gonna building web application using React as frontend and python as backend.

dire socketBOT
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AI-generated Answer for night1117123321

Great—here’s the verified way to wire ElevenLabs Text-to-Speech (TTS) into a React frontend with a Python backend.

Architecture (recommended by docs)

  • Never call ElevenLabs directly from React; keep your xi-api-key on the server and forward requests through your Python backend. Include the key in the xi-api-key header only on the server. (elevenlabs.io)

Choose your voice and model

  • Get a voice_id your backend can use via GET /v1/voices. (elevenlabs.io)
  • Pick a model based on latency/quality needs:
    • eleven_flash_v2_5: ultra‑low latency for conversational uses.
    • eleven_multilingual_v2: highest quality for media.
    • eleven_v3 (Alpha): most expressive, but not for real‑time; API access is limited. See the models overview and model guidance. (elevenlabs.io) help.elevenlabs.io)

Backend (Python) options

  • One‑shot synthesis (returns an audio file): POST /v1/text-to-speech/:voice_id with JSON body containing text, optional model_id, and output_format (e.g., mp3_44100_128). Your backend returns the audio payload to the browser. (elevenlabs.io)
  • Streaming audio (lower perceived latency): POST /v1/text-to-speech/:voice_id/stream. The API streams raw audio bytes over HTTP chunked transfer; the official Python SDK provides helpers to consume the stream. Your backend can relay the stream to the client. (elevenlabs.io)
  • Need timestamps for UI highlighting/sync?
    • HTTP: /with-timestamps returns base64 audio plus character‑level alignment arrays. (elevenlabs.io)
    • Streaming + timestamps: /stream/with-timestamps returns a stream of JSON chunks with base64 audio and alignment. (elevenlabs.io)
  • Real‑time partial text (WebSocket): wss://api.elevenlabs.io/v1/text-to-speech/:voice_id/stream-input (or multi‑stream variant). Supports sending text incrementally and receiving audio chunks; optional sync_alignment, auto_mode, and SSML parsing flags are available. Use only from your backend or a secured environment. (elevenlabs.io)

Request parameters you’ll likely use

  • text: the text to speak. (elevenlabs.io)
  • model_id: pick from models that “can_do_text_to_speech.” (elevenlabs.io)
  • output_format: codec_sampleRate_bitrate (e.g., mp3_44100_128; μ‑law and PCM are available for telephony). (elevenlabs.io) help.elevenlabs.io)
  • voice_settings: optional per‑request overrides (speed, stability, similarity_boost). (elevenlabs.io)
  • language_code: language enforcement currently supported only on Turbo v2.5 and Flash v2.5. (elevenlabs.io)

Frontend (React)

  • Call your Python endpoint, then play the returned audio (file bytes from “convert”, a proxied stream from “stream”, or decode base64 from the “with‑timestamps” endpoints). The API shapes and streaming behavior are documented above. (elevenlabs.io)

SSML and pauses

  • Natural pauses: use <break time="Xs" /> in your text (up to 3s). Phoneme tags are
dusky python
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how to get text from ai response?

dire socketBOT
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AI-generated Answer for night1117123321

Short answer:

  • In real time, read the agent_response event. It carries the assistant’s text.
  • From SDKs, use the message/callback hooks that surface that same text.
  • After the call, fetch the transcript via the Conversations REST API.

How to do it

  • WebSocket (raw):

    • Listen for messages where type === "agent_response". The text is in agent_response_event.agent_response. You may also receive agent_response_correction if the reply was interrupted. (elevenlabs.io)

  • JavaScript/React SDK:

    • Provide an onMessage handler and use the event type to pick out the AI’s text. In chat mode, the SDK surfaces message.type === 'agent_response' with message.text. You can also call conversation.getId() later if you need the ID to fetch history. (elevenlabs.io)
    • If you’re using the React hook (@elevenlabs/react), pass an onMessage option and handle agent messages there. (elevenlabs.io)

  • Python SDK:

    • Pass callback_agent_response to Conversation(...). The SDK invokes it with the agent’s response text. Optional: callback_agent_response_correction handles truncated text after barge‑in. (elevenlabs.io)

  • After the session (server-side/history):

    • GET /v1/convai/conversations/:conversation_id returns transcript[], containing role and message for each turn. Use the conversation ID you got from the SDK (getId) or by listing conversations. (elevenlabs.io)

Related references

Sources:
Client events | ElevenLabs Documentation
JavaScript SDK | ElevenLabs Documentation
React SDK | ElevenLabs Documentation
Python SDK | ElevenLabs Documentation
Get conversation details | ElevenLabs Documentation
Client events | ElevenLabs Documentation
Agent WebSockets | ElevenLabs Documentation
JavaScript SDK | ElevenLabs Documentation
React SDK | ElevenLabs Documentation
Python SDK | ElevenLabs Documentation
Get conversation details | ElevenLabs Documentation

dusky python
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Option A — Use the Conversational AI WebSocket (agent speaks back automatically)
Create/configure an Agent in the dashboard to choose model/voice; note its agent_id. You can also fetch/update agent config via the API.
Open a WebSocket to wss://api.elevenlabs.io/v1/convai/conversation?agent_id=YOUR_AGENT_ID. For private agents, obtain a signed URL from your server; never expose your API key client‑side.
Send the user’s text as a WebSocket message: {"type":"user_message","text":"..."}.
Listen for messages. The agent returns:
agent_response (text) and
audio events with base64 audio. Also read the initial conversation_initiation_metadata to get agent_output_audio_format (e.g., pcm_16000) so you can decode/play it.

Can you give me sample code using react?