> ## Documentation Index > Fetch the complete documentation index at: https://developers.telnyx.com/llms.txt > Use this file to discover all available pages before exploring further. # Assistant Chat > This endpoint allows a client to send a chat message to a specific AI Assistant. The assistant processes the message and returns a relevant reply based on the current conversation context. Refer to the Conversation API to [create a conversation](https://developers.telnyx.com/api-reference/conversations/create-a-conversation), [filter existing conversations](https://developers.telnyx.com/api-reference/conversations/list-conversations), [fetch messages for a conversation](https://developers.telnyx.com/api-reference/conversations/get-conversation-messages), and [manually add messages to a conversation](https://developers.telnyx.com/api-reference/conversations/create-message). ## OpenAPI ````yaml /openapi/source/external/inference/inference-embedding.json post /ai/assistants/{assistant_id}/chat openapi: 3.1.0 info: version: 2.0.0 title: Telnyx API x-latency-category: responsive x-endpoint-cost: light description: SIP trunking, SMS, MMS, Call Control and Telephony Data Services. contact: email: support@telnyx.com servers: - url: https://api.telnyx.com/v2 description: Version 2.0.0 of the Telnyx API security: - bearerAuth: [] tags: - name: Chat description: Generate text with LLMs - name: Assistants description: Configure AI assistant specifications - name: Conversations description: Manage historical AI assistant conversations - name: File-based Text-to-Speech description: Turn audio into text or text into audio. - name: Embeddings description: Embed documents and perform text searches - name: Clusters description: Identify common themes and patterns in your embedded documents - name: Fine Tuning description: Customize LLMs for your unique needs - name: OpenAI Embeddings description: >- OpenAI-compatible embeddings endpoints for generating vector representations of text paths: /ai/assistants/{assistant_id}/chat: post: tags: - Assistants summary: Assistant Chat description: >- This endpoint allows a client to send a chat message to a specific AI Assistant. The assistant processes the message and returns a relevant reply based on the current conversation context. Refer to the Conversation API to [create a conversation](https://developers.telnyx.com/api-reference/conversations/create-a-conversation), [filter existing conversations](https://developers.telnyx.com/api-reference/conversations/list-conversations), [fetch messages for a conversation](https://developers.telnyx.com/api-reference/conversations/get-conversation-messages), and [manually add messages to a conversation](https://developers.telnyx.com/api-reference/conversations/create-message). operationId: assistant_chat_public_assistants__assistant_id__chat_post parameters: - name: assistant_id in: path description: Unique identifier of the assistant. required: true schema: type: string title: Assistant Id requestBody: required: true content: application/json: schema: $ref: '#/components/schemas/AssistantChatReq' responses: '200': description: Successful Response content: application/json: schema: $ref: '#/components/schemas/AssistantChatResponse' '422': description: Validation Error content: application/json: schema: $ref: '#/components/schemas/HTTPValidationError' x-codeSamples: - lang: JavaScript source: |- import Telnyx from 'telnyx'; const client = new Telnyx({ apiKey: process.env['TELNYX_API_KEY'], // This is the default and can be omitted }); const response = await client.ai.assistants.chat('assistant_id', { content: 'Tell me a joke about cats', conversation_id: '42b20469-1215-4a9a-8964-c36f66b406f4', }); console.log(response.content); - lang: Python source: | import os from telnyx import Telnyx client = Telnyx( api_key=os.environ.get("TELNYX_API_KEY"), # This is the default and can be omitted ) response = client.ai.assistants.chat( assistant_id="assistant_id", content="Tell me a joke about cats", conversation_id="42b20469-1215-4a9a-8964-c36f66b406f4", ) print(response.content) - lang: Go source: "package main\n\nimport (\n\t\"context\"\n\t\"fmt\"\n\n\t\"github.com/team-telnyx/telnyx-go\"\n\t\"github.com/team-telnyx/telnyx-go/option\"\n)\n\nfunc main() {\n\tclient := telnyx.NewClient(\n\t\toption.WithAPIKey(\"My API Key\"),\n\t)\n\tresponse, err := client.AI.Assistants.Chat(\n\t\tcontext.TODO(),\n\t\t\"assistant_id\",\n\t\ttelnyx.AIAssistantChatParams{\n\t\t\tContent: \"Tell me a joke about cats\",\n\t\t\tConversationID: \"42b20469-1215-4a9a-8964-c36f66b406f4\",\n\t\t},\n\t)\n\tif err != nil {\n\t\tpanic(err.Error())\n\t}\n\tfmt.Printf(\"%+v\\n\", response.Content)\n}\n" - lang: Java source: |- package com.telnyx.sdk.example; import com.telnyx.sdk.client.TelnyxClient; import com.telnyx.sdk.client.okhttp.TelnyxOkHttpClient; import com.telnyx.sdk.models.ai.assistants.AssistantChatParams; import com.telnyx.sdk.models.ai.assistants.AssistantChatResponse; public final class Main { private Main() {} public static void main(String[] args) { TelnyxClient client = TelnyxOkHttpClient.fromEnv(); AssistantChatParams params = AssistantChatParams.builder() .assistantId("assistant_id") .content("Tell me a joke about cats") .conversationId("42b20469-1215-4a9a-8964-c36f66b406f4") .build(); AssistantChatResponse response = client.ai().assistants().chat(params); } } - lang: Ruby source: |- require "telnyx" telnyx = Telnyx::Client.new(api_key: "My API Key") response = telnyx.ai.assistants.chat( "assistant_id", content: "Tell me a joke about cats", conversation_id: "42b20469-1215-4a9a-8964-c36f66b406f4" ) puts(response) - lang: PHP source: >- ai->assistants->chat( 'assistant_id', content: 'Tell me a joke about cats', conversationID: '42b20469-1215-4a9a-8964-c36f66b406f4', name: 'Charlie', ); var_dump($response); } catch (APIException $e) { echo $e->getMessage(); } - lang: CLI source: |- telnyx ai:assistants chat \ --api-key 'My API Key' \ --assistant-id assistant_id \ --content 'Tell me a joke about cats' \ --conversation-id 42b20469-1215-4a9a-8964-c36f66b406f4 components: schemas: AssistantChatReq: properties: content: type: string title: Content description: The message content sent by the client to the assistant example: Tell me a joke about cats name: type: string title: Name description: The optional display name of the user sending the message example: Charlie conversation_id: type: string title: Conversation Id description: >- A unique identifier for the conversation thread, used to maintain context example: 42b20469-1215-4a9a-8964-c36f66b406f4 stream: type: boolean title: Stream description: >- When true, the response is streamed as Server-Sent Events (`text/event-stream`): `delta` events carry content fragments as they are generated, a final `done` event carries the full content plus `whatsapp_template`, and a terminal `error` event reports failures that happen after streaming started. When false (default), the response is a single JSON object. default: false type: object required: - content - conversation_id title: AssistantChatReq AssistantChatResponse: properties: content: type: string title: Content description: >- The assistant's generated response based on the input message and context. example: >- Why did the cat sit on the computer? Because it wanted to keep an eye on the mouse! type: object required: - content title: AssistantChatResponse HTTPValidationError: properties: detail: items: $ref: '#/components/schemas/ValidationError' type: array title: Detail type: object title: HTTPValidationError example: detail: - loc: - body - name msg: Field required type: missing ValidationError: properties: loc: items: anyOf: - type: string - type: integer type: array title: Location msg: type: string title: Message type: type: string title: Error Type type: object required: - loc - msg - type title: ValidationError securitySchemes: bearerAuth: type: http scheme: bearer ````