telnyx-ai-assistants-c…
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
Claude Code
$ npx -y skills add team-telnyx/ai --skill telnyx-ai-assistants-python --agent claude-code
Codex
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a codex -y
Cursor
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a cursor -y
Gemini CLI
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a gemini-cli -y
GitHub Copilot
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a github-copilot -y
OpenCode
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a opencode -y
Windsurf
$ npx skills add team-telnyx/ai --skill telnyx-ai-assistants-python -a windsurf -y
name: telnyx-ai-assistants-python description: >- AI voice assistants with custom instructions, knowledge bases, and tool integrations. metadata: author: telnyx product: ai-assistants language: python generated_by: telnyx-openapi-pipeline contract: v2
<!-- Auto-generated from Telnyx OpenAPI specs. Do not edit. -->
pip install telnyx
import os
from telnyx import Telnyx
client = Telnyx(
api_key=os.environ.get("TELNYX_API_KEY"), # This is the default and can be omitted
public_key=os.environ.get("TELNYX_PUBLIC_KEY"), # Required for client.webhooks.unwrap() (webhook verification)
)All examples below assume `client` is already initialized as shown above.
All API calls can fail with network errors, rate limits (429), validation errors (422), or authentication errors (401). Always handle errors in production code:
import telnyx
try:
assistant = client.ai.assistants.create(
instructions="You are a helpful assistant.",
name="my-resource",
model="openai/gpt-4o",
)
except telnyx.APIConnectionError:
print("Network error — check connectivity and retry")
raise
except telnyx.RateLimitError:
# 429: rate limited — wait, then retry the request (bounded exponential backoff)
import time
time.sleep(1) # Check Retry-After header for actual delay
# ...retry the call here (give up after a few attempts); otherwise re-raise:
raise
except telnyx.APIStatusError as e:
print(f"API error {e.status_code}: {e.message}")
if e.status_code == 422:
print("Validation error — check required fields and formats")
raise # A failed request must never look like success to the callerCommon error codes: `401` invalid API key, `403` insufficient permissions, `404` resource not found, `422` validation error (check field formats), `429` rate limited (retry with exponential backoff).
Do not invent Telnyx parameters, enums, response fields, or webhook fields.
Assistant creation is the entrypoint for any AI assistant integration. Agents need the exact creation method and the top-level fields returned by the SDK.
`client.ai.assistants.create()` — `POST /ai/assistants`
| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `name` | string | Yes | | | `instructions` | string | Yes | System instructions for the assistant. | | `tags` | array[string] | No | Tags associated with the assistant. | | `model` | string | No | ID of the model to use when `external_llm` is not set. | | `tools` | array[object] | No | Deprecated for new integrations. | | ... | | | +28 optional params in [references/api-details.md](references/api-details.md) |
assistant = client.ai.assistants.create(
instructions="You are a helpful assistant.",
name="my-resource",
model="openai/gpt-4o",
)
print(assistant.id)Primary response fields:
Chat is the primary runtime path. Agents need the exact assistant method and the response content field.
`client.ai.assistants.chat()` — `POST /ai/assistants/{assistant_id}/chat`
| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `content` | string | Yes | The message content sent by the client to the assistant | | `conversation_id` | string (UUID) | Yes | A unique identifier for the conversation thread, used to mai... | | `assistant_id` | string (UUID) | Yes | Unique identifier of the assistant. | | `name` | string | No | The optional display name of the user sending the message | | `stream` | boolean | No | When true, the response is streamed as Server-Sent Events (`... |
response = client.ai.assistants.chat(
assistant_id="550e8400-e29b-41d4-a716-446655440000",
content="Tell me a joke about cats",
conversation_id="42b20469-1215-4a9a-8964-c36f66b406f4",
)
print(response.content)Primary response fields:
Test creation is the main validation path for production assistant behavior before deployment.
`client.ai.assistants.tests.create()` — `POST /ai/assistants/tests`
| Parameter | Type | Required | Description | |-----------|------|----------|-------------| | `name` | string | Yes | A descriptive name for the assistant test. | | `destination` | string | Yes | The target destination for the test conversation. | | `instructions` | string | Yes | Detailed instructions that define the test scenario and what... | | `rubric` | array[object] | Yes | Evaluation criteria used to assess the assistant's performan... | | `description` | string | No | Optional detailed description of what this test evaluates an... | | `telnyx_conversation_channel` | object | No | The communication channel through w
This repo is the one-stop shop for AI Agents and AI-first developers building with Telnyx — everything an agent needs to build production-grade applications and manage its account, from signup to funding.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
AI voice assistants with custom instructions, knowledge bases, and tool integrations.
Access Telnyx LLM inference APIs, embeddings, and AI analytics for call insights and summaries. This skill provides REST API…
You MUST use this before any creative work - creating features, building components, adding functionality, modifying behavior, or…
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