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telnyx-ai-assistants-pythontelnyx AI assistants Python 搜索

Agent Skill

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

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CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:telnyx-ai-assistants-python(telnyx AI assistants Python 搜索)
来源仓库:https://github.com/team-telnyx/skills
仓库路径:skills/telnyx-ai-assistants-python
安装命令:
npx skills add https://github.com/team-telnyx/skills --skill telnyx-ai-assistants-python
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/team-telnyx/skills --skill telnyx-ai-assistants-python

简介

辅助 Python 项目开发、测试与依赖管理。

  • 适合阅读代码、定位问题、整理运行命令或分析数据处理逻辑。
  • 需确认项目虚拟环境和依赖版本后使用。
  • 涉及执行脚本或访问外部 API 时应明确输入输出范围。
  • telnyx-ai-assistants-python 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Telnyx AI Assistants - Python

Installation

pip install telnyx

Setup

import os
from telnyx import Telnyx

client = Telnyx(
    api_key=os.environ.get("TELNYX_API_KEY"),  # This is the default and can be omitted
)

All examples below assume client is already initialized as shown above.

Error Handling

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.",
        model="openai/gpt-4o",
        name="my-resource",
    )
except telnyx.APIConnectionError:
    print("Network error — check connectivity and retry")
except telnyx.RateLimitError:
    import time
    time.sleep(1)  # Check Retry-After header for actual delay
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")

Common 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).

Important Notes

  • Phone numbers must be in E.164 format (e.g., +13125550001). Include the + prefix and country code. No spaces, dashes, or parentheses.
  • Pagination: List methods return an auto-paginating iterator. Use for item in page_result: to iterate through all pages automatically.
  • Model availability varies by account. If a model returns 422 "not available for inference", use client.ai.assistants.list() to discover working models. Commonly available: openai/gpt-4o, Qwen/Qwen3-235B-A22B.

Reference Use Rules

Do not invent Telnyx parameters, enums, response fields, or webhook fields.

Core Tasks

Create an assistant

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

ParameterTypeRequiredDescription
namestringYes
modelstringYesID of the model to use.
instructionsstringYesSystem instructions for the assistant.
toolsarray[object]NoThe tools that the assistant can use.
tool_idsarray[string]No
descriptionstringNo
...+12 optional params in references/api-details.md
assistant = client.ai.assistants.create(
    instructions="You are a helpful assistant.",
    model="openai/gpt-4o",
    name="my-resource",
)
print(assistant.id)

Primary response fields:

  • assistant.id
  • assistant.name
  • assistant.model
  • assistant.instructions
  • assistant.created_at
  • assistant.description

Chat with an assistant

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

ParameterTypeRequiredDescription
contentstringYesThe message content sent by the client to the assistant
conversation_idstring (UUID)YesA unique identifier for the conversation thread, used to mai...
assistant_idstring (UUID)Yes
namestringNoThe optional display name of the user sending the message
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:

  • response.content

Create an assistant test

Test creation is the main validation path for production assistant behavior before deployment.

client.ai.assistants.tests.create()POST /ai/assistants/tests

ParameterTypeRequiredDescription
namestringYesA descriptive name for the assistant test.
destinationstringYesThe target destination for the test conversation.
instructionsstringYesDetailed instructions that define the test scenario and what...
rubricarray[object]YesEvaluation criteria used to assess the assistant's performan...
descriptionstringNoOptional detailed description of what this test evaluates an...
telnyx_conversation_channelobjectNoThe communication channel through which the test will be con...
max_duration_secondsintegerNoMaximum duration in seconds that the test conversation shoul...
...+1 optional params in references/api-details.md
assistant_test = client.ai.assistants.tests.create(
    destination="+15551234567",
    instructions="Act as a frustrated customer who received a damaged product. Ask for a refund and escalate if not satisfied with the initial response.",
    name="Customer Support Bot Test",
    rubric=[{
        "criteria": "Assistant responds within 30 seconds",
        "name": "Response Time",
    }, {
        "criteria": "Provides correct product information",
        "name": "Accuracy",
    }],
)
print(assistant_test.test_id)

Primary response fields:

  • assistant_test.test_id
  • assistant_test.name
  • assistant_test.destination
  • assistant_test.created_at
  • assistant_test.instructions
  • assistant_test.description

Important Supporting Operations

Use these when the core tasks above are close to your flow, but you need a common variation or follow-up step.

Get an assistant

Fetch the current state before updating, deleting, or making control-flow decisions.

client.ai.assistants.retrieve()GET /ai/assistants/{assistant_id}

ParameterTypeRequiredDescription
assistant_idstring (UUID)Yes
call_control_idstring (UUID)No
fetch_dynamic_variables_from_webhookbooleanNo
from_string (E.164)No
...+1 optional params in references/api-details.md
assistant = client.ai.assistants.retrieve(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
)
print(assistant.id)

Primary response fields:

  • assistant.id
  • assistant.name
  • assistant.created_at
  • assistant.description
  • assistant.dynamic_variables
  • assistant.dynamic_variables_webhook_url

Update an assistant

Create or provision an additional resource when the core tasks do not cover this flow.

client.ai.assistants.update()POST /ai/assistants/{assistant_id}

ParameterTypeRequiredDescription
assistant_idstring (UUID)Yes
namestringNo
modelstringNoID of the model to use.
instructionsstringNoSystem instructions for the assistant.
...+16 optional params in references/api-details.md
assistant = client.ai.assistants.update(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
)
print(assistant.id)

Primary response fields:

  • assistant.id
  • assistant.name
  • assistant.created_at
  • assistant.description
  • assistant.dynamic_variables
  • assistant.dynamic_variables_webhook_url

List assistants

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.list()GET /ai/assistants

assistants_list = client.ai.assistants.list()
print(assistants_list.data)

Response wrapper:

  • items: assistants_list.data

Primary item fields:

  • id
  • name
  • created_at
  • description
  • dynamic_variables
  • dynamic_variables_webhook_url

Import assistants from external provider

Import existing assistants from an external provider instead of creating from scratch.

client.ai.assistants.imports()POST /ai/assistants/import

ParameterTypeRequiredDescription
providerenum (elevenlabs, vapi, retell)YesThe external provider to import assistants from.
api_key_refstringYesIntegration secret pointer that refers to the API key for th...
import_idsarray[string]NoOptional list of assistant IDs to import from the external p...
assistants_list = client.ai.assistants.imports(
    api_key_ref="my-openai-key",
    provider="elevenlabs",
)
print(assistants_list.data)

Response wrapper:

  • items: assistants_list.data

Primary item fields:

  • id
  • name
  • created_at
  • description
  • dynamic_variables
  • dynamic_variables_webhook_url

Get All Tags

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tags.list()GET /ai/assistants/tags

tags = client.ai.assistants.tags.list()
print(tags.tags)

Primary response fields:

  • tags.tags

List assistant tests with pagination

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tests.list()GET /ai/assistants/tests

ParameterTypeRequiredDescription
test_suitestringNoFilter tests by test suite name
telnyx_conversation_channelstringNoFilter tests by communication channel (e.g., 'web_chat', 'sm...
destinationstringNoFilter tests by destination (phone number, webhook URL, etc....
...+1 optional params in references/api-details.md
page = client.ai.assistants.tests.list()
page = page.data[0]
print(page.test_id)

Response wrapper:

  • items: page.data
  • pagination: page.meta

Primary item fields:

  • name
  • created_at
  • description
  • destination
  • instructions
  • max_duration_seconds

Get all test suite names

Inspect available resources or choose an existing resource before mutating it.

client.ai.assistants.tests.test_suites.list()GET /ai/assistants/tests/test-suites

test_suites = client.ai.assistants.tests.test_suites.list()
print(test_suites.data)

Response wrapper:

  • items: test_suites.data

Primary item fields:

  • data

Get test suite run history

Fetch the current state before updating, deleting, or making control-flow decisions.

client.ai.assistants.tests.test_suites.runs.list()GET /ai/assistants/tests/test-suites/{suite_name}/runs

ParameterTypeRequiredDescription
suite_namestringYes
test_suite_run_idstring (UUID)NoFilter runs by specific suite execution batch ID
statusstringNoFilter runs by execution status (pending, running, completed...
pageobjectNoConsolidated page parameter (deepObject style).
page = client.ai.assistants.tests.test_suites.runs.list(
    suite_name="my-test-suite",
)
page = page.data[0]
print(page.run_id)

Response wrapper:

  • items: page.data
  • pagination: page.meta

Primary item fields:

  • status
  • created_at
  • updated_at
  • completed_at
  • conversation_id
  • conversation_insights_id

Additional Operations

Use the core tasks above first. The operations below are indexed here with exact SDK methods and required params; use references/api-details.md for full optional params, response schemas, and lower-frequency webhook payloads. Before using any operation below, read the optional-parameters section and the response-schemas section so you do not guess missing fields.

OperationSDK methodEndpointUse whenRequired params
Trigger test suite executionclient.ai.assistants.tests.test_suites.runs.trigger()POST /ai/assistants/tests/test-suites/{suite_name}/runsTrigger a follow-up action in an existing workflow rather than creating a new top-level resource.suite_name
Get assistant test by IDclient.ai.assistants.tests.retrieve()GET /ai/assistants/tests/{test_id}Fetch the current state before updating, deleting, or making control-flow decisions.test_id
Update an assistant testclient.ai.assistants.tests.update()PUT /ai/assistants/tests/{test_id}Modify an existing resource without recreating it.test_id
Delete an assistant testclient.ai.assistants.tests.delete()DELETE /ai/assistants/tests/{test_id}Remove, detach, or clean up an existing resource.test_id
Get test run history for a specific testclient.ai.assistants.tests.runs.list()GET /ai/assistants/tests/{test_id}/runsFetch the current state before updating, deleting, or making control-flow decisions.test_id
Trigger a manual test runclient.ai.assistants.tests.runs.trigger()POST /ai/assistants/tests/{test_id}/runsTrigger a follow-up action in an existing workflow rather than creating a new top-level resource.test_id
Get specific test run detailsclient.ai.assistants.tests.runs.retrieve()GET /ai/assistants/tests/{test_id}/runs/{run_id}Fetch the current state before updating, deleting, or making control-flow decisions.test_id, run_id
Delete an assistantclient.ai.assistants.delete()DELETE /ai/assistants/{assistant_id}Remove, detach, or clean up an existing resource.assistant_id
Get Canary Deployclient.ai.assistants.canary_deploys.retrieve()GET /ai/assistants/{assistant_id}/canary-deploysFetch the current state before updating, deleting, or making control-flow decisions.assistant_id
Create Canary Deployclient.ai.assistants.canary_deploys.create()POST /ai/assistants/{assistant_id}/canary-deploysCreate or provision an additional resource when the core tasks do not cover this flow.versions, assistant_id
Update Canary Deployclient.ai.assistants.canary_deploys.update()PUT /ai/assistants/{assistant_id}/canary-deploysModify an existing resource without recreating it.versions, assistant_id
Delete Canary Deployclient.ai.assistants.canary_deploys.delete()DELETE /ai/assistants/{assistant_id}/canary-deploysRemove, detach, or clean up an existing resource.assistant_id
Assistant Sms Chatclient.ai.assistants.send_sms()POST /ai/assistants/{assistant_id}/chat/smsRun assistant chat over SMS instead of direct API chat.from_, to, assistant_id
Clone Assistantclient.ai.assistants.clone()POST /ai/assistants/{assistant_id}/cloneTrigger a follow-up action in an existing workflow rather than creating a new top-level resource.assistant_id
List scheduled eventsclient.ai.assistants.scheduled_events.list()GET /ai/assistants/{assistant_id}/scheduled_eventsFetch the current state before updating, deleting, or making control-flow decisions.assistant_id
Create a scheduled eventclient.ai.assistants.scheduled_events.create()POST /ai/assistants/{assistant_id}/scheduled_eventsCreate or provision an additional resource when the core tasks do not cover this flow.telnyx_conversation_channel, telnyx_end_user_target, telnyx_agent_target, scheduled_at_fixed_datetime, +1 more
Get a scheduled eventclient.ai.assistants.scheduled_events.retrieve()GET /ai/assistants/{assistant_id}/scheduled_events/{event_id}Fetch the current state before updating, deleting, or making control-flow decisions.assistant_id, event_id
Delete a scheduled eventclient.ai.assistants.scheduled_events.delete()DELETE /ai/assistants/{assistant_id}/scheduled_events/{event_id}Remove, detach, or clean up an existing resource.assistant_id, event_id
Add Assistant Tagclient.ai.assistants.tags.add()POST /ai/assistants/{assistant_id}/tagsCreate or provision an additional resource when the core tasks do not cover this flow.tag, assistant_id
Remove Assistant Tagclient.ai.assistants.tags.remove()DELETE /ai/assistants/{assistant_id}/tags/{tag}Remove, detach, or clean up an existing resource.assistant_id, tag
Get assistant texmlclient.ai.assistants.get_texml()GET /ai/assistants/{assistant_id}/texmlFetch the current state before updating, deleting, or making control-flow decisions.assistant_id
Add Assistant Toolclient.ai.assistants.tools.add()PUT /ai/assistants/{assistant_id}/tools/{tool_id}Modify an existing resource without recreating it.assistant_id, tool_id
Remove Assistant Toolclient.ai.assistants.tools.remove()DELETE /ai/assistants/{assistant_id}/tools/{tool_id}Remove, detach, or clean up an existing resource.assistant_id, tool_id
Test Assistant Toolclient.ai.assistants.tools.test()POST /ai/assistants/{assistant_id}/tools/{tool_id}/testTrigger a follow-up action in an existing workflow rather than creating a new top-level resource.assistant_id, tool_id
Get all versions of an assistantclient.ai.assistants.versions.list()GET /ai/assistants/{assistant_id}/versionsFetch the current state before updating, deleting, or making control-flow decisions.assistant_id
Get a specific assistant versionclient.ai.assistants.versions.retrieve()GET /ai/assistants/{assistant_id}/versions/{version_id}Fetch the current state before updating, deleting, or making control-flow decisions.assistant_id, version_id
Update a specific assistant versionclient.ai.assistants.versions.update()POST /ai/assistants/{assistant_id}/versions/{version_id}Create or provision an additional resource when the core tasks do not cover this flow.assistant_id, version_id
Delete a specific assistant versionclient.ai.assistants.versions.delete()DELETE /ai/assistants/{assistant_id}/versions/{version_id}Remove, detach, or clean up an existing resource.assistant_id, version_id
Promote an assistant version to mainclient.ai.assistants.versions.promote()POST /ai/assistants/{assistant_id}/versions/{version_id}/promoteTrigger a follow-up action in an existing workflow rather than creating a new top-level resource.assistant_id, version_id
List MCP Serversclient.ai.mcp_servers.list()GET /ai/mcp_serversInspect available resources or choose an existing resource before mutating it.None
Create MCP Serverclient.ai.mcp_servers.create()POST /ai/mcp_serversCreate or provision an additional resource when the core tasks do not cover this flow.name, type_, url
Get MCP Serverclient.ai.mcp_servers.retrieve()GET /ai/mcp_servers/{mcp_server_id}Fetch the current state before updating, deleting, or making control-flow decisions.mcp_server_id
Update MCP Serverclient.ai.mcp_servers.update()PUT /ai/mcp_servers/{mcp_server_id}Modify an existing resource without recreating it.mcp_server_id
Delete MCP Serverclient.ai.mcp_servers.delete()DELETE /ai/mcp_servers/{mcp_server_id}Remove, detach, or clean up an existing resource.mcp_server_id
List Toolsclient.ai.tools.list()GET /ai/toolsInspect available resources or choose an existing resource before mutating it.None
Create Toolclient.ai.tools.create()POST /ai/toolsCreate or provision an additional resource when the core tasks do not cover this flow.type_, display_name
Get Toolclient.ai.tools.retrieve()GET /ai/tools/{tool_id}Fetch the current state before updating, deleting, or making control-flow decisions.tool_id
Update Toolclient.ai.tools.update()PATCH /ai/tools/{tool_id}Modify an existing resource without recreating it.tool_id
Delete Toolclient.ai.tools.delete()DELETE /ai/tools/{tool_id}Remove, detach, or clean up an existing resource.tool_id

For exhaustive optional parameters, full response schemas, and complete webhook payloads, see references/api-details.md.

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