telnyx-ai-assistants-python

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Telnyx AI Assistants - Python

Telnyx AI 助手 - Python

Installation

安装

bash

pip install telnyx

bash

pip install telnyx

Setup

配置

python

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.

python

import os
from telnyx import Telnyx

client = Telnyx(
    api_key=os.environ.get("TELNYX_API_KEY"),  # 这是默认配置，可以省略
)

以下所有示例均假设

client

已按照上述方式完成初始化。

Error Handling

错误处理

All API calls can fail with network errors, rate limits (429), validation errors (422), or authentication errors (401). Always handle errors in production code:

python

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:

invalid API key,

insufficient permissions,

resource not found,

validation error (check field formats),

rate limited (retry with exponential backoff).

所有API调用都可能因网络错误、速率限制(429)、校验错误(422)或认证错误(401)失败。生产环境代码中请务必处理错误：

python

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)  # 请查看Retry-After header获取实际需要延迟的时间

except telnyx.APIStatusError as e:
    print(f"API error {e.status_code}: {e.message}")
    if e.status_code == 422:
        print("校验错误 — 请检查必填字段和格式")

常见错误码：

API密钥无效，

权限不足，

资源未找到，

校验错误（请检查字段格式），

速率受限（请使用指数退避重试）。

Important Notes

重要注意事项

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
```
.

电话号码必须采用E.164格式（例如
```
+13125550001
```
），包含
```
+
```
前缀和国家码，不得包含空格、短横线或括号。
分页： 列表方法返回自动分页的迭代器，使用
```
for item in page_result:
```
即可自动遍历所有分页。
模型可用性因账号而异。如果某个模型返回422 "not available for inference"，请使用
```
client.ai.assistants.list()
```
查找可用模型。常用可用模型：
```
openai/gpt-4o
```
、
```
Qwen/Qwen3-235B-A22B
```
。

Reference Use Rules

参考使用规则

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

If the parameter, enum, or response field you need is not shown inline in this skill, read references/api-details.md before writing code.
Before using any operation in
```
## Additional Operations
```
, read the optional-parameters section and the response-schemas section.

请勿自行编造Telnyx参数、枚举值、响应字段或Webhook字段。

如果你需要的参数、枚举值或响应字段未在本skill中明确展示，请在编写代码前阅读references/api-details.md。
在使用
```
## 附加操作
```
中的任何接口前，请阅读可选参数章节和响应结构章节。

Core Tasks

核心任务

Create an assistant

创建助手

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
`model`	string	Yes	ID of the model to use.
`instructions`	string	Yes	System instructions for the assistant.
`tools`	array[object]	No	The tools that the assistant can use.
`tool_ids`	array[string]	No
`description`	string	No
...			+12 optional params in references/api-details.md

python

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
```

助手创建是所有AI助手集成的入口。Agent需要使用准确的创建方法和SDK返回的顶层字段。

client.ai.assistants.create()

—

POST /ai/assistants

参数	类型	必填	描述
`name`	string	是
`model`	string	是	要使用的模型ID。
`instructions`	string	是	给助手的系统指令。
`tools`	array[object]	否	助手可以使用的工具。
`tool_ids`	array[string]	否
`description`	string	否
...			还有12个可选参数，详见references/api-details.md

python

assistant = client.ai.assistants.create(
    instructions="You are a helpful assistant.",
    model="openai/gpt-4o",
    name="my-resource",
)
print(assistant.id)

主要响应字段：

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

Chat with an assistant

与助手对话

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
`name`	string	No	The optional display name of the user sending the message

python

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
```

对话是核心运行流程。Agent需要使用准确的助手方法和响应内容字段。

client.ai.assistants.chat()

—

POST /ai/assistants/{assistant_id}/chat

参数	类型	必填	描述
`content`	string	是	客户端发送给助手的消息内容
`conversation_id`	string (UUID)	是	对话线程的唯一标识符，用于维护上下文...
`assistant_id`	string (UUID)	是
`name`	string	否	发送消息的用户的可选显示名称

python

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)

主要响应字段：

```
response.content
```

Create an assistant test

创建助手测试

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 which the test will be con...
`max_duration_seconds`	integer	No	Maximum duration in seconds that the test conversation shoul...
...			+1 optional params in references/api-details.md

python

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
```

测试创建是生产环境助手部署前验证行为的主要途径。

client.ai.assistants.tests.create()

—

POST /ai/assistants/tests

参数	类型	必填	描述
`name`	string	是	助手测试的描述性名称。
`destination`	string	是	测试对话的目标地址。
`instructions`	string	是	定义测试场景和测试规则的详细指令...
`rubric`	array[object]	是	评估助手表现的评价标准...
`description`	string	否	可选的详细描述，说明该测试评估的内容...
`telnyx_conversation_channel`	object	否	执行测试使用的通信渠道...
`max_duration_seconds`	integer	否	测试对话的最大持续时长（秒）...
...			还有1个可选参数，详见references/api-details.md

python

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)

主要响应字段：

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

Important Supporting Operations

重要支持操作

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

当上述核心任务接近你的业务流程，但你需要通用的变体或后续步骤时，请使用这些接口。

Get an assistant

获取助手详情

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

client.ai.assistants.retrieve()

—

GET /ai/assistants/{assistant_id}

Parameter	Type	Required	Description
`assistant_id`	string (UUID)	Yes
`call_control_id`	string (UUID)	No
`fetch_dynamic_variables_from_webhook`	boolean	No
`from_`	string (E.164)	No
...			+1 optional params in references/api-details.md

python

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
```

在更新、删除或做出控制流决策前获取当前状态。

client.ai.assistants.retrieve()

—

GET /ai/assistants/{assistant_id}

参数	类型	必填	描述
`assistant_id`	string (UUID)	是
`call_control_id`	string (UUID)	否
`fetch_dynamic_variables_from_webhook`	boolean	否
`from_`	string (E.164)	否
...			还有1个可选参数，详见references/api-details.md

python

assistant = client.ai.assistants.retrieve(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
)
print(assistant.id)

主要响应字段：

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

Update an assistant

更新助手

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

client.ai.assistants.update()

—

POST /ai/assistants/{assistant_id}

Parameter	Type	Required	Description
`assistant_id`	string (UUID)	Yes
`name`	string	No
`model`	string	No	ID of the model to use.
`instructions`	string	No	System instructions for the assistant.
...			+16 optional params in references/api-details.md

python

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
```

当核心任务未覆盖该流程时，创建或配置额外资源。

client.ai.assistants.update()

—

POST /ai/assistants/{assistant_id}

参数	类型	必填	描述
`assistant_id`	string (UUID)	是
`name`	string	否
`model`	string	否	要使用的模型ID。
`instructions`	string	否	给助手的系统指令。
...			还有16个可选参数，详见references/api-details.md

python

assistant = client.ai.assistants.update(
    assistant_id="550e8400-e29b-41d4-a716-446655440000",
)
print(assistant.id)

主要响应字段：

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

List assistants

列出助手

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

client.ai.assistants.list()

—

GET /ai/assistants

python

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
```

在修改资源前查看可用资源或选择现有资源。

client.ai.assistants.list()

—

GET /ai/assistants

python

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

响应包装结构：

条目:
```
assistants_list.data
```

主要条目字段：

```
id
```
```
name
```
```
created_at
```
```
description
```
```
dynamic_variables
```
```
dynamic_variables_webhook_url
```

Import assistants from external provider

从外部提供商导入助手

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

client.ai.assistants.imports()

—

POST /ai/assistants/import

Parameter	Type	Required	Description
`provider`	enum (elevenlabs, vapi, retell)	Yes	The external provider to import assistants from.
`api_key_ref`	string	Yes	Integration secret pointer that refers to the API key for th...
`import_ids`	array[string]	No	Optional list of assistant IDs to import from the external p...

python

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
```

无需从头创建，直接从外部提供商导入现有助手。

client.ai.assistants.imports()

—

POST /ai/assistants/import

参数	类型	必填	描述
`provider`	enum (elevenlabs, vapi, retell)	是	要导入助手的外部提供商。
`api_key_ref`	string	是	指向外部提供商API密钥的集成密钥指针...
`import_ids`	array[string]	否	可选的要从外部提供商导入的助手ID列表...

python

assistants_list = client.ai.assistants.imports(
    api_key_ref="my-openai-key",
    provider="elevenlabs",
)
print(assistants_list.data)

响应包装结构：

条目:
```
assistants_list.data
```

主要条目字段：

```
id
```
```
name
```
```
created_at
```
```
description
```
```
dynamic_variables
```
```
dynamic_variables_webhook_url
```

Get All Tags

获取所有标签

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

client.ai.assistants.tags.list()

—

GET /ai/assistants/tags

python

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

Primary response fields:

```
tags.tags
```

在修改资源前查看可用资源或选择现有资源。

client.ai.assistants.tags.list()

—

GET /ai/assistants/tags

python

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

主要响应字段：

```
tags.tags
```

List assistant tests with pagination

分页列出助手测试

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

client.ai.assistants.tests.list()

—

GET /ai/assistants/tests

Parameter	Type	Required	Description
`test_suite`	string	No	Filter tests by test suite name
`telnyx_conversation_channel`	string	No	Filter tests by communication channel (e.g., 'web_chat', 'sm...
`destination`	string	No	Filter tests by destination (phone number, webhook URL, etc....
...			+1 optional params in references/api-details.md

python

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
```

在修改资源前查看可用资源或选择现有资源。

client.ai.assistants.tests.list()

—

GET /ai/assistants/tests

参数	类型	必填	描述
`test_suite`	string	否	按测试套件名称筛选测试
`telnyx_conversation_channel`	string	否	按通信渠道筛选测试（例如'web_chat'、'sm...）
`destination`	string	否	按目标地址筛选测试（电话号码、Webhook URL等...）
...			还有1个可选参数，详见references/api-details.md

python

page = client.ai.assistants.tests.list()
page = page.data[0]
print(page.test_id)

响应包装结构：

条目:
```
page.data
```
分页信息:
```
page.meta
```

主要条目字段：

```
name
```
```
created_at
```
```
description
```
```
destination
```
```
instructions
```
```
max_duration_seconds
```

Get all test suite names

获取所有测试套件名称

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

client.ai.assistants.tests.test_suites.list()

—

GET /ai/assistants/tests/test-suites

python

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

Response wrapper:

items:
```
test_suites.data
```

Primary item fields:

```
data
```

在修改资源前查看可用资源或选择现有资源。

client.ai.assistants.tests.test_suites.list()

—

GET /ai/assistants/tests/test-suites

python

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

响应包装结构：

条目:
```
test_suites.data
```

主要条目字段：

```
data
```

Get test suite run history

获取测试套件运行历史

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

Parameter	Type	Required	Description
`suite_name`	string	Yes
`test_suite_run_id`	string (UUID)	No	Filter runs by specific suite execution batch ID
`status`	string	No	Filter runs by execution status (pending, running, completed...
`page`	object	No	Consolidated page parameter (deepObject style).

python

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
```

在更新、删除或做出控制流决策前获取当前状态。

client.ai.assistants.tests.test_suites.runs.list()

—

GET /ai/assistants/tests/test-suites/{suite_name}/runs

参数	类型	必填	描述
`suite_name`	string	是
`test_suite_run_id`	string (UUID)	否	按特定套件执行批次ID筛选运行记录
`status`	string	否	按执行状态筛选运行记录（pending、running、completed...）
`page`	object	否	统一分页参数（deepObject格式）。

python

page = client.ai.assistants.tests.test_suites.runs.list(
    suite_name="my-test-suite",
)
page = page.data[0]
print(page.run_id)

响应包装结构：

条目:
```
page.data
```
分页信息:
```
page.meta
```

主要条目字段：

```
status
```
```
created_at
```
```
updated_at
```
```
completed_at
```
```
conversation_id
```
```
conversation_insights_id
```

Additional Operations

附加操作

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.

Operation	SDK method	Endpoint	Use when	Required params
Trigger test suite execution	`client.ai.assistants.tests.test_suites.runs.trigger()`	`POST /ai/assistants/tests/test-suites/{suite_name}/runs`	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	`suite_name`
Get assistant test by ID	`client.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 test	`client.ai.assistants.tests.update()`	`PUT /ai/assistants/tests/{test_id}`	Modify an existing resource without recreating it.	`test_id`
Delete an assistant test	`client.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 test	`client.ai.assistants.tests.runs.list()`	`GET /ai/assistants/tests/{test_id}/runs`	Fetch the current state before updating, deleting, or making control-flow decisions.	`test_id`
Trigger a manual test run	`client.ai.assistants.tests.runs.trigger()`	`POST /ai/assistants/tests/{test_id}/runs`	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	`test_id`
Get specific test run details	`client.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 assistant	`client.ai.assistants.delete()`	`DELETE /ai/assistants/{assistant_id}`	Remove, detach, or clean up an existing resource.	`assistant_id`
Get Canary Deploy	`client.ai.assistants.canary_deploys.retrieve()`	`GET /ai/assistants/{assistant_id}/canary-deploys`	Fetch the current state before updating, deleting, or making control-flow decisions.	`assistant_id`
Create Canary Deploy	`client.ai.assistants.canary_deploys.create()`	`POST /ai/assistants/{assistant_id}/canary-deploys`	Create or provision an additional resource when the core tasks do not cover this flow.	`versions` , `assistant_id`
Update Canary Deploy	`client.ai.assistants.canary_deploys.update()`	`PUT /ai/assistants/{assistant_id}/canary-deploys`	Modify an existing resource without recreating it.	`versions` , `assistant_id`
Delete Canary Deploy	`client.ai.assistants.canary_deploys.delete()`	`DELETE /ai/assistants/{assistant_id}/canary-deploys`	Remove, detach, or clean up an existing resource.	`assistant_id`
Assistant Sms Chat	`client.ai.assistants.send_sms()`	`POST /ai/assistants/{assistant_id}/chat/sms`	Run assistant chat over SMS instead of direct API chat.	`from_` , `to` , `assistant_id`
Clone Assistant	`client.ai.assistants.clone()`	`POST /ai/assistants/{assistant_id}/clone`	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	`assistant_id`
List scheduled events	`client.ai.assistants.scheduled_events.list()`	`GET /ai/assistants/{assistant_id}/scheduled_events`	Fetch the current state before updating, deleting, or making control-flow decisions.	`assistant_id`
Create a scheduled event	`client.ai.assistants.scheduled_events.create()`	`POST /ai/assistants/{assistant_id}/scheduled_events`	Create 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 event	`client.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 event	`client.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 Tag	`client.ai.assistants.tags.add()`	`POST /ai/assistants/{assistant_id}/tags`	Create or provision an additional resource when the core tasks do not cover this flow.	`tag` , `assistant_id`
Remove Assistant Tag	`client.ai.assistants.tags.remove()`	`DELETE /ai/assistants/{assistant_id}/tags/{tag}`	Remove, detach, or clean up an existing resource.	`assistant_id` , `tag`
Get assistant texml	`client.ai.assistants.get_texml()`	`GET /ai/assistants/{assistant_id}/texml`	Fetch the current state before updating, deleting, or making control-flow decisions.	`assistant_id`
Add Assistant Tool	`client.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 Tool	`client.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 Tool	`client.ai.assistants.tools.test()`	`POST /ai/assistants/{assistant_id}/tools/{tool_id}/test`	Trigger 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 assistant	`client.ai.assistants.versions.list()`	`GET /ai/assistants/{assistant_id}/versions`	Fetch the current state before updating, deleting, or making control-flow decisions.	`assistant_id`
Get a specific assistant version	`client.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 version	`client.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 version	`client.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 main	`client.ai.assistants.versions.promote()`	`POST /ai/assistants/{assistant_id}/versions/{version_id}/promote`	Trigger a follow-up action in an existing workflow rather than creating a new top-level resource.	`assistant_id` , `version_id`
List MCP Servers	`client.ai.mcp_servers.list()`	`GET /ai/mcp_servers`	Inspect available resources or choose an existing resource before mutating it.	None
Create MCP Server	`client.ai.mcp_servers.create()`	`POST /ai/mcp_servers`	Create or provision an additional resource when the core tasks do not cover this flow.	`name` , `type_` , `url`
Get MCP Server	`client.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 Server	`client.ai.mcp_servers.update()`	`PUT /ai/mcp_servers/{mcp_server_id}`	Modify an existing resource without recreating it.	`mcp_server_id`
Delete MCP Server	`client.ai.mcp_servers.delete()`	`DELETE /ai/mcp_servers/{mcp_server_id}`	Remove, detach, or clean up an existing resource.	`mcp_server_id`
List Tools	`client.ai.tools.list()`	`GET /ai/tools`	Inspect available resources or choose an existing resource before mutating it.	None
Create Tool	`client.ai.tools.create()`	`POST /ai/tools`	Create or provision an additional resource when the core tasks do not cover this flow.	`type_` , `display_name`
Get Tool	`client.ai.tools.retrieve()`	`GET /ai/tools/{tool_id}`	Fetch the current state before updating, deleting, or making control-flow decisions.	`tool_id`
Update Tool	`client.ai.tools.update()`	`PATCH /ai/tools/{tool_id}`	Modify an existing resource without recreating it.	`tool_id`
Delete Tool	`client.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.

请优先使用上述核心任务。下方的操作已在此处索引了准确的SDK方法和必填参数；完整的可选参数、响应结构和低频Webhook payload请查看references/api-details.md。在使用下方任意操作前，请阅读可选参数章节和响应结构章节，请勿猜测缺失字段。

操作	SDK方法	端点	适用场景	必填参数
触发测试套件执行	`client.ai.assistants.tests.test_suites.runs.trigger()`	`POST /ai/assistants/tests/test-suites/{suite_name}/runs`	在现有工作流中触发后续操作，而非创建新的顶层资源。	`suite_name`
根据ID获取助手测试	`client.ai.assistants.tests.retrieve()`	`GET /ai/assistants/tests/{test_id}`	在更新、删除或做出控制流决策前获取当前状态。	`test_id`
更新助手测试	`client.ai.assistants.tests.update()`	`PUT /ai/assistants/tests/{test_id}`	修改现有资源，无需重新创建。	`test_id`
删除助手测试	`client.ai.assistants.tests.delete()`	`DELETE /ai/assistants/tests/{test_id}`	移除、解绑或清理现有资源。	`test_id`
获取特定测试的运行历史	`client.ai.assistants.tests.runs.list()`	`GET /ai/assistants/tests/{test_id}/runs`	在更新、删除或做出控制流决策前获取当前状态。	`test_id`
触发手动测试运行	`client.ai.assistants.tests.runs.trigger()`	`POST /ai/assistants/tests/{test_id}/runs`	在现有工作流中触发后续操作，而非创建新的顶层资源。	`test_id`
获取特定测试运行的详情	`client.ai.assistants.tests.runs.retrieve()`	`GET /ai/assistants/tests/{test_id}/runs/{run_id}`	在更新、删除或做出控制流决策前获取当前状态。	`test_id` , `run_id`
删除助手	`client.ai.assistants.delete()`	`DELETE /ai/assistants/{assistant_id}`	移除、解绑或清理现有资源。	`assistant_id`
获取金丝雀发布配置	`client.ai.assistants.canary_deploys.retrieve()`	`GET /ai/assistants/{assistant_id}/canary-deploys`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id`
创建金丝雀发布配置	`client.ai.assistants.canary_deploys.create()`	`POST /ai/assistants/{assistant_id}/canary-deploys`	当核心任务未覆盖该流程时，创建或配置额外资源。	`versions` , `assistant_id`
更新金丝雀发布配置	`client.ai.assistants.canary_deploys.update()`	`PUT /ai/assistants/{assistant_id}/canary-deploys`	修改现有资源，无需重新创建。	`versions` , `assistant_id`
删除金丝雀发布配置	`client.ai.assistants.canary_deploys.delete()`	`DELETE /ai/assistants/{assistant_id}/canary-deploys`	移除、解绑或清理现有资源。	`assistant_id`
助手短信对话	`client.ai.assistants.send_sms()`	`POST /ai/assistants/{assistant_id}/chat/sms`	通过SMS而非直接API调用运行助手对话。	`from_` , `to` , `assistant_id`
克隆助手	`client.ai.assistants.clone()`	`POST /ai/assistants/{assistant_id}/clone`	在现有工作流中触发后续操作，而非创建新的顶层资源。	`assistant_id`
列出计划事件	`client.ai.assistants.scheduled_events.list()`	`GET /ai/assistants/{assistant_id}/scheduled_events`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id`
创建计划事件	`client.ai.assistants.scheduled_events.create()`	`POST /ai/assistants/{assistant_id}/scheduled_events`	当核心任务未覆盖该流程时，创建或配置额外资源。	`telnyx_conversation_channel` , `telnyx_end_user_target` , `telnyx_agent_target` , `scheduled_at_fixed_datetime` , 还有1个参数
获取计划事件	`client.ai.assistants.scheduled_events.retrieve()`	`GET /ai/assistants/{assistant_id}/scheduled_events/{event_id}`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id` , `event_id`
删除计划事件	`client.ai.assistants.scheduled_events.delete()`	`DELETE /ai/assistants/{assistant_id}/scheduled_events/{event_id}`	移除、解绑或清理现有资源。	`assistant_id` , `event_id`
添加助手标签	`client.ai.assistants.tags.add()`	`POST /ai/assistants/{assistant_id}/tags`	当核心任务未覆盖该流程时，创建或配置额外资源。	`tag` , `assistant_id`
移除助手标签	`client.ai.assistants.tags.remove()`	`DELETE /ai/assistants/{assistant_id}/tags/{tag}`	移除、解绑或清理现有资源。	`assistant_id` , `tag`
获取助手TexML	`client.ai.assistants.get_texml()`	`GET /ai/assistants/{assistant_id}/texml`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id`
添加助手工具	`client.ai.assistants.tools.add()`	`PUT /ai/assistants/{assistant_id}/tools/{tool_id}`	修改现有资源，无需重新创建。	`assistant_id` , `tool_id`
移除助手工具	`client.ai.assistants.tools.remove()`	`DELETE /ai/assistants/{assistant_id}/tools/{tool_id}`	移除、解绑或清理现有资源。	`assistant_id` , `tool_id`
测试助手工具	`client.ai.assistants.tools.test()`	`POST /ai/assistants/{assistant_id}/tools/{tool_id}/test`	在现有工作流中触发后续操作，而非创建新的顶层资源。	`assistant_id` , `tool_id`
获取助手的所有版本	`client.ai.assistants.versions.list()`	`GET /ai/assistants/{assistant_id}/versions`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id`
获取特定助手版本	`client.ai.assistants.versions.retrieve()`	`GET /ai/assistants/{assistant_id}/versions/{version_id}`	在更新、删除或做出控制流决策前获取当前状态。	`assistant_id` , `version_id`
更新特定助手版本	`client.ai.assistants.versions.update()`	`POST /ai/assistants/{assistant_id}/versions/{version_id}`	当核心任务未覆盖该流程时，创建或配置额外资源。	`assistant_id` , `version_id`
删除特定助手版本	`client.ai.assistants.versions.delete()`	`DELETE /ai/assistants/{assistant_id}/versions/{version_id}`	移除、解绑或清理现有资源。	`assistant_id` , `version_id`
将助手版本升级为正式版	`client.ai.assistants.versions.promote()`	`POST /ai/assistants/{assistant_id}/versions/{version_id}/promote`	在现有工作流中触发后续操作，而非创建新的顶层资源。	`assistant_id` , `version_id`
列出MCP服务器	`client.ai.mcp_servers.list()`	`GET /ai/mcp_servers`	在修改资源前查看可用资源或选择现有资源。	无
创建MCP服务器	`client.ai.mcp_servers.create()`	`POST /ai/mcp_servers`	当核心任务未覆盖该流程时，创建或配置额外资源。	`name` , `type_` , `url`
获取MCP服务器	`client.ai.mcp_servers.retrieve()`	`GET /ai/mcp_servers/{mcp_server_id}`	在更新、删除或做出控制流决策前获取当前状态。	`mcp_server_id`
更新MCP服务器	`client.ai.mcp_servers.update()`	`PUT /ai/mcp_servers/{mcp_server_id}`	修改现有资源，无需重新创建。	`mcp_server_id`
删除MCP服务器	`client.ai.mcp_servers.delete()`	`DELETE /ai/mcp_servers/{mcp_server_id}`	移除、解绑或清理现有资源。	`mcp_server_id`
列出工具	`client.ai.tools.list()`	`GET /ai/tools`	在修改资源前查看可用资源或选择现有资源。	无
创建工具	`client.ai.tools.create()`	`POST /ai/tools`	当核心任务未覆盖该流程时，创建或配置额外资源。	`type_` , `display_name`
获取工具	`client.ai.tools.retrieve()`	`GET /ai/tools/{tool_id}`	在更新、删除或做出控制流决策前获取当前状态。	`tool_id`
更新工具	`client.ai.tools.update()`	`PATCH /ai/tools/{tool_id}`	修改现有资源，无需重新创建。	`tool_id`
删除工具	`client.ai.tools.delete()`	`DELETE /ai/tools/{tool_id}`	移除、解绑或清理现有资源。	`tool_id`

如需完整的可选参数、全量响应结构和完整的Webhook payload，请参考references/api-details.md。