Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/team-telnyx/ai/telnyx-ai-inference-pythonnpx skills add team-telnyx/ai --skill telnyx-ai-inference-pythongit clone --depth 1 https://github.com/team-telnyx/aiWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/team-telnyx/ai/telnyx-ai-inference-python)<a href="https://agentmods.dev/skills/team-telnyx/ai/telnyx-ai-inference-python"><img src="https://agentmods.dev/badge/skills/team-telnyx/ai/telnyx-ai-inference-python.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5 | $0.00035 | $0.06748 |
| Opus 5 | $0.00017 | $0.03374 |
| Sonnet 5 | $0.00007 | $0.01350 |
| Haiku 4.5 | $0.00003 | $0.00675 |
Grade A, and why
telnyx-ai-inference-python scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 5d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
94% identical to telnyx-ai-inference-curl — 568 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 785 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Telnyx Ai Inference - 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:
result = client.messages.send(to="+13125550001", from_="+13125550002", text="Hello")
except telnyx.APIConnectionError:
print("Network error — check connectivity and retry")
except telnyx.RateLimitError:
# 429: rate limited — wait and retry with exponential backoff
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
- Pagination: List methods return an auto-paginating iterator. Use
for item in page_result:to iterate through all pages automatically.
Transcribe speech to text
Transcribe speech to text. This endpoint is consistent with the OpenAI Transcription API and may be used with the OpenAI JS or Python SDK.
POST /ai/audio/transcriptions
response = client.ai.audio.transcribe(
model="distil-whisper/distil-large-v2",
)
print(response.text)
Returns: duration (number), segments (array[object]), text (string), words (array[object])
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 5d ago First seen · 785 lines · 35 tokens per session scan A a87ac09e33f1
telnyx-ai-inference-python is a skill published in the GitHub repository team-telnyx/ai (212 stars, last pushed yesterday), licensed MIT. It adds 35 tokens to every session and 6,748 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it A with 0 findings. It is 94% identical to telnyx-ai-inference-curl, differing in 568 lines, and is treated as a copy.
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