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We Open-Sourced Our AI Calling Framework (So You Don't Waste 2-3 Months)

#opensource #ai #agents #python

Siphon

Three months.
That’s how long many teams spend building telephony infrastructure before writing a single line of actual conversation logic for an AI voice agent.

Not because the AI was hard.
Because telephony is brutal.

Today, we’re open-sourcing the solution so you don’t have to go through the same pain.

The Hidden Problem with AI Calling Agents

Building an AI calling agent sounds straightforward:

  • Use an LLM
  • Add speech-to-text
  • Add text-to-speech
  • Connect it to a phone number

In reality, that’s where most teams hit a wall.

To make real phone calls, you end up dealing with:

  • SIP trunks & PSTN providers
  • Low-latency, bidirectional audio
  • Real-time orchestration of STT, LLM, and TTS
  • Call state, interruptions, transfers
  • Scaling, monitoring, recordings, persistence

The result?
Most teams spend weeks or months on infrastructure before they ever touch the conversation itself.

We did too. And eventually asked:

“Why is building voice AI still this hard?”

Introducing Siphon

Siphon is an open-source Python framework that handles the telephony complexity for you, so you can focus on building great conversations.

Here’s what a complete AI receptionist looks like with Siphon:

from siphon.agent import Agent
from siphon.plugins import openai, cartesia, deepgram

agent = Agent(
    agent_name="receptionist",
    llm=openai.LLM(model="gpt-4"),
    tts=cartesia.TTS(voice="helpful-assistant"),
    stt=deepgram.STT(model="nova-2"),
    system_instructions="""
    You are a friendly receptionist for Acme Corp.
    Help callers schedule appointments or route them correctly.
    """
)

if __name__ == "__main__":
    agent.start()
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Run this, and your agent can answer real phone calls via any SIP provider (Twilio, Telnyx, etc.).

What Siphon Handles for You

  • 🔌 SIP & PSTN connectivity
    Works with any SIP provider, no FreeSWITCH pain.

  • ⚡ Real-time audio pipeline
    Built on LiveKit with streaming audio and sub-500ms voice-to-voice latency.

  • 🤖 AI orchestration
    Plug-and-play support for LLMs, STT, and TTS.

Swap providers with a single line:

  llm=anthropic.LLM(model="claude-3-5-sonnet")
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  • 📈 Production-ready by default Auto-scaling, call recordings, transcripts, state handling, and observability.

Quick Start

Install:

pip install siphon-ai
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Create an agent:

from siphon.agent import Agent
from siphon.plugins import openai, cartesia, deepgram

agent = Agent(
    agent_name="my_first_agent",
    llm=openai.LLM(),
    tts=cartesia.TTS(),
    stt=deepgram.STT(),
    system_instructions="You are a helpful assistant.",
)

agent.start()
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That’s it.
Your agent is live and answering phone calls.

(Full setup, outbound calling, and advanced examples are in the docs.)

Why We Open-Sourced It

We could’ve kept Siphon proprietary or turned it into a closed SaaS.

But we believe voice AI shouldn’t be locked behind massive infrastructure effort.

Siphon is:

  • Apache 2.0 licensed
  • Provider-agnostic
  • Fully self-hostable
  • No vendor lock-in

Use it commercially, modify it, or build on top of it.

What You Can Build

  • 📞 Customer support agents
  • 📅 Appointment scheduling
  • 💼 Sales qualification
  • 📊 Surveys & feedback collection
  • 🏥 Healthcare intake systems

If it involves phone calls and conversations, Siphon handles the hard parts.

Get Involved

⭐ GitHub: https://github.com/blackdwarftech/siphon
📖 Docs: https://siphon.blackdwarf.in/docs
🐛 Issues & feature requests welcome
🤝 PRs encouraged

We’re building Siphon in public and would love community feedback.

If you’ve ever thought

“I wish building AI calling agents was simpler”

— give Siphon a try.

Built by BLACKDWARF
Mission: Democratize complex technologies for developers.

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