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LLM-neutral Python agent framework with built-in multi-channel messaging and document automation.

Project description

Agentix

Build production-ready AI agents with any LLM provider โ€” OpenAI, Claude, Gemini, DeepSeek, or your own endpoint.

Agentix is a modular, pure-Python framework designed to scale from solo developer projects to enterprise-grade deployments, with built-in tools, multi-channel integrations, and advanced reasoning control.


๐Ÿš€ Key Features

  • ๐Ÿง  LLM-neutral Works with OpenAI, Anthropic (Claude), Google Gemini, DeepSeek, Ollama, vLLM, LiteLLM

  • ๐Ÿ” True Agent Loop input โ†’ LLM โ†’ tools โ†’ LLM โ†’ result

  • ๐Ÿ›  Built-in Tools Filesystem, shell, web search, task management, sub-agents

  • ๐Ÿ“„ Document Skills (out of the box) PDF, Word, Excel, PowerPoint

  • ๐ŸŒ Multi-channel Gateway Slack, WhatsApp, Email, Webhooks

  • ๐Ÿงฉ Extensible Architecture Skills, plugins, MCP servers, multi-agent orchestration

  • โš™๏ธ Production Ready Logging, sandboxing, hooks, structured output, streaming


๐Ÿ“ฆ Installation

pip install agentix-agent-sdk

Optional extras:

pip install agentix-agent-sdk[gateway]   # Slack / WhatsApp / Email
pip install agentix-agent-sdk[all]       # Full install

โšก Quickstart

Simple query

import asyncio
from agentix import AgentixAgentOptions, query, ResultMessage

async def main():
    options = AgentixAgentOptions(
        name="assistant",
        provider="openai",
        model="gpt-4o",
        system_prompt="You are a helpful assistant."
    )

    async for msg in query("What is 2 + 2?", options=options):
        if isinstance(msg, ResultMessage):
            print(msg.result)

asyncio.run(main())

Multi-turn agent

import asyncio
from agentix import AgentixAgentOptions, AgentixClient, ResultMessage

async def main():
    options = AgentixAgentOptions(
        name="assistant",
        provider="anthropic",
        model="claude-sonnet-4",
    )

    async with AgentixClient(options) as client:
        async for msg in client.query("Explain Python generators"):
            if isinstance(msg, ResultMessage):
                print(msg.result)

asyncio.run(main())

๐Ÿง  Core Concepts

Agent Loop

Agentix follows a Claude-style reasoning loop:

User โ†’ LLM โ†’ Tool Use โ†’ LLM โ†’ ... โ†’ Final Answer

๐Ÿ›  Built-in Capabilities

Tools

  • Filesystem: Read, Write, Edit, Search
  • Shell: Bash execution
  • Web: Search & fetch
  • Utility: Task tracking, user input
  • Agents: Delegate to sub-agents

Skills

  • pdf โ€” extraction, OCR, merge
  • docx โ€” Word automation
  • pptx โ€” presentation generation
  • xlsx โ€” Excel workflows

Some document features require LibreOffice (soffice) in PATH


๐Ÿค– Multi-Agent Support

from agentix import AgentDefinition

options = AgentixAgentOptions(
    agents={
        "researcher": AgentDefinition(
            description="Search and summarize",
            tools=["WebSearch"]
        )
    }
)

๐Ÿ”Œ MCP Support

Connect external tool ecosystems via Model Context Protocol:

options = AgentixAgentOptions(
    mcp_servers={
        "filesystem": {
            "type": "stdio",
            "command": "npx",
            "args": ["@modelcontextprotocol/server-filesystem"]
        }
    }
)

๐ŸŒ Gateway (Optional)

Run agents across:

  • Slack
  • WhatsApp
  • Email
  • Webhooks
agentix-gateway

โš™๏ธ Configuration

Project-based configuration:

.agentix/
โ”œโ”€โ”€ settings.json
โ”œโ”€โ”€ agents/
โ”œโ”€โ”€ skills/
โ”œโ”€โ”€ hooks/

๐Ÿ” Security & Sandbox

  • Filesystem isolation
  • Controlled tool execution
  • Plugin verification

๐Ÿ“Š Observability

  • Structured logging (JSON)
  • Tool-level tracing
  • Streaming support

๐Ÿ”‘ Environment Variables

AGENTIX_PROVIDER=openai
AGENTIX_MODEL=gpt-4o
AGENTIX_API_KEY=your-key

๐Ÿ“š Documentation

https://docs.agentix.aftws.com/


๐Ÿค Contributing

Contributions welcome โ€” please include tests and documentation.


๐Ÿ“„ License

MIT


๐Ÿ”— Links


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