Hexify SDK

Config-driven Python SDK for building AI agents and RAG pipelines.

Import name: hexify · Pip name: hexify-ai · Python: 3.10+

v1 is a library, not a hosted API: config in, working agent out, in one Python call.

from hexify import Agent

agent = Agent(
    name="assistant",
    llm="claude-sonnet-5",
    system_prompt="You are a helpful assistant.",
)
print(agent.run("Hello!"))

Install

pip install hexify-ai

From this repo: pip install -e ".[dev]".

Quickstart (under 5 minutes)

  1. Python 3.10+ and an Anthropic API key.
  2. Set ANTHROPIC_API_KEY (export ANTHROPIC_API_KEY=sk-ant-... or, in PowerShell, $env:ANTHROPIC_API_KEY="sk-ant-...").
  3. pip install hexify-ai
  4. Run the snippet above, or:
python examples/basic_agent.py

Subsequent agent.run(...) calls on the same instance keep in-process conversation memory.

RAG + tools

from hexify import Agent, RAG

rag = RAG(
    source="./docs",
    embedder="openai",
    vectorstore="pgvector",
    pg_connection_string="postgresql://user:pass@localhost/hexify",
)
agent = Agent(
    name="support-bot",
    llm="claude-sonnet-5",
    rag=rag,
    tools=["web_search"],
    system_prompt="You are a support agent for Acme App.",
)
print(agent.run("How do I reset my password?"))

v1 models: claude-sonnet-5 (default), claude-haiku-4-5.
v1 vectorstore: pgvector only.
v1 built-in tools: web_search and send_email (deterministic stubs — no live web or SMTP).

RAG also needs OPENAI_API_KEY (embeddings) and a Postgres database with the vector extension.

CLI

hexify init
hexify run hexify.json --message "Hello"
hexify run hexify.json          # interactive prompt (quit / Ctrl-D to exit)

hexify.json is an AgentConfig file. Folder rag_source values are resolved relative to that file. Set HEXIFY_PG_CONNECTION_STRING when RAG is enabled.

Environment

Variable Used by
ANTHROPIC_API_KEY Claude (Agent.run)
OPENAI_API_KEY OpenAI embeddings (RAG)
HEXIFY_PG_CONNECTION_STRING pgvector (RAG, hexify run)

Custom tools

from hexify.tools import tool

@tool(
    name="order_status",
    description="Look up an order by id.",
    input_schema={
        "type": "object",
        "properties": {"order_id": {"type": "string"}},
        "required": ["order_id"],
    },
)
def order_status(args: dict) -> str:
    return f"Order {args['order_id']} shipped."

Then pass tools=["order_status"] (and any built-ins) into Agent.

Logging

Each Agent.run emits one JSON line on the hexify.run logger: tokens, latency (ms), tool names, RAG hit count, and ok. hexify run prints these on stderr.

Examples

Docs

Develop

pip install -e ".[dev]"
ruff check .
pytest --cov=hexify

License

MIT — see LICENSE.

Project links

Data verified by PyPI on Aug 26, 2026
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Key dates

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  • Released:
Newer release available (0.1.1)

1 maintainer

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Avatar for asad926 from gravatar.com asad926

Credits

Author: Hexify SDK Contributors

GitHub Statistics

Data verified by PyPI on Aug 26, 2026
The GitHub source repository was provided by the project maintainers and verified by PyPI at the time of upload. Stars, forks, and open issues/PRs are derived from that repository and have not been independently verified.

License

MIT License (MIT)

Requires

Python >=3.10

Provides Extra

dev

Tags

agents ai claude llm rag

Classifiers

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