iragent

iragent is a simple framework for building OpenAI‑Like, tool‑using software agents.
It sits halfway between a prompt‑engineering playground and a full orchestration layer—perfect for experiments, research helpers and production micro‑agents.

✨ Key features

SimpleAgenticRAG + KnowledgeGraphBuilder

SimpleAgenticRAG combines a FAISS-powered retriever (KnowledgeGraphBuilder) with agent-based orchestration for question answering.
It follows a Retriever → Generator flow: search relevant chunks, then generate an answer with your LLM.

Example (Local LLM)

Installation:

pip install iragent[rag]

from sentence_transformers import SentenceTransformer
from iragent.models import KnowledgeGraphBuilder
from iragent.agent import AgentFactory
from iragent.models import SimpleAgenticRAG

base_url= "http://127.0.0.1:1234/v1" # use your own base_url from api provider or local provider like ollama.
api_key = "no-key" # use your own api_key.
model = "qwen3-4b-instruct-2507"

emb_model = SentenceTransformer("all-MiniLM-L6-v2")
kg = KnowledgeGraphBuilder(embedding_model=emb_model, index_dir="./text-store/")
texts = ["FAISS (Facebook AI Similarity Search) is a library for efficient similarity search and clustering of dense vectors.",
        "It is written in C++ with bindings for Python, and is widely used for large-scale nearest-neighbor search.", 
        "FAISS supports both exact search and approximate search algorithms, making it flexible for different speed/accuracy needs.", 
        "The library was developed by Facebook’s AI Research (FAIR) team."]
kg.build_index_from_texts(texts)
agent_factory = AgentFactory(
    base_url=base_url,
    api_key=api_key,
    model=model,
)

rag = SimpleAgenticRAG(
    kg = kg,
    agent_factory= agent_factory
)
answer = rag.ask("Who developed FAISS?")

See examples/SimpleAgenticRAG for more usage.

🚀 Installation

# Requires Python 3.10+
pip install iragent
# For AgenticRAG
pip install iragent[rag]
# For AgenticRAG with GPU
pip install iragent[rag-gpu]
# Or directly from GitHub
pip install git+https://github.com/parssky/iragent.git

⚡ Quick start

from iragent.tools import get_time_now, simple_termination

factory = AgentFactory(base_url,api_key, model)

agent1 = factory.create_agent(name="time_reader",
                            system_prompt="You are that one who can read time. there is a fucntion named get_time_now(), you can call it whether user ask about time or date.",
                            fn=[get_time_now]
                            )
agent2 = factory.create_agent(name="date_exctractor", 
                              system_prompt= "You are that one who extract time from date. only return time.")
agent3 = factory.create_agent(name="date_converter", 
                              system_prompt= "You are that one who write the time in Persian. when you wrote time, then in new line write [#finish#]")

manager = AutoAgentManager(
    init_message="what time is it?",
    agents= [agent1,agent2,agent3],
    first_agent=agent1,
    max_round=5,
    termination_fn=simple_termination,
    termination_word="[#finish#]"
)

res = manager.start()
res.content

More docs

visit below url: https://parssky.github.io/iragent/namespacemembers.html

📚 More Usage Examples

Explore practical examples and use cases in the example directory.

Development

git clone https://github.com/parssky/iragent.git
cd iragent
python -m venv .venv && source .venv/bin/activate
pip install -e ".[dev]"          # ruff, pytest, etc.

🤝 Contributing

Pull requests are welcome! Please open an issue first if you plan large‑scale changes. 1- Fork → create feature branch

2- Write tests & follow ruff style (ruff check . --fix)

3- Submit PR; GitHub Actions will run lint & tests.

📄 License

This project is released under the MIT License.