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Observed since 20 Oct, 22:32 UTC
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AgentLab — a modular framework for building, evaluating, and comparing LLM-powered agents.
A modular, composable framework for building, evaluating, and comparing LLM-powered agents.
pip install agentlab
Or with optional provider extras:
pip install agentlab[llm] # OpenAI, Anthropic, Google SDKs
pip install agentlab[rerank] # Cohere + CrossEncoder rerankers
pip install agentlab[dev] # Development tools
AgentLab is organized like scoped packages — each sub-package has one clear responsibility:
| Sub-package | Equivalent to | Responsibility |
|---|---|---|
agentlab | @agentlab | Top-level exports and version info |
agentlab.llm | @agentlab/llm | LLM providers (OpenAI, Anthropic, Google, etc.) |
agentlab.embedding | @agentlab/embedding | Embedding models (OpenAI, Cohere, Sentence Transformers) |
agentlab.retriever | @agentlab/retriever | Vector, keyword, and hybrid retrieval |
agentlab.reranker | @agentlab/reranker | Rerankers (Cohere API, CrossEncoder local) |
agentlab.agents | @agentlab/agents | Agent registry and base agent class |
agentlab.execution | @agentlab/execution | Experiment runner (sequential & parallel) |
agentlab.config | @agentlab/config | API key management and settings |
from agentlab.agents import agent
from agentlab.llm import get_llm
from agentlab.embedding import get_embedding
from agentlab.retriever import get_retriever
from agentlab.reranker import get_reranker
from agentlab.execution import run_experiment
# 1. Define an agent using the @agent decorator
@agent(name="my_researcher")
class MyResearcher:
def __init__(self, llm):
self.llm = llm
def run(self, query: str) -> str:
return self.llm.generate(f"Research: {query}")
# 2. Build components
llm = get_llm(provider="openai", model="gpt-4o")
embedding = get_embedding(provider="openai", model="text-embedding-3-small")
retriever = get_retriever(provider="faiss")
reranker = get_reranker(provider="cohere")
# 3. Run an experiment
result = run_experiment({
"agents": ["my_researcher"],
"llms": [{"provider": "openai", "model": "gpt-4o", "temperature": 0.2}],
"embeddings": [{"provider": "openai", "model": "text-embedding-3-small"}],
"retrievers": [{"provider": "faiss"}],
"mode": "Sequential"
})
Create a .env file in your project root:
OPENAI_API_KEY=sk-...
ANTHROPIC_API_KEY=sk-ant-...
GOOGLE_API_KEY=AI...
COHERE_API_KEY=...
VOYAGE_API_KEY=...
MIT
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.1.0 | 23 Jul 2026 | 17 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 22:32 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:1ce04b3a9b598f879e3ba290f03cd80dc6fdb3db1db138cfba706a167af83abd