AgentCI Client Config
Define evaluations and framework configurations for AI agent applications using simple TOML files.
📚 Full Documentation | 🚀 Getting Started | 📖 TOML Schema Guides
What is This?
AgentCI Client Config provides a TOML-based configuration format for:
- Evaluations: Test cases for AI agents and tools with support for accuracy, performance, consistency, and safety testing
- Framework Configurations: Patterns for discovering agents and tools in popular AI frameworks (LangChain, LlamaIndex, Pydantic AI, OpenAI, Google ADK, Agno)
Quick Example
Create evaluation configs in .agentci/evals/:
# .agentci/evals/test_accuracy.toml
[eval]
description = "Test that the agent responds with correct information"
type = "accuracy"
[eval.targets]
agents = ["my_agent"]
[[eval.cases]]
prompt = "What is the capital of France?"
expected.exact = "Paris"
Create framework configs in .agentci/frameworks/:
# .agentci/frameworks/my_framework.toml
[framework]
name = "my-framework"
dependencies = ["my-framework"]
[[agents]]
path = "my_framework.Agent"
args.model = "llm"
args.prompt = "system_prompt"
execution.method = "run"
execution.args.prompt = "user_input"
Installation
pip install agentci-client-config
Documentation
For complete TOML schema documentation and guides:
- Getting Started - Project setup and first configs
- Evaluation Schema - Complete guide to evaluation TOML format
- Framework Schema - Complete guide to framework TOML format
- Python API - Optional programmatic usage
Features
Evaluations
- Six evaluation types: accuracy, performance, consistency, safety, llm, custom
- Flexible matching: exact, contains, regex, semantic similarity
- Schema validation: Validate structured JSON outputs
- Tool call validation: Verify correct tool usage
- Multiple iterations: Run tests multiple times for consistency
Frameworks
- Built-in support: LangChain, LlamaIndex, Pydantic AI, OpenAI Agents, Google ADK, Agno
- Custom frameworks: Define your own discovery patterns
- Agent discovery: Map framework parameters to standard fields
- Tool discovery: Configure tool types (decorator, function, class, constructor)
- Execution config: Define how to run agents and tools
Directory Structure
your-project/
├── .agentci/
│ ├── evals/ # Evaluation configurations
│ │ ├── accuracy.toml
│ │ ├── performance.toml
│ │ └── safety.toml
│ └── frameworks/ # Framework configurations (optional)
│ └── custom.toml
├── src/
└── tests/
License
MIT
Release files for agentci-client-config 0.1.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| agentci_client_config-0.1.3.tar.gz | 105.6 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| agentci_client_config-0.1.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 122.4 kB
Release files / agentci_client_config-0.1.3.tar.gz
| Download URL | agentci_client_config-0.1.3.tar.gz |
|---|---|
| Size | 105.6 kB |
| Tags | Source |
|
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Release files / agentci_client_config-0.1.3-py3-none-any.whl
| Download URL | agentci_client_config-0.1.3-py3-none-any.whl |
|---|---|
| Size | 16.8 kB |
| Tags | Python 3 |
|
SHA-256 checksum How to use checksums |
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Uploaded using Trusted Publishing? What is trusted publishing? |
No |
| Uploaded via |
uv/0.9.5
|