logic-engine / docs /getting-started /installation.md
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# Installation
## For Users
=== "uv"
```bash
uv add ace-framework
```
=== "With extras"
```bash
uv add 'ace-framework[all]' # All optional features
uv add 'ace-framework[instructor]' # Structured outputs (Instructor)
uv add 'ace-framework[langchain]' # LangChain integration
uv add 'ace-framework[browser-use]' # Browser automation
uv add 'ace-framework[claude-code]' # Claude Code CLI integration
uv add 'ace-framework[claude-sdk]' # Anthropic SDK integration steps
uv add 'ace-framework[observability]' # Opik monitoring + cost tracking
uv add 'ace-framework[deduplication]' # Skill deduplication (embeddings)
uv add 'ace-framework[transformers]' # Local model support
```
## For Contributors
=== "UV (Recommended)"
```bash
git clone https://github.com/kayba-ai/agentic-context-engine
cd agentic-context-engine
uv sync # Installs everything (10-100x faster than pip)
```
=== "uv"
```bash
git clone https://github.com/kayba-ai/agentic-context-engine
cd agentic-context-engine
uv add -e .
```
## Requirements
- **Python 3.12**
- An API key for your LLM provider
## Configure Your LLM
The recommended way to set up your API keys and model selection:
```bash
ace setup
```
This interactive wizard validates your API key and model, then saves config to `ace.toml` (model names, safe to commit) and `.env` (API keys, gitignored). See [Setup](setup.md) for full details.
### Manual alternative
If you prefer not to use the wizard, set environment variables directly:
```bash
export OPENAI_API_KEY="sk-..."
```
Or create a `.env` file (add to `.gitignore`):
```bash
OPENAI_API_KEY=sk-...
```
## Verify Installation
```python
from ace import ACELiteLLM
# Uses ace.toml + .env from `ace setup`
agent = ACELiteLLM.from_setup()
print(agent.ask("Hello!"))
```
Or without `ace setup`:
```python
agent = ACELiteLLM.from_model("gpt-4o-mini")
print(agent.ask("Hello!"))
```
## Set Up Coding Agent Skills (Optional)
If you want the hosted `kayba` CLI or `kayba setup`, install the cloud extra first:
```bash
uv add 'ace-framework[cloud]'
```
Then, if you use Claude Code, install the Kayba pipeline skill:
```bash
kayba setup
```
This installs the evaluation pipeline skill to `.claude/skills/` and prints CLI instructions. See [Hosted API](../integrations/hosted-api.md) for details.
## What to Read Next
- [Setup](setup.md) — configure models and API keys
- [Quick Start](quick-start.md) — build your first self-learning agent
- [How ACE Works](../concepts/overview.md) — understand the architecture