GitHub - Tennisee-data/acf: Agent Code Factory is dedicated to executing AI locally with the best possible results.

git clone https://github.com/Tennisee-data/acf.git
cd acf
pip install -e .

# Option A: Ollama (recommended - local, free)
brew install ollama          # macOS (see ollama.ai for Linux/Windows)
ollama serve                 # Start server (keep this running!)
ollama pull qwen2.5-coder:7b # In another terminal

# Option B: LM Studio (local, GUI)
# Download from https://lmstudio.ai, start local server on port 1234

# Option C: Cloud API
export OPENAI_API_KEY=sk-...      # or
export ANTHROPIC_API_KEY=sk-...

acf check                              # Verify LLM backend is working
acf run "Add user authentication"      # Run your first feature

git clone https://github.com/Tennisee-data/acf.git
cd acf
pip install -e .

pip install -e ".[semantic]"   # Semantic RAG (better code retrieval)
pip install -e ".[openai]"     # OpenAI backend
pip install -e ".[anthropic]"  # Anthropic backend
pip install -e ".[full]"       # Everything

pip install "acf[semantic]"
pip install "acf[openai]"
pip install "acf[anthropic]"
pip install "acf[full]"

acf run "Build a REST API with FastAPI"
acf run "Add user authentication" --repo ./my-project
acf run "Build an API" --output ./my-api    # Custom output directory

2026-01-24-130821/                # Project directory (run ID by default)
├── app/                          # Your generated code at root level
│   └── main.py
├── requirements.txt
├── .gitignore                    # Includes .acf/
└── .acf/                         # Pipeline history (gitignored)
    └── runs/
        └── 2026-01-24-130821/    # Run artifacts
            ├── state.json        # Pipeline state
            ├── feature_spec.json # Parsed requirements
            ├── design_proposal.json
            ├── change_set.json
            ├── diff.patch
            └── *.md              # Reports

acf run "Build REST API" --output ./my-project

acf run "feature" [OPTIONS]

# Basic run with auto-approval
acf run "Add login rate-limit" --auto-approve

# Full pipeline with all quality checks
acf run "Build payment API" --api-contract --coverage --secrets-scan --code-review

# Resume a paused run
acf run "Add feature" --resume 2026-01-24-130821

# Iterate on existing project
acf iterate 2026-01-24-130821 "Add error handling"

# List all runs
acf list

# Show run details
acf show 2026-01-24-130821

# Extract generated code to a directory
acf extract 2026-01-24-130821 --output ./my-project

# Create git scaffold with proper structure
acf scaffold 2026-01-24-130821

# Generate tests for existing code
acf generate-tests 2026-01-24-130821

# Deploy generated project
acf deploy 2026-01-24-130821 --version v1.0.0

# Browse extensions
acf marketplace search "security"
acf marketplace featured

# Install extensions
acf marketplace install secrets-scan
acf marketplace install semantic-rag

# Manage installed extensions
acf extensions list
acf extensions enable secrets-scan

# Run a skill on a file or directory
acf skill run add-error-handling ./src/main.py
acf skill run add-type-hints ./src --dry-run

# Run a chained skill (multi-step transformation)
acf skill chain production-ready ./src

# List and inspect installed skills
acf skill list
acf skill show add-error-handling

# manifest.yaml
name: my-skill
version: 1.0.0
type: skill
author: Your Name
description: What it does
license: free
skill_class: MySkill
input_type: files
output_type: modified_files
file_patterns: ["*.py"]
supports_dry_run: true

# skill.py
from skills.base import BaseSkill, FileChange, SkillInput, SkillOutput

class MySkill(BaseSkill):
    def run(self, input_data: SkillInput) -> SkillOutput:
        changes = []
        for path in input_data.target_paths:
            content = path.read_text()
            modified = self.transform(content)
            if modified != content:
                changes.append(FileChange(
                    path=path,
                    original_content=content,
                    modified_content=modified,
                    change_type="modified",
                ))
        return SkillOutput(
            success=True,
            changes=changes,
            summary=f"Transformed {len(changes)} files",
        )

    def transform(self, content: str) -> str:
        # Your transformation logic
        return content

[llm]
backend = "auto"  # ollama, lmstudio, openai, anthropic
model_general = "qwen2.5-coder:7b"  # Must match an installed model
model_code = "qwen2.5-coder:7b"

[extensions]
extensions_dir = "~/.coding-factory/extensions"

[routing]
# Enable to use different models for different task complexities
# All models must be installed: ollama pull <model>
enabled = true
model_cheap = "qwen2.5-coder:7b"    # Simple tasks
model_medium = "yi-coder:9b"         # Medium complexity
model_premium = "qwen2.5-coder:32b"  # Complex tasks

# One library per line
requests
fastapi
sqlalchemy

[patterns]
# Add custom regex patterns to flag
api_key_in_code = "api[_-]?key\\s*=\\s*['\"][^'\"]+['\"]"

[components]
# Map component types to Tailwind classes
button_primary = "bg-blue-500 hover:bg-blue-600 text-white px-4 py-2 rounded"

cp -r official_extensions/* ~/.coding-factory/extensions/agents/
acf extensions list

mkdir my-agent && cd my-agent

name: my-agent
version: 1.0.0
type: agent
author: Your Name
description: What it does
license: free
hook_point: "after:implementation"
agent_class: MyAgent

from dataclasses import dataclass, field
from typing import Any

@dataclass
class AgentOutput:
    success: bool
    data: dict[str, Any]
    errors: list[str] | None = None
    artifacts: list[str] | None = None
    metadata: dict[str, Any] = field(default_factory=dict)
    agent_name: str | None = None

class MyAgent:
    def __init__(self, llm: Any, **kwargs):
        self.llm = llm
        self.name = "my-agent"

    def run(self, input_data) -> AgentOutput:
        context = input_data.context
        # Your logic here
        return AgentOutput(
            success=True,
            data={"result": "done"},
            agent_name=self.name
        )

cp -r my-agent ~/.coding-factory/extensions/agents/
acf run "Build an API" --auto-approve

export ACF_MARKETPLACE_API_KEY=acf_sk_xxxx...

my-extension/
├── manifest.yaml    # Required: name, version, type, description
├── agent.py         # Your code
└── README.md        # Documentation

acf marketplace submit ./my-extension --price 15.00
# Use --price 0 for free extensions

~/.coding-factory/
├── extensions/          # Installed extensions
│   ├── agents/
│   ├── profiles/
│   ├── rag/
│   └── skills/
└── memory/              # Learning from past runs