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Agent Git: Agent Version Control, Open-Branching, and Reinforcement Learning MDP for Agentic AI. A Standalone Agentic AI Infrastructure Layer for LangGraph Ecosystems

Agent-Git 최신버젼 다운로드

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<h1 align="center">Agent Git: Agent Version Control, Open-Branching, and Reinforcement Learning MDP for Agentic AI</h1>

[![Docs](https://img.shields.io/badge/docs-latest-blue?logo=readthedocs&logoColor=auto)](https://katadavidxd.github.io/Agent-Git/)
[![GitHub stars](https://img.shields.io/github/stars/katadavidxd/agent-git?logo=github&logoColor=auto)](https://github.com/KataDavidXD/Agent-Git/stargazers)
[![License](https://img.shields.io/github/license/katadavidxd/agent-git?logoColor=auto)](https://github.com/KataDavidXD/Agent-Git/blob/main/LICENSE)
[![Pre-release Wheel](https://img.shields.io/badge/Download-Pre--release-blue?logo=python&logoColor=white)](https://github.com/KataDavidXD/Agent-Git/releases/tag/V0.1.0-alpha)

[![WeChat](https://img.shields.io/badge/WeChat-AgentGit-green?logo=wechat&logoColor=white)](https://github.com/user-attachments/assets/e0759fe0-45a9-40b1-9c5c-a9869aee5b63)
[![Reddit](https://img.shields.io/badge/Reddit-AgentGit-orange?logo=reddit&logoColor=white)](https://www.reddit.com/r/AgentGit/s/mstmirU8zo)
[![Discord](https://img.shields.io/badge/Discord-5865F2?logo=discord&logoColor=auto)](https://discord.gg/AUDaTm7p)

</div>

<p align="center">
  <a href="https://katadavidxd.github.io/Agent-Git/">📖 <b>Documentation </b></a>
  &nbsp;&nbsp;•&nbsp;&nbsp;
  <a href="https://github.com/KataDavidXD/Agent-Git/blob/main/Agent_Git.pdf">🧾 <b>White Paper</b></a>
  &nbsp;&nbsp;•&nbsp;&nbsp;
  <a href="https://camo.hku.hk/research-labs/research-labs-lab-for-ai-agents-in-business-and-economics/">🏛️ <b>Our Lab</b></a>
</p>

Check https://github.com/KataDavidXD/WTB-AgenticWorkflowTestBench for production repo.

**Agent Git** is the first self-contained package that extends the standard Agentic framework, such as
LangGraph and Agno by introducing Git-like version control for AI conversations. By enabling operators
such as State Commit, State Revert, and Branching, Agent Git provides durable and reproducible
checkpoints, allowing users to reverse actions and travel to previous states on a Markov Chain of
Agentic flow.

## Overview

Agent Git is a comprehensive version control framework for LangGraph agents that introduces
Git-like operations. Analogous to how Git lets developers commit, branch, and checkout code,
Agent Git enables equivalent operations via a three-layer architecture.

### Core Concepts

* **Commit State** : A saved snapshot of an agent’s state (internal context + tool usage), persisted in the database.
* **External Session** : A logical container holding multiple Internal Sessions.
* **Internal Session** : A single agent instance with rollback ability, linked to an External Session.
* **Session History** : Message sequence within an Internal Session, including commits, branches, and LangGraph BaseMessages (AI, Human, System, Tool).
* **State Revert** : Restores the agent to an earlier Commit State.
* **Tool** : A stateless executable called by humans, LLMs, or scripts.
* **Tool Revert** : Reverses tool effects based on commit records (simple reversion for state-independent tools, compensating actions for path-dependent tools).
* **Branching** : Git-like branching from a Commit State, creating parallel exploration paths without affecting the original trajectory.

### Key Features

- **Checkpoint & Rollback**: Create restore points and travel back in conversation history
- **Non-Destructive Branching**: Rollbacks create new branches, preserving all timelines
- **Tool Reversal**: Undo side effects of tool operations (database writes, API calls, etc.)
- **Persistent State**: SQLite-backed storage survives restarts
- **Drop-in Integration**: Works seamlessly with existing LangGraph applications
- **Production Ready**: Comprehensive error handling, testing, and performance optimization

## Timeline

[Nov 2025]: v0.1.0-alpha — Excited to announce: The initial release of Agent-Git has been accepted for the WMAC: Bridging Large Language Models and Multi-Agent Systems, AAAI Workshop 2026!

[Nov 2025]: v0.2.0-alpha Release — Introduced two-level rollback mechanics and architectural improvements (new manager classes, checkpoint management).

## 📦 Download Pre-release Wheel

You can download the **pre-release version** of Agent Git as a Python wheel from our GitHub Releases:

[![Pre-release Wheel](https://img.shields.io/badge/Download-Pre--release-blue?logo=python&logoColor=white)](https://github.com/KataDavidXD/Agent-Git/releases/tag/V0.2.0-alpha)

> ⚠️ This is a pre-release version. Please use with caution and report any issues.

## Installation

## Quick Start Video: Download & Prepare to Use

### Using uv (Recommended)

```bash
# Install from wheel file
uv pip install agent_git_langchain-0.1.0-py3-none-any.whl

# Or install with dependencies
uv pip install agent_git_langchain-0.1.0-py3-none-any.whl --reinstall
```

### Using pip

```bash
pip install agent_git_langchain-0.1.0-py3-none-any.whl
```

### Required Dependencies

```bash
# Install LangChain and LangGraph
pip install langchain langchain-openai langgraph

# Set your OpenAI API key
export OPENAI_API_KEY="your-api-key-here"
```

## Quick Start

### Prerequisites: User Setup

Agent Git automatically creates a default user on first run:

- **Username**: `rootusr`
- **Password**: `1234`
- **User ID**: `1`

You can use this default user or create your own:

```python
from agentgit.database.repositories.user_repository import UserRepository
from agentgit.auth.user import User
from datetime import datetime

user_repo = UserRepository()  # Auto-creates rootusr

# Option A: Use default user
user = user_repo.find_by_username("rootusr")

# Option B: Create custom user
new_user = User(username="alice", created_at=datetime.now())
new_user.set_password("secure_password")
user = user_repo.save(new_user)
```

### Simple Example

# 1. Get user
user_repo = UserRepository()
user = user_repo.find_by_username("rootusr")

# 2. Create session
external_repo = ExternalSessionRepository()
session = external_repo.create(ExternalSession(
    user_id=user.id,
    session_name="My First Agent",
    created_at=datetime.now()
))

# 3. Define tools
@tool
def calculate_sum(a: int, b: int) -> int:
    """Add two numbers together."""
    return a + b

# 4. Create agent
agent = RollbackAgent(
    external_session_id=session.id,
    model=ChatOpenAI(model="gpt-4o-mini"),
    tools=[calculate_sum],
    auto_checkpoint=True
)

# 5. Chat!
response = agent.run("What is 25 + 17?")
print(response)
```

## Usage Patterns

Agent Git offers two approaches: **Manual** (fine-grained control) and **AgentService** (simplified, production-recommended).

### Option 1: Manual Approach

Full control over all components—ideal for custom configurations.

```python
from agentgit.agents.rollback_agent import RollbackAgent
from agentgit.sessions.external_session import ExternalSession
from agentgit.database.repositories.external_session_repository import ExternalSessionRepository
from agentgit.database.repositories.checkpoint_repository import CheckpointRepository
from agentgit.database.repositories.internal_session_repository import InternalSessionRepository
from agentgit.database.repositories.user_repository import UserRepository
from agentgit.auth.user import User
from langchain_openai import ChatOpenAI
from langchain_core.tools import tool
from datetime import datetime

# Step 1: Create or get a user
user_repo = UserRepository()  # Auto-creates 'rootusr' with ID=1
user = user_repo.find_by_username("rootusr")

# Step 2: Setup repositories
external_repo = ExternalSessionRepository()
checkpoint_repo = CheckpointRepository()
internal_repo = InternalSessionRepository()

external_session = external_repo.create(ExternalSession(
    user_id=user.id,
    session_name="Rollback Demo",
    created_at=datetime.now()
))

# Define a tool with side effects
order_database = {}  # Simulated database

@tool
def create_order(order_id: str, amount: float) -> str:
    """Create a new order in the database."""
    order_database[order_id] = {"amount": amount, "status": "created"}
    return f"Order {order_id} created for ${amount}"

def reverse_create_order(args, result):
    """Reverse order creation by deleting it."""
    order_id = args['order_id']
    if order_id in order_database:
        del order_database[order_id]
    return f"Order {order_id} deleted"

# Create agent with rollback capability
agent = RollbackAgent(
    external_session_id=external_session.id,
    model=ChatOpenAI(model="gpt-4o-mini"),
    tools=[create_order],
    reverse_tools={"create_order": reverse_create_order},
    auto_checkpoint=True,
    checkpoint_repo=checkpoint_repo,
    internal_session_repo=internal_repo
)

# Conversation flow
print("=== Original Timeline ===")
agent.run("Hello! I need to create some orders.")

# Create manual checkpoint before operations
checkpoint_msg = agent.create_checkpoint_tool("Before order creation")
print(checkpoint_msg)
# Extract checkpoint ID from message: "✓ Checkpoint 'Before order creation' created successfully (ID: 1)"
safe_checkpoint_id = int(checkpoint_msg.split("ID: ")[1].rstrip(")")) # In practice, parse this from checkpoint_msg

# Create some orders (auto-checkpoints created after each)
agent.run("Please create order #1001 for $250")
print(f"Database state: {order_database}")

agent.run("Now create order #1002 for $150")
print(f"Database state: {order_database}")

agent.run("Create one more order #1003 for $300")
print(f"Database state: {order_database}")
# Database now has: {1001: ..., 1002: ..., 1003: ...}

# Get conversation history length
original_history = agent.get_conversation_history()
print(f"Original history length: {len(original_history)} messages")

# Oops! We need to go back to before the orders were created
print("\n=== Performing Rollback ===")

# Rollback to the safe checkpoint - creates a new branch
branched_agent = RollbackAgent.from_checkpoint(
    checkpoint_id=safe_checkpoint_id,
    external_session_id=external_session.id,
    model=ChatOpenAI(model="gpt-4o-mini"),
    tools=[create_order],
    reverse_tools={"create_order": reverse_create_order},
    checkpoint_repo=checkpoint_repo,
    internal_session_repo=internal_repo
)

# Check the branched agent's state
branched_history = branched_agent.get_conversation_history()
print(f"Branched history length: {len(branched_history)} messages")
print(f"Database state after branch: {order_database}")

# The branch has the state from before the checkpoint
# But the tool operations haven't been reversed yet
# To reverse tools, get the checkpoint and rollback from its track position
checkpoint = checkpoint_repo.get_by_id(safe_checkpoint_id)
if "tool_track_position" in checkpoint.metadata:
    track_position = checkpoint.metadata["tool_track_position"]
    reverse_results = agent.rollback_tools_from_track_index(track_position)

print("\nTool Reversal Results:")
    for result in reverse_results:
        if result.reversed_successfully:
            print(f"✓ Reversed {result.tool_name}")
        else:
            print(f"✗ Failed to reverse {result.tool_name}: {result.error_message}")

print(f"Database after tool reversal: {order_database}")

# Continue with different actions on the branch
print("\n=== New Branch Timeline ===")
branched_agent.run("Let's create just one order instead: #2001 for $500")
print(f"Database state: {order_database}")

# Original agent can still continue independently
print("\n=== Original Timeline Continues ===")
agent.run("Create another order #1004 for $200")

# Show conversation histories to prove independence
print("\n=== Timeline Independence Verification ===")
original_conv = agent.get_conversation_history()
branched_conv = branched_agent.get_conversation_history()

print(f"\nOriginal timeline - conversation history ({len(original_conv)} messages):")
for i, msg in enumerate(original_conv[-4:], start=len(original_conv)-3):  # Show last 4 messages
    role = msg.get('role', 'unknown')
    content = msg.get('content', '')[:80]  # Truncate long messages
    print(f"  [{i}] {role}: {content}...")

print(f"\nBranched timeline - conversation history ({len(branched_conv)} messages):")
for i, msg in enumerate(branched_conv, start=1):
    role = msg.get('role', 'unknown')
    content = msg.get('content', '')[:80]
    print(f"  [{i}] {role}: {content}...")

# Verify both sessions exist
all_sessions = internal_repo.get_by_external_session(external_session.id)
print(f"\nTotal internal sessions (branches): {len(all_sessions)}")
print(f"Original session ID: {agent.internal_session.id}")
print(f"Branched session ID: {branched_agent.internal_session.id}")
print(f"Branch parent: {branched_agent.internal_session.parent_session_id}")
print(f"Is branch: {branched_agent.internal_session.is_branch()}")
```

### Option 2: AgentService (Recommended)

Simplified API with automatic dependency management—**55% less boilerplate code**.

```python
from agentgit.agents.agent_service import AgentService
from agentgit.sessions.external_session import ExternalSession
from agentgit.database.repositories.external_session_repository import ExternalSessionRepository
from agentgit.database.repositories.user_repository import UserRepository
from langchain_core.tools import tool
from datetime import datetime

# Define tools
@tool
def process_payment(amount: float, order_id: str) -> str:
    """Process a payment for an order."""
    return f"Payment of ${amount} processed for order {order_id}"

def reverse_payment(args, result):
    """Reverse a payment."""
    print(f"  ✓ Reversed: Refunded ${args['amount']} for order {args['order_id']}")
    return f"Refunded ${args['amount']} for order {args['order_id']}"

# Step 1: Create user and external session (same as before)
user_repo = UserRepository()
user = user_repo.find_by_username("rootusr")

external_repo = ExternalSessionRepository()
external_session = external_repo.create(ExternalSession(
    user_id=user.id,
    session_name="Payment Processing",
    created_at=datetime.now()
))

# Step 2: Initialize service (auto-creates all repositories)
service = AgentService()
# ✓ No manual repository creation
# ✓ Model config loaded from environment
# ✓ All dependencies managed internally

# Step 3: Create agent with minimal code
agent = service.create_new_agent(
    external_session_id=external_session.id,
    tools=[process_payment],
    reverse_tools={"process_payment": reverse_payment},
    auto_checkpoint=True
)
# ✓ No model creation needed
# ✓ No repository passing needed
# ✓ Best-practice defaults applied

# Step 4: Use the agent
response1 = agent.run("Process a payment of $150 for order #1001")
print(response1)

# Create checkpoint
checkpoint_msg = agent.create_checkpoint_tool("Before second payment")
checkpoint_id = int(checkpoint_msg.split("ID: ")[1].split(")")[0])

response2 = agent.run("Process another payment of $250 for order #1002")
print(response2)

# Step 5: List checkpoints using service utility
checkpoints = service.list_checkpoints(agent.internal_session.id)
print(f"Total checkpoints: {len(checkpoints)}")

# Step 6: Resume session later
# Simulate app restart
service = AgentService()
resumed_agent = service.resume_agent(
    external_session_id=external_session.id,
    tools=[process_payment],
    reverse_tools={"process_payment": reverse_payment}
)
# ✓ Conversation history automatically restored
# ✓ Session state automatically loaded
# ✓ Ready to continue immediately

if resumed_agent:
    response3 = resumed_agent.run("What payments did we process?")
    print(response3)

# Step 7: Rollback with automatic tool reversal
rolled_back = service.rollback_to_checkpoint(
    external_session_id=external_session.id,
    checkpoint_id=checkpoint_id,
    rollback_tools=True,  # Automatically reverses payment operations!
    tools=[process_payment],
    reverse_tools={"process_payment": reverse_payment}
)
# ✓ Checkpoint retrieved automatically
# ✓ Tool operations reversed automatically
# ✓ New branch created automatically
# ✓ Ready to use immediately

if rolled_back:
    response4 = rolled_back.run("Let's try a different payment amount: $300 for order #1003")
    print(response4)
    print()
```

**Key Differences:**

| Feature                         | Manual          | AgentService       |
| ------------------------------- | --------------- | ------------------ |
| **Setup Code**            | ~45 lines       | ~8 lines           |
| **Repository Management** | Manual creation | Automatic          |
| **Model Config**          | Manual setup    | Auto from env vars |
| **Rollback**              | 25-30 lines     | 1 line             |
| **Session Resume**        | 15-20 lines     | 1 line             |
| **Best For**              | Custom configs  | Production apps    |

## Core Operations

### Creating Checkpoints

```python
# Automatic checkpoints (after tool calls)
agent = RollbackAgent(..., auto_checkpoint=True)

# Manual checkpoints
checkpoint_msg = agent.create_checkpoint_tool("Before risky operation")

# List all checkpoints
agent.list_checkpoints_tool()

# Get checkpoint details
agent.get_checkpoint_info_tool(checkpoint_id=1)
```

### Rolling Back

```python
# Rollback creates a new branch (preserves original timeline)
new_agent = RollbackAgent.from_checkpoint(
    checkpoint_id=checkpoint_id,
    external_session_id=session.id,
    model=model,
    tools=tools,
    reverse_tools=reverse_tools,
    checkpoint_repo=checkpoint_repo,
    internal_session_repo=internal_repo
)

# Or use AgentService for one-liner
rolled_back = service.rollback_to_checkpoint(
    external_session_id=session.id,
    checkpoint_id=checkpoint_id,
    rollback_tools=True
)
```

### Tool Reversal

```python
# Define tool
@tool
def save_record(record_id: str, data: str) -> str:
    """Save data to database."""
    db.write(record_id, data)
    return f"Saved {record_id}"

# Define reverse function
def reverse_save(args, result):
    """Delete the saved record."""
    db.delete(args['record_id'])
    return f"Deleted {args['record_id']}"

# Register when creating agent
agent = RollbackAgent(
    ...,
    tools=[save_record],
    reverse_tools={"save_record": reverse_save}
)
```

### Managing Branches

```python
# Check if session is a branch
agent.internal_session.is_branch()

# Get parent session ID
agent.internal_session.parent_session_id

# Get branch point checkpoint
agent.internal_session.branch_point_checkpoint_id

# List all branches for a session
branches = internal_repo.get_by_external_session(session.id)
print(f"Total branches: {len(branches)}")
```

## Common Use Cases

### 1. Customer Support Recovery

```python
# Agent helps customer, makes mistake
agent.run("Process refund of $500")

# Realize error, rollback to before refund
checkpoint_id = 5  # From before refund
corrected = service.rollback_to_checkpoint(
    external_session_id=session.id,
    checkpoint_id=checkpoint_id,
    rollback_tools=True  # Reverses the refund!
)

# Try again with correct amount
corrected.run("Process refund of $50")
```

### 2. A/B Testing

```python
# Create checkpoint after gathering context
checkpoint_msg = agent.create_checkpoint_tool("Context gathered")
checkpoint_id = 1

# Test approach A
branch_a = RollbackAgent.from_checkpoint(checkpoint_id, ...)
response_a = branch_a.run("Explain technically")

# Test approach B
branch_b = RollbackAgent.from_checkpoint(checkpoint_id, ...)
response_b = branch_b.run("Explain simply")

# Compare results
print(f"Technical: {len(response_a)} chars")
print(f"Simple: {len(response_b)} chars")
```

### 3. Safe Exploration

```python
# Create checkpoint before risky operation
agent.create_checkpoint_tool("Before deletion")

# Try risky operation
agent.run("Delete all test records")

# If something goes wrong, rollback
service.rollback_to_checkpoint(
    external_session_id=session.id,
    checkpoint_id=checkpoint_id,
    rollback_tools=True  # Undoes deletions!
)
```

## Environment Configuration

Agent Git uses environment variables for configuration:

```bash
# Required
export OPENAI_API_KEY="sk-..."

# Optional (AgentService defaults)
export BASE_URL="https://api.openai.com/v1"  # Custom API endpoint
export DEFAULT_MODEL="gpt-4o-mini"            # Default model
export DEFAULT_TEMPERATURE="0.7"              # Default temperature
```

## API Reference

### RollbackAgent Methods

```python
# Conversation
agent.run(message: str) -> str

# Checkpoints
agent.create_checkpoint_tool(name: str) -> str
agent.list_checkpoints_tool() -> str
agent.get_checkpoint_info_tool(checkpoint_id: int) -> str
agent.cleanup_auto_checkpoints_tool(keep_latest: int) -> str

# State inspection
agent.get_conversation_history() -> List[dict]
agent.get_session_state() -> dict
agent.get_tool_track() -> List[ToolInvocationRecord]

# Rollback
RollbackAgent.from_checkpoint(checkpoint_id, ...) -> RollbackAgent
agent.rollback_tools_from_track_index(position: int) -> List[ReverseResult]
```

### AgentService Methods

```python
# Agent management
service.create_new_agent(external_session_id, tools, ...) -> RollbackAgent
service.resume_agent(external_session_id) -> RollbackAgent | None

# Rollback
service.rollback_to_checkpoint(
    external_session_id,
    checkpoint_id,
    rollback_tools=True
) -> RollbackAgent | None

# Utilities
service.list_checkpoints(internal_session_id) -> List[Checkpoint]
```

## Architecture

The session hierarchy follows a tree structure:

**Key Concepts:**

- **External Session**: Container for related conversations (one per user/use-case)
- **Internal Session**: Actual agent instance (can have multiple branches)
- **Checkpoint**: Snapshot of conversation state at a specific point
- **Branch**: New internal session created from a checkpoint (preserves original timeline)

## Troubleshooting

### Common Issues

**Issue**: `sqlite3.IntegrityError: FOREIGN KEY constraint failed`

**Solution**: Ensure you're using a valid `user_id` when creating external sessions.

**Issue**: Rollback doesn't reverse tool effects

**Solution**: Register reverse functions in `reverse_tools` parameter.

**Issue**: Can't find previous conversation

**Solution**: Use `service.resume_agent(external_session_id)` to load the active session.

**Issue**: Model not configured

**Solution**: Set `OPENAI_API_KEY` environment variable or pass model explicitly.

## Documentation

For detailed information, see:

- `whitePaper.pdf` - Complete architecture and design documentation
- API documentation (coming soon)
- Deployment guide (coming soon)

## Contributing

We welcome contributions! Agent Git is open source and actively seeking:

- Bug reports and feature requests
- Tool implementations with reverse functions
- Documentation improvements
- Performance optimizations

Partners: **HKU Lab for AI Agents in Business and Economics**

👉 [Learn more](https://camo.hku.hk/research-labs/research-labs-lab-for-ai-agents-in-business-and-economics/)

## License
Agent Git is released under the Apache 2.0 License, ensuring compatibility with the LangGraph and Agno ecosystems while providing patent protection and commercial-friendly terms.

## Support

- GitHub Issues: Report bugs or request features
- Documentation: See `whitePaper.pdf`

Incoming System Addon: Agent-Testing

---

Built for the LangChain/LangGraph community

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