# LangChain v1.0 Migration Notes

## What Changed

The codebase has been updated to use **LangChain v1.0** API, which introduced breaking changes from v0.x.

## Key Changes Made

### 1. Agent Creation API

**Before (v0.x):**

```python
from langchain.agents import AgentExecutor, create_openai_tools_agent
from langchain_core.prompts import ChatPromptTemplate, MessagesPlaceholder
from langchain_core.tools import Tool

# Create tools as Tool objects
tools = [
    Tool(name="navigate", func=navigate_wrapper, description="..."),
    # ... more tools
]

# Create prompt with MessagesPlaceholder
prompt = ChatPromptTemplate.from_messages([...])

# Create agent and executor
agent = create_openai_tools_agent(llm, tools, prompt)
agent_executor = AgentExecutor(agent=agent, tools=tools, ...)

# Execute
result = await agent_executor.ainvoke({"input": task})
```

**After (v1.0):**

```python
from langchain.agents import create_agent

# Create tools as simple functions with docstrings
def navigate(url: str) -> str:
    """Navigate to a URL. Input should be a valid URL."""
    return asyncio.run(self.browser.navigate(url))

tools = [navigate, click, type_text, ...]  # Just functions!

# Create agent directly
agent = create_agent(
    model="gpt-4o-mini",
    tools=tools,
    system_prompt="Your instructions here"
)

# Execute with messages format
result = await agent.ainvoke(
    {"messages": [{"role": "user", "content": task}]}
)
```

### 2. Tool Definition

**Before:**

-   Tools were defined as `Tool` objects
-   Required explicit `name`, `func`, and `description` parameters

**After:**

-   Tools are simple Python functions
-   Function docstring becomes the tool description
-   Function name becomes the tool name
-   Much simpler and cleaner!

### 3. Response Format

**Before:**

```python
result = await agent_executor.ainvoke({"input": task})
output = result.get("output")
```

**After:**

```python
result = await agent.ainvoke({"messages": [{"role": "user", "content": task}]})
output = result["messages"][-1].content
```

### 4. Pydantic Models

Also updated Pydantic models to use v2.0 syntax:

**Before:**

```python
class Settings(BaseSettings):
    field: str

    class Config:
        env_file = ".env"
```

**After:**

```python
from pydantic import ConfigDict

class Settings(BaseSettings):
    model_config = ConfigDict(env_file=".env")

    field: str
```

## Benefits of v1.0

1. **Simpler API**: Less boilerplate code
2. **Better Tool Definition**: Functions with docstrings vs Tool objects
3. **Built on LangGraph**: Better durability and streaming support
4. **Cleaner Code**: More intuitive and Pythonic
5. **Better Performance**: Optimized execution

## Migration Checklist

-   [x] Replace `create_openai_tools_agent` with `create_agent`
-   [x] Remove `AgentExecutor` usage
-   [x] Convert `Tool` objects to simple functions
-   [x] Update invocation format to use messages
-   [x] Update response parsing
-   [x] Fix Pydantic v2.0 deprecations
-   [x] Test all functionality

## Running the Application

The application now works with LangChain v1.0:

```bash
# Install dependencies
uv pip install -e .
playwright install chromium

# Set up environment
cp .env.example .env
# Edit .env and add OPENAI_API_KEY

# Run
python main.py
```

## Documentation

-   [LangChain v1.0 Overview](https://docs.langchain.com/oss/python/langchain/overview)
-   [Migration Guide](https://docs.langchain.com/oss/python/migrate/langchain-v1)
-   [Release Notes](https://docs.langchain.com/oss/python/releases/langchain-v1)

## Issues Fixed

-   ✅ `ImportError: cannot import name 'AgentExecutor'` - Fixed by using new API
-   ✅ Pydantic deprecation warnings - Fixed by using ConfigDict
-   ✅ All imports working correctly
-   ✅ Application runs successfully