Johnnylugm Tech Methodology V2 Langchain Adapter

LangChain Adapter

Bridge between LangChain ecosystem and methodology-v2.

Quick Start

import sys
sys.path.insert(0, '/workspace/methodology-v2')
sys.path.insert(0, '/workspace/langchain-adapter/scripts')

from langchain_adapter import LangChainMigrator, MethodologyLLMWrapper

# Migrate existing LangChain project
migrator = LangChainMigrator()
new_code = migrator.migrate("old_langchain_project.py")
print(new_code)

# Use LangChain LLM in methodology-v2
from langchain_openai import ChatOpenAI
llm = MethodologyLLMWrapper(ChatOpenAI())

# Use in Crew
from methodology import Crew
crew = Crew(agents=[llm_agent], process="sequential")

Features

Migration Guide

Before (LangChain)

from langchain_openai import ChatOpenAI
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain

llm = ChatOpenAI()
prompt = PromptTemplate(template="{question}", input_variables=["question"])
chain = LLMChain(llm=llm, prompt=prompt)
result = chain.run("What is AI?")

After (methodology-v2)

from methodology import SmartRouter
from langchain_adapter import MethodologyLLMWrapper

# Wrap LangChain LLM
llm = MethodologyLLMWrapper(ChatOpenAI())

# Use with SmartRouter
router = SmartRouter()
result = router.complete("What is AI?")

Integration Methods

1. Use LangChain LLM

from langchain_adapter import MethodologyLLMWrapper
from langchain_anthropic import ChatAnthropic

# Wrap any LangChain LLM
wrapped = MethodologyLLMWrapper(ChatAnthropic(model="claude-3-sonnet"))
result = wrapped.invoke("Hello")

2. Use LangChain Tools

from langchain.agents import load_tools
from langchain_adapter import ToolAdapter

# Load LangChain tools
tools = load_tools(["serpapi", "llm-math"])

# Convert to methodology-v2 format
adapter = ToolAdapter()
m2v2_tools = adapter.convert_tools(tools)

3. Migrate Memory

from langchain.memory import ConversationBufferMemory
from langchain_adapter import MemoryBridge

# LangChain memory
lc_memory = ConversationBufferMemory()

# Convert to methodology-v2 storage
bridge = MemoryBridge()
m2v2_storage = bridge.migrate_memory(lc_memory)

CLI Usage

# Analyze LangChain code
python langchain_adapter.py analyze old_chain.py

# Auto-migrate
python langchain_adapter.py migrate old_chain.py --output new_methodology.py

# Convert tools
python langchain_adapter.py convert-tools --input tools.json

Supported LangChain Components

Error Handling

See Also

• references/ langchain_patterns.md
• references/migration_examples.md

Source: johnnylugm-tech/methodology-v2 — distributed by TomeVault.