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LangChain BaseChatModel adapter for somm — lets LangChain/LangGraph/deepagents apps use somm as their LLM substrate

Project description

somm-langchain

LangChain BaseChatModel adapter for somm.

Lets LangChain / LangGraph / deepagents apps use somm as their LLM substrate — telemetry, routing, cost tracking, provider fallback, sommelier model memory — all without changing the agent-framework call sites.

import somm
from somm_langchain import SommChatModel

llm = somm.llm(project="my_agent")
chat = SommChatModel(somm_llm=llm, workload="agent_thinking")

from deepagents import create_deep_agent
agent = create_deep_agent(model=chat, tools=[...])

SommChatModel supports bind_tools() and routes tool-using calls through somm's neutral tool-calling shape (see docs/tool-calling.md). The adapter is thin: message translation in, somm.llm().generate() through, ChatGeneration out.

Built for agent orchestrators that run on deepagents and similar LangChain-based stacks, which mandate a tool-calling BaseChatModel.

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