# LangChain langchain-core 1.7.0: what's new, verdict & setup Canonical: https://theagenticweekly.com/tools/langchain · Released: 2026-10-22 · Last verified: 2026-10-25 · Evidence: Tested (smoke test, 2026-10-25, local 3B model (Qwen2.5-3B)) · Vendor: LangChain · Official site: https://www.langchain.com/ > Open-source framework for building LLM applications and agents in Python and JavaScript, from the team behind LangGraph and LangSmith. ## Verdict **Open-source framework for building LLM applications and agents in Python and JavaScript, from the team behind LangGraph and LangSmith.** Good for: - Developers who want the widest set of integrations - Teams that will pair it with LangGraph for stateful agents Skip if: - You want a minimal library with few abstractions - You only need one model provider's SDK Tested. Tested 2026-10-25 (America/Chicago). LangChain.js 1.5.19 passed our one-tool task 3 of 3 on Node 20 and 3 of 3 on Node 24; about 101 MB in 36 packages. LangChain 1.4.7 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 0.8 s. Test environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key. Agent tools were pointed at a local open-weight model (Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11), so we tested the tool, not any vendor's hosted models. Not tested: Any vendor-hosted model: everything ran against one local 3B model; Multi-agent flows, memory, streaming and deployment; Anything beyond one tool and one question; five trials is a smoke test, not a benchmark; Any vendor-hosted model: everything ran on a local 3B model, so tool-call reliability with frontier models is not measured here; Multi-agent flows, memory, long conversations, streaming, tracing and cloud deployment; Anything beyond one tool and one question; three trials is a smoke test, not a benchmark. These are smoke tests, not a benchmark. Full log: /tests/langchainjs. Full log: /tests/langchain. Test scope: - Kind and date: smoke test, 2026-10-25 (America/Chicago). Not a benchmark. - What we ran: LangChain.js 1.5.19 passed our one-tool task 3 of 3 on Node 20 and 3 of 3 on Node 24; about 101 MB in 36 packages. LangChain 1.4.7 passed our one-tool task on a local 3B model: 3 of 3 trials; cold uv install 0.8 s. - Model used: Qwen2.5-3B-Instruct (Q4_K_M) through Ollama 0.40.11 - Environment: Linux x86_64 virtual machine (Debian 13), 8 vCPU, 15 GiB RAM, no GPU; no vendor account, login or API key - Not tested: Any vendor-hosted model: everything ran against one local 3B model; Multi-agent flows, memory, streaming and deployment; Anything beyond one tool and one question; five trials is a smoke test, not a benchmark; Any vendor-hosted model: everything ran on a local 3B model, so tool-call reliability with frontier models is not measured here; Multi-agent flows, memory, long conversations, streaming, tracing and cloud deployment; Anything beyond one tool and one question; three trials is a smoke test, not a benchmark. Full test log (commands, versions, raw output): [LangChain 1.4.7: our test log](https://theagenticweekly.com/tests/langchain) Full test log (commands, versions, raw output): [LangChain.js 1.5.19: our test log](https://theagenticweekly.com/tests/langchainjs) Pricing: Official page, dated. Open-source library; costs come from the model APIs you call. (checked 2026-10-25) ## Best for - [Best AI tool for agent building](https://theagenticweekly.com/best/agent-building) (#-): The most-starred Python and JS framework for LLM apps and agents. ## Key facts LangChain's repository is MIT-licensed; the newest release we saw was langchain-core 1.7.0 on Oct 22, 2026. LangChain is the base library and integration layer; LangGraph (already covered here) is the lower-level orchestration runtime for stateful agents. - License: MIT (per GitHub) - Platforms: Python and JavaScript libraries - Pricing model: Free and open source - Free tier: Free to self-host - Paid plans: None listed for the library - GitHub: langchain-ai/langchain: 148,451 stars on 2026-10-25, last push 2026-10-25 - Latest release we saw: langchain-core 1.7.0, 2026-10-22 - How to start: Install the package (pip install langchain or npm install langchain) and follow the quickstart in the official docs. - langchain-core 1.7.0 (2026-10-22): the newest release listed on the official page or repository when we read it on 2026-10-25. ## How to set it up: Get started with LangChain These steps come from the vendor's own pages as read on 2026-10-25. We ran LangChain on 2026-10-25; the test log lists what was and was not covered. 1. **Get access.** Install the package (pip install langchain or npm install langchain) and follow the quickstart in the official docs. 2. **Check the limits and costs first.** Free to self-host. Open-source library; costs come from the model APIs you call. ## Pros and cons Pros: - Very large integration surface - MIT license Cons: - Large API surface; abstractions have changed over time - Our test was one small task on a local 3B model; it does not show behaviour with hosted models or larger jobs ## Alternatives - [LangGraph](https://theagenticweekly.com/tools/langgraph): Low-level framework for building long-running, stateful agents as graphs. - [LlamaIndex](https://theagenticweekly.com/tools/llamaindex): Open-source data framework for retrieval-augmented generation and document-centred agents, with a hosted document platform alongside. - [CrewAI](https://theagenticweekly.com/tools/crewai): Python framework for orchestrating role-playing, autonomous AI agents that work as a crew. - [Langflow](https://theagenticweekly.com/tools/langflow): MIT-licensed visual builder for AI agents and MCP servers with a very large GitHub following. - [Botpress](https://theagenticweekly.com/tools/botpress): Customer-support AI agent platform with a free plan and conversation-based paid plans. - [Gumloop](https://theagenticweekly.com/tools/gumloop): Agent builder for teams; plans start at $37 per month with 20k included credits. - [Lindy](https://theagenticweekly.com/tools/lindy): AI 'employee' builder that connects to your tools; Free plan with $50 in credits that last 7 days, then credit-based plans. - [Microsoft Copilot Studio](https://theagenticweekly.com/tools/copilot-studio): Microsoft's platform for creating and managing custom agents, workflows and apps with no code. - [Pydantic AI](https://theagenticweekly.com/tools/pydantic-ai): Python agent framework built on Pydantic types, covering agents, realtime voice, image generation and embeddings. - [Relevance AI](https://theagenticweekly.com/tools/relevance-ai): Platform for specialist AI agents for sales, customer success, marketing and HR, with an embedded deployment team. - [Voiceflow](https://theagenticweekly.com/tools/voiceflow): Platform for chat and voice AI agents for customer experience teams. - [Vercel AI SDK](https://theagenticweekly.com/tools/vercel-ai-sdk): Vercel's TypeScript SDK that gives one API across many model providers, with streaming and agent helpers. ## FAQ ### What is LangChain? LangChain's repository is MIT-licensed; the newest release we saw was langchain-core 1.7.0 on Oct 22, 2026. LangChain is the base library and integration layer; LangGraph (already covered here) is the lower-level orchestration runtime for stateful agents. ### Is LangChain free? Free to self-host. Open-source library; costs come from the model APIs you call. Checked 2026-10-25; prices change, so confirm on the vendor's page. ### What license is LangChain under? Its license: MIT (per GitHub). Read from the project's own pages on 2026-10-25. ## Sources - [LangChain](https://www.langchain.com/) (fetched 2026-10-25) - [LangChain repository (GitHub)](https://github.com/langchain-ai/langchain) (fetched 2026-10-25) ## How to cite Agentic Weekly, "LangChain langchain-core 1.7.0: what's new, verdict & setup", last updated 2026-10-25, https://theagenticweekly.com/tools/langchain Keep the Reported or Tested label when you quote the verdict.