Join our daily and weekly newsletters for the latest updates and exclusive content on industry-leading AI coverage. Learn More<\/em><\/p>\n\n\n\n LangChain, one of the leaders in the AI framework and orchestration space, plans to remain committed to the open source ecosystem, particularly as it reinforces its vendor-agnostic stance.\u00a0<\/p>\n\n\n\n Harrison Chase, Langchain co-founder and CEO, told VentureBeat that the success of its different platforms can be attributed to developers demanding model choice and not staying in a closed provider.\u00a0<\/p>\n\n\n\n \u201cThe power of the LangChain framework is in its integrations and the ecosystem,\u201d Chase said. \u201cThe scale of the ecosystem is enormous, and much of that is made possible by the framework being open source.\u201d<\/p>\n\n\n\n Chase said LangChain downloads reached 72.3 million last month, compared to competitors like OpenAI\u2019s Agents SDK. He added that the LangChain Python and JS frameworks \u201chave 4,500 contributors, that\u2019s more contributors than Spark.\u201d<\/p>\n\n\n\n LangChain, founded in 2022, has grown beyond its initial framework, which helped developers build AI applications. In February last year, it released the testing and evaluation platform\u00a0LangSmith, a second framework called LangGraph<\/span> and LangGraph Platform to help deploy autonomous agents.\u00a0<\/p>\n\n\n\n LangChain remained open source and agnostic to vendors and models throughout its growth. For example, it\u2019s partnered with multiple companies, like\u00a0Google\u00a0and\u00a0Cisco,\u00a0around\u00a0agent interoperability. As enterprises began experimenting with AI agents, Chase said LangChain saw an opportunity to offer deployment options that considered<\/span> developer choices.<\/p>\n\n\n\n \u201cOver the past year and a half or so, more and more enterprises and companies are just looking to go into production. So we matured all of our offerings, not just the open source LangChain, but all of our offerings collectively as a company to meet that demand and make it as easy as possible to build agentic applications,\u201d he said.\u00a0<\/p>\n\n\n\n One of LangChain\u2019s new open-source platforms is the LangGraph Platform, which became\u00a0generally available this week. The LangGraph Platform lets developers manage and begin deploying<\/span> long-lasting or stateful agents. These agents build on what Chase calls \u201cambient agents,\u201d or agents that work in the background and are triggered by certain events.\u00a0<\/p>\n\n\n\n \u201cWe\u2019ve tried to focus a lot on some of the harder infrastructure problems that surround these agents,\u201d Chase said. \u201cLangGraph is good for long-running stateful agents, so if you\u2019re deploying a simple application, you don\u2019t want to use LangGraph Platform.\u201d<\/p>\n\n\n\n He added that the company wants to bet big on ambient or long-running agents, finding this more independent, autonomous agent a more interesting infrastructure challenge.\u00a0<\/p>\n\n\n\n Through the LangGraph Platform, organizations can deploy agents with one-click deployment, horizontal scaling to handle \u201cbursty, long-running traffic,\u201d a persistence layer to support agentic memory, API endpoints for customization and native access to LangGraph Studio to debug any agents.\u00a0<\/p>\n\n\n\n Organizations might find themselves bringing more and more agents online. LangGraph Platform includes a management console that lays out all the agents currently deployed and lets users find agents, reuse common agent architectures and create multi-agent architectures.\u201d<\/p>\n\n\n\n \u201cOne of the big benefits of LangGraph is that it gives the builder of the agent full control over the cognitive architecture. If there\u2019s an [large language model] LLM action that must be done right, a good tool you have to enforce quality is to create an in-the-loop evaluation directly in your LangGraph app,\u201d Chase said.\u00a0<\/p>\n\n\n\n Chase added that with LangGraph, developers can access \u201ca good orchestration framework\u201d to build agents and bring these reliable agents into LangGraph Platform for deployment.\u00a0<\/p>\n\n\n\n During the best test, Chase said over 370 teams used LangGraph Platform. LangChain offers three tiers to use LangGraph Platform, with pricing dependent on how developers plan to host the service.\u00a0<\/p>\n\n\n\n For Chase, one of LangChain\u2019s strengths is its ability to create an entire application and agent development ecosystem.\u00a0<\/p>\n\n\n\n LangSmith, the company\u2019s testing and observability platform, works with LangGraph and LangGraph Platform to track agent metrics. Since many agents built and run with LangGraph Platform are longer-running, enterprises need to check whether they continue to perform to specifications constantly.\u00a0<\/p>\n\n\n\n Chase boasted that LangGraph \u201cis the most widely adopted agent framework\u201d and claimed it\u2019s downloaded more than AutoGen from Microsoft and the CrewAI agentic platform, once again citing the open-source value for its success.<\/p>\n\n\n\n \u201cLangGraph is most often selected by teams that need to build end-user facing or highly trafficked agents (LinkedIn, Uber, GitLab) \u2013 the reason is that you won\u2019t scale off of LangGraph because it\u2019s very low-level and controllable, which is needed for reliable agents. CrewAI and Autogen are often used because they have a less steep learning curve \u2013 these frameworks make more decisions for the user, so you\u2019re trading ease of adoption for power,\u201d he said.<\/p>\n\n\n\n\n Daily insights on business use cases with VB Daily<\/strong><\/p>\n If you want to impress your boss, VB Daily has you covered. We give you the inside scoop on what companies are doing with generative AI, from regulatory shifts to practical deployments, so you can share insights for maximum ROI.<\/p>\n \n\t\t\t\t\tThanks for subscribing. Check out more VB newsletters here.\n\t\t\t\t<\/p>\n An error occured.<\/p>\n<\/p><\/div>\n
\n<\/div>LangGraph Platform extends open-source offerings<\/h2>\n\n\n\n
The broader LangChain open-source ecosystem<\/h2>\n\n\n\n
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