Guides | ğŸ¦œï¸�ğŸ”— Langchain






Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKGet startedIntroductionInstallationQuickstartLangChain Expression LanguageInterfaceHow toCookbookLangChain Expression Language (LCEL)Why use LCEL?ModulesModel I/â€‹ORetrievalChainsMemoryAgentsCallbacksModulesSecurityGuidesAdaptersDebuggingDeploymentEvaluationFallbacksLangSmithRun LLMs locallyModel comparisonPrivacyPydantic compatibilitySafetyMoreGuidesGuidesDesign guides for key parts of the development processğŸ—ƒï¸� Adapters1 itemsğŸ“„ï¸� DebuggingIf you're building with LLMs, at some point something will break, and you'll need to debug. A model call will fail, or the model output will be misformatted, or there will be some nested model calls and it won't be clear where along the way an incorrect output was created.ğŸ—ƒï¸� Deployment1 itemsğŸ—ƒï¸� Evaluation4 itemsğŸ“„ï¸� FallbacksWhen working with language models, you may often encounter issues from the underlying APIs, whether these be rate limiting or downtime. Therefore, as you go to move your LLM applications into production it becomes more and more important to safeguard against these. That's why we've introduced the concept of fallbacks.ğŸ—ƒï¸� LangSmith1 itemsğŸ“„ï¸� Run LLMs locallyUse caseğŸ“„ï¸� Model comparisonConstructing your language model application will likely involved choosing between many different options of prompts, models, and even chains to use. When doing so, you will want to compare these different options on different inputs in an easy, flexible, and intuitive way.ğŸ—ƒï¸� Privacy1 itemsğŸ“„ï¸� Pydantic compatibility- Pydantic v2 was released in June, 2023 (https://docs.pydantic.dev/2.0/blog/pydantic-v2-final/)ğŸ—ƒï¸� Safety5 itemsPreviousSecurityNextOpenAI AdapterCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.
Design guides for key parts of the development process
Design guides for key parts of the development process ->: Guides | ğŸ¦œï¸�ğŸ”— Langchain






Skip to main contentğŸ¦œï¸�ğŸ”— LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKGet startedIntroductionInstallationQuickstartLangChain Expression LanguageInterfaceHow toCookbookLangChain Expression Language (LCEL)Why use LCEL?ModulesModel I/â€‹ORetrievalChainsMemoryAgentsCallbacksModulesSecurityGuidesAdaptersDebuggingDeploymentEvaluationFallbacksLangSmithRun LLMs locallyModel comparisonPrivacyPydantic compatibilitySafetyMoreGuidesGuidesDesign guides for key parts of the development processğŸ—ƒï¸� Adapters1 itemsğŸ“„ï¸� DebuggingIf you're building with LLMs, at some point something will break, and you'll need to debug. A model call will fail, or the model output will be misformatted, or there will be some nested model calls and it won't be clear where along the way an incorrect output was created.ğŸ—ƒï¸� Deployment1 itemsğŸ—ƒï¸� Evaluation4 itemsğŸ“„ï¸� FallbacksWhen working with language models, you may often encounter issues from the underlying APIs, whether these be rate limiting or downtime. Therefore, as you go to move your LLM applications into production it becomes more and more important to safeguard against these. That's why we've introduced the concept of fallbacks.ğŸ—ƒï¸� LangSmith1 itemsğŸ“„ï¸� Run LLMs locallyUse caseğŸ“„ï¸� Model comparisonConstructing your language model application will likely involved choosing between many different options of prompts, models, and even chains to use. When doing so, you will want to compare these different options on different inputs in an easy, flexible, and intuitive way.ğŸ—ƒï¸� Privacy1 itemsğŸ“„ï¸� Pydantic compatibility- Pydantic v2 was released in June, 2023 (https://docs.pydantic.dev/2.0/blog/pydantic-v2-final/)ğŸ—ƒï¸� Safety5 itemsPreviousSecurityNextOpenAI AdapterCommunityDiscordTwitterGitHubPythonJS/TSMoreHomepageBlogCopyright Â© 2023 LangChain, Inc.