Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksArgillaConfidentContextInfinoLabel StudioLLMonitorPromptLayerSageMaker TrackingStreamlitTrubricsChat loadersComponentsCallbacksLabel StudioOn this pageLabel StudioLabel Studio is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the collection and evaluation of responses through human feedback.In this guide, you will learn how to connect a LangChain pipeline to Label Studio to:Aggregate all input prompts, conversations, and responses in a single LabelStudio project. This consolidates all the data in one place for easier labeling and analysis.Refine prompts and responses to create a dataset for supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) scenarios. The labeled data can be used to further train the LLM to improve its performance.Evaluate model responses through human feedback. LabelStudio provides an interface for humans to review and provide feedback on model responses, allowing evaluation and iteration.Installation and setup‚ÄãFirst install latest versions of Label Studio and Label Studio API client:pip install -U label-studio label-studio-sdk openaiNext, run label-studio on the command line to start the local LabelStudio instance at http://localhost:8080. See the Label Studio installation guide for more options.You'll need a token to make API calls.Open your LabelStudio instance in your browser, go to Account & Settings > Access Token and copy the key.Set environment variables with your LabelStudio URL, API key and OpenAI API key:import
Label Studio is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the collection and evaluation of responses through human feedback.
Label Studio is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the collection and evaluation of responses through human feedback. ->: Skip to main contentü¶úÔ∏èüîó LangChainDocsUse casesIntegrationsAPICommunityChat our docsLangSmithJS/TS DocsSearchCTRLKProvidersAnthropicAWSGoogleMicrosoftOpenAIMoreComponentsLLMsChat modelsDocument loadersDocument transformersText embedding modelsVector storesRetrieversToolsAgents and toolkitsMemoryCallbacksArgillaConfidentContextInfinoLabel StudioLLMonitorPromptLayerSageMaker TrackingStreamlitTrubricsChat loadersComponentsCallbacksLabel StudioOn this pageLabel StudioLabel Studio is an open-source data labeling platform that provides LangChain with flexibility when it comes to labeling data for fine-tuning large language models (LLMs). It also enables the preparation of custom training data and the collection and evaluation of responses through human feedback.In this guide, you will learn how to connect a LangChain pipeline to Label Studio to:Aggregate all input prompts, conversations, and responses in a single LabelStudio project. This consolidates all the data in one place for easier labeling and analysis.Refine prompts and responses to create a dataset for supervised fine-tuning (SFT) and reinforcement learning with human feedback (RLHF) scenarios. The labeled data can be used to further train the LLM to improve its performance.Evaluate model responses through human feedback. LabelStudio provides an interface for humans to review and provide feedback on model responses, allowing evaluation and iteration.Installation and setup‚ÄãFirst install latest versions of Label Studio and Label Studio API client:pip install -U label-studio label-studio-sdk openaiNext, run label-studio on the command line to start the local LabelStudio instance at http://localhost:8080. See the Label Studio installation guide for more options.You'll need a token to make API calls.Open your LabelStudio instance in your browser, go to Account & Settings > Access Token and copy the key.Set environment variables with your LabelStudio URL, API key and OpenAI API key:import