fix format

docusaurus.config.js

@@ -48,13 +48,13 @@ const config = {
           lastVersion: "current",
           versions: {
             current: {
-              label: '1.0',
+              label: "1.0",
               badge: false,
             },
             "2.0": {
               label: "2.0",
               banner: "unreleased",
-            }
+            },
           },
           sidebarPath: require.resolve("./sidebars.js"),
           remarkPlugins: [

versioned_docs/version-2.0/concepts.md

@@ -4,29 +4,29 @@ Explanations, clarification and discussion of key topics in LangSmith.
 
 ### Admin
 
-- [ ]  Organizations
-- [ ]  Workspaces
-- [ ]  Users
-- [ ]  API Keys
-- [ ]  Personal Access Tokens
-- [ ]  Roles
+- [ ] Organizations
+- [ ] Workspaces
+- [ ] Users
+- [ ] API Keys
+- [ ] Personal Access Tokens
+- [ ] Roles
 
 ### Tracing
 
-- [ ]  Projects
-- [ ]  Traces
-- [ ]  Runs
-- [ ]  Tags
-- [ ]  Metadata
+- [ ] Projects
+- [ ] Traces
+- [ ] Runs
+- [ ] Tags
+- [ ] Metadata
 
 ### Evaluation
 
-- [ ]  Prompts
-- [ ]  Experiment
-- [ ]  Datasets
-- [ ]  Feedback
-- [ ]  Evaluator
+- [ ] Prompts
+- [ ] Experiment
+- [ ] Datasets
+- [ ] Feedback
+- [ ] Evaluator
 
-- [ ]  Annotation Queue
-- [ ]  Prompt
-- [ ]  Playground
+- [ ] Annotation Queue
+- [ ] Prompt
+- [ ] Playground

versioned_docs/version-2.0/how_to_guides.md

@@ -4,102 +4,102 @@ Step-by-step guides that cover key tasks, operations and common problems.
 
 ### Setup
 
-- [ ]  Create an account and API Key
-- [ ]  Setup an organization
-- [ ]  Setup a workspace
-- [ ]  Setup Billing
-- [ ]  Assigning Roles (enterprise only)
+- [ ] Create an account and API Key
+- [ ] Setup an organization
+- [ ] Setup a workspace
+- [ ] Setup Billing
+- [ ] Assigning Roles (enterprise only)
 
 ### Deployment
 
-- [ ]  Self-hosting LangSmith on Kubernetes
-- [ ]  Self-hosting LangSmith via Docker Compose
-- [ ]  Setting up Auth
+- [ ] Self-hosting LangSmith on Kubernetes
+- [ ] Self-hosting LangSmith via Docker Compose
+- [ ] Setting up Auth
 
 ### Tracing
 
-- [ ]  Annotate code for tracing
-    - [ ]  `traceable`
-    - [ ]  wrapping OpenAI or Custom LLM
-    - [ ]  RunTree
-- [ ]  Log traces to specific project
-- [ ]  Toggle tracing on and off
-- [ ]  Sample traces
-- [ ]  Add metadata and tags to traces
-- [ ]  Get run_id and trace_id
-- [ ]  Mask inputs and outputs
-- [ ]  Log a trace using LangChain
-- [ ]  Log a trace using instructor
-- [ ]  Exporting traces
-    - [ ]  Link to data format in reference section
-- [ ]  Log multi-modal traces
+- [ ] Annotate code for tracing
+  - [ ] `traceable`
+  - [ ] wrapping OpenAI or Custom LLM
+  - [ ] RunTree
+- [ ] Log traces to specific project
+- [ ] Toggle tracing on and off
+- [ ] Sample traces
+- [ ] Add metadata and tags to traces
+- [ ] Get run_id and trace_id
+- [ ] Mask inputs and outputs
+- [ ] Log a trace using LangChain
+- [ ] Log a trace using instructor
+- [ ] Exporting traces
+  - [ ] Link to data format in reference section
+- [ ] Log multi-modal traces
 
 ### Datasets
 
-- [ ]  Create a dataset in the application
-- [ ]  Create a dataset using the API
-- [ ]  Export datasets
-- [ ]  Import datasets
-- [ ]  Version datasets
-- [ ]  Add metadata to examples
-- [ ]  Filter examples from a dataset
-- [ ]  Add a trace to a dataset
+- [ ] Create a dataset in the application
+- [ ] Create a dataset using the API
+- [ ] Export datasets
+- [ ] Import datasets
+- [ ] Version datasets
+- [ ] Add metadata to examples
+- [ ] Filter examples from a dataset
+- [ ] Add a trace to a dataset
 
 ### Evaluation
 
-- [ ]  Run an evaluation
-- [ ]  Run an evaluation from the playground
-- [ ]  Run an evaluation on a particular version of dataset
-- [ ]  Run an evaluation on subset of dataset
-- [ ]  Use off-the-shelf LangChain evaluators
-- [ ]  Use custom evaluators
-- [ ]  Evaluate on intermediate steps
-- [ ]  Compare experiment results
-- [ ]  Track regressions and improvements
-- [ ]  Export experiment
-- [ ]  Unit test LLM applications
-- [ ]  View trace for an evaluation run
-- [ ]  Run a pairwise evaluation (coming soon)
-- [ ]  Audit evaluation scores (coming soon)
+- [ ] Run an evaluation
+- [ ] Run an evaluation from the playground
+- [ ] Run an evaluation on a particular version of dataset
+- [ ] Run an evaluation on subset of dataset
+- [ ] Use off-the-shelf LangChain evaluators
+- [ ] Use custom evaluators
+- [ ] Evaluate on intermediate steps
+- [ ] Compare experiment results
+- [ ] Track regressions and improvements
+- [ ] Export experiment
+- [ ] Unit test LLM applications
+- [ ] View trace for an evaluation run
+- [ ] Run a pairwise evaluation (coming soon)
+- [ ] Audit evaluation scores (coming soon)
 
 ### Human Feedback
 
-- [ ]  Attach user feedback from your application to traces
-- [ ]  Annotate traces inline
-- [ ]  Add trace to annotation queue
-- [ ]  Annotate traces in the annotation queue
+- [ ] Attach user feedback from your application to traces
+- [ ] Annotate traces inline
+- [ ] Add trace to annotation queue
+- [ ] Annotate traces in the annotation queue
 
 ### Monitoring and Automations
 
-- [ ]  Filter for runs
-- [ ]  Use a trace filter
-- [ ]  View the monitor charts
-- [ ]  Slice chart by metadata and tag
-- [ ]  Set up a rule
-    - [ ]  Online evaluation
-    - [ ]  Annotation Queue addition
-    - [ ]  Dataset addition
-    - [ ]  Webhook action
-- [ ]  Group traces as threads
-- [ ]  View threads
+- [ ] Filter for runs
+- [ ] Use a trace filter
+- [ ] View the monitor charts
+- [ ] Slice chart by metadata and tag
+- [ ] Set up a rule
+  - [ ] Online evaluation
+  - [ ] Annotation Queue addition
+  - [ ] Dataset addition
+  - [ ] Webhook action
+- [ ] Group traces as threads
+- [ ] View threads
 
 ### Prompt Hub
 
-- [ ]  Create a prompt
-- [ ]  Update a prompt
-- [ ]  Pull prompts in code
-- [ ]  Open a prompt from a trace
-- [ ]  Open a prompt from an experiment
+- [ ] Create a prompt
+- [ ] Update a prompt
+- [ ] Pull prompts in code
+- [ ] Open a prompt from a trace
+- [ ] Open a prompt from an experiment
 
 ### Playground
 
-- [ ]  Run a prompt in the playground
-- [ ]  Run a prompt on a custom model
+- [ ] Run a prompt in the playground
+- [ ] Run a prompt on a custom model
 
 ### Proxy
 
-- [ ]  Run proxy
-- [ ]  Make a request to the proxy
-- [ ]  Turn off caching
-- [ ]  Stream results
-- [ ]  Turn on tracing
+- [ ] Run proxy
+- [ ] Make a request to the proxy
+- [ ] Turn off caching
+- [ ] Stream results
+- [ ] Turn on tracing

versioned_docs/version-2.0/reference.md

@@ -2,8 +2,8 @@
 
 Technical reference that covers the LangSmith API, SDKs, data format, and architecture.
 
-- [ ]  LangSmith Python SDK
-- [ ]  LangSmith TypeScript SDK
-- [ ]  LangSmith API Reference
-- [ ]  Data format
-- [ ]  Architecture diagram
+- [ ] LangSmith Python SDK
+- [ ] LangSmith TypeScript SDK
+- [ ] LangSmith API Reference
+- [ ] Data format
+- [ ] Architecture diagram

versioned_docs/version-2.0/release_notes.md

@@ -1 +1 @@
-# Release Notes
+# Release Notes

versioned_docs/version-2.0/tutorials.md

@@ -2,13 +2,13 @@
 
 New to LangSmith? This is the place to start. Here, you'll find a hands-on introduction to key LangSmith workflows.
 
-Build up datasets from production traces
-Iterate on prompts
-Create a data flywheel to optimize your LLM application
-Debug your LLM application
-Utilize LLM-as-a-judge evaluators
-Evaluate RAG applications
-Prompt iteration as a non-developer
-Reduce noise during evaluation
-Evaluate agents
-Back testing
+* Build up datasets from production traces
+* Iterate on prompts
+* Create a data flywheel to optimize your LLM application
+* Debug your LLM application
+* Utilize LLM-as-a-judge evaluators
+* Evaluate RAG applications
+* Prompt iteration as a non-developer
+* Reduce noise during evaluation
+* Evaluate agents
+* Back testing