spelling mistake

Author: maxdeichmann

.cursor/rules/available-internal-links.mdc

@@ -40,6 +40,23 @@ Add the following to your `mcp.json`:
 
 <Tab>
 
+Add Langfuse Docs MCP to Copilot in VSCode via the one-click install:
+
+<div className="flex gap-2 mt-3 mb-6">
+  <Button asChild>
+    <Link
+      href="vscode:mcp/install?%7B%22name%22%3A%22langfuse-docs%22%2C%22url%22%3A%22https%3A%2F%2Flangfuse.com%2Fapi%2Fmcp%22%7D"
+      target="_blank"
+      rel="noopener noreferrer"
+    >
+      Install MCP Server in VS Code
+    </Link>
+  </Button>
+</div>
+
+<details>
+<summary>Manual configuration</summary>
+
 Add Langfuse Docs MCP to Copilot in VSCode via the following steps:
 
 1. Open Command Palette (⌘+Shift+P)
@@ -49,6 +66,8 @@ Add Langfuse Docs MCP to Copilot in VSCode via the following steps:
 5. Select name (e.g. `langfuse-docs`) and whether to save in user or workspace settings
 6. You're all set! The MCP server is now available in Agent mode
 
+</details>
+
 </Tab>
 
 <Tab>

components-mdx/docs-mcp-server-installation.mdx

@@ -30,12 +30,12 @@ from langfuse import get_client
 langfuse = get_client()
 
 # Create a span using a context manager
-with langfuse.start_as_current_span(name="process-request") as span:
+with langfuse.start_as_current_observation(as_type="span", name="process-request") as span:
     # Your processing logic here
     span.update(output="Processing complete")
 
     # Create a nested generation for an LLM call
-    with langfuse.start_as_current_generation(name="llm-response", model="gpt-3.5-turbo") as generation:
+    with langfuse.start_as_current_observation(as_type="generation", name="llm-response", model="gpt-3.5-turbo") as generation:
         # Your LLM call logic here
         generation.update(output="Generated response")
 

components-mdx/get-started/python-sdk.mdx

@@ -18,27 +18,31 @@ You can use this integration together with the Langfuse [Python SDK](/docs/obser
 The [`@observe()` decorator](/docs/observability/sdk/python/instrumentation#custom-instrumentation) provides a convenient way to automatically wrap your instrumented code and add additional attributes to the trace.
 
 ```python
-from langfuse import observe, get_client
+from langfuse import observe, propagate_attributes, get_client
 
 langfuse = get_client()
-
+ 
 @observe()
-def my_instrumented_function(input):
-
-    # Run your application here
-    output = my_llm_call(input)
-
-    langfuse.update_current_trace(
-        input=input,
-        output=output,
+def my_llm_pipeline(input):
+    # Add additional attributes (user_id, session_id, metadata, version, tags) to all spans created within this execution scope
+    with propagate_attributes(
         user_id="user_123",
         session_id="session_abc",
         tags=["agent", "my-trace"],
         metadata={"email": "[email protected]"},
         version="1.0.0"
-    )
+    ):
+
+        # YOUR APPLICATION CODE HERE
+        result = call_llm(input)
+
+        # Update the trace input and output
+        langfuse.update_current_trace(
+            input=input,
+            output=result,
+        )
 
-    return output
+        return result
 ```
 
 Learn more about using the Decorator in the [Python SDK](/docs/observability/sdk/python/instrumentation#custom-instrumentation) docs.
@@ -49,24 +53,26 @@ Learn more about using the Decorator in the [Python SDK](/docs/observability/sdk
 The [Context Manager](/docs/observability/sdk/python/instrumentation#custom-instrumentation) allows you to wrap your instrumented code using context managers (with `with` statements), which allows you to add additional attributes to the trace.
 
 ```python
-from langfuse import get_client
+from langfuse import get_client, propagate_attributes
 
 langfuse = get_client()
 
-with langfuse.start_as_current_span(name="my-trace") as span:
-    
-    # Run your application here
-    output = my_llm_call(input)
-
-    # Pass additional attributes to the span
-    span.update_trace(
-        input=input,
-        output=output,
+with langfuse.start_as_current_observation(as_type="span", name="my-trace") as span:
+    # Add additional attributes (user_id, session_id, metadata, version, tags) to all spans created within this execution scope
+    with propagate_attributes(
         user_id="user_123",
         session_id="session_abc",
-        tags=["agent", "my-trace"],
-        metadata={"email": "[email protected]"},
-        version="1.0.0"
+        metadata={"experiment": "variant_a", "env": "prod"},
+        version="1.0"
+    ):
+    
+        # YOUR APPLICATION CODE HERE
+        result = call_llm("some input")
+
+        # Update the trace input and output
+        langfuse.start_as_current_observation(
+            input=input,
+            output=result,
         )
 
 # Flush events in short-lived applications

components-mdx/integration-learn-more.mdx

@@ -32,7 +32,8 @@ langfuse = get_client()
 
 prompt = langfuse.get_prompt("movie-critic")
 
-with langfuse.start_as_current_generation(
+with langfuse.start_as_current_observation(
+    as_type="generation",
     name="movie-generation",
     model="gpt-4o",
     prompt=prompt

components-mdx/prompt-linking.mdx

@@ -7,6 +7,7 @@
 - Jannik Maierhöfer, [@jmaierhoefer](https://x.com/jmaierhoefer), [GitHub](https://github.com/jannikmaierhoefer), [LinkedIn](https://www.linkedin.com/in/maierhoefer/)
 - Felix Krauth, [@felixkrrr](https://x.com/felixkrrr), [GitHub](https://github.com/felixkrrr), [LinkedIn](https://www.linkedin.com/in/krauth/)
 - Akio Nuernberger, [@AkioNuernberger](https://x.com/AkioNuernberger), [LinkedIn](https://www.linkedin.com/in/akio-nuernberger/)
-- Nimar Blume, [GitHub](https://github.com/nimarb), [LinkedIn](https://www.linkedin.com/in/nimar/)
+- Nimar Blume, [@nimarblu](https://x.com/nimarblu), [GitHub](https://github.com/nimarb), [LinkedIn](https://www.linkedin.com/in/nimar/)
 - Michael Froehlich, [GitHub](https://github.com/FroeMic), [LinkedIn](https://www.linkedin.com/in/m-froehlich)
 - Valeriy Meleshkin, [GitHub](https://github.com/sumerman), [LinkedIn](https://www.linkedin.com/in/valeriy-meleshkin-5610ab58)
+- Lotte Verheyden, [GitHub](https://github.com/Lotte-Verheyden), [LinkedIn](https://www.linkedin.com/in/lotteverheyden/)

components-mdx/team-members.mdx

@@ -1,7 +1,7 @@
 import { DotPattern } from "./magicui/dot-pattern";
 
 export const Background = () => (
-  <div className="absolute top-0 bottom-0 left-0 right-0 -z-50">
+  <div className="absolute top-0 bottom-0 left-0 right-0 -z-50 pointer-events-none">
     <DotPattern
       width={15}
       height={15}

components/Background.tsx

@@ -1,29 +1,21 @@
 import Cal, { getCalApi } from "@calcom/embed-react";
 import { useEffect } from "react";
 
-export function ScheduleDemo({
-  className,
-  region,
-}: {
-  className?: string;
-  region: "us" | "eu";
-}) {
+export function ScheduleDemo({ className }: { className?: string }) {
   useEffect(() => {
     (async function () {
       const cal = await getCalApi();
       cal("ui", {
         styles: { branding: { brandColor: "#000000" } },
-        hideEventTypeDetails: false,
+        hideEventTypeDetails: true,
         layout: "month_view",
       });
     })();
   }, []);
 
-  const calLink = region === "us" ? "team/langfuse/intro" : "team/langfuse/intro-eu";
-
   return (
     <Cal
-      calLink={calLink}
+      calLink="team/langfuse/intro"
       className={className}
       style={{ width: "100%", height: "100%", overflow: "scroll" }}
       config={{ layout: "month_view" }}

components/CalComScheduleDemo.tsx

@@ -4,7 +4,7 @@ import IconGithub from "./icons/github";
 export const GithubMenuBadge = () => (
   <a
     href="https://github.com/langfuse/langfuse"
-    className="group h-8 flex shrink-0 flex-row items-center rounded border border-primary/10 overflow-hidden transition-opacity"
+    className="hidden sm:flex group h-8 shrink-0 flex-row items-center rounded border border-primary/10 overflow-hidden transition-opacity"
     target="_blank"
     rel="nofollow noreferrer"
     title="GitHub Repository"

components/GitHubBadge.tsx

@@ -19,9 +19,14 @@ export function HiringBadge() {
       onMouseLeave={() => setIsHovered(false)}
       onFocus={() => setIsHovered(true)}
       onBlur={() => setIsHovered(false)}
+      style={{ width: "max-content" }}
     >
-      {isHovered ? "Looking for 🐐s!" : "Hiring in Berlin and SF"}
+      <span className={cn(isHovered && "invisible")}>
+        Hiring in Berlin and SF
+      </span>
+      <span className={cn("absolute", !isHovered && "invisible")}>
+        Looking for 🐐s!
+      </span>
     </Link>
   );
 }
-