fix(langgraph): uncomment FOUNDRY_PROJECT_ENDPOINT in .env.example (microsoft-foundry#411)

Leave the value empty so the Foundry toolkit VS Code extension can

auto-populate the project endpoint (and model deployment name) when

scaffolding from these samples.

Author: kuojianlu

samples/python/hosted-agents/langgraph/invocations/01-langgraph-chat/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=

samples/python/hosted-agents/langgraph/responses/01-langgraph-chat/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=

samples/python/hosted-agents/langgraph/responses/04-mcp/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=

samples/python/hosted-agents/langgraph/responses/05-workflows/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 # This sample chains three LLM calls and requires a model strong enough

samples/python/hosted-agents/langgraph/responses/06-files/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=

samples/python/hosted-agents/langgraph/responses/07-human-in-the-loop/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=

samples/python/hosted-agents/langgraph/responses/08-observability/.env.example

@@ -1,6 +1,6 @@
 # Foundry project endpoint — auto-injected in hosted containers.
 # Only set manually if running without `azd ai agent run`.
-# FOUNDRY_PROJECT_ENDPOINT=https://<account>.services.ai.azure.com/api/projects/<project>
+FOUNDRY_PROJECT_ENDPOINT=
 
 # Model deployment name — must match a deployment in your Foundry project.
 AZURE_AI_MODEL_DEPLOYMENT_NAME=