more work on getting-started/task-engine example

docs/code/getting-started/task-engine/server.cue

@@ -0,0 +1,66 @@
+package examples
+
+import "strings"
+
+server: {
+  @flow(server)
+
+  // task: get auth from external command
+  gcp: {
+    @task(os.Exec)
+    cmd: ["gcloud", "auth", "print-access-token"]
+    stdout: string
+    key:    strings.TrimSpace(stdout)
+  }
+
+  run: {
+    @task(api.Serve)
+
+    port: "8080"
+    routes: {
+
+      // simple hello route
+      "/hello": {
+        method: "GET"
+        resp: {
+          status: 200
+          body: "hallo chat!"
+        }
+      }
+
+      // echo request object back as json
+      "/jsonecho": {
+        method: ["GET", "POST"]
+        req: body: {}
+        resp: json: req
+      }
+
+      // our gemini call warpped in an API
+      "/chat": {
+        @flow()
+
+        method: "POST"
+
+        // input schema
+        req: {
+          body: {
+            msg: string
+          }
+        }
+
+        // task: api call via reusable task
+        call: _gemini & {
+          apikey: gcp.key
+          msg: req.body.msg
+        }
+
+        // the response to user
+        resp: {
+          status: 200
+          body: call.final.text
+        }
+      }
+
+    }
+  }
+}

docs/code/getting-started/task-engine/vertex.cue

@@ -2,6 +2,13 @@ package examples
 
 import "strings"
 
+// inputs supplied via tags
+inputs: {
+  model: string @tag(model)
+  prompt: string @tag(prompt)
+  msg: string @tag(msg)
+}
+
 vertex_chat: {
   @flow() // define a flow
 
@@ -19,7 +26,9 @@ vertex_chat: {
     call: _gemini & {
       apikey: gcp.key
 
-      msg: "What is the CUE language?"
+      model: inputs.model
+      prompt: inputs.prompt
+      msg: inputs.msg
 
       resp: body: _
     }
@@ -37,11 +46,10 @@ vertex_chat: {
 _gemini: {
   @task(api.Call)
 
+  apikey: string
   model: string | *"gemini-1.0-pro-002:generateContent"
-
+  prompt: string | *"You are an assistant who is very concise when responding."
   msg: string
-  apikey: string
-  prompt: string | *"You are a model which is direct and concise when responding."
 
   req: {
     host: "https://us-central1-aiplatform.googleapis.com"
@@ -71,6 +79,7 @@ _gemini: {
   resp: {
     body: _
   }
+  @print(resp.body)
 
   // task-local ETL
   final: {

docs/content/getting-started/task-engine.md

@@ -25,9 +25,19 @@ Hof's task engine is an extension of cue/flow with
 
 ### Example
 
+<br>
 
-{{<codePane title="hof flow example.cue" file="code/getting-started/task-engine/vertex.html" >}}
+A workflow for calling an LLM from the command line.
 
+{{<codePane title="hof flow vertex.cue -t msg='What is the CUE language?'" file="code/getting-started/task-engine/vertex.html" >}}
+
+<br>
+
+Wrapping the workflow in an API server.
+
+`hof flow @server` (with both CUE files in the same directory, we can omit the filenames)
+
+{{<codePane title="server.cue" file="code/getting-started/task-engine/server.html" >}}
 
 ### Command