implemented chat and workflows

src/routes/chat.ts

@@ -96,6 +96,44 @@ export function chatRoutes() {
   const app = new Hono<AuthContext>();
   app.use("*", requireUser);
 
+  // Infer workflow step from which agents have been run
+  function inferWorkflowStep(sessions: Array<{ moduleId: string; status: string }>, messages: Array<{ role: string; content: string }>): { workflowActive: boolean; workflowStep: number; goal: string } {
+    const doneModules = new Set(sessions.filter(s => s.status === "done").map(s => s.moduleId));
+    let step = 0;
+    let goal = "";
+
+    // Extract goal from conversation (look for "I have an interview at..." or "prepare for...")
+    for (const m of messages) {
+      if (m.role === "user") {
+        const lower = m.content.toLowerCase();
+        if (lower.includes("interview at") || lower.includes("prepare for") || lower.includes("role at") || lower.includes("apply to")) {
+          goal = m.content;
+          break;
+        }
+      }
+    }
+
+    // Infer step from completed modules
+    // Step 1: Workflow started (user described goal)
+    if (goal) step = 1;
+    // Step 2: User shared JD/role info
+    if (messages.filter(m => m.role === "user" && m.content.length > 30).length >= 2) step = 2;
+    // Step 3: Resume agent done
+    if (doneModules.has("resume")) step = 3;
+    // Step 4: Interview session created
+    if (doneModules.has("sara")) step = 4;
+    // Step 5: Roleplay session created
+    if (doneModules.has("emily")) step = 5;
+    // Step 6: QScore computed
+    if (doneModules.has("qscore")) step = 6;
+
+    return {
+      workflowActive: step > 0,
+      workflowStep: step,
+      goal: goal || "Career preparation",
+    };
+  }
+
   app.post("/", async (c) => {
     const userId = c.get("userId");
     const body = chatSchema.parse(await c.req.json());
@@ -110,7 +148,9 @@ export function chatRoutes() {
       if (result?.reply) {
         const reply = cleanWorkflowTag(String(result.reply));
         const workflow = extractWorkflowTag(String(result.reply));
-        return c.json({ reply, workflow, sessions: (result as any).sessions ?? [] });
+        const sessions = (result as any).sessions ?? [];
+        const stepInfo = inferWorkflowStep(sessions, body.messages);
+        return c.json({ reply, workflow, sessions, ...stepInfo });
       }
     } catch (err) {
       console.warn("Rivet chat unavailable, using direct LLM:", err instanceof Error ? err.message : String(err));
@@ -239,6 +279,7 @@ export function chatRoutes() {
         reply: cleanWorkflowTag(reply),
         workflow: extractWorkflowTag(reply),
         sessions,
+        ...inferWorkflowStep(sessions, body.messages),
       });
     } catch (llmErr) {
       console.error("Direct LLM chat error:", llmErr);

src/routes/workflows.ts

@@ -1,15 +1,23 @@
 import { Hono } from "hono";
 import { z } from "zod";
-import { createClient } from "rivetkit/client";
+import { createClient, type Client } from "rivetkit/client";
 import { config } from "../config.js";
 import { requireUser, type AuthContext } from "../auth/clerk.js";
 import type { Registry } from "../actors/registry.js";
 
-const client = createClient<Registry>(config.rivetEndpoint);
+// Lazy-load the Rivet client to avoid connecting at import time when the engine
+// isn't running (avoids "failed to fetch metadata" spam on startup).
+let _client: Client<Registry> | null = null;
+function getClient(): Client<Registry> {
+  if (!_client) {
+    _client = createClient<Registry>(config.rivetEndpoint);
+  }
+  return _client;
+}
 
 // Per changes.md §5: one unified userActor per user.
 function userActorFor(userId: string) {
-  return client.userActor.getOrCreate([userId]);
+  return getClient().userActor.getOrCreate([userId]);
 }
 
 export function workflowRoutes() {