feat: QA fixes, new APIs (assignments, rubrics, custom exams), Generation page enhancements

- Fix ELAI video generation (correct render endpoint, script splitting for 60s limit)
- Fix speaking script generation error handling and empty response display
- Add custom exam list API (GET /api/exam/custom/list)
- Add assignments REST API (list, create, get)
- Add rubrics REST API (list, create)
- Enhance Generation page: dynamic exam structures, auto-module selection, preview dialog, audio player
- Improve submit feedback with exam ID and status in toast notifications
- Fix ExamsListPage to show both custom exams and exam sessions
- Connect RubricsPage to backend API with fallback data
- Add Dockerfile, docker-compose.yml, requirements.txt for deployment
- Fix placement, grading, scoring, and auth controllers
- Add ErrorBoundary component for frontend resilience
- Add QA report and credentials documentation

Made-with: Cursor

custom_addons/encoach_ai/services/elai_service.py

@@ -12,6 +12,14 @@ except ImportError:
 
 ELAI_BASE = "https://apis.elai.io/api/v1"
 
+AVATAR_PRESETS = {
+    "vadim": {"code": "vadim.casual", "gender": "male", "voice": "en-GB-RyanNeural"},
+    "gia": {"code": "gia.casual", "gender": "female", "voice": "en-US-AriaNeural"},
+    "zara": {"code": "zara.regular", "gender": "female", "voice": "en-US-JennyNeural"},
+    "mason": {"code": "mason.casual", "gender": "male", "voice": "en-US-GuyNeural"},
+    "default": {"code": "gia.casual", "gender": "female", "voice": "en-US-AriaNeural"},
+}
+
 
 class ElaiService:
     """Generate avatar videos for listening exercises and instructional content."""
@@ -33,6 +41,7 @@ class ElaiService:
         return {
             "Authorization": f"Bearer {self._get_token()}",
             "Content-Type": "application/json",
+            "Accept": "application/json",
         }
 
     def _log(self, action, latency, status="success", error=None):
@@ -47,6 +56,14 @@ class ElaiService:
         except Exception:
             pass
 
+    def _resolve_avatar(self, avatar_id):
+        if not avatar_id or avatar_id == "default":
+            return AVATAR_PRESETS["default"]
+        key = avatar_id.split(".")[0].lower() if "." in avatar_id else avatar_id.lower()
+        if key in AVATAR_PRESETS:
+            return AVATAR_PRESETS[key]
+        return {"code": avatar_id, "gender": "female", "voice": "en-US-AriaNeural"}
+
     def list_avatars(self):
         """List available ELAI avatars."""
         if not _requests:
@@ -55,23 +72,84 @@ class ElaiService:
         resp.raise_for_status()
         return resp.json()
 
+    @staticmethod
+    def _split_script(script, max_chars=500):
+        """Split a long script into chunks that stay under ELAI's 60s/slide limit.
+
+        Uses ~10 chars/second heuristic, so 500 chars ~ 50s (with safety margin).
+        Splits on sentence boundaries ('. ', '? ', '! ', newlines).
+        """
+        if len(script) <= max_chars:
+            return [script]
+        import re
+        sentences = re.split(r'(?<=[.!?])\s+|\n+', script)
+        chunks, current = [], ""
+        for sent in sentences:
+            if not sent.strip():
+                continue
+            if current and len(current) + len(sent) + 1 > max_chars:
+                chunks.append(current.strip())
+                current = sent
+            else:
+                current = f"{current} {sent}" if current else sent
+        if current.strip():
+            chunks.append(current.strip())
+        return chunks or [script]
+
     def create_video(self, script, *, avatar_id=None, title="EnCoach Video", language="en"):
         """Create an avatar video from a script.
 
+        Automatically splits long scripts into multiple slides to stay under
+        ELAI's 60-second-per-slide limit.
+
         Returns:
             dict with 'video_id', 'status'
         """
         if not _requests:
             raise RuntimeError("requests package not installed")
+
+        avatar_preset = self._resolve_avatar(avatar_id)
+        avatar_code = avatar_preset["code"]
+        avatar_src = f"https://elai-avatars.s3.us-east-2.amazonaws.com/common/{avatar_code.replace('.', '/')}/{avatar_code.replace('.', '_')}.png"
+
+        chunks = self._split_script(script)
+        slides = []
+        for idx, chunk in enumerate(chunks, 1):
+            slides.append({
+                "id": idx,
+                "speech": chunk,
+                "language": "English",
+                "voice": avatar_preset["voice"],
+                "voiceType": "text",
+                "voiceProvider": "azure",
+                "avatar": {
+                    "code": avatar_code,
+                    "gender": avatar_preset["gender"],
+                },
+                "canvas": {
+                    "version": "4.4.0",
+                    "background": "#ffffff",
+                    "objects": [
+                        {
+                            "type": "avatar",
+                            "left": 151.5,
+                            "top": 36,
+                            "fill": "#4868FF",
+                            "scaleX": 0.3,
+                            "scaleY": 0.3,
+                            "height": 1080,
+                            "width": 1080,
+                            "src": avatar_src,
+                        }
+                    ],
+                },
+            })
+        _logger.info("ELAI: creating video with %d slide(s) from %d chars", len(slides), len(script))
+
         payload = {
             "name": title,
-            "slides": [
-                {
-                    "speech": script,
-                    "avatar": avatar_id or "default",
-                    "language": language,
-                }
-            ],
+            "slides": slides,
+            "tags": ["encoach"],
         }
         t0 = time.time()
         try:
@@ -83,8 +161,31 @@ class ElaiService:
             )
             resp.raise_for_status()
             data = resp.json()
+            video_id = data.get("_id", data.get("id"))
+
+            # Step 2: trigger rendering -- ELAI requires a separate render call
+            try:
+                render_resp = _requests.post(
+                    f"{ELAI_BASE}/videos/render/{video_id}",
+                    headers=self._headers(),
+                    timeout=30,
+                )
+                render_resp.raise_for_status()
+                _logger.info("ELAI render triggered for video %s", video_id)
+            except Exception as render_err:
+                _logger.warning("ELAI render trigger failed for %s: %s (video created but not rendered)", video_id, render_err)
+
             self._log("create_video", int((time.time() - t0) * 1000))
-            return {"video_id": data.get("_id", data.get("id")), "status": data.get("status", "pending")}
+            return {"video_id": video_id, "status": "rendering"}
+        except _requests.exceptions.HTTPError as exc:
+            body = ""
+            try:
+                body = exc.response.text[:500]
+            except Exception:
+                pass
+            _logger.error("ELAI create_video failed: %s — %s", exc, body)
+            self._log("create_video", int((time.time() - t0) * 1000), "error", f"{exc} | {body}")
+            raise RuntimeError(f"ELAI API error: {exc.response.status_code} — {body}") from exc
         except Exception as exc:
             self._log("create_video", int((time.time() - t0) * 1000), "error", str(exc))
             raise
@@ -100,9 +201,11 @@ class ElaiService:
         )
         resp.raise_for_status()
         data = resp.json()
+        video_url = data.get("url", "") or data.get("video_url", "")
         return {
             "video_id": video_id,
             "status": data.get("status", "unknown"),
-            "url": data.get("url", ""),
+            "url": video_url,
+            "video_url": video_url,
             "duration": data.get("duration"),
         }