Yamen Ahmad
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882179870c
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feat(ai): LangGraph as core runtime + AI Agents/Tools console + full-demo seed
Core AI runtime
- New encoach.ai.agent + encoach.ai.tool models with M2M tool binding,
graph topology (simple|plan_review_revise|rag|react), model + fallback,
temperature, max_tokens, response_format, max_revisions, quality checks
and system prompt fields.
- services/agent_runtime.py compiles a langgraph.StateGraph per agent
and caches the build per (key, write_date). Emits a structured trace
(output, tool_calls, retrieval_hits, revisions, quality_issues,
ms, model_used, fallback_used) and auto-falls-back on rate-limit/5xx.
- services/agent_tools.py registers 11 tool handlers wrapping existing
services: resources.search, rubric.fetch, outcomes.fetch,
student.profile, quality.cefr_check, quality.ai_detect,
quality.content_gate, course_plan.save (mutates),
course_plan.save_materials (mutates), scoring.grade_writing,
scoring.grade_speaking.
- 7 default agents seeded via data/agents_defaults.xml: course_planner,
course_week_materials, exam_generator, exercise_generator, lms_tutor,
writing_grader, speaking_grader.
- Feature flag encoach_ai.use_langgraph_runtime (default True).
- encoach_ai_course pipeline now routes through AgentRuntime when on,
legacy SDK path kept as fallback.
Admin UI
- /admin/ai/prompts is now a tabbed Agents | Tools | Prompts console.
- AIAgentsPanel: card grid + config dialog (model/temp/graph/tools/
system prompt) + built-in Test Runner showing live trace.
- AIToolsPanel: registry table with category badges, mutates flag,
schema viewer, edit dialog.
- New /api/ai/agents* and /api/ai/tools* controller (list/get/update/
test, list-tools, toggle-tool).
- Sidebar label nav.aiPrompts -> nav.aiAgents (AI Agents and Tools).
- EN + AR (RTL) translations for ~80 new keys.
Smart Wizard pages
- /admin/quick-setup hub + CourseWizard, CoursePlanWizard,
RubricWizard, ExamStructureWizard step-by-step flows.
- /admin/course-plans list + detail pages.
- /teacher/quick-setup mirror.
Full demo seed + 8-role E2E
- seed_full_demo.py adds the 5 missing user_types (approver, corporate,
mastercorporate, agent, developer), activates a 2-stage exam-approval
workflow with one pending request, creates a GE1-aligned 12-week B1
course plan with 6 detailed Week-1 materials (reading 400w, writing,
listening 4-min script, speaking, grammar present simple vs continuous,
vocabulary), and inserts sample ai.log + ai.feedback rows.
- reset_demo_passwords.py forces every demo login back to canonical
passwords (admin123/teacher123/student123/approver123/corporate123/
master123/agent123/dev123).
- e2e_full_scenario.py: 46/46 PASS read-only API smoke across all
8 roles, including a live LangGraph round-trip on writing_grader.
- e2e_approval_chain.py: 6/6 PASS mutation E2E - approver approves
stage 1, admin approves stage 2, linked encoach.exam.custom flips
to status=published, verified via psql.
Docs
- docs/PROJECT_SUMMARY.md updated to 2026-04-25: new Latest events
bullets, refreshed credentials table, full sections 22 (LangGraph
runtime) and 23 (full demo seed + 8-role E2E).
- docs/ENCOACH_FULL_DEMO_QA_REPORT.md added with credentials,
per-endpoint PASS/FAIL, mutation chain proof, LangGraph live output.
- backend/GE1 Course Outline_ Fall AY25-26.pdf vendored as the
reference outline the GE1 plan/materials are aligned to.
Dependencies
- requirements.txt: langgraph>=0.2.0, langchain-core>=0.3.0.
- encoach_ai/__manifest__.py: external_dependencies updated.
Made-with: Cursor
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2026-04-25 03:14:22 +04:00 |
|
Yamen Ahmad
|
3972023a30
|
feat(backend): Phase 2/3 hardening release
Roadmap P0 — platform safety & ops
- Merge duplicate encoach.student.attempt/answer models into encoach_scoring
and drop the stale encoach_exam_template copies.
- Remove duplicate /api/exam/* routes; canonicalize on one controller tree.
- Gate raw-SQL seeds in seed_demo_data.py behind an explicit env flag.
- Add /api/health and /api/health/ready (DB + LLM reachability) endpoints.
- Fix docker-compose + ship odoo-docker.conf for container-local runs.
- Enforce OpenAI request_timeout=30s and @jwt_required on all AI/coach routes.
- Promote canonical cefr_mapper to encoach_ai.services.cefr_mapper.
- JWT cache TTL=30s + invalidation hook on user mutation.
Roadmap P1 — exam correctness & data provenance
- Wire QualityChecker + IeltsValidator into exam submit with a
pending_review gate (encoach_ai.services.question_validator).
- Populate RAG metadata (course_id, subject_id, entity_id, taxonomy) on
encoach_vector embeddings and add a chunking pipeline (>2000 chars).
- Add provenance fields on encoach.question (model, prompt_hash, log_id)
and validate LLM output with schema before DB insert.
- Unify response envelope to {items,total,page,size}.
- Approval reject rollback with savepoint atomicity.
- Ticket notifications on status/assignee change.
Roadmap P2 — performance & observability
- Reports: replace Python loops with SQL read_group aggregations.
- X-Request-ID middleware + structured JSON logs.
- In-process/Prometheus counters and openapi.py controller exporting a
spec by scanning @http.route decorators.
- Paymob real checkout + HMAC-SHA512 webhook verification, backed by a
new encoach.paymob.order model and ir.config_parameter credentials.
- JWT refresh tokens + revocation table.
- Composite DB indexes on hot report/ticket/attempt paths.
Roadmap P3 — human-in-the-loop & compliance
- Human-in-the-loop exam review workflow (pending_review → publish) with
new review controller and status transitions.
- encoach.ai.prompt model + versioning + admin editor endpoints (one
active version per key, render-preview dry run).
- Student feedback loop → encoach.ai.feedback (upsert per user/subject,
admin triage + resolve endpoints).
- GDPR export (/api/gdpr/export) and right-to-erasure (/api/gdpr/delete)
with anonymization, tombstone record, and admin-self-erasure guard.
- HttpCase smoke tests for /api/health and /api/health/ready.
Made-with: Cursor
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2026-04-19 14:16:09 +04:00 |
|
Yamen Ahmad
|
6a62a43d61
|
feat: Generation Page AI workflows + AI/Vector modules + exam session fixes
Generation Page (complete rebuild):
- Full production-parity exam generation wizard with 4 IELTS modules
- Reading: AI passage gen, 5 exercise types (MCQ, Fill, Write, T/F, Match)
- Listening: 4 section types, AI context gen, TTS audio gen (ElevenLabs)
- Writing: Task 1/2, AI instruction gen, word limits, marks
- Speaking: 3 parts, AI script gen, avatar video gen (7 avatars)
- Per-module config: timer, CEFR difficulty, access, approval, rubrics
- Exam submission workflow (draft/published)
Exam Structures:
- New encoach.exam.structure model + CRUD controller
- ExamStructuresPage wired to real API
AI Module (encoach_ai):
- OpenAI service, ElevenLabs TTS, AWS Polly, ELAI avatars
- AI settings model with Odoo config parameters
- 7 generation endpoints (passage, exercises, instructions, scripts, context)
Vector Module (encoach_vector):
- pgvector integration for RAG-based content search
- Embedding service with sentence-transformers
Exam Session Fixes:
- Fixed ExamSession.tsx field mapping (question_type→type, exam_title→title)
- Fixed submit payload to include attempt_id and answers
- Fixed normalizeType to handle null/undefined
Tested: 12/12 API tests passed, browser-verified with real OpenAI calls
Made-with: Cursor
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2026-04-11 14:27:03 +04:00 |
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