# Agent V3 - Index

Serviciul principal al platformei DIDI. Analizeaza continut (text, URL, imagine, audio, video) pentru detectarea dezinformarii. Produce scoruri 0-100 pe 4 componente si un verdict agregat.

**Port**: 24803
**Framework**: Express 5 + TypeScript
**Container**: didi-agent-v3

---

## Infrastructura data-layer

Data layer rulează **local pe mașina de deployment**, ca containere Docker pe `didi-network`. Nu există cluster extern — serviciile se adresează prin **numele de container Docker**, nu prin IP de mașină. Config real din env-ul `didi-agent-v3`:

| Serviciu | Container (target) | Config | Credentials |
|---|---|---|---|
| **PostgreSQL 17** | `didi-postgres:5432` | DB `DIDI`, schema `bos_analysis` | user `bos_interface` / `interface` |
| **Redis 7** | `didi-cache:6379` | DB 0 | parolă `redis123` |
| **RabbitMQ 3.12** | `staging-dataLayer-rabbitmq:5672` | vhost `/` | user `admin` / `rabbitmq123` |

**Clienți ioredis centralizați** via `src/shared/redis/connection.ts` — `createRedisConnection(label)`. Zero `new Redis({...})` inline. Auto-reconnect + reconnectOnError.

**RabbitMQ client** via `src/queue/connection.ts` + `src/shared/queue/constants.ts`. Vhost `/` (`encodeURIComponent()` la construirea URI-ului AMQP).

**Bootstrap auto-populate**: la startup, didi-framework detectează dacă `didi:framework:manifest` lipsește în Redis și auto-rulează `POST /api/sync-redis`. Zero intervenție manuală pe fresh deploy.

---

## Integrare cu platforma AI (Lot 1)

Backend-ul (Lot 2) **apelează** serviciile platformei AI (Lot 1) prin HTTP — nu implementează niciunul intern. Fiecare are un URL **configurabil din env**, cu **fail-open**: orice eroare (timeout, 5xx, network, feature flag off) → analiza continuă fără serviciul respectiv (fallback la calea locală sau skip). Cum funcționează intern brain/RAG, atom cache, extractorii, forensic, buster etc. e documentat în platforma AI (Lot 1); aici descriem doar contractul de integrare.

| Serviciu Lot 1 | Env (default) | Folosit pentru | Fail-open |
|---|---|---|---|
| didi_brain | `DIDI_BRAIN_URL` (`http://10.11.10.12:8090`) | Verification cache + analysis atom cache pentru claims/techniques/ai-tampered | → LLM direct |
| extractors | `EXTRACTORS_URL` (`http://<HOST_IP>:54400`) | Extragere conținut/metadata | → skip |
| video analysis (buster) | `VIDEO_ANALYSIS_URL` (`http://<HOST_IP>:54600`) | Analiză video | → procesare locală |
| forensic | `FORENSIC_API_URL` (`http://forensic-features-api:8080`) | Forensic features imagine | → skip |
| whisper (audio) | `M17_WHISPER_URL` (`http://10.11.10.17:54300`) | Transcriere audio | → Groq → OpenAI |
| web search | `M17_WEB_API_URL` (`http://10.11.10.13:51100`) | Căutare web claims/source | fallback când brain MISS |
| LLM router | `LLM_ROUTER_URL` (`http://10.11.10.17:14011`) | Inferență LLM primară (Qwen local) | → OpenRouter |
| vision | `VISION_LLM_URL` (`http://10.11.10.17:14011`) | OCR + AI detection imagine | → Gemini / GPT-4o |
| domain check | `DOMAIN_CHECK_API_URL` (`http://<domain-check-host>:11000`) | WHOIS/DNS/SSL/blacklist domeniu | → skip |

IP-urile GPU `10.11.10.17:14011` (LLM/vision) și `10.11.10.17:54300` (whisper) sunt **default**, configurabile din env.

**Client brain (cod backend, `src/shared/brain/client.ts`)**: `gatherFromBrain()` (verification cache lookup + evidence pentru claims), `writeVerificationCacheAsync()`, `lookupAnalysisAtom()` / `writeAnalysisAtomAsync()` / `patchAnalysisAtomGold()` (analysis atom cache pentru techniques/ai-tampered), plus helpers de hashing. Detaliul acestei integrări backend e la secțiunea „Funcționalități suplimentare".

---

## Tier-aware execution (premium vs free)

Agent-v3 ruleaza chain-uri diferite de modele LLM in functie de **planul de abonament** al utilizatorului.

### Cum se determina tier-ul

1. Fiecare request face `checkCredits()` la didiFramework, care returneaza `planType` (1-6) in raspuns
2. `getSearchTier(planType)` din `src/shared/credits.ts` mapeaza:
   - `plan_type` 1-3 → tier `'free'`
   - `plan_type` 4-6 → tier `'premium'`
3. `tier` (variabila `searchTier` in cod) e propagat prin toate straturile:
   - **Sync routes**: `pipeline-routes.ts`, `ai-tampered-routes.ts` → `PipelineInput.searchTier`
   - **Async via queue**: `component-worker.ts` deriva din `taskMessage.planType`
   - `ComponentRunner.runAll()` → `AnalysisInput.searchTier`
   - Fiecare executor primeste `tier` ca parametru la `execute()`
   - `verdict-explanation.ts`: primeste `tier` la `generate()`
   - `vision.ts` / `callVision()`: primeste `tier`
   - `transcription.ts` / `transcribe()`: primeste `tier` in options
   - M17 search (claims/source-assessment): trimite `X-Search-Tier: premium` header

### Ce se schimba per tier

| Component/Stage | Free primary | Premium primary |
|-----------------|--------------|-----------------|
| Techniques screening | Qwen 3.5 397B local | Gemini 3 Flash Preview (OR) |
| Techniques deep | Qwen 3.5 397B local | Claude Sonnet 4.6 (OR) |
| AI-Tampered screening | Qwen 3.5 397B local | Gemini 3 Flash Preview (OR) |
| AI-Tampered deep | Qwen 3.5 397B local | Claude Sonnet 4.6 (OR) |
| Claims extraction | Qwen 3.5 397B local | Gemini 3 Flash Preview (OR) |
| Claims verification | Qwen 3.5 397B local | Claude Sonnet 4.6 (OR) |
| Source extraction | Qwen 3.5 397B local | Gemini 3 Flash Preview (OR) |
| Source evaluation | Qwen 3.5 397B local | Claude Sonnet 4.6 (OR) |
| Verdict reviewer | Qwen 3.5 397B local | Gemini 3 Flash Preview (OR) |
| Vision (OCR + AI detect) | Qwen Vision local | Gemini 3 Flash Preview (OR) |
| Transcription (audio) | M17-Whisper local | Groq-Whisper |
| Web search (claims/source) | M17 SearXNG | M17 + Brave + Tavily (via X-Search-Tier header) |

Fallback chain pentru premium termina pe Qwen local (safety net, 0 cost) — zero erori de rutare daca cloud crapa.

### Cum se incarca stage assignments tier-based

Executoarele citesc cheia Redis `didi:config:{component}:v1:stage_assignments` cu structura **tier-nested**:
```json
{
  "techniques_screening": {
    "free":    { "models": [{ order:1, model_key: "qwen35:Qwen3.5-397B-A17B", ...}, ...] },
    "premium": { "models": [{ order:1, model_key: "openrouter:google/gemini-3-flash-preview", ...}, ...] }
  },
  "techniques_deep": { "free": {...}, "premium": {...} }
}
```

Helper `resolveStageAssignment(assignments, stageCode, tier)` returneaza chain-ul corect, cu **fallback automat la 'free'** daca 'premium' lipseste. Asta protejeaza utilizatorii premium daca configul nu e complet.

---

## Componente de analiza

Serviciul ruleaza 4 componente independente + un calculator de verdict:

| Componenta     | Ce face                                                | Scor produs       |
|----------------|--------------------------------------------------------|--------------------|
| Techniques     | Detecteaza tehnici de manipulare (propaganda, apel emotional, etc.) | manipulation_score 0-100 |
| AI-Tampered    | Detecteaza continut generat/modificat de AI            | ai_probability 0-100 |
| Claims         | Extrage afirmatii si le verifica prin cautare web      | credibility_score 0-100 |
| Domain         | Analizeaza domeniul sursa (varsta, SSL, blacklist, reputatie) | trust_score 0-100 |
| Verdict        | Agrega scorurile componentelor intr-un scor final de risc | risk_score 0-100 |

Fiecare componenta (in afara de Domain) foloseste un pipeline in 2 etape:
- **Screening**: analiza rapida cu un model LLM rapid
- **Deep Analysis**: analiza detaliata pe fiecare dimensiune/categorie detectata

Fiecare etapa are 3 nivele de fallback (primary -> fallback_1 -> fallback_2 -> fallback_3).

---

## Structura fisierelor

```
src/
  index.ts                              -- Server Express, middleware, montare rute
  api/                                  -- Rute organizate pe subdirectoare (fiecare *-routes.ts la root e shim de re-export)
    routes.ts / techniques.ts           -- Endpoint-uri Techniques (+ /health general)
    ai-tampered/                        -- Endpoint-uri AI-Tampered
    claims/                             -- Endpoint-uri Claims (analyze, config, results)
    source-assessment/                  -- Endpoint-uri Source Assessment (config, models, stage-assignments, analyze)
    domain.ts                           -- Endpoint-uri Domain (legacy)
    media.ts                            -- Endpoint-uri Media/Fisiere (upload/download MinIO)
    pipeline/                           -- Pipeline complet + Istoric + Extensie + dry-run.ts + cancel.ts (cancel/resume) + async.ts
    moderation/                         -- HIL Moderation (queue.ts, flag-stats.ts, _gold-promotion.ts, _middleware.ts)
  components/
    component-runner.ts                 -- Orchestrator direct (invocare executori fara HTTP intern)
    techniques/
      executor.ts                       -- Executor Techniques: screening -> deep analysis -> scoring (params din Redis)
    ai-tampered/
      executor.ts                       -- Executor AI-Tampered: disclosure check -> screening -> deep -> scoring (params din Redis)
    claims/
      executor.ts                       -- Executor Claims: extractie afirmatii -> verificare web -> scoring (params din Redis)
    source-assessment/
      executor.ts                       -- Executor Source Assessment: extractie sursa -> M17 search -> evaluare (params din Redis)
    moderation/
      triage.ts                         -- Decide daca o sesiune intra in coada review (config Redis, feature-flag `triage_enabled`)
      queue-manager.ts                  -- Operatii PG pe `bos_analysis.moderation_queue` (enqueue/list/get/claim/resolve/stats)
    pipeline/
      executor.ts                       -- Orchestrator pipeline: ruleaza toate componentele + verdict
      verdict-calculator.ts             -- Calcul verdict cu input profiles per tip input (params din Redis)
      verdict-explanation.ts            -- Generare explicatie bilingva (RO+EN) via LLM
      virality-calculator.ts            -- Calcul scor viralitate (factori: emotie, urgenta, reach)
      types.ts                          -- Tipuri interne pipeline
  shared/
    media/
      transcription.ts                  -- Transcriere audio: M17-Whisper -> Groq -> OpenAI (fallback chain)
      vision.ts                         -- Analiza imagine: Qwen Local -> Gemini Flash -> GPT-4o (fallback chain)
      video-processor.ts               -- Pipeline video: download -> extrage cadre -> transcriere + viziune
      media-service.ts                  -- Interfata unificata media (download, format, cleanup)
    persistence/
      persist-service.ts                -- Coordonare Redis (cache) + PostgreSQL (permanent)
      pg-adapter.ts                     -- Adaptor PostgreSQL: save/load/history/delete pe schema bos_analysis
      pg-pool.ts                        -- Pool conexiuni PostgreSQL (singleton)
    redis/
      connection.ts                     -- Factory centralizat ioredis (ACL ready, retry, reconnectOnError)
      keys.ts                           -- Registru central chei Redis
      session-store.ts                  -- Stocare sesiuni in Redis ca JSON (TTL 7 zile)
    brain/
      client.ts                         -- Client didi-brain: gather cu verification lookup + write cache + analysis atom lookup/write/patch (gold/silver/bronze tiers, fire-and-forget writes)
    queue/
      constants.ts                      -- Topologie cozi: exchange, routing keys, prioritati
    types/
      component-results.ts              -- Definitii tipuri pentru toate cele 5 rezultate componente
      analysis-session.ts               -- Tipul AnalysisSession (wrapper root al unei analize)
      api-responses.ts                  -- Tipuri raspunsuri API (success/error envelope)
    test-utils/
      fixtures.ts                       -- Date de test (sesiuni, rezultate componente)
      mock-pg.ts                        -- Mock PostgreSQL pool pentru teste
      mock-redis.ts                     -- Mock Redis pentru teste
    helpers/
      empty-media-response.ts           -- Raspuns standardizat cand media nu are continut text
    auth/
      jwt-verify.ts                     -- Verificare criptografica JWT RS256 via Keycloak JWKS (Modul 7)
      guards.ts                         -- Route guards (resolveUserId, authRequired, requireRole, ROLES_ADMIN)
    observability/
      metrics.ts                        -- Metrici Prometheus business + OTel tracing + /metrics server workeri (Modul 8)
      queue-depth-poller.ts             -- Poller RabbitMQ Management API → gauge didi_queue_depth / didi_active_workers
    credits.ts                          -- Verificare si deducere credite utilizator (via didiFramework)
  config/
    analysisLimits.ts                   -- Limite text: min 20, max 50000 caractere + validare UTF-8
  queue/
    dispatcher.ts                       -- Dispatch mesaje catre RabbitMQ (async)
    connection.ts                       -- Manager conexiune RabbitMQ
    aggregator.ts                       -- Agregator verdict (consuma rezultate componente)
    types.ts                            -- Tipuri mesaje coada (dispatch, result, etc.)
    workers/
      component-worker.ts              -- Worker generic (consuma din coada, ruleaza componenta)
      techniques-worker.ts             -- Worker Techniques (config)
      ai-tampered-worker.ts            -- Worker AI-Tampered (config)
      claims-worker.ts                 -- Worker Claims (config)
  worker-entrypoints/
    techniques.ts                       -- Entry point Docker: worker techniques (2 replici)
    ai-tampered.ts                      -- Entry point Docker: worker ai-tampered (2 replici)
    claims.ts                           -- Entry point Docker: worker claims (3 replici)
    domain.ts                           -- Entry point Docker: worker domain (2 replici)
    aggregator.ts                       -- Entry point Docker: verdict aggregator (2 replici)
  scripts/
    export-schemas.ts                   -- Export scheme Zod ca JSON Schema
    init-priority-queues.ts             -- Initializare cozi RabbitMQ cu prioritati
```

**Nota**: `queue/constants.ts` (topologie cozi: exchange, routing keys, prioritati) se afla la `shared/queue/constants.ts`.

---

## API - Toate endpoint-urile

### General (`/api/v3`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /health | Health check (raspunde cu service name, version, timestamp) | api/routes.ts |

**Nota**: `/health` este montat pe routerul `/api/v3`, deci path-ul complet este `/api/v3/health`.

### Techniques (`/api/v3/techniques`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /definitions | Ierarhie completa tehnici din Redis (dimensiuni -> subdimensiuni -> tehnici) | api/routes.ts |
| GET | /config | Configurare completa din Redis | api/routes.ts |
| GET | /models | Lista modele LLM disponibile | api/routes.ts |
| GET | /stage-assignments | Configurare etape (screening/deep) | api/routes.ts |
| PUT | /stage-assignments | Actualizeaza configurare etape | api/routes.ts |
| POST | /test-model | Testeaza conexiunea la un model LLM | api/routes.ts |
| POST | /test-openrouter | Testeaza OpenRouter cu provider routing | api/routes.ts |
| POST | /analyze | Analiza text sincrona | api/routes.ts -> components/techniques/executor.ts |
| POST | /analyze-media | Analiza media sincrona (imagine/audio/video) | api/routes.ts -> shared/media/* -> components/techniques/executor.ts |
| POST | /analyze-async | Analiza asincrona via RabbitMQ | api/routes.ts -> queue/dispatcher.ts |
| GET | /results/:sessionId | Rezultate intermediare din Redis | api/routes.ts |

### AI-Tampered (`/api/v3/ai-tampered`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /health | Health check | api/ai-tampered-routes.ts |
| GET | /config | Configurare completa din Redis | api/ai-tampered-routes.ts |
| GET | /models | Lista modele LLM | api/ai-tampered-routes.ts |
| GET | /categories | Categorii + ierarhie indicatori AI | api/ai-tampered-routes.ts |
| GET | /stage-assignments | Configurare etape | api/ai-tampered-routes.ts |
| PUT | /stage-assignments | Actualizeaza configurare etape | api/ai-tampered-routes.ts |
| POST | /quick | Analiza rapida fara LLM (doar euristici) | api/ai-tampered-routes.ts -> components/ai-tampered/executor.ts |
| POST | /analyze | Analiza text completa cu LLM | api/ai-tampered-routes.ts -> components/ai-tampered/executor.ts |
| POST | /analyze-image | Analiza imagine pentru AI (doar viziune) | api/ai-tampered-routes.ts -> shared/media/vision.ts |
| POST | /analyze-media | Analiza media sincrona | api/ai-tampered-routes.ts -> shared/media/* -> components/ai-tampered/executor.ts |
| POST | /analyze-async | Analiza asincrona via RabbitMQ | api/ai-tampered-routes.ts -> queue/dispatcher.ts |
| GET | /results/:sessionId | Rezultate intermediare din Redis | api/ai-tampered-routes.ts |
| POST | /test-model | Testeaza model LLM | api/ai-tampered-routes.ts |

### Claims (`/api/v3/claims`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /health | Health check | api/claims-routes.ts |
| GET | /config | Configurare + tipuri/statusuri din framework | api/claims-routes.ts |
| GET | /types | Tipuri de afirmatii (VF, EF, RE, etc.) | api/claims-routes.ts |
| GET | /statuses | Statusuri verificare (VT, LT, UV, etc.) | api/claims-routes.ts |
| GET | /models | Lista modele LLM | api/claims-routes.ts |
| GET | /stage-assignments | Configurare etape | api/claims-routes.ts |
| PUT | /stage-assignments | Actualizeaza configurare etape | api/claims-routes.ts |
| POST | /analyze | Analiza text: extractie + verificare afirmatii | api/claims-routes.ts -> components/claims/executor.ts |
| POST | /analyze-media | Analiza media sincrona | api/claims-routes.ts -> shared/media/* -> components/claims/executor.ts |
| POST | /analyze-async | Analiza asincrona via RabbitMQ | api/claims-routes.ts -> queue/dispatcher.ts |
| GET | /results/:sessionId | Rezultate intermediare din Redis | api/claims-routes.ts |
| POST | /test-model | Testeaza model LLM | api/claims-routes.ts |

### Pipeline complet (`/api/v3/pipeline`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| POST | /analyze | Analiza completa sincrona (toate componentele) | api/pipeline-routes.ts -> components/pipeline/executor.ts |
| POST | /analyze-url | Analiza URL inteligenta (detecteaza YouTube, imagine, articol) | api/pipeline-routes.ts -> shared/media/video-processor.ts |
| POST | /analyze-media | Analiza media sincrona (shortcut) | api/pipeline-routes.ts -> components/pipeline/executor.ts |
| POST | /analyze-async | Analiza completa asincrona via RabbitMQ | api/pipeline-routes.ts -> queue/dispatcher.ts |
| GET | /:sessionId/status | Status sesiune (polling) | api/pipeline-routes.ts -> shared/redis/session-store.ts |
| GET | /:sessionId/component/:name | Rezultat o singura componenta | api/pipeline-routes.ts -> shared/redis/session-store.ts |
| GET | /:sessionId/result | Rezultat complet sesiune | api/pipeline-routes.ts -> shared/persistence/persist-service.ts |
| GET | /:sessionId/queue-status | Status coada async (progres %) | api/pipeline-routes.ts -> queue/dispatcher.ts |
| GET | /queue-health | Sanatate RabbitMQ | api/pipeline-routes.ts -> queue/connection.ts |
| GET | /verdict-config | Configurare verdict (categorii, ponderi, override-uri din Redis) | api/pipeline-routes.ts |
| POST | /dry-run | Rezolvă planul complet de execuție fără dispatch (ce componente rulează/skip + de ce, chain-uri model/tier, profil verdict). Read-only: fără session id, fără credite, fără mesaje. Modul 1. | api/pipeline/dry-run.ts |
| POST | /:sessionId/cancel | Anulează o sesiune în execuție (flag Redis; workerii short-circuit, aggregator finalizează `canceled`). Idempotent, owner/admin. | api/pipeline/cancel.ts |
| POST | /:sessionId/resume | Resume din checkpoint — re-dispatch DOAR componentele necompletate (`dispatcher.resumeDispatch`). Owner/admin. | api/pipeline/cancel.ts |

### Istoric (`/api/v3/pipeline`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /history | Istoric utilizator paginat | api/pipeline-routes.ts -> shared/persistence/pg-adapter.ts |
| GET | /history/:id | O intrare din istoric | api/pipeline-routes.ts -> shared/persistence/persist-service.ts |
| DELETE | /history/:id | Sterge intrare din istoric | api/pipeline-routes.ts -> shared/persistence/persist-service.ts |
| GET | /history/admin | Istoric admin (toti utilizatorii, filtre) | api/pipeline-routes.ts -> shared/persistence/pg-adapter.ts |
| GET | /history/admin/:id | O intrare admin | api/pipeline-routes.ts -> shared/persistence/persist-service.ts |
| DELETE | /history/admin/:id | Sterge intrare admin | api/pipeline-routes.ts -> shared/persistence/persist-service.ts |

### Extensie browser (`/api/v3/pipeline/extension`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| POST | /analyze | Analiza via API key (nu JWT) | api/pipeline-routes.ts -> components/pipeline/executor.ts |
| POST | /keys | Creeaza API key pentru extensie | api/pipeline-routes.ts (proxy -> didiFramework) |
| GET | /keys | Lista API keys | api/pipeline-routes.ts (proxy -> didiFramework) |
| DELETE | /keys/:id | Sterge API key | api/pipeline-routes.ts (proxy -> didiFramework) |

### Media/Fisiere (`/api/v3/media`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| POST | /upload-url | Obtine URL presemnat pentru upload in MinIO | api/routes.ts |
| POST | /upload | Upload direct fisier (multipart, max 50MB) | api/routes.ts |
| POST | /download-url | Obtine URL presemnat pentru download din MinIO | api/routes.ts |
| GET | /file/:bucket/{*objectKey} | Proxy servire fisiere din MinIO (suporta range requests, Express 5 wildcard) | api/routes.ts |

### Source Assessment (`/api/v3/source-assessment`)

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| GET | /health | Health check | api/source-assessment-routes.ts |
| GET | /config | Configurare (scoring_config + framework sources) | api/source-assessment-routes.ts |
| GET | /models | Modele LLM disponibile | api/source-assessment-routes.ts |
| GET | /stage-assignments | Configurare etape | api/source-assessment-routes.ts |
| PUT | /stage-assignments | Actualizeaza etape | api/source-assessment-routes.ts |
| POST | /test-model | Test conectivitate model | api/source-assessment-routes.ts |
| POST | /analyze | Analiza sursa (text + optional URL) | api/source-assessment-routes.ts -> components/source-assessment/executor.ts |
| POST | /analyze-media | Analiza sursa din media | api/source-assessment-routes.ts |

### Domain (`/api/v3/domain`) — LEGACY, inlocuit de Source Assessment

| Metoda | Path | Ce face | Logica in fisier |
|--------|------|---------|------------------|
| POST | /analyze | Analiza domeniu sincrona (apeleaza Domain Check API extern) | api/routes.ts |
| POST | /analyze-async | Analiza domeniu asincrona | api/routes.ts -> queue/dispatcher.ts |

### HIL Moderation (`/api/v3/moderation`)

| Metoda | Path | Roluri permise | Ce face | Logica in fisier |
|--------|------|----------------|---------|------------------|
| GET | /queue | admin, moderator, senior_moderator | Listeaza coada review (filtre: `status` CSV, `priority` CSV, `assigned_to=me\|user`) | api/moderation-routes.ts -> components/moderation/queue-manager.ts |
| GET | /queue/:queueId | admin, moderator, senior_moderator | Intrare coada + sesiunea analiza JOIN-ed | api/moderation-routes.ts -> components/moderation/queue-manager.ts |
| POST | /queue/:queueId/claim | moderator, senior_moderator | Claim atomic (UPDATE conditionat pe pending) — assigneaza la user-ul JWT | api/moderation-routes.ts -> components/moderation/queue-manager.ts |
| PUT | /queue/:queueId/resolve | moderator, senior_moderator | Resolve cu actiune `approved` \| `corrected` \| `rejected` + corrections JSONB diff | api/moderation-routes.ts -> components/moderation/queue-manager.ts -> shared/brain/client.ts (PATCH atom gold) |
| POST | /flag | orice user autenticat | Flag user (extensie browser) — enqueue review | api/moderation-routes.ts -> components/moderation/queue-manager.ts |
| GET | /stats | admin, moderator, senior_moderator | Counts pe tier/component + `hit_rate_24h` | api/moderation-routes.ts -> components/moderation/queue-manager.ts |

**Auth (Faza D done 2026-05-02)**: `requireRole()` și `requireAuth()` din `moderation-routes.ts` aplică role check **strict** când `STAGING_MODE=false` (production). În staging (`STAGING_MODE=true`, default actual): GET-urile de read trec fără JWT (legacy), `/flag` cere body `user_id` sau JWT. Vezi `IMPLEMENTATION_PLAN_HIL_BRAIN.md` Faza D pentru permission matrix completa.

Constants in `moderation-routes.ts`:
- `ROLES_READ = ['admin', 'moderator', 'senior_moderator']` — citire queue/stats
- `ROLES_WRITE = ['moderator', 'senior_moderator']` — claim/resolve (admin nu modifică queue, doar vede)
- `STAGING = process.env.STAGING_MODE === 'true'` — controller pentru soft auth fallback

---

## Autentificare JWT (Modul 7)

Fișier: `src/shared/auth/jwt-verify.ts` (+ guards în `src/shared/auth/guards.ts`).

Verificare **criptografică** a token-urilor JWT — nu doar la gateway, ci și în backend, deci un acces direct pe `:24803` (bypass Kong) sau prin nginx-ul admin-dashboard este la fel de protejat.

- **RS256 via Keycloak JWKS**: fiecare Bearer JWT e verificat împotriva JWKS-ului realm-ului emitent (`didi-clients` / `didi-admins`, allow-list `JWT_ALLOWED_REALMS`). JWKS descărcat remote și cache-uit per realm (`createRemoteJWKSet` din `jose`).
- **Respinge cu 401** (`error_code: JWT_INVALID`): token forjat (semnătură invalidă pe cheile noastre), expirat/`nbf` (validare `exp`/`nbf`), sau emis de un realm foreign (issuer în afara allow-list). Un token cu issuer `didi-*` spoofat tot pică pe semnătură.
- Fără header `Authorization` → request rămâne anonim (route guards decid). Bearer non-JWT (API key opac) trece netransformat.
- `jwtIdentityMiddleware()` populează `req.jwtUserId` / `req.jwtEmail` / `req.jwtRoles` din payload-ul **verificat** (`realm_access.roles`).
- Env: `KEYCLOAK_URL` (default `http://didi-keycloak:8080/auth`), `JWT_ALLOWED_REALMS`, `JWT_VERIFY_ENABLED` (`false` → decode-only, doar dev, cu warning zgomotos).

## Observabilitate (Modul 8)

Fișiere: `src/shared/observability/metrics.ts` + `src/shared/observability/queue-depth-poller.ts`.

**Metrici Prometheus** (client `prom-client`), inclusiv metrici business DiDi:
- `didi_analyses_completed_total` / `didi_analyses_failed_total` (labels: component, tier, media_type, verdict/reason)
- `didi_pipeline_duration_seconds` (histogram, per component+tier)
- `didi_llm_calls_total` + `didi_llm_tokens_total` (provider, model, component)
- `didi_brain_cache_hits_total` / `..._misses_total` (verification + atom)
- `didi_queue_depth` + `didi_active_workers` (gauge, per component+plan) — alimentate de `queue-depth-poller.ts` care interoghează RabbitMQ Management API la 30s (fail-open)
- `didi_dlq_messages_total`, `didi_http_requests_total`, `didi_http_request_duration_seconds` + default Node/process metrics

**Server `/metrics`**: expus de agent-v3 (Express) și de fiecare container worker via `startWorkerMetricsServer()` (workerii n-au app Express, deci server HTTP minimal dedicat pentru scrape).

**OpenTelemetry tracing**: `initObservability()` pornește OTel NodeSDK cu auto-instrumentations (Express, http, redis, amqplib, pg) când `OTEL_EXPORTER_OTLP_ENDPOINT` e setat (default `http://didi-otel-collector:4317`); altfel disabled.

## Spec OpenAPI

Fișier: `openapi.yaml` la root-ul serviciului (OpenAPI 3.0.3, Modulele 1-3). Descrie toate endpoint-urile (async 202 + poll, pipeline cu dependențe explicite, dry-run/cancel/resume, istoric, moderare HIL). Security: `bearerAuth` (JWT Keycloak RS256 verificat în backend, nu doar la gateway).

## Fluxul de date

### Analiza text (sincrona)

```
Request POST /api/v3/pipeline/analyze { text }
  |
  v
Validare text (20-50000 caractere) + Verificare credite
  |
  v
PipelineExecutor.execute()
  |
  v
ComponentRunner.runAll() -- ruleaza in paralel:
  |-- TechniquesV3Executor: screening -> deep analysis -> manipulation_score
  |-- AITamperedExecutor:   disclosure check -> screening -> deep -> ai_probability
  |-- ClaimsExecutor:       extractie afirmatii -> brain /v1/gather (cache check + evidence) -> fresh HIT skip LLM / miss: LLM verificare + fire-and-forget cache write -> credibility_score
  |-- analyzeDomain():      analiza locala (daca exista URL) -> trust_score
  |
  v
VerdictCalculator.calculate() -- functie pura, fara I/O
  |-- Selecteaza INPUT PROFILE per input_type (din Redis didi:config:pipeline:v1:input_profiles)
  |     Profiluri: text_no_url, text_with_url, image, audio, video, url
  |     Fiecare profil defineste: ponderi, override-uri active, reguli INCONCLUSIVE
  |-- Extrage scoruri componente (0-100)
  |-- Aplica ponderi din profil (ex: image: ai=50%, tech=20%, claims=15%, source=15%)
  |     Fallback la ponderi globale daca profilul nu exista
  |-- Aplica multiplicator topic INAINTE de override (nu amplifica bonusurile)
  |-- Aplica override-uri din profil (doar cele activate per input type):
  |     - synergy_bonus: 2+ componente cu risc >= threshold (+bonus/componenta, max cap)
  |     - false_claims: afirmatii false (+bonus/claim, max cap)
  |     - unverified_verifiable: claims verificabile neverificate (bonus fix)
  |     - severe_techniques: tehnici severe (bonus fix)
  |     - undisclosed_ai: AI nedeclarat (bonus fix)
  |     - untrusted_source: sursa neincrezuta/suspecta (bonus fix, din source_assessment)
  |     - blacklisted_source: sursa pe lista neagra (bonus fix, din source_assessment)
  |     - source_red_flags: red flags sursa (+bonus/flag, max cap)
  |     - override cap total per profil (default 50)
  |-- Rotunjire inainte de mapare la categorii
  |-- Mapare la risk_category, risk_level, severity (din Redis)
  |-- Calcul confidence (bonusuri/penalitati din profil)
  |-- INCONCLUSIVE check din profil (componenta primara crapat, min_components, required_any)
  |-- Virality: delegat la virality-calculator.ts (scor + factori + nivel)
  |
  v
PersistService.persist() -- salveaza in Redis + PostgreSQL
  |
  v
Response: AnalysisSession cu toate componentele
```

### Analiza media (audio/video)

```
Request POST /api/v3/techniques/analyze-media { media_url, media_type }
  |
  v
Verificare credite
  |
  v
Procesare media:
  |-- Audio: transcribe() via M17-Whisper -> Groq -> OpenAI
  |-- Video: download (yt-dlp) -> extrage cadre (ffmpeg) -> transcriere + viziune
  |-- Imagine: callVision() OCR -> text extras
  |
  v
Text extras -> TechniquesV3Executor (la fel ca text)
  |
  v
PersistService.persist()
  |
  v
Response: AnalysisSession cu metadata extractie (durata, provider, cadre analizate)
```

### Analiza asincrona

```
Request POST /api/v3/pipeline/analyze-async { text/media_url, plan_type }
  |
  v
Validare + Creditare
  |
  v
Dispatcher.dispatch() -> publica in RabbitMQ
  |
  v
Response 202: { session_id, poll_url, result_url }

--- In fundal (workeri Docker separati) ---

ComponentWorker consuma din coada -> ruleaza componenta -> publica rezultat in analysis.results
  |
  v
Aggregator consuma din analysis.results -> asteapta toate componentele -> VerdictCalculator
  |
  v
PersistService.persist() -> sesiune finala in Redis + PostgreSQL

--- Clientul polleaza ---

GET /api/v3/pipeline/{sessionId}/queue-status -> progres + componente finalizate
GET /api/v3/pipeline/{sessionId}/result -> sesiune completa cand status=completed
```

---

## Servicii externe apelate

| Serviciu | Scop | Unde in cod |
|----------|------|-------------|
| **Redis** local (`didi-cache:6379`, DB 0, parolă redis123) | Config framework + cache sesiuni (TTL 7 zile), acces prin `createRedisConnection()` | shared/redis/* |
| **PostgreSQL 17** local (`didi-postgres:5432`, DB `DIDI`, user `bos_interface`) | Stocare permanenta (schema bos_analysis) | shared/persistence/* |
| **RabbitMQ** local (`staging-dataLayer-rabbitmq:5672`, vhost `/`, user admin) | Cozi async pentru workeri | queue/* |
| MinIO (9000) | Stocare fisiere media | api/routes.ts (media endpoints) |
| OpenRouter API | Modele LLM (Gemini, GPT-4o, Claude, etc.) | components/*/executor.ts |
| OpenAI API | LLM fallback + Whisper transcriere | components/*/executor.ts, shared/media/transcription.ts |
| Groq API | LLM fallback + Whisper transcriere | components/*/executor.ts, shared/media/transcription.ts |
| M17-Whisper (`M17_WHISPER_URL`, default `http://10.11.10.17:54300`, configurabil din env) | Transcriere audio primara | shared/media/transcription.ts |
| M17 Web API (10.11.10.13:51100) | Fallback cautare web — folosit cand brain dezactivat sau MISS fara evidence | components/claims/executor.ts, components/source-assessment/executor.ts |
| **didi-brain** (Lot 1, `DIDI_BRAIN_URL` default `http://10.11.10.12:8090`) | Verification cache claims (`/v1/gather`, `/v1/verification_cache`) + analysis atom cache techniques/ai-tampered (`/v1/analysis_atom*`) — vezi „Integrare cu platforma AI (Lot 1)" | shared/brain/client.ts, components/*/executor.ts |
| Vision LLM (Lot 1, `VISION_LLM_URL` default `http://10.11.10.17:14011`) | Analiza imagine (OCR + AI detection) | shared/media/vision.ts |
| Domain Check API (<domain-check-host>:11000) | Analiza domeniu (WHOIS, DNS, SSL, blacklist) | api/routes.ts (domain/analyze) |
| didiFramework (didi-framework:3005) | Verificare/deducere credite + API keys extensie + sync framework → Redis local | shared/credits.ts, api/pipeline-routes.ts |

---

## Baza de date PostgreSQL

Schema: `bos_analysis`

| Tabel | Ce stocheaza | Cheie |
|-------|-------------|-------|
| analysis_session | Sesiunea root: user, input, status, timing, risk_score | session_id (UUID) |
| analysis_techniques | Rezultat componenta Techniques (JSONB: techniques_detected, coupling_context) | session_id FK |
| analysis_ai_tampered | Rezultat componenta AI-Tampered (JSONB: indicators_detected, image_analysis) | session_id FK |
| analysis_claims | Rezultat componenta Claims (JSONB: claims_verified, claims_by_status) | session_id FK |
| analysis_domain | Rezultat componenta Domain (trust_score, red_flags TEXT[], warnings) | session_id FK |
| analysis_verdict | Verdict final (risk_score, JSONB: applied_weights, context_summary) | session_id FK |
| moderation_queue | Coada review HIL (FK → analysis_session.session_id UUID): tier, priority, status, assigned_to, corrections JSONB | queue_id (UUID) |

Tabelul `analysis_session` are 6 coloane suplimentare pentru HIL: `review_status`, `human_corrected`, `human_corrections` (JSONB), `verified_by`, `verified_at`, `review_notes` (adaugate via migration `011_add_moderation.sql` rulata de didiFramework).

In schema `bos_parammgmt`, didiFramework owneste 3 tabele de config citite de agent-v3 prin Redis: `moderation_config` (single row), `sensitive_topic`, `moderation_role`.

Salvarea este tranzactionala (all-or-nothing). Ce produce componenta = ce se salveaza (zero transformari).

---

## Chei Redis importante

### Framework (FrameworkKeys) — permanente, scrise de didiFramework sync-redis

| Cheie | Scop |
|-------|------|
| didi:framework:manifest | Index categorii config |
| didi:framework:techniques | Ierarhie tehnici: dimensiuni -> subdimensiuni -> tehnici -> indicatori |
| didi:framework:sources | Parametri credibilitate sursa |
| didi:framework:claims | Parametri claims (tipuri, statusuri, confidence) |
| didi:framework:verdicts | Categorii verdict, risk mappings, severity assessments |
| didi:framework:weights | Ponderi componente, scenarii, multiplicatori |
| didi:framework:providers | Config provideri LLM (optional) |
| didi:framework:dimensions_compact | Lista compacta dimensiuni pentru prompts screening |

### Config componente (ConfigKeys) — permanente, scrise de didiFramework sync-redis

**Toate `stage_assignments` sunt tier-nested** (structura `{stage_code: {free: {...}, premium: {...}}}`) dupa migration 006 (tier column). Chain-urile de modele sunt diferite per tier — vezi sectiunea "Tier-aware execution" de mai sus.

| Cheie | Scop |
|-------|------|
| didi:config:pipeline:v1:component_config | Config executor pipeline + video track weights |
| didi:config:pipeline:v1:session_config | Config sesiune pipeline |
| didi:config:pipeline:v1:verdict_config | Override-uri, synergy, confidence (globale, fallback) |
| didi:config:pipeline:v1:input_profiles | **Profiluri verdict per input type (6 profile cu ponderi, override-uri, INCONCLUSIVE rules)** |
| didi:config:techniques:v3:available_models | Modele LLM Techniques (union free + premium) |
| didi:config:techniques:v3:stage_assignments | **Tier-nested** asignari etape Techniques |
| didi:config:techniques:v3:scoring_config | **Parametri scoring: count_scaler, severe_threshold, intensity bonus, bonuses** |
| didi:config:techniques:v3:dimensions_compact | Lista compacta dimensiuni Techniques |
| didi:config:claims:v1:available_models | Modele LLM Claims (union free + premium) |
| didi:config:claims:v1:stage_assignments | **Tier-nested** asignari etape Claims |
| didi:config:claims:v1:scoring_config | **Parametri scoring: status_weights, unverified behavior, claim_type_weights** |
| didi:config:ai-tampered:v1:available_models | Modele LLM AI-Tampered (union free + premium) |
| didi:config:ai-tampered:v1:stage_assignments | **Tier-nested** asignari etape AI-Tampered |
| didi:config:ai-tampered:v1:scoring_config | **Parametri scoring: blend_weights, disclosure_impact, thresholds, undisclosed_threshold** |
| didi:config:ai-tampered:v1:vision_models | Legacy flat vision config (fallback — nou e `didi:config:vision:v1:stage_assignments`) |
| didi:config:source-assessment:v1:available_models | Modele LLM Source Assessment (union free + premium) |
| didi:config:source-assessment:v1:stage_assignments | **Tier-nested** asignari etape Source Assessment |
| didi:config:source-assessment:v1:scoring_config | **Parametri scoring: axis_weights, verdict_thresholds** |
| didi:config:source-assessment:v1:prompts:extraction | Prompt extractie metadata sursa |
| didi:config:source-assessment:v1:prompts:evaluation | Prompt evaluare sursa cu categorii framework |
| didi:config:verdict:v1:stage_assignments | **Tier-nested** asignari Verdict reviewer (stage: verdict_review) |
| didi:config:verdict:v1:available_models | Legacy fallback pentru verdict-explanation.ts |
| didi:config:vision:v1:stage_assignments | **Tier-nested** asignari Vision (stage: image_analysis — OCR + AI detection + video frames) |
| didi:config:vision:v1:prompts:extraction | Prompt viziune: extractie text din imagine |
| didi:config:vision:v1:prompts:video_frames | Prompt viziune: analiza cadre video |
| didi:config:vision:v1:prompts:ai_detection | Prompt viziune: detectie AI in imagine |
| didi:config:moderation:v1:settings | Setari moderation + brain client (thresholds: `confidence_low`, `risk_grey_min/max`, feature flags: `triage_enabled`, `brain_enabled`, `brain_url`, `brain_lookup_timeout_ms`, `brain_per_component`) — citit cu cache 60s |
| didi:config:moderation:v1:sensitive_topics | Lista topice sensibile pentru triage (auto-enqueue daca match) |
| didi:config:moderation:v1:roles | Map roluri moderation (folosit la role check soft) |

**Toate cheile config au corespondent in PG** (`bos_parammgmt.component_config` + `component_prompt` + `component_stage_assignment` + `moderation_config` + `sensitive_topic` + `moderation_role`). Sync-redis le citeste din PG si le scrie in Redis. Admin dashboard editeaza PG, apoi sync to Redis.

### Sesiuni pipeline (SessionKeys) — TTL 7 zile

| Pattern | Scop |
|---------|------|
| didi:pipeline:{sessionId}:status | Status executie pipeline (JSON: PipelineStatus) |
| didi:pipeline:{sessionId}:{component} | Rezultat componenta (JSON: TechniquesResult etc.) |
| didi:pipeline:{sessionId}:verdict | Verdict final (JSON: VerdictResult) |

### Istoric (HistoryKeys) — TTL 7 zile

| Pattern | Scop |
|---------|------|
| didi:pipeline:history:entry:{sessionId} | Date intrare istoric (JSON: input + metadata) |
| didi:pipeline:history:user:{userId} | Sorted set istoric utilizator (score=timestamp, member=sessionId) |

### Coada (QueueKeys) — TTL scurt (30s-5min)

| Pattern | Scop |
|---------|------|
| didi:queue:session:{sessionId} | Stare fan-in agregare (JSON: partial AnalysisSession) |
| didi:queue:lock:{sessionId}:{component} | Lock executie componenta (previne duplicare worker) |
| didi:queue:aggregator:{sessionId} | Lock agregator (previne calcul verdict concurent) |

### Rezultate intermediare (AgentKeys) — TTL 7 zile

| Pattern | Scop |
|---------|------|
| agent:result:{sessionId}:{component}:{stage} | Rezultat intermediar etapa (screening, deep_analysis) |
| agent:result:{sessionId}:ai-tampered:visual | Rezultat analiza vizuala AI |
| agent:result:{sessionId}:ai-tampered:final | Rezultat final AI tampered (media merged) |
| agent:result:{sessionId}:ai-tampered:media | Rezultat intermediar AI tampered media |

### Media cache (MediaCacheKeys) — TTL 1 ora

Scrise de media-preprocess worker. Citite de component workers.

| Pattern | Scop |
|---------|------|
| agent:media:{sessionId}:transcript | Transcript audio (Whisper) |
| agent:media:{sessionId}:vision:misinformation | Output Vision frames — analiza manipulare |
| agent:media:{sessionId}:vision:ai_detection | Output Vision frames — detectie AI |
| agent:media:{sessionId}:merged_text | Transcript + vision misinformation (pentru techniques + claims) |
| agent:media:{sessionId}:lock | Lock procesare media (previne duplicare) |
| agent:media:{sessionId}:ready | Semnal finalizare pre-procesare ("1") |

### Extensie (ExtensionKeys) — permanente

| Pattern | Scop |
|---------|------|
| didi:extension:key:{apiKey} | Cache API key extensie browser |

---

## Docker Compose - Servicii

| Serviciu | Replici | Rol |
|----------|---------|-----|
| agent-v3 | 1 | Server API principal (port 24803) |
| worker-media-preprocess | 2 | Pre-procesare media: 1× download, 1× ffmpeg, 1× transcriptie, 2× Vision. Cache in Redis. Dispatche-aza component workers. |
| worker-techniques | 2 | Consuma din coada techniques. Citeste media din Redis cache. |
| worker-ai-tampered | 2 | Consuma din coada ai-tampered. Citeste media din Redis cache. 2-track video scoring (text 40% + visual 60%). |
| worker-claims | 3 | Consuma din coada claims (mai lent, mai multe replici). Citeste merged_text din Redis cache (transcript + text vizual). |
| worker-domain | 2 | Consuma din coada domain |
| verdict-aggregator | 2 | Colecteaza rezultate si calculeaza verdict |

Dependinte sistem in container: ffmpeg, yt-dlp, python3 (pentru video download si procesare).

### Fluxul async media (video/audio/image)

```
POST /api/v3/pipeline/analyze-async { media_type: "video" }
  |
  v
Dispatcher → analysis.media_preprocess.{plan} (1 task)
  |
  v
MediaPreprocessWorker:
  1. Download video (1×)
  2. ffmpeg: extract frames uniform (1×) + extract audio (1×)
  3. Whisper: transcriere audio (1×)
  4. Vision misinformation: analiza frames (1×)
  5. Vision ai_detection: analiza frames (1×)
  6. Salveaza in Redis (TTL 1h):
     - agent:media:{sid}:transcript
     - agent:media:{sid}:vision:misinformation
     - agent:media:{sid}:vision:ai_detection
     - agent:media:{sid}:merged_text
     - agent:media:{sid}:ready
  7. Dispatche-aza: techniques + ai_tampered + claims (+ domain daca URL)
  |
  v
Component Workers (citesc din Redis cache, zero download/ffmpeg):
  - techniques: primeste merged_text (transcript + vizual)
  - ai_tampered: primeste transcript (Track 1 text) + vision:ai_detection (Track 2 visual)
  - claims: primeste merged_text (transcript + text vizibil de pe ecran)
  - domain: primeste doar URL (skip pe media fara URL)
  |
  v
Verdict Aggregator → verdict (neschimbat)
```

Fallback: daca media preprocess esueaza, component workers proceseaza media local (safety net).

### Fluxul async text/URL (neschimbat)

Dispatcher → direct la component workers (fara media preprocess).

---

## Timeout-uri pe rute

| Ruta | Timeout | Motiv |
|------|---------|-------|
| /api/v3/pipeline/* | 660s (11 min) | Download video + transcriere + analiza completa |
| /api/v3/techniques/analyze-media | 300s (5 min) | Transcriere media + analiza |
| /api/v3/ai-tampered/analyze-media | 300s (5 min) | Procesare media + analiza |
| /api/v3/claims/analyze-media | 300s (5 min) | Transcriere + extractie + verificare |
| Toate celelalte | 180s (3 min) | Analiza text standard (server.timeout) |
| keepAliveTimeout | 665s | Usor mai mare decat max per-route timeout |
| headersTimeout | 670s | Usor mai mare decat keepAliveTimeout |

---

## Tipuri de raspuns

### AnalysisSession (raspuns standard pentru toate analizele)

```
{
  session_id, user_id, user_email,
  input_type (text/url/image/audio/video),
  input_text, input_url, input_media_url,
  input_hash,                               // SHA256
  status (pending/running/completed/failed),
  components_run[], components_skipped[],
  risk_score, risk_category, risk_level,
  confidence, confidence_level,
  started_at, completed_at, total_duration_ms,
  scenario_applied, topic_applied,
  source_app, api_version: "v3",
  created_at,

  techniques: {
    manipulation_score, total_severity, dimensions_affected[], techniques_count,
    techniques_detected[], coupling_context,
    llm_screening, llm_deep,
    screening_duration_ms, deep_analysis_duration_ms, total_duration_ms,
    fallbacks_screening, fallbacks_deep
  },
  ai_tampered: {
    ai_probability, verdict, risk_score, categories_affected[], indicators_count,
    disclosure_detected, disclosure_explicit, disclosure_text,
    indicators_detected[], coupling_context,
    llm_screening, llm_deep,
    screening_duration_ms, deep_analysis_duration_ms, total_duration_ms,
    fallbacks_screening, fallbacks_deep,
    content_type, image_analysis
  },
  claims: {
    total_claims, verified_true, verified_false, unverified, opinions,
    credibility_score, interpretation,
    claims_by_status, claims_by_type, claims_verified[],
    llm_extraction, llm_verification,
    extraction_duration_ms, verification_duration_ms, total_duration_ms,
    web_searches_made
  },
  domain: { domain, trust_score, verdict, risk_level, red_flags[], warnings[], duration_ms, ... },
  verdict: {
    risk_score, risk_category, risk_category_color,
    risk_level, risk_level_color,
    severity, recommended_action,
    confidence, confidence_level,
    score_manipulation, score_claims, score_ai, score_source, score_context,
    applied_weights, override_applied, override_type, override_reason, override_adjustment,
    context_summary, components_used[], weights_source, duration_ms,
    explanation_ro, explanation_en,
    virality_score, virality_level, virality_factors[]
  }
}
```

### Raspuns async (202 Accepted)

```
{
  success: true, async: true,
  data: { session_id, status: "processing", queued_components[], plan_type, poll_url, result_url }
}
```

### Raspuns media gol (cand nu s-a extras text din media)

```
{
  success: true,
  data: {
    session_id, status: "completed",
    input_type, input_media_url, media_type,
    skipped: true, skip_reason: "no_text_content" | "transcription_failed" | "vision_failed" | "extraction_failed",
    message: "...",
    techniques: null, ai_tampered: null, claims: null, domain: null, verdict: null,
    components_run: [], components_skipped: ["techniques", "ai_tampered", "claims"],
    risk_score: null, risk_category: null,
    metadata: { extraction_duration_ms, provider_tried }
  }
}
```

---

## Schimbari de logica (2026-03-20)

### Verdict INCONCLUSIVE determinist pe media fara claims

Fisier: `components/pipeline/verdict-calculator.ts`

Daca claims nu a produs rezultat (null) pe input video/audio/image → forteaza `risk_category = INCONCLUSIVE`. Inainte, LLM reviewer-ul decidea (inconsistent: +14 pe un video, +45 pe altul identic). Acum e determinist in cod.

LLM reviewer-ul (`verdict-explanation.ts`) nu mai penalizeaza pentru componente lipsa — instructiune explicita in prompt.

### Claims primeste text vizual din video frames

Fisier: `queue/workers/component-worker.ts`

Claims primeste `merged_text` (transcript audio + text vizibil de pe ecran) in loc de doar transcript. Permite verificarea afirmatiilor scrise pe ecran (titluri, statistici, URL-uri).

Prompt-ul claims extraction (Redis `didi:config:claims:v1:prompts:extraction`) instruieste LLM-ul sa distinga intre text citat de pe ecran (extrage ca claim) si observatii Vision AI (ignora).

### AI Tampered video: ponderi 40% text + 60% vizual

Fisier: `queue/workers/component-worker.ts`

Ponderile 2-track video scoring inversate: text 40% + vizual 60% (era text 60% + vizual 40%). Deepfake-uri cu voce reala dar fete AI primeau scor mic (34%) — vizualul trebuie sa domine pe video.

Prag minim text track: 200 chars. Sub 200 chars, text track e skip-uit si vizualul primeste 100% weight.

### Prompt AI detection Vision — 3 tiere forensic

Redis: `didi:config:vision:v1:prompts:ai_detection`

Tier 1: artefacte grosolane (warping, extra fingers) → AI_CONFIDENCE 75-95
Tier 2: indicii subtile deepfake modern (face-background mismatch, skin uniformity, hair boundary, eye reflections) → AI_CONFIDENCE 45-75
Tier 3: evaluare context (face closeup TV = minim 30, nu 0) → AI_CONFIDENCE 30-40

AI_CONFIDENCE: 0 interzis pe face closeup video.

### Techniques: intensity bonus diminishing returns

Fisier: `components/techniques/executor.ts`

Formula veche (liniara): `(avgIntensity - 1) * 0.05` → intensity 8 = 0.35 (35pp bonus)
Formula noua (sqrt + cap): `min(0.15, sqrt(avgIntensity - 1) * 0.05)` → intensity 8 = 0.13 (13pp bonus)

Previne scor 100% pe editoriale/jurnalism de investigatie cu ton puternic dar fara manipulare reala.

### Limite durata media

Fisiere: `api/pipeline-routes.ts` (API check), `shared/media/video-processor.ts` (ffprobe check)

- Video: max 180s (3 minute)
- Audio: max 420s (7 minute)

Doua guard-uri: API (instant, daca frontend trimite `media_duration_sec`) + ffprobe (dupa download, safety net).

### Optimizari claims

Fisiere: `components/claims/executor.ts`, `components/component-runner.ts`

- Claims global timeout: 300s → 600s
- Claims Qwen timeout: 60s → 120s (Redis config)
- Claims cap: 10 → 7 (skip low priority)
- Chunks paralele: 3 → 5
- Transcript trunchiat la 4000 chars pentru claims pe media

### Video frame sampling uniform

Fisier: `shared/media/video-processor.ts`

Inainte: `fps=1/5` secvential → frames doar din primele 50s. Video 5 min = 83% ignorat.
Acum: interval dinamic = `durata / maxFrames` → acoperire uniforma 100%. Minim 3 frames pe orice video.

---

## Funcționalități suplimentare (în afara celor 9 module de caiet)

Secțiunile de mai jos sunt **cod backend real**, dar reprezintă funcționalitate în plus față de cele 9 module ale caietului de sarcini. Tot aici se încadrează și **Tier-aware execution (premium vs free)**, **Virality** (`virality-calculator.ts`) și **HIL Moderation** (secțiunea următoare). Logica internă a brain-ului (RAG, tiering atom pe brain-side) aparține platformei AI (Lot 1); aici e descrisă doar integrarea client-side din agent-v3.

### Brain v2 Atom Cache (integrare client-side)

Brain v2 introduce un cache de **rezultate de analiza per componenta** (analysis atoms), in plus fata de verification cache-ul existent pentru claims. Salveaza output-ul deep analysis pentru `techniques` si `ai_tampered` indexat pe `(content_hash, component, tier, prompt_hash, framework_version)`. Hit fresh + tier potrivit (gold/silver) → skip LLM complet.

### Tier-uri atom

| Tier | Cum se obtine | Cum se foloseste |
|------|--------------|------------------|
| `gold` | Promovat manual via PATCH din HIL Moderation (action: approved sau corrected) | Hit fresh `gold` → folosit cu prioritate maxima |
| `silver` | Auto-scris de agent-v3 dupa fiecare analiza reusita pe tier `premium` | Hit fresh `silver` → folosit (overridable de gold) |
| `bronze` | Tier intermediar pe brain side (rezervat) | Ignorat de agent-v3 (skip LLM doar pe gold OR silver) |

Brain refuza scrieri pentru tier `free` — atoms scrise doar din premium analyses (calitate consistenta).

### Client extensie (`src/shared/brain/client.ts`)

Pe langa helperele existente (`gatherFromBrain`, `writeVerificationCacheAsync`, `evidenceOverlap`), clientul expune:

- `lookupAnalysisAtom({ content_hash, component, tier, prompt_hash, framework_version })` → `{ atom_id, data: AnalysisAtomData, cache_tier: AtomCacheTier, staleness: AtomStaleness } | null`
- `writeAnalysisAtomAsync(payload)` — fire-and-forget POST `/v1/analysis_atom`, doar pentru `tier = premium`
- `patchAnalysisAtomGold(atomId, corrections)` — promoveaza atom la `gold` cu corectiile umane (apelat din `moderation-routes.ts` pe resolve)
- helpers: `computeContentHash(text)`, `computePromptHash(prompt)`, `computeFrameworkVersion(...)`
- types: `AnalysisAtomData`, `AtomCacheTier` (`'gold' | 'silver' | 'bronze'`), `AtomStaleness` (`'fresh' | 'stale_framework' | 'stale_prompt' | 'miss'`)

### Config & feature flags (Redis: `didi:config:moderation:v1:settings`, cache 60s)

| Cheie | Rol |
|-------|-----|
| `brain_enabled` | Master switch — false → toate apelurile atom skip-uite, fallback direct LLM |
| `brain_url` | Override per environment (default `DIDI_BRAIN_URL` env) |
| `brain_lookup_timeout_ms` | Timeout per lookup (default tipic 800ms) |
| `brain_per_component` | Granular: `{techniques: bool, ai_tampered: bool, claims: bool}` |

Fail-open in toate cazurile: orice eroare brain (timeout, 5xx, network, feature flag off) → continua cu LLM. Atom cache nu poate bloca o analiza.

### Integrare in executoare

Atat `components/techniques/executor.ts` cat si `components/ai-tampered/executor.ts`:

```
execute(input):
  // START — atom lookup
  if (brain_enabled && brain_per_component[component]) {
    atom = await lookupAnalysisAtom({ content_hash, component, tier, prompt_hash, framework_version })
    if (atom && atom.staleness === 'fresh' && (atom.cache_tier === 'gold' || atom.cache_tier === 'silver')) {
      return atomToComponentResult(atom.data)   // skip LLM complet
    }
  }

  // ... screening + deep analysis (LLM normal flow) ...

  // END — atom write (happy path AND early-exit branches)
  writeAnalysisAtomAsync({ ... })   // fire-and-forget, doar tier=premium
  return result
```

Atom write e plasat pe **ambele** ramuri (happy path si early-exit pe disclosure detected / no techniques) — orice rezultat reprezentativ se cache-uieste.

### Promovare la gold via HIL

In `moderation-routes.ts` handler-ul `PUT /queue/:queueId/resolve`:

- `action = 'approved'` → patch atomii existenti per componenta (`techniques`, `ai_tampered`, `claims`) la `gold` (semnal: omul confirma rezultatul automat)
- `action = 'corrected'` → patch atomii la `gold` cu `corrections` aplicate (omul a editat output-ul automat — varianta corectata devine fontul de adevar)
- `action = 'rejected'` → nu touch-uie atoms (rezultatul a fost gresit, dar nu avem corectie validata)

PATCH-ul foloseste `(content_hash, component, tier, prompt_hash, framework_version)` pentru a localiza atomii potriviti pe brain side.

### Endpoint-uri brain v2 folosite

| Metoda | Path | Folosit de |
|--------|------|-----------|
| POST | /v1/analysis_atom/lookup | `lookupAnalysisAtom()` la START in techniques + ai-tampered |
| POST | /v1/analysis_atom | `writeAnalysisAtomAsync()` la END in techniques + ai-tampered (premium only) |
| PATCH | /v1/analysis_atom/{id} | `patchAnalysisAtomGold()` din HIL resolve |
| GET | /v1/analysis_atom/stats | Endpoint diagnostic (folosit la nevoie) |
| POST | /v1/gather | Existent — claims (verification cache lookup + evidence) |
| POST | /v1/verification_cache | Existent — claims write |

---

## HIL Moderation

Human-in-the-loop pentru sesiuni cu confidence scazut, scor in zona gri, sau topice sensibile. Triage-ul ruleaza dupa persistenta (NU blocheaza analiza) si decide daca sesiunea intra in coada de review uman. Moderatorii claim & resolve via REST API; rezolutiile pozitive (approved/corrected) promoveaza atomii la `gold` in brain.

### Triage (`src/components/moderation/triage.ts`)

Citeste config din Redis (`didi:config:moderation:v1:settings`, cache 60s):

| Threshold | Rol |
|-----------|-----|
| `confidence_low` | Sub aceasta valoare → enqueue review (model nesigur) |
| `risk_grey_min/max` | Banda gri risk_score (ex. 40-60) → enqueue review (rezultat ambiguu) |
| `sensitive_topics` | Match in continut → enqueue review automat |

Feature-flag protected: `triage_enabled = false` → triage no-op total.

### Queue manager (`src/components/moderation/queue-manager.ts`)

Operatii directe pe `bos_analysis.moderation_queue` via `shared/persistence/pg-pool.ts`:

| Functie | Ce face |
|---------|---------|
| `enqueueForReview(session, reason, priority)` | Idempotent — skip daca exista deja entry pending pentru acest `session_id` |
| `listQueue(filters)` | Listare cu filtre `status` CSV, `priority` CSV, `assigned_to` |
| `getQueueEntry(queueId)` | Entry + JOIN pe `analysis_session` (sesiunea full) |
| `claimQueueEntry(queueId, userId)` | UPDATE atomic conditionat pe `status = 'pending'` |
| `resolveQueueEntry(queueId, action, corrections, notes)` | UPDATE status + scrie `human_corrected` / `human_corrections` / `verified_by` / `verified_at` pe `analysis_session` |
| `getQueueStats()` | Counts pe tier/component + `hit_rate_24h` |

### Integrare in pipeline

Triage hook apelat **dupa** `persistService.persist(session)` in:
- `src/components/pipeline/executor.ts` (sync path)
- `src/queue/aggregator.ts` (async path)

Wrapping try/catch — orice eroare in triage e log-uita, NU se propaga. Analiza nu se blocheaza niciodata din cauza moderation.

### Role check soft

Middleware-ul JWT (`src/index.ts`) extrage `req.jwtRoles` din `realm_access.roles`. Endpoint-urile `/api/v3/moderation/*`:

- **Staging fara JWT roles** (Keycloak nu trimite role): permit (pentru testing)
- **Productie cu JWT**: require rol `moderator` (sau echivalent din `didi:config:moderation:v1:roles`)

Politica e soft (permit pe absent) ca sa nu blocheze flows-uri de testare interne.

### `userFlagged` flow

`POST /api/v3/moderation/flag` permite oricarui user autenticat (sau extensiei browser) sa raporteze o sesiune. Cand sesiunea e creata cu `user_flagged = true` (request body field), flag-ul e plumbed prin:

- `PipelineInput.userFlagged` (`components/pipeline/types.ts`)
- `SessionState.userFlagged` (`queue/types.ts`)
- `api/pipeline-routes.ts` extrage din body si forward-eaza

Triage citeste flag-ul si forteaza enqueue indiferent de threshold-uri (semnal uman = priority).