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mjasin ef82effeac docs: add git workflow and MCP integration guidelines to agent persona documentation 2026-05-05 15:13:40 +02:00
mjasin 311eaa8b04 feat: normalize subscription architecture, integrate pgvector, and implement Stripe webhook subscription management. 2026-05-05 15:07:48 +02:00
mjasin e21c24b66d feat: implement multi-tenancy support across knowledge services and normalize TenantId to string type. 2026-05-03 17:52:12 +02:00
mjasin eac0e9057e refactor: migrate agent configurations and skills to the .agent directory and add project documentation 2026-05-03 16:17:43 +02:00
mjasin afdfc31d1a feat: implement KM-RAG methodology artifacts and core architectural standards with supporting query and service updates 2026-05-03 16:12:07 +02:00
mjasin 1f187b5125 feat: implement semantic search, knowledge unit extraction, and visualization components 2026-05-03 15:59:30 +02:00
mjasin 94ecc7a404 feat: implement cross-device reading progress synchronization using SignalR and remove legacy quiz generation services. 2026-05-02 19:55:07 +02:00
mjasin e5611758f1 feat: implement Stripe product configuration and add token-based input validation using Microsoft.ML.Tokenizers 2026-05-02 10:31:28 +02:00
mjasin 0ed89ef5a4 feat: implement AI-driven text streaming and dynamic knowledge graph generation in AiAssistantBubble 2026-05-01 20:34:00 +02:00
mjasin 0cc25bb412 feat: add Microsoft.Extensions.Logging.Abstractions package and global logging namespace import 2026-05-01 20:24:42 +02:00
mjasin 93d8dfde7e refactor: remove Stripe webhook controller, optimize MainLayout rendering, and update DI registration in Program.cs 2026-05-01 20:12:36 +02:00
mjasin 47bffd629f feat: add application preloader, identity roles, and resilient database initialization with automated seeding 2026-05-01 09:07:26 +02:00
94 changed files with 4476 additions and 391 deletions
@@ -24,6 +24,10 @@ description: Standards for cross-platform compatibility (Web & MAUI Hybrid)
- Use `IPlatformService.GetDeviceContext()` to determine `DeviceType` (Phone, Tablet, Desktop).
- Adapt UI layout dynamically based on the context (e.g., sidebars on Tablet/Desktop, bottom navigation on Phone).
- **Real-time & Events (SignalR / UI):**
- **Debouncing**: Implement trailing-edge debouncing using `CancellationTokenSource` and `Task.Delay` for high-frequency UI events (like scrolling). Do not just drop events inside a time window, as the final state might be lost.
- **Dependency Isolation**: Blazor WebAssembly (`Web.Client`) cannot reference projects that require `Microsoft.AspNetCore.App` (like SignalR Hubs). Keep SignalR abstractions in `UI.Shared` and the Hub implementation strictly on the server (`Infrastructure` or `Web.New`).
- **Dependency Injection:**
- Register implementations in `MauiProgram.cs` for mobile and `Program.cs` for web.
- Components in `NexusReader.UI.Shared` must only depend on the interfaces.
+29
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@@ -0,0 +1,29 @@
---
name: km-rag-methodology
description: Expertise in implementing Knowledge-Map RAG (KM-RAG), focusing on structured Knowledge Units, Graph relationships, and multi-stage retrieval in .NET.
tags: [RAG, KnowledgeMap, GraphRAG, AI, .NET, CleanArchitecture]
version: 1.0.0
---
# KM-RAG Methodology
This skill provides a comprehensive framework for transitioning from basic chunk-based RAG to a structured **Knowledge-Map RAG (KM-RAG)** approach.
## Core Concepts
- **Knowledge Units (KU)**: Granular pieces of information with stable IDs and types (Section, Table, Definition, Rule).
- **Knowledge Map (Graph)**: Explicit links between units (`Next`, `Defines`, `Contains`) enabling contextual expansion.
- **Multi-Stage Retrieval**: A pipeline starting with semantic candidate generation followed by graph expansion and optional reranking.
- **Provenance & Governance**: Full traceability of AI answers back to their source units.
## Key Artifacts
- [Core Concepts](artifacts/core_concepts.md): Deep dive into the methodology.
- [Implementation Patterns (.NET)](artifacts/implementation_patterns.md): C# code for units, links, and retrieval.
- [Quality Checklist](artifacts/evaluation_checklist.md): Metrics and safety procedures.
- [Deep Research Report](artifacts/deep-research-report-rag.md): Original research on the KM-RAG approach.
## Usage
Use this skill when:
- Designing or refactoring RAG systems for high precision.
- Implementing multi-tenant knowledge bases.
- Enhancing AI answers with structural context from a graph.
- Building evaluation pipelines for hallucination detection.
@@ -0,0 +1,28 @@
# Core Concepts of KM-RAG (Knowledge-Map RAG)
Knowledge-Map RAG (KM-RAG) shifts the paradigm from "mechanical chunking" to "structured knowledge engineering".
## 1. From Chunks to Knowledge Units (KU)
Instead of random character-based splits, knowledge is partitioned into **Knowledge Units** that preserve structural meaning:
- **Unit Types**: `Section`, `Table`, `Definition`, `ProcedureStep`, `PolicyRule`.
- **Properties**: Stable ID, Version, Canonical Text, Rendered Context, Provenance (source, page, path).
## 2. The Knowledge Map (Graph)
Relationships between Knowledge Units are explicitly modeled to enhance retrieval and context assembly:
- `HAS_UNIT`: Document contains Unit.
- `NEXT` / `PREVIOUS`: Sequential flow between units.
- `DEFINES`: Unit defines a specific entity or term.
- `REFERENCES`: Unit refers to another unit.
- `EXCEPTION_OF`: Unit describes an exception to a rule in another unit.
## 3. Retrieval Strategy: "Plan over Similarity"
Retrieval is not just `top-k` similarity but a multi-stage process:
1. **Candidate Generation**: Hybrid search (Vector + Keyword) to find potential matches.
2. **Graph Expansion**: Pulling related units (e.g., "Get the section this table belongs to" or "Get the definition of term X used here").
3. **Reranking**: Using a Cross-Encoder to precisely score the expanded candidates.
4. **Context Assembly**: Building a grounded context with explicit citations.
## 4. Governance and Provenance
- **Audit Trail**: Every answer must be traceable back to specific Knowledge Units with valid provenance.
- **Permission-Aware**: Retrieval filters must enforce ACLs at the unit/graph level before the LLM sees the data.
- **Continuous Evaluation**: Monitoring "Faithfulness" (groundedness) and "Answer Relevance" using tools like RAGAS or TruLens.
@@ -0,0 +1,588 @@
# Mapa Wiedzy i kontrola w RAG: jak wdrożyć „nowe podejście” w sposób inżynieryjny
## Executive summary
Autor posta (entity["people","Vladimir Alekseichenko","dataworkshop ceo"], entity["organization","DataWorkshop","ml/ai training poland"]) kontrastuje „klasyczny” RAG oparty o mechaniczne chunkowanie i wektoryzację z podejściem, w którym buduje się **Mapę Wiedzy**: „graf z metadanymi, powiązaniami i odniesieniami do źródeł” (w kontekście praktyki na danych z entity["organization","Giełda Papierów Wartościowych w Warszawie","warsaw stock exchange"]). citeturn2view0turn2view1
W tym raporcie formalizuję tę ideę jako **KnowledgeMap RAG (KMRAG)**: RAG, w którym warstwa „R” nie jest tylko wyszukiwaniem semantycznym po losowych fragmentach, ale **kontrolowanym wyborem jednostek wiedzy** (sekcja, tabela, rekord, definicja, reguła) powiązanych grafowo, z pełną **proweniencją (skąd to jest), politykami dostępu, wersjonowaniem i testowalnością**. To jest spójne z tezą autora, że „R w RAG” to przede wszystkim **ryzyko**: jeśli retrieval jest błędny, model będzie „pewnie” odpowiadał na podstawie złego kontekstu. citeturn2view0turn6view0
Ponieważ nie podałeś ograniczeń (skala, budżet, SLA/latencja), przyjmuję **brak specyficznych constraintów** i podaję warianty: od małych wdrożeń (Postgres/pgvector) po architektury wielotenancy (Qdrant/Pinecone/Weaviate) oraz hybrydy graf + wektory. citeturn12search2turn14search1turn14search16turn14search0turn14search2
Najważniejsze rekomendacje wdrożeniowe:
Po pierwsze, zastąp „losowe chunki” **jednostkami sensu**: segmentacją strukturalną (nagłówki/sekcje/tabele) i/lub semantyczną, z metadanymi i relacjami (poprzedni/następny, należy do sekcji, cytuje, definiuje). citeturn6view0turn11search1turn11search29
Po drugie, zbuduj **Mapę Wiedzy jako graf** (property graph) + indeksy (wektorowy i leksykalny/hybrydowy). Praktycznie: graf przechowuje relacje i proweniencję, a wektory dają tani „candidate generation”; dopiero potem używasz grafu do „dociągnięcia” brakujących kontekstów i do audytu. To jest zgodne z rodziną podejść GraphRAG (np. publikacja entity["company","Microsoft","tech company"] o GraphRAG: graf encji + „community summaries” dla lepszych odpowiedzi na pytania globalne). citeturn0search1turn3search4turn3search20
Po trzecie, „kontrola zamiast nadziei” oznacza: (a) **mierniki retrieval i generation**, (b) automatyczne testy regresji i audyt ścieżki źródeł, (c) monitoring i alerty driftu oraz incydentów bezpieczeństwa (prompt injection, data leakage). W praktyce: RAGAS/TruLens + OWASP LLM Top 10 jako checklisty, plus logowanie „trace” (kontekst → odpowiedź → cytowania). citeturn4search1turn4search2turn4search6turn4search13turn4search7
## Definicja podejścia „Mapa Wiedzy zamiast losowych chunków”
W poście autor opisuje Mapę Wiedzy jako artefakt, który budujesz **w 3 dni**: „graf z metadanymi, powiązaniami i odniesieniami do źródeł” (wspomina też kontekst narzędziowy: repozytorium na entity["company","GitHub","code hosting platform"] i notatki w entity["company","Obsidian","note-taking app company"]). citeturn2view1
Jednocześnie w dłuższym materiale autor rozwija intuicję, dlaczego „chunking + vector DB” bywa drogą donikąd: mechaniczne cięcie rozrywa jednostki sensu (akapit, tabela), a model językowy zwykle **nie weryfikuje kontekstu** odpowiada w oparciu o to, co mu dostarczysz, nawet jeśli kontekst jest sprzeczny (stąd losowość i halucynacje). citeturn6view0turn7view1
### Precyzyjna definicja operacyjna (KMRAG)
**KnowledgeMap RAG (KMRAG)** to architektura RAG, w której warstwa „R” jest realizowana przez:
**Reprezentację wiedzy**: dokumenty są przekształcane do zbioru **jednostek wiedzy** (Knowledge Units) o stabilnej proweniencji (ID, wersja, lokalizacja w źródle) i spójnej semantyce (sekcja definicji, tabela, rozdział, procedura), a nie losowych wycinków znaków. citeturn6view0turn11search9turn16search0
**Mapę (graf) zależności**: jednostki są węzłami grafu (np. DOCUMENT → SECTION → UNIT; ENTITY ↔ UNIT; UNIT ↔ UNIT przez „refers_to/next/derives_from”), a krawędzie niosą informację ułatwiającą retrieval i audyt (np. „to jest definicja terminu X”, „to jest wyjątek od reguły”). citeturn2view1turn10search3turn3search4
**Polityki retrieval**: zapytanie jest mapowane na intencję i encje, a retrieval wykonuje plan: generuje kandydatów (wektory/keyword/hybrid), następnie rozszerza kontekst grafowo (np. sekcja nadrzędna, definicje encji, powiązane tabele), na końcu dokonuje selekcji (rerank/pruning) i buduje kontekst z cytowaniami. citeturn12search3turn12search11turn10search6turn10search31
**Kontrolę i audytowalność**: system jest projektowany tak, aby można było odpowiedzieć na pytania: „Dlaczego ten fragment?”, „Czy użytkownik miał uprawnienia?”, „Jaka wersja źródła?”, „Czy odpowiedź jest ugruntowana (grounded) w kontekście?”. Autor wprost wiąże „mapę wiedzy” z uszczelnianiem rozwiązań, wymaganiami prawnymi/bezpieczeństwa oraz audytowalnością. citeturn7view1turn14search2
### Dlaczego „losowe chunki” są słabą abstrakcją inżynieryjną
Mechaniczne chunkowanie jest często liczone w znakach/tokenach; nawet z overlapem rozrywa strukturę i wymusza „magiczne” heurystyki (większy chunk_size, więcej chunków w kontekście), które łatwo psują wcześniej działające przypadki i utrudniają stabilną ewaluację. citeturn6view0
Z perspektywy governance kluczowy problem jest też bezpieczeństwo: w jednym dokumencie mogą być fragmenty o różnych poziomach dostępu, więc „wrzucanie wszystkiego do jednego kontekstu” łamie zasady separacji i komplikuje zgodność (ten motyw pojawia się u autora wprost). citeturn7view1turn14search2
## Architektura referencyjna i komponenty
Poniżej przedstawiam architekturę komponentową KMRAG, obejmującą: ingestion, mapę wiedzy, strategie segmentacji, embeddingi i wektory, retrievery i rerankery, prompt engineering i grounding, oraz kontrolę halucynacji i ewaluację.
### Diagram architektury
```mermaid
flowchart LR
subgraph Ingestion
A[Źródła: PDF/HTML/DOCX/DB] --> B[Parsing + normalizacja]
B --> C[Jednostki wiedzy: sekcje, tabele, rekordy]
C --> D[Metadane: źródło, wersja, ACL, lokalizacja]
C --> E[Ekstrakcja encji/relacji]
E --> G[(Graf / Mapa Wiedzy)]
C --> F[Embedding + indeks]
F --> V[(Vector DB)]
end
subgraph QueryTime
Q[Zapytanie użytkownika] --> R[Routing/intencja/encje]
R --> V1[Candidate gen: vector/keyword/hybrid]
V1 --> V
V --> K[Top-K kandydatów]
K --> G1[Graph expansion\n(definicje, zależności, sekcje)]
G1 --> G
G --> S[Context assembly + dedup + cytowania]
S --> L[LLM generacja\n(z zasadą "answer from sources")]
L --> O[Odpowiedź + cytowania + confidence]
end
subgraph Control
O --> M[Logi/trace]
M --> EV[Ewaluacja offline/online]
M --> MON[Monitoring KPI + alerty]
end
```
Model ten jest kompatybilny zarówno z „klasycznym RAG” w sensie pracy na wektorach (RAG w ujęciu Lewis et al. zakłada połączenie pamięci parametrycznej i nieparametrycznej poprzez retrieval z indeksu wektorowego), jak i z odmianami grafowymi (GraphRAG: budowa grafu encji i „community summaries” jako warstwa indeksu). citeturn0search2turn0search5turn0search1turn3search4
image_group{"layout":"carousel","aspect_ratio":"16:9","query":["GraphRAG architecture diagram","knowledge graph retrieval augmented generation diagram","vector database similarity search diagram","Neo4j graph visualization example"],"num_per_query":1}
### Ingestion: parsowanie, normalizacja i jednostki wiedzy
W KMRAG ingestion nie kończy się na „wyciągnij tekst z PDF”. Kluczowe jest zachowanie/rekonstrukcja struktury: tytuły, listy, tabele, numer stron, sekcje. Biblioteka entity["company","Unstructured","document processing company"] wprost opisuje „partitioning” jako ekstrakcję ustrukturyzowanych elementów (Title/NarrativeText/ListItem itd.), aby móc decydować, co zachować. citeturn16search0turn16search8turn16search4
Jeśli pracujesz na bardzo różnych formatach lub potrzebujesz także metadanych i obsługi np. zaszyfrowanych PDF, narzędzia z ekosystemu entity["organization","Apache Software Foundation","open source foundation"] (Apache Tika) podkreślają możliwość parsowania PDF, w tym obsługi dokumentów szyfrowanych przy podaniu hasła. citeturn16search1turn16search30
Wniosek projektowy: „Jednostka wiedzy” w KMRAG to obiekt typu np.:
- `unit_type`: `section`, `definition`, `table`, `row`, `procedure_step`, `policy_rule`
- `canonical_text` (tekst do embeddingu i rerankingu)
- `rendered_context` (tekst/fragment do wklejenia do prompta)
- `provenance`: `source_id`, `page`, `section_path`, `span_offsets`
- `governance`: `acl_tags`, `pii_class`, `retention_class`
- `links`: `prev/next`, `references`, `same_topic`
Taki model danych bezpośrednio adresuje problem autora: model nie „weźmie odpowiedzialności” za konfliktujący kontekst, więc to system ma pilnować jakości kontekstu i jego zaufania. citeturn6view0turn7view1
### Strategie segmentacji: od „chunków” do „węzłów” (Nodes)
Jeżeli musisz działać na tekście, i tak będziesz coś „dzielił” różnica polega na tym, czy są to losowe fragmenty znaków, czy **węzły semantyczne**.
- W ekosystemie entity["company","LangChain","llm app framework company"] często proponuje się `RecursiveCharacterTextSplitter` jako „solidny default” dla wielu przypadków, ale to nadal jest heurystyka bazująca na znakach i separatorach. citeturn11search8turn11search0
- entity["company","LlamaIndex","llm data framework company"] oferuje semantyczne parsowanie węzłów: `SemanticSplitterNodeParser` dzieli tekst na grupy zdań powiązane semantycznie (z użyciem embeddingów), a dokumentacja podkreśla, że to alternatywa dla stałego rozmiaru chunków. citeturn11search1turn11search9turn11search29
KMRAG traktuje segmentację jako element modelowania danych: węzły mają typ, hierarchię i relacje.
### Embeddingi i Vector DB: candidate generation + filtrowanie po metadanych
Embeddingi są nadal bardzo użyteczne, ale w KMRAG pełnią rolę „szybkiego generatora kandydatów”, a nie „wyroczni”.
Otwartoźródłowo, entity["company","Hugging Face","ml model hub company"] utrzymuje Sentence Transformers, które dostarcza zarówno modele embeddingowe (bi-encoders), jak i rerankery (cross-encoders). citeturn12search38turn12search3
Warstwa metadanych jest w KMRAG krytyczna: np. do ograniczania domeny, wersji dokumentu, języka, daty wejścia w życie, uprawnień.
- entity["company","Qdrant","vector database company"] opisuje payload/metadata i filtrowanie oraz zaleca indeksowanie pól payload dla efektywności filtrowania. citeturn11search2turn11search6turn11search37
- entity["company","Pinecone","vector database company"] opisuje filtrowanie po metadanych oraz pokazuje wzorzec multitenancy przez namespaces. citeturn11search7turn14search16turn14search12
- entity["company","Weaviate","vector database company"] opisuje hybrydę BM25F + wektory (fuzja wyników i wagi są konfigurowalne) oraz posiada natywną wielodzierżawność (tenant per request). citeturn12search0turn14search0
- entity["company","Milvus","vector database project"] dokumentuje hybrydę sparse+dense i wskazuje scenariusze, w których połączenie poprawia wyniki (semantyka + dopasowanie słów kluczowych). citeturn12search1turn12search5
W KMRAG niemal zawsze warto rozważyć hybrid retrieval (dense + sparse), bo ogranicza „semantic drift” i poprawia precyzję przy terminach domenowych (np. numery, nazwy własne). Jest to wspólny wątek w dokumentacji Weaviate i Pinecone, opisującej fuzję wyników i podejścia do hybrydy. citeturn12search0turn11search3turn11search19
### Retrievery, rerankery i kontrola halucynacji
KMRAG rozdziela retrieval na etapy:
**Candidate generation (tani):** dense retriever (np. dual-encoder) i/lub sparse (BM25). Klasyczna praca o dense retrieval (DPR) pokazuje dual-encoder jako praktyczny mechanizm retrieval i porównuje go do BM25 w QA. citeturn8search0turn8search4
**Reranking (droższy):** cross-encoder reranker znacząco poprawia ranking, ale jest kosztowny, bo ocenia pary (query, doc) wspólnie w modelu. Sentence Transformers opisuje retrieve&rerank pipeline oraz rolę CrossEncodera. citeturn12search11turn12search19
**Graph expansion (precyzja i kompletność):** graf dostarcza „brakujących mostów” (definicje, zależności, wyjątki, kontekst sekcji) oraz daje audyt to jest sedno „Mapy Wiedzy”. W wariantach GraphRAG (Microsoft) graf jest budowany z encji i relacji, a następnie grupowany w społeczności i streszczany, co poprawia odpowiedzi na pytania „globalne” (np. „jakie są główne tematy w korpusie?”), gdzie naiwny RAG zawodzi. citeturn0search1turn0search13turn3search4turn3search20
**Halucynacje i „kontrola”:** literatura proponuje pętle weryfikacji (np. ChainofVerification: draft → pytania weryfikacyjne → niezależne odpowiedzi → final) i mechanizmy samorefleksji (SelfRAG) oraz korekty retrieval (CRAG). Są to techniki „kontroli” na poziomie architektury, a nie tylko promptu. citeturn8search3turn9search1turn9search2
## Opcje projektowe i tradeoffy
### Porównanie: klasyczny RAG vs KMRAG
| Wymiar | Klasyczny „chunk + vector DB” | KMRAG (Mapa Wiedzy) | Konsekwencja praktyczna |
|---|---|---|---|
| Jednostka indeksowania | fragment znaków/tokenów | jednostka sensu: sekcja/tabela/rekord + typ | mniej „urwanych” kontekstów, mniej przypadkowości |
| Reprezentacja | embedding + (czasem) metadata | embedding + metadata + graf relacji + proweniencja | lepsza ścieżka audytu i „dlaczego to” |
| Retrieval | topk similarity | plan retrieval: hybrid + graf expansion + rerank | wyższa precyzja i odporność na trudne pytania |
| Zmiany w danych | częsty reindex, ryzyko regresji | wersjonowanie, testy regresji per typ jednostki | stabilniejsze wdrożenia i migracje |
| Bezpieczeństwo/ACL | łatwo mieszać fragmenty o różnych uprawnieniach | ACL na poziomie jednostki i ścieżki grafu | mniejsze ryzyko wycieku kontekstu |
| Debuggowanie | „dlaczego takie chunki?” | „jaki węzeł, z jakiego źródła, jaka relacja?” | szybsze RCA i audyt |
Uzasadnienie co do problemów chunkingu i „model ufa kontekstowi” pochodzi z materiału autora; definicja Mapy Wiedzy jako grafu z metadanymi i odniesieniami jest wprost w poście. citeturn6view0turn2view1turn7view1
### Wybory technologiczne: wektory, graf, hybryda
Poniżej pokazuję typowe opcje i kompromisy (bez narzuconych constraintów dobór zależy od QPS, wolumenu i wymagań bezpieczeństwa).
**Vector store**
- Qdrant: mocne filtrowanie payload + mechanizmy multitenancy (w tym „tiered multitenancy”). citeturn11search6turn14search1turn14search18
- Pinecone: proste multitenancy przez namespaces; dobrze opisane podejścia do hybrid search (single hybrid index vs osobne indeksy, z plusami i minusami). citeturn14search16turn11search3
- Weaviate: wbudowany hybrid BM25F + wektor, oraz multitenancy z tenantem w operacjach. citeturn12search0turn14search0
- Milvus: rozbudowane podejścia do sparse+dense i multivector, z dokumentacją dla hybrydy. citeturn12search1turn12search5turn12search33
- pgvector: dobre, gdy chcesz „mniej systemów” i akceptujesz kompromisy wydajności; repo dokumentuje różnice IVFFlat vs HNSW (build time/memory vs speedrecall). citeturn12search2turn12search14
- Elasticsearch: istotny, gdy potrzebujesz „enterprise security” (RBAC, field/documentlevel security) i hybrydowego wyszukiwania w jednej platformie. citeturn14search2turn14search15
**Graph / Knowledge Map store**
- Neo4j: bogate wzorce GraphRAG (graph traversal, fulltext, vector, text2cypher). Neo4j publikuje GraphRAG field guide i pakiet GraphRAG dla Pythona. citeturn10search18turn10search14turn10search31turn10search2
- Microsoft GraphRAG: gotowy pipeline budowy grafowego indeksu (encje → społeczności → streszczenia), opensource na GitHubie + dokumentacja „Getting started”. citeturn3search0turn3search31turn3search20turn0search1
- LlamaIndex KnowledgeGraphIndex: praktyczna automatyzacja budowy grafu z tekstu i query po encjach. citeturn10search3turn10search11
**Kompromisy**
- Skalowalność: graf może zmniejszać liczbę „strzałów” w LLM (np. przez prestreszczenia społeczności w GraphRAG) kosztem cięższego ingestion i większej złożoności danych. citeturn0search1turn3search4
- Latencja: rerankery crossencoder podnoszą jakość, ale zwiększają czas (N par do oceny); dlatego standardem jest retrieval → rerank topN, nie rerank całego korpusu. citeturn12search11turn12search19
- Koszt: hybryda i graf często zwiększają koszt ingest (LLM do ekstrakcji encji/relacji), ale zmniejszają koszt „ratowania” jakości w runtime przez kolejne heurystyki. To jest w duchu argumentu autora o „dokładaniu miniklocków” versus poprawa fundamentu. citeturn6view0turn7view1
- Maintainability: mniej „magicznych” parametrów chunk_size; więcej jawnych typów jednostek i testów per typ. citeturn7view1turn13search3
- Security/data governance: najlepiej wspierać **permissionaware retrieval** już w retrieverze (prefilter), bo wtedy model nie ma czego „wyciec”. Dokumentacja Elastic i wektor DB pokazuje mechanizmy RBAC/DLS, namespaces/tenants i filtrowanie po metadanych. citeturn14search2turn14search16turn14search0turn11search6
## Migracja z klasycznego RAG do KMRAG
Migracja jest łatwiejsza, jeśli potraktujesz ją jak refactoring warstwy danych i retrieval, a nie „przepisanie wszystkiego od zera”.
### Ścieżka migracji krok po kroku
**Krok pierwszy: ustal bazową prawdę (baseline) i testy.**
Bez ewaluacji będziesz „liczyć na cud” wprost przeciwieństwo postulatu „kontrola zamiast nadziei”. Zacznij od małego zestawu pytań i oczekiwań (golden set) oraz logowania kontekstu i odpowiedzi. W praktyce możesz użyć RAGAS (metryki retrieval i faithfulness bez konieczności pełnych anotacji) oraz TruLens (RAG triad: context relevance, groundedness, answer relevance). citeturn4search1turn4search2turn4search6
**Krok drugi: dołóż metadane i proweniencję zanim dołożysz graf.**
W klasycznym RAG często brakuje stabilnych ID i lokalizacji w źródle; tymczasem autor wiąże mapę wiedzy z odniesieniami do źródeł. Minimalny zestaw to: `source_id`, `version`, `page/section`, `timestamp`, `acl_tags`. Mechanizmy filtrowania po metadanych są standardem m.in. w Pinecone i Qdrant. citeturn2view1turn11search7turn11search6
**Krok trzeci: zamień chunki na węzły o typach i relacjach.**
Zamiast „1000 znaków”, twórz: `SectionNode`, `TableNode`, `DefinitionNode`, `PolicyNode`. Jeśli nie możesz od razu, przejdź etapowo przez semantyczne node parsers (LlamaIndex) lub segmentację po strukturze dokumentu (partitioning). citeturn11search9turn16search0turn11search1
**Krok czwarty: zbuduj Mapę Wiedzy (graf) i zacznij od najtańszego użycia w runtime.**
Nie musisz od razu robić pełnego „GraphRAG global”. Najpierw używaj grafu do: (a) definicji i wyjątków, (b) dołączania kontekstu „nadrzędna sekcja” / „poprzedninastępny”, (c) audytu ścieżki cytowań. Dopiero potem dokładaj stricte grafowe retrievery. citeturn10search6turn10search31turn3search4
**Krok piąty: wprowadź gating i rollout.**
Zgodnie z najlepszymi praktykami ewaluacji: iteruj, porównuj wersje, ustaw continuous evaluation i progi akceptacji. citeturn13search3turn13search35
### Proponowana sekwencja wdrożenia
| Faza | Co dostarczasz | Typowy czas (brak constraintów) | Kryterium „done” |
|---|---|---:|---|
| Audit RAG | logi + golden set + baseline metryk | 12 tyg. | masz mierzalne recall/faithfulness + top failure modes |
| Metadata-first | proweniencja + filtry + ACL | 12 tyg. | brak „orphan” chunków bez źródła; prefiltrowanie działa |
| Nodes & map | węzły typowane + relacje | 24 tyg. | stable IDs, relacje prev/next/contains/refers_to |
| Hybrid + rerank | dense+sparse + rerank topN | 13 tyg. | poprawa metryk retrieval bez wzrostu halucynacji |
| Graph expansion | dołączanie kontekstu grafem | 24 tyg. | poprawa trudnych pytań „łączących fakty” |
| Produkcja | monitoring KPI + procedury incydentów | ciągłe | CE + alerty + playbook audytu |
Metryki i praktykę continuous evaluation wspiera dokumentacja OpenAI (zalecenia dot. progów context recall/precision i pipelineu ewaluacji), co jest spójne z „kontrolą” jako procesem, nie jednorazową konfiguracją. citeturn13search3turn13search27
## Implementacje przykładowe
Poniższe implementacje są „szkieletami” (reference implementations). W obu wariantach zakładam brak narzuconych wymagań co do skali, więc pokazuję rozwiązania, które da się skalować horyzontalnie (wektor DB) i/lub uprościć (pgvector zamiast osobnej bazy).
### Stack A: opensource embeddings + opensource Vector DB (Sentence Transformers + Qdrant) + graf w Neo4j
**Kiedy wybrać:** gdy chcesz uniezależnić embeddingi od dostawcy, mieć pełną kontrolę nad danymi i implementować multitenancy/filtry wprost w wektor DB. Payload/filtry i multitenancy są natywnie wspierane w Qdrant. citeturn11search6turn14search1turn14search7
**Zależności (przykład):** `sentence-transformers`, `qdrant-client`, `neo4j`, parser dokumentów (`unstructured` lub Tika).
```python
# --- Ingestion: parse -> units -> embeddings -> Qdrant + graph ---
from dataclasses import dataclass
from typing import Iterable, Optional
import hashlib
import time
from sentence_transformers import SentenceTransformer, CrossEncoder
from qdrant_client import QdrantClient, models as qmodels
from neo4j import GraphDatabase
@dataclass
class KnowledgeUnit:
unit_id: str
source_id: str
version: str
unit_type: str # e.g. "section", "definition", "table"
text: str # canonical text for embedding
page: Optional[int] = None
section_path: Optional[str] = None
acl: str = "public" # e.g. role/tenant tag
def stable_id(source_id: str, version: str, unit_type: str, page: str, text: str) -> str:
raw = f"{source_id}|{version}|{unit_type}|{page}|{text}".encode("utf-8")
return hashlib.sha256(raw).hexdigest()[:24]
# 1) Embeddings (bi-encoder) + reranker (cross-encoder)
embed_model = SentenceTransformer("sentence-transformers/all-MiniLM-L6-v2") # example
reranker = CrossEncoder("cross-encoder/ms-marco-MiniLM-L-6-v2") # example
# 2) Vector DB: Qdrant
qdrant = QdrantClient(url="http://localhost:6333", timeout=30)
COLLECTION = "kmrag_units"
DIM = embed_model.get_sentence_embedding_dimension()
qdrant.recreate_collection(
collection_name=COLLECTION,
vectors_config=qmodels.VectorParams(size=DIM, distance=qmodels.Distance.COSINE),
)
# Index payload fields frequently used in filters (performance)
qdrant.create_payload_index(
collection_name=COLLECTION,
field_name="acl",
field_schema=qmodels.PayloadSchemaType.KEYWORD,
)
qdrant.create_payload_index(
collection_name=COLLECTION,
field_name="source_id",
field_schema=qmodels.PayloadSchemaType.KEYWORD,
)
# 3) Graph DB: Neo4j (property graph)
neo4j_driver = GraphDatabase.driver(
"neo4j://localhost:7687", auth=("neo4j", "password")
)
def upsert_units(units: Iterable[KnowledgeUnit]) -> None:
batch = list(units)
# embeddings
vectors = embed_model.encode([u.text for u in batch], normalize_embeddings=True)
# upsert into Qdrant with payload metadata (provenance + ACL)
qdrant.upsert(
collection_name=COLLECTION,
points=[
qmodels.PointStruct(
id=u.unit_id,
vector=vectors[i].tolist(),
payload={
"source_id": u.source_id,
"version": u.version,
"unit_type": u.unit_type,
"page": u.page,
"section_path": u.section_path,
"acl": u.acl,
"ingested_at": int(time.time()),
},
)
for i, u in enumerate(batch)
],
)
# build/update graph nodes + relationships
cypher = """
UNWIND $rows AS r
MERGE (d:Document {source_id: r.source_id, version: r.version})
MERGE (u:Unit {unit_id: r.unit_id})
SET u.unit_type = r.unit_type,
u.page = r.page,
u.section_path = r.section_path
MERGE (d)-[:HAS_UNIT]->(u)
"""
with neo4j_driver.session() as s:
s.run(cypher, rows=[u.__dict__ for u in batch])
# --- Query-time retrieval: vector -> graph expansion -> rerank -> context ---
def retrieve(query: str, acl: str, top_k: int = 30, rerank_k: int = 8):
qvec = embed_model.encode([query], normalize_embeddings=True)[0].tolist()
# 1) Candidate generation with metadata filter (permission-aware)
hits = qdrant.search(
collection_name=COLLECTION,
query_vector=qvec,
limit=top_k,
query_filter=qmodels.Filter(
must=[qmodels.FieldCondition(key="acl", match=qmodels.MatchValue(value=acl))]
),
)
candidate_ids = [h.id for h in hits]
# 2) Graph expansion: pull neighbor units from same document/section (simple example)
expand_cypher = """
MATCH (u:Unit) WHERE u.unit_id IN $ids
OPTIONAL MATCH (d:Document)-[:HAS_UNIT]->(u)
OPTIONAL MATCH (d)-[:HAS_UNIT]->(u2:Unit)
WHERE u2.section_path = u.section_path
RETURN DISTINCT u2.unit_id AS unit_id
LIMIT 200
"""
with neo4j_driver.session() as s:
rows = s.run(expand_cypher, ids=candidate_ids).data()
expanded_ids = list({r["unit_id"] for r in rows}) or candidate_ids
# 3) Fetch texts for reranking (here: from Qdrant payload 'text' not stored; you'd load from your storage)
# In production: keep canonical text in your doc store; Qdrant payload keeps provenance only.
# For demo: assume we can map id->text elsewhere:
id_to_text = load_texts(expanded_ids) # implement in your system
pairs = [(query, id_to_text[i]) for i in expanded_ids]
scores = reranker.predict(pairs)
ranked = sorted(zip(expanded_ids, scores), key=lambda x: x[1], reverse=True)[:rerank_k]
return ranked # list of (unit_id, score) + you can also return provenance from payload
def load_texts(unit_ids):
# Placeholder: pull canonical text from your document store / data lake
raise NotImplementedError
```
Co w tym szkielecie jest „Mapą Wiedzy”: Neo4j przechowuje relacje (Document→Unit, a dalej możesz dodać Entity↔Unit, REFERENCES, NEXT), a Qdrant przechowuje wektory + payload do filtrowania; filtrowanie i indeksowanie payload jest sformalizowane w dokumentacji Qdrant. citeturn11search6turn11search2turn14search7
Rerank to klasyczny krok „retrievethenrerank” opisywany przez Sentence Transformers, gdzie CrossEncoder podnosi jakość finalnych wyników kosztem obliczeń. citeturn12search11turn12search19
### Stack B: managed LLM + Vector DB (OpenAI + Pinecone) + graf (Neo4j GraphRAG / Text2Cypher)
**Kiedy wybrać:** gdy zależy Ci na szybkości iteracji, jakości modeli oraz gotowych mechanizmach „structured output”, a retrieval chcesz oprzeć o managed vector DB z namespaces i hybrid search. citeturn13search1turn14search16turn11search3
W wariancie managed sensownie jest też wykorzystać Structured Outputs do wymuszenia formatu odpowiedzi (np. `answer` + `citations[]`), co jest elementem „kontroli” i audytu. OpenAI opisuje Structured Outputs jako mechanizm gwarantujący zgodność odpowiedzi z JSON Schema. citeturn13search1turn13search8
```python
# --- Managed stack: OpenAI embeddings + Pinecone + structured outputs + graph retrieval ---
from openai import OpenAI
from pinecone import Pinecone
from neo4j_graphrag import GraphRAG # example usage; adjust to actual package API
OPENAI_MODEL_EMB = "text-embedding-3-large"
OPENAI_MODEL_GEN = "gpt-5.4-mini" # example; choose by latency/cost needs
client = OpenAI()
pc = Pinecone(api_key="PINECONE_API_KEY")
index = pc.Index("kmrag")
def embed(texts):
resp = client.embeddings.create(model=OPENAI_MODEL_EMB, input=texts)
return [d.embedding for d in resp.data]
def upsert_to_pinecone(units, namespace):
vecs = embed([u["text"] for u in units])
index.upsert(
vectors=[
(u["unit_id"], vecs[i], {
"source_id": u["source_id"],
"version": u["version"],
"unit_type": u["unit_type"],
"page": u.get("page"),
"section_path": u.get("section_path"),
"acl": u.get("acl"),
})
for i, u in enumerate(units)
],
namespace=namespace, # multitenancy / workspace isolation
)
def retrieve_candidates(query, namespace, acl, top_k=30):
qvec = embed([query])[0]
res = index.query(
vector=qvec,
top_k=top_k,
include_metadata=True,
namespace=namespace,
filter={"acl": {"$eq": acl}},
)
return res["matches"]
# Optional: graph retrieval pattern via Text2Cypher (Neo4j GraphRAG package)
# The idea: use graph schema + question -> generated Cypher -> execute -> return records as extra grounded context.
gr = GraphRAG(neo4j_uri="neo4j+s://...", user="neo4j", password="...")
ANSWER_SCHEMA = {
"name": "kmrag_answer",
"schema": {
"type": "object",
"properties": {
"answer": {"type": "string"},
"citations": {
"type": "array",
"items": {
"type": "object",
"properties": {
"unit_id": {"type": "string"},
"source_id": {"type": "string"},
"quote": {"type": "string"}
},
"required": ["unit_id", "source_id"]
}
},
"confidence": {"type": "number", "minimum": 0, "maximum": 1}
},
"required": ["answer", "citations", "confidence"]
}
}
def answer(query, namespace, acl):
hits = retrieve_candidates(query, namespace, acl)
text_context = "\n\n".join(
f"[{m['id']}] ({m['metadata'].get('source_id')}) {load_unit_text(m['id'])}"
for m in hits[:8]
)
graph_context = gr.text2cypher_retrieve(query) # e.g. definitions, relationships
system = (
"Odpowiadasz wyłącznie na podstawie kontekstu i grafu.\n"
"Jeśli brakuje danych, powiedz wprost, czego nie wiesz.\n"
"Zwróć cytowania do unit_id/source_id."
)
resp = client.responses.create(
model=OPENAI_MODEL_GEN,
input=[
{"role": "system", "content": system},
{"role": "user", "content": f"Pytanie: {query}\n\nKontekst:\n{text_context}\n\nGraf:\n{graph_context}"}
],
text={
"format": {
"type": "json_schema",
"json_schema": {**ANSWER_SCHEMA, "strict": True}
}
}
)
return resp.output_text
def load_unit_text(unit_id):
# fetch canonical unit text from your storage
raise NotImplementedError
```
Źródła dla tego stosu: OpenAI opisuje nowe modele embeddingowe (`text-embedding-3-small/large`) i guide embeddings, a także Structured Outputs i evaluation best practices. citeturn13search2turn13search1turn13search3turn13search9
Pinecone opisuje hybrydę oraz filtrowanie po metadanych i multitenancy przez namespaces. citeturn11search3turn11search7turn14search16
Wzorzec Text2Cypher tłumaczenie pytania + schematu grafu na Cypher i wykonanie query jest opisany w materiałach Neo4j. citeturn10search2turn10search6turn10search10
## Kontrola jakości, audyt i monitoring
„Kontrola zamiast nadziei” warto potraktować jako trzy warstwy: (A) kontrola danych i retrieval, (B) kontrola generacji, (C) kontrola procesu (ewaluacja i monitoring).
### Metryki i ewaluacja
**Ewaluacja retrieval** (czyt. „czy przynosimy właściwy kontekst”)
- Recall@K / Precision@K / MRR / NDCG: standardowe metryki IR; w pracach o retrieval z grafami i/lub KG są one explicite używane do oceny retrieval (np. praca o RAG+KG dla customer service raportuje MRR/Recall@K/NDCG@K). citeturn10search1turn10search5
- Offline test set buduj iteracyjnie na podstawie prawdziwych porażek (failure traces) to jest zgodne z podejściem „evaluation flywheel” i continuous evaluation. citeturn13search35turn13search3
**Ewaluacja generation** (czyt. „czy odpowiedź jest ugruntowana w źródłach”)
- RAGAS: framework do „referencefree evaluation” RAG, mierzący różne wymiary retrieval i generation. citeturn4search1turn4search5
- TruLens: RAG triad context relevance, groundedness, answer relevance jako praktyczny zestaw ocen dla halucynacji. citeturn4search2turn4search6
**Progi jakości (przykład)**
OpenAI w evaluation best practices podaje przykładowe targety (np. context recall ≥ 0.85, context precision > 0.7) jako część praktyk ewaluacji i porównywania wersji. Traktuj to jako punkt startowy, nie prawo natury. citeturn13search3
### Checklist audytu KMRAG
**Dane i ingestion**
- Czy parser zachowuje strukturę (sekcje/tabele/numery stron) i czy masz testy parsera na „trudnych dokumentach” (tabele, wielokolumnowe layouty)? citeturn16search0turn16search10turn6view0
- Czy każda jednostka wiedzy ma stabilne `source_id`, `version`, lokalizację i politykę retencji/PII? citeturn7view1turn14search2
**Mapa Wiedzy**
- Czy graf ma jasno zdefiniowane typy węzłów i relacje (HAS_UNIT, DEFINES, EXCEPTION_OF, REFERENCES, NEXT), oraz czy masz reguły walidacji (np. brak cykli w „NEXT”, spójność sekcji)? citeturn2view1turn10search31
- Czy ekstrakcja encji/relacji jest mierzalna (precision/recall) i odporna na duplikaty/rozbieżności nazw? (w praktyce: canonicalization + entity resolution). Koncepcja grafu encji jako indeksu jest centralna w GraphRAG. citeturn0search1turn0search13
**Retrieval**
- Czy stosujesz prefilter po ACL/tenant (permission-aware retrieval), zanim cokolwiek trafi do prompta? (mechanizmy namespaces/tenants i DLS/RBAC istnieją w narzędziach retrieval). citeturn14search16turn14search0turn14search2
- Czy masz hybrydę dense+sparse tam, gdzie słowa kluczowe są krytyczne (regulacje, numery, tickery)? Pinecone i Weaviate opisują hybrydę jako fuzję wyników. citeturn11search3turn12search0
- Czy reranking działa na topN, a nie na setkach wyników (koszt/latencja), i czy jest mierzony? citeturn12search11turn12search19
**Generacja i grounding**
- Czy model ma jasną instrukcję „answer from sources” oraz czy odpowiedź wymusza strukturę (JSON schema) i cytowania? Structured Outputs jest mechanizmem wspierającym niezawodność formatu. citeturn13search1turn13search8
- Czy masz mechanizm „I dont know / insufficient evidence” zamiast konfabulacji (np. minimalny próg evidence coverage)? Podejścia typu CoVe/SelfRAG/CRAG pokazują, że pętle weryfikacji i korekty podnoszą factuality. citeturn8search3turn9search1turn9search2
**Bezpieczeństwo**
- Czy testujesz prompt injection na poziomie aplikacji, nie tylko promptu? OWASP opisuje prompt injection jako manipulację zachowaniem modelu przez wejście, a cheat sheet sugeruje praktyki obrony. citeturn4search3turn4search7turn4search13
- Czy masz kontrolę kosztu (rate limits, timeouts, budżety tokenów) to też „kontrola”, bo DoS na LLM to realny wektor ryzyka (OWASP LLM Top 10 zawiera kategorie dot. DoS i supply chain). citeturn4search13turn13search12
### KPI i monitoring w produkcji
Rekomendowany zestaw KPI (z podziałem na warstwy):
**Retrieval KPI**
- Context Recall@K / Context Precision@K (offline i online na próbie logów). citeturn13search3turn4search1
- % zapytań, w których retrieval zwraca „pustkę” lub tylko niskie score (sugeruje routing lub brak danych).
**Generation KPI**
- Faithfulness/groundedness (TruLens/RAGAS). citeturn4search1turn4search6
- Citation coverage: % zdań mających przypisane źródło, oraz „citation accuracy” (czy cytat faktycznie zawiera wspierający fragment). SelfRAG raportuje poprawę citation accuracy w długich generacjach jako jeden z efektów frameworku. citeturn9search1turn9search9
**Ops KPI**
- Latencja p95/p99 per etap (retrieval, rerank, LLM).
- Koszt per zapytanie (tokeny, liczba wywołań modeli) + alerty „unbounded consumption”. OpenAI publikuje production best practices i evaluation tooling jako część przejścia prototyp → produkcja. citeturn13search12turn13search3
**Narzędzia do obserwowalności**
- RAGAS opisuje łączenie ewaluacji z tracingiem/analizą (np. Phoenix). citeturn4search34
- TruLens ma integracje i dokumentację quickstart dla trace + feedback. citeturn4search2turn4search27
- Jeśli używasz OpenAI, masz też guidance dot. ewaluacji i ciągłego monitorowania regresji. citeturn13search3turn13search6
### Typowe failure modes KMRAG i mitigacje
**„Graf rośnie w chaos” (sprawl, duplikaty encji, zła kanonikalizacja).**
Mitigacja: wprowadź entity resolution, reguły normalizacji nazw, walidację schematu grafu i testy na podzbiorze; zacznij od grafu dokumentsekcjaunit, dopiero potem dodawaj encje/relacje automatyczne. GraphRAG wprost zaczyna od grafu encji jako indeksu, ale też pipelineu budowy i transformacji danych, co sugeruje konieczność procesu, nie jednorazowego prompta. citeturn3search0turn0search1
**„Retrieval jest poprawny semantycznie, ale zły merytorycznie” (conflicts).**
Mitigacja: hybryda dense+sparse + rerank + kontrola jakości źródeł + mechanizmy korekty (CRAG: evaluator jakości retrieval i akcje naprawcze). citeturn9search2turn11search3turn12search0
**„Źródła przenoszą instrukcje (prompt injection z dokumentów)”**
Mitigacja: separacja „instructions vs data”, sanitation, polityki „nie wykonuj instrukcji z kontekstu”, oraz przede wszystkim permission-aware retrieval (prefilter). OWASP opisuje prompt injection i praktyki obrony. citeturn4search3turn4search7turn14search2
**„Latency/cost eksploduje przez reranking i graf”**
Mitigacja: ogranicz N rerankowanych kandydatów; cache embeddingów; cache wyników graf expansion; prestreszczenia (GraphRAG community summaries) dla klas pytań globalnych. citeturn12search11turn0search1turn3search4
**„Zgodność i audyt”**
Mitigacja: loguj trace: query → (filtry ACL) → dokumenty → fragmenty → odpowiedź; uzupełnij o standardy zarządzania ryzykiem i bezpieczeństwem (entity["organization","NIST","us standards institute"] AI RMF; entity["organization","ISO","international standards body"]/IEC 27001; entity["organization","OWASP","security foundation"] LLM Top 10). Zapewnia to język kontroli dla audytu, nawet jeśli implementacje są różne. citeturn15search1turn15search2turn4search13turn15search3
### Źródła priorytetowe do dalszej pracy
Najbardziej „nośne” (loadbearing) źródła do wdrożenia KMRAG, w kolejności praktycznej użyteczności:
Źródła autora: definicja Mapy Wiedzy (graf + metadane + odniesienia) oraz argument o „R jako ryzyku” i potrzebie kontroli retrieval. citeturn2view1turn7view1
Podstawy RAG: praca Lewis et al. (RAG jako retrieval + generacja z nieparametrycznej pamięci) jako fundament terminologiczny. citeturn0search2turn0search5
GraphRAG: publikacja i repozytorium Microsoft (graf encji, społeczności, streszczenia) jako referencyjny wariant Mapy Wiedzy w postaci pipelineu. citeturn0search1turn3search0turn3search4turn3search20
KGRAG / hybrydy: prace o łączeniu KG i RAG (np. HybridRAG; RAG+KG w customer service) pokazują, że graf zmniejsza skutki segmentacji i poprawia retrieval. citeturn10search0turn10search1
Ewaluacja i kontrola jakości: RAGAS + TruLens + best practices ewaluacji jako praktyczny „system kontroli”. citeturn4search1turn4search2turn13search3
Bezpieczeństwo: OWASP prompt injection i LLM Top 10 jako checklisty dla warstwy „R” i integracji z danymi. citeturn4search3turn4search13turn4search7
@@ -0,0 +1,23 @@
# Quality and Evaluation Checklist
To move from "hope-based RAG" to "controlled RAG", implement these checks.
## 1. Retrieval Metrics (Search Quality)
- [ ] **Context Recall**: Are the units necessary to answer the question actually in the retrieved set?
- [ ] **Context Precision**: Is the retrieved set clean of irrelevant noise?
- [ ] **MRR (Mean Reciprocal Rank)**: Is the most relevant unit appearing at the top?
## 2. Generation Metrics (Answer Quality)
- [ ] **Faithfulness (Groundedness)**: Can every claim in the answer be traced to a retrieved Knowledge Unit?
- [ ] **Answer Relevance**: Does the answer actually address the user's intent?
- [ ] **Citation Accuracy**: Do the citations correctly point to the unit that supports the claim?
## 3. Governance & Safety
- [ ] **ACL Pre-Filtering**: Is there a hard check ensuring units from different tenants/roles are NEVER mixed?
- [ ] **PII Scanning**: Are units scanned for sensitive data during ingestion?
- [ ] **Hallucination Gating**: Is there a "Confidence Score" or "Low Evidence" flag to warn users?
## 4. Operational Health
- [ ] **Latency Monitoring**: Break down time spent in: Embedding -> Vector Search -> Graph Expansion -> Reranking -> LLM.
- [ ] **Token Efficiency**: Are we sending unnecessary fluff to the LLM, or is the context tightly packed with relevant units?
- [ ] **Index Drift**: Are we re-evaluating the "Golden Set" of questions when we update embedding models or chunking strategies?
@@ -0,0 +1,89 @@
# Implementation Patterns for KM-RAG in .NET
This guide outlines how to implement KM-RAG patterns using C# and .NET, building on existing infrastructures like EF Core and `Microsoft.Extensions.AI`.
## 1. Defining Knowledge Units
Represent units as strongly-typed entities to capture metadata and relationships.
```csharp
public enum KnowledgeUnitType { Section, Table, Definition, Step, Rule }
public class KnowledgeUnit
{
public string Id { get; set; } // Stable Hash(Source, Content, Version)
public string SourceId { get; set; }
public string Version { get; set; }
public KnowledgeUnitType Type { get; set; }
public string Content { get; set; }
public string MetadataJson { get; set; } // page, section_path, etc.
public Vector? Embedding { get; set; }
// Graph Relationships
public List<KnowledgeUnitLink> OutgoingLinks { get; set; } = new();
}
public class KnowledgeUnitLink
{
public string TargetUnitId { get; set; }
public string RelationType { get; set; } // "Next", "Defines", "References"
}
```
## 2. Multi-Stage Retrieval
Transition from simple `Take(Limit)` to a pipeline.
### Step A: Hybrid Candidate Generation
Combine `pgvector` cosine similarity with full-text search if available.
```csharp
var queryVector = await _embeddingGenerator.GenerateAsync(queryText);
var candidates = await _dbContext.KnowledgeUnits
.Where(u => u.TenantId == tenantId)
.OrderBy(u => u.Embedding.CosineDistance(queryVector))
.Take(20) // Get more candidates for reranking
.Select(u => new { u.Id, u.Content, u.Type })
.ToListAsync();
```
### Step B: Graph Expansion
Retrieve related units to provide full context.
```csharp
// Example: Get "Contextual Neighbors"
var expandedIds = await _dbContext.KnowledgeUnitLinks
.Where(l => candidateIds.Contains(l.SourceUnitId) && l.RelationType == "ParentSection")
.Select(l => l.TargetUnitId)
.Distinct()
.ToListAsync();
var contextUnits = await _dbContext.KnowledgeUnits
.Where(u => expandedIds.Contains(u.Id))
.ToListAsync();
```
## 3. Reranking and Citations
Use a model to score the relevance of the expanded context and ensure the LLM cites sources.
```csharp
// System Prompt for Grounded Generation
var systemPrompt = @"
You are a precision assistant. Answer ONLY using the provided Knowledge Units.
If the information is missing, state 'Information not found in knowledge map'.
Each answer segment MUST include a citation in format [UnitId].
";
// Response Structure (using System.Text.Json or Structured Outputs)
public class RagResponse
{
public string Answer { get; set; }
public List<Citation> Citations { get; set; }
}
```
## 4. Ingestion Workflow
Instead of `string.Split`, use structural parsers:
1. **Parse**: Extract sections/tables (e.g., using `Unstructured` or custom Logic).
2. **Normalize**: Assign stable IDs based on content hash + source metadata.
3. **Embed**: Generate vectors for the canonical text of each unit.
4. **Relate**: Build links (e.g., `prev` -> `curr` -> `next`).
@@ -0,0 +1,40 @@
---
name: nexus-architecture-standards
description: Guidelines and automated checks for maintaining Clean Architecture and SaaS standards in the NexusReader project.
tags: [Architecture, CleanArchitecture, .NET, MediatR, SaaS, MultiTenancy]
version: 1.0.0
---
# NexusReader Architecture Standards
This skill defines the architectural guardrails for the NexusReader project to ensure consistency, scalability, and security.
## Core Rules
### 1. Clean Architecture Layers
- **Domain**: Pure business logic, entities, and enums. Zero dependencies on other layers.
- **Application**: Use cases, MediatR handlers, and interfaces. Depends ONLY on Domain.
- **Infrastructure**: Implementation details (DB context, AI services, Auth). Depends on Application and Domain.
- **Web/Mobile**: Presentation layer. Depends on Application (and Infrastructure for DI setup).
> [!CAUTION]
> **Application MUST NOT depend on Infrastructure.** This is a common failure mode. Always use abstractions (interfaces) in Application and implement them in Infrastructure.
### 2. Multi-Tenancy (Tenant Isolation)
- Every entity related to user data MUST have a `TenantId` property.
- Every query MUST filter by `TenantId` to prevent data leakage.
- Default `TenantId` is "global" for shared resources.
### 3. Error Handling
- Use `FluentResults` (`Result<T>`) for all Application services and handlers.
- Avoid throwing exceptions for expected business failures; use `Result.Fail()`.
### 4. MediatR Patterns
- **Queries**: Read-only operations. Should return `Result<T>`. Use `AsNoTracking()` in EF Core.
- **Commands**: State-changing operations. Should return `Result` or `Result<T>`.
## Audit Scripts
- [ArchCheck.sh](scripts/arch_check.sh): A shell script to scan for illegal cross-layer imports.
## Reference Materials
- [Layer Dependency Matrix](artifacts/layer_matrix.md)
@@ -0,0 +1,15 @@
#!/bin/bash
# Simple script to check for Clean Architecture violations in NexusReader
APP_DIR="src/NexusReader.Application"
VIOLATIONS=$(grep -r "using NexusReader.Infrastructure" "$APP_DIR")
if [ -n "$VIOLATIONS" ]; then
echo "ERROR: Clean Architecture violations found in $APP_DIR:"
echo "$VIOLATIONS"
exit 1
else
echo "SUCCESS: No illegal Infrastructure dependencies found in Application layer."
exit 0
fi
@@ -8,6 +8,7 @@ description: Clean Architecture & CQRS implementation for .NET 10 with Blazor Hy
- `NexusReader.Domain`: Enterprise business rules (Entities, Value Objects, Domain Events).
- `NexusReader.Application`: Application business rules (Commands, Queries, DTOs, Mappings, Interfaces).
- `NexusReader.Infrastructure`: Data access, external services, and platform-specific implementations.
- **Persistence**: Use `IDbContextFactory<AppDbContext>` for long-running operations or when multiple units of work are needed in a single scope (especially in Blazor).
- `NexusReader.UI.Shared`: UI logic and Blazor components.
- `NexusReader.Maui` / `NexusReader.Web`: Platform host projects.
@@ -16,6 +17,7 @@ description: Clean Architecture & CQRS implementation for .NET 10 with Blazor Hy
- **Queries**: Read-only operations, return `Task<Result<T>>`.
- **Commands**: State-changing operations, return `Task<Result>` or `Task<Result<T>>`.
- **Handlers**: Located in `Application` layer, grouped by feature (e.g., `Queries/Reader/...`).
- **Client-Server Boundaries**: DO NOT execute MediatR handlers directly from WASM/MAUI clients if the handler relies on server-only infrastructure (e.g., `AppDbContext`, `IHubContext`). Instead, the client must trigger an API or SignalR endpoint, and the server dispatches the MediatR command.
- **Functional Error Handling:**
- Mandatory use of `FluentResults`.
@@ -35,4 +37,7 @@ description: Clean Architecture & CQRS implementation for .NET 10 with Blazor Hy
- **Cross-Platform Strategy:**
- Maximize code sharing in `NexusReader.UI.Shared`.
- Use `IPlatformService` (or similar abstractions) for native features, implemented in `Infrastructure.Mobile` or Maui projects.
- Use `IPlatformService` (or similar abstractions) for native features, implemented in `Infrastructure.Mobile` or Maui projects.
- **Code Validation (CRITICAL):**
- **Mandatory Build Verification**: After any code change, the agent MUST run `dotnet build` on the solution. The agent must verify that the build completes with `Exit code: 0` and without errors before concluding the task or requesting user feedback.
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---
name: nexus-code-review
description: Code Review Checklist and Standards for NexusReader SaaS
---
# NexusReader Code Review Standards
When conducting or receiving a code review for NexusReader, ensure the implementation adheres to the following critical architectural and performance standards:
## 1. Architectural Boundaries (CQRS & Blazor Hybrid)
- [ ] **Client vs. Server Execution**: MediatR handlers that depend on server-side infrastructure (`AppDbContext`, `IHubContext`, secrets) MUST NOT be executed directly from client environments (WASM/MAUI).
- [ ] **Dependency Leakage**: Ensure `NexusReader.Web.Client` (WASM) does not reference `NexusReader.Infrastructure` if the infrastructure requires `Microsoft.AspNetCore.App` framework references.
- [ ] **SignalR Bridges**: Client-initiated state changes should be sent via SignalR `SendAsync` to a server Hub, which then dispatches the internal `MediatR` command.
## 2. Event Handling & Debouncing
- [ ] **High-Frequency UI Events**: UI actions like scrolling, resizing, or typing must be debounced.
- [ ] **Trailing-Edge Debounce**: Use a `CancellationTokenSource` and `Task.Delay` to ensure the *last* event in a rapid sequence is executed. Do not use simple time-window drops, as they result in lost final states.
- [ ] **Async Void**: Ensure UI event handlers do not use `async void` unless they are top-level framework event bindings, and even then, they must catch all exceptions.
## 3. SignalR & Real-Time Contexts
- [ ] **Authentication Context**: Do not rely on `IHttpContextAccessor` inside MediatR handlers triggered by SignalR Hubs. Use `Context.UserIdentifier` directly from the Hub and pass it as a command parameter.
- [ ] **Connection State**: Always check `HubConnection.State == HubConnectionState.Connected` before attempting to send messages from the client.
- [ ] **Targeted Broadcasting**: Use SignalR `Groups` (e.g., `$"User_{userId}"`) to broadcast updates only to the devices owned by the relevant user.
## 4. Performance & Scalability
- [ ] **Database Write Contention**: High-frequency telemetry (like reading progress) should ideally be batched or cached in-memory before writing to SQL, unless real-time persistence is strictly required.
- [ ] **Memory Leaks**: Ensure all components and services that subscribe to events (e.g., `OnProgressReceived`, JS Observers) implement `IDisposable` or `IAsyncDisposable` and properly unsubscribe.
## 5. Standard Nexus Guidelines
- [ ] **Result Pattern**: Ensure all application logic returns `Result` or `Result<T>` via FluentResults. No exceptions for control flow.
- [ ] **AI Prompts**: Ensure changes to AI logic do not bypass the `PromptRegistry` or token estimation limits defined in `AiSettings`.
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# Definition of Done (DoD)
1. **Architecture Compliance:** Feature follows CQRS flow. Logic is in Handlers. Result is wrapped in `Result<T>` from FluentResult.
2. **Modularization:** Code is in `/src`, tests in `/tests`. Module-specific logic is isolated.
3. **UI/UX Integrity:** - "Vertical Flow Check" passed (Assistant is part of the document stream, not an absolute pop-up).
- No "Layout Shift" during AI content streaming.
- Safe-area-insets respected for iOS/Android notches.
4. **Code Quality:** C# 14 syntax used (Primary Constructors, etc.). Scoped CSS (.razor.css) implemented.
5. **D3.js Performance:** JS Modules correctly disposed using `IAsyncDisposable`.
6. **Persistence:** State survives manual page refresh (Local/Session Storage integration).
7. **Mapping:** All entity-to-DTO conversions must use Mapster.
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# Agent Personas
## NexusArchitect
- **Role:** Lead Architect & Creative Technologist (.NET 10 & Blazor)
- **Persona:** Professional, precise, Senior Full-Stack Engineer focused on performance and "invisible UI".
- **Architecture Role:** Lead Clean Architecture Specialist.
- **Skills:** [nexus-clean-architecture, nexus-ui-engine, nexus-graph-d3, blazor-state-performance, blazor-hybrid-bridge, semantic-kernel-orchestrator, nexus-identity-saas, dotnet-async-void]
- **Technical Constraints:**
- **Directory Structure:** Strict separation: `/src` (app code) and `/tests` (testing code) at solution root level.
- **Patterns:** Mandatory CQRS via `MediatR` (LuckyPennySoftware implementation). No business logic in UI components.
- **Async:** Strict zero-tolerance for `async void`. All async operations must return `Task` or `ValueTask`. Event handlers must use `Func<Task>` or async-compatible patterns.
- **Error Handling:** All handlers must return `Result<T>` via `FluentResult`.
- **Mapping:** Use `Mapster` exclusively. Zero-tolerance for AutoMapper.
- **Platform:** Target .NET 10 with Native AOT compatibility in mind for mobile performance.
- **Verification:** Follow "Verification-led development" — the agent must plan the test before writing the feature code.
- **UI Framework:** Use Blazor Component Model. NEVER generate raw HTML/CSS; always use isolated Razor Components (.razor + .razor.css).
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---
type: agent-definitions
version: 1.0
---
# Agent Personas
## 👤 NexusArchitect
**Role:** Lead Architect & Creative Technologist (.NET 10 & Blazor)
**Persona:** Professional, precise, Senior Full-Stack Engineer focused on performance and "invisible UI".
---
## 🏗️ Architecture Philosophy
- **Clean Architecture:** Strict separation of concerns. `Domain` -> `Application` <- `Infrastructure`.
- **CQRS Pattern:** Mandatory use of `MediatR`. Logic belongs in handlers, not UI components.
- **Result Pattern:** Zero exceptions for flow control. All handlers return `Result<T>` via `FluentResult`.
- **Mapping:** Exclusive use of `Mapster`. (Zero tolerance for AutoMapper).
---
## 🛠️ Technical Constraints
>
> [!IMPORTANT]
> **Zero Tolerance for `async void`**
> All async operations must return `Task` or `ValueTask`. Event handlers must use `Func<Task>` or async-compatible patterns.
- **Platform:** Target .NET 10 with **Native AOT** compatibility. Optimize for mobile performance.
- **UI Framework:** Blazor Component Model. No raw HTML/CSS; use isolated Razor Components (.razor + .razor.css).
- **Directory Structure:** `/src` for app code and `/tests` for testing code at solution root level.
---
## 🧪 Development Workflow
1. **Verification-Led:** Plan and define tests/verification steps *before* writing feature code.
2. **Step-by-Step Execution:** Break complex tasks into manageable, verifiable chunks.
3. **Layer Integrity:** Always check for illegal cross-layer dependencies (e.g., Application depending on Infrastructure).
4. **Mandatory Build Gate:** After **every** code change, run `dotnet build` on the full solution. The agent MUST NOT proceed or report completion if there are any `error CS*` compiler errors. All build errors must be resolved before moving to the next step.
> [!IMPORTANT]
> **Build command:** `dotnet build NexusReader.slnx --no-restore`
> Run from the solution root `/home/mjasin/Projekty/ejajBook`. Build warnings are acceptable; errors are not.
> [!IMPORTANT]
> **Git Workflow & Integration**
> All tasks originating from the repository must be performed on a separate branch. To connect to the Git repository, use the `gitea-ovh` MCP server.
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# 🔍 NexusReader Code Review Backlog
## 🔴 CRITICAL — Fix Before Next Release
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Removed `AddMediatR` from `AddApplication()` and `AddInfrastructure()`. Unified registration in Host (`Program.cs`, `MauiProgram.cs`). Added `IInfrastructureMarker` and a startup validation check in `Web.New` that throws `InvalidOperationException` if `AddInfrastructure` is missing.
- **DoD:** Application fails fast with a clear error if `AddInfrastructure()` is omitted.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Added `VerifyGroundednessAsync` to `IKnowledgeService` and implemented it in `KnowledgeService` (Infrastructure). Updated `VerifyGroundednessCommandHandler` in Application to inject `IKnowledgeService` instead of `IChatClient`.
- **DoD:** No `IChatClient` or `IEmbeddingGenerator` references remain in `NexusReader.Application`.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Threaded `tenantId` through all `IKnowledgeService` methods and `ProcessKnowledgeUnitsAsync`. Scoped `SemanticKnowledgeCache` and `KnowledgeUnit` lookups/writes to the provided `tenantId`. Updated API endpoints in `Program.cs` and `WasmKnowledgeService` to pass the authenticated user's `TenantId`.
- **DoD:** No hardcoded `"global"` TenantId in write paths. Extracted units are always scoped to the caller's tenant.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Changed `NexusUser.TenantId` from `Guid` to `string`. All entities now use `string` for `TenantId`, allowing the use of `"global"` as a sentinel value.
- **DoD:** All entities use the same `TenantId` type. All query filters are consistent.
---
## 🟠 MAJOR — High Priority Fixes
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Added `File.Exists` check and granular `try-catch` around `EpubReader.ReadBookAsync` to prevent unhandled exceptions and provide descriptive error messages.
- **DoD:** Corrupted or missing files return `Result.Fail` instead of crashing.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Verified `IDbContextFactory<AppDbContext>` is correctly registered via `AddDbContextFactory` in `Infrastructure/DependencyInjection.cs`.
- **DoD:** Webhook and profile endpoints successfully resolve the factory.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Implemented `Coordinator.Clear()` (which calls `KnowledgeGraphService.Clear()`) in `ReaderCanvas.razor`'s `OnInitialized`.
- **DoD:** Stale graph data is cleared upon component initialization.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Created `UserProfileDto` to exclude sensitive internal IDs like `TenantId` and DB GUIDs. Updated `/identity/profile` endpoint to project into this DTO using `.Select()`.
- **DoD:** Internal IDs are no longer exposed in the profile API.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Added `HasIndex(x => x.TenantId)` to `NexusUser`, `Ebook`, and `QuizResult` in `AppDbContext`. `KnowledgeUnit` and `SemanticKnowledgeCache` already had them.
- **DoD:** Tenant-scoped queries are optimized via DB indexes.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Refactored `KnowledgeService.ProcessKnowledgeUnitsAsync` to pre-fetch all existing unit IDs in a single batch query, eliminating the N+1 `FindAsync` and `AnyAsync` calls.
- **DoD:** Batch processing performance is significantly improved.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Added `TenantId` property to `Ebook` entity with mandatory validation and index. Updated `AppDbContext` configuration.
- **DoD:** Ebooks are now isolated at the database level.
---
- **Status:** ✅ Resolved (2026-05-03)
- **Implementation:** Added `TenantId` property to `QuizResult` entity with mandatory validation and index.
- **DoD:** Quiz results are now isolated at the database level.
---
## 🟡 MINOR — Technical Debt & UX
### [MN-01] Missing Logging in `KnowledgeCoordinator`
- **Action:** Add `ILogger<KnowledgeCoordinator>` and log successful/failed extraction steps.
### [MN-02] Hardcoded "Gemini-1.5-Flash" in Domain
- **File:** `Domain/Entities/SemanticKnowledgeCache.cs:20`
- **Action:** Move the default model ID to a constant in `AiSettings`.
### [MN-03] UI: Shimmer Effect Lack Animation
- **File:** `UI.Shared/Components/Molecules/GroundednessBadge.razor`
- **Action:** Add `@keyframes` for the shimmer effect in CSS.
### [MN-04] Identity: Google Callback Lack Error Handling
- **File:** `Web.New/Program.cs:340`
- **Action:** Better UI feedback when `ExternalLoginInfo` is null.
### [MN-05] Tokenizer Initialization is Expensive
- **File:** `Infrastructure/Services/KnowledgeService.cs:43`
- **Action:** Make `_tokenizer` static or Singleton to avoid recreating it per request.
### [MN-06] Mapster: Global Configuration Check
- **Action:** Ensure `TypeAdapterConfig.GlobalSettings.Scan(...)` is only called once.
### [MN-07] SignalR: Missing Reconnection Logic
- **Action:** Implement `hubConnection.OnReconnected` in `SyncService.cs`.
### [MN-10] Performance: Large EPUB Parsing
- **Action:** Implement streaming extraction for EPUBs over 10MB.
---
## 🧪 TESTING — Coverage Gaps
### [TEST-01] Integration Tests for KM-RAG Retrieval
- **Action:** Create `tests/NexusReader.IntegrationTests`.
- **Scenario:** Ingest a document, then verify that `GetRelevantContext` returns the correct snippets with tenant isolation active.
---
## 📊 Summary Table
| Severity | Count | Status |
|---|---|---|
| 🔴 Critical | 4 | 4 resolved |
| 🟠 Major | 8 | 8 resolved |
| 🟡 Minor | 8 | Unresolved |
| 🧪 Tests | 1 | Unresolved |
| **Total** | **21** | **12 resolved** |
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@@ -1,6 +1,6 @@
services:
db:
image: postgres:17-alpine
image: pgvector/pgvector:pg17
container_name: nexus-db
environment:
POSTGRES_USER: nexus_user
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@@ -0,0 +1,44 @@
using Microsoft.Extensions.DependencyInjection;
using Microsoft.EntityFrameworkCore;
using NexusReader.Infrastructure.Persistence;
using Microsoft.Extensions.Configuration;
using NexusReader.Domain.Entities;
using System;
using System.Linq;
using System.Threading.Tasks;
var configuration = new ConfigurationBuilder()
.AddJsonFile("src/NexusReader.Web.New/appsettings.json")
.Build();
var services = new ServiceCollection();
var pgConnectionString = configuration.GetConnectionString("PostgresConnection");
if (!string.IsNullOrEmpty(pgConnectionString))
{
services.AddDbContext<AppDbContext>(options => options.UseNpgsql(pgConnectionString));
}
else
{
services.AddDbContext<AppDbContext>(options => options.UseSqlite(configuration.GetConnectionString("SqliteConnection")));
}
var serviceProvider = services.BuildServiceProvider();
using var scope = serviceProvider.CreateScope();
var dbContext = scope.ServiceProvider.GetRequiredService<AppDbContext>();
try
{
var user = await dbContext.Users.FirstOrDefaultAsync(u => u.Email == "admin@nexus.com");
if (user == null)
{
Console.WriteLine("User admin@nexus.com NOT FOUND in database.");
}
else
{
Console.WriteLine($"User found: {user.Email}, Id: {user.Id}, EmailConfirmed: {user.EmailConfirmed}");
}
}
catch (Exception ex)
{
Console.WriteLine($"Error accessing database: {ex.Message}");
}
@@ -0,0 +1,15 @@
using Microsoft.EntityFrameworkCore;
using NexusReader.Domain.Entities;
namespace NexusReader.Application.Abstractions.Persistence;
public interface IApplicationDbContext
{
DbSet<SemanticKnowledgeCache> SemanticKnowledgeCache { get; }
DbSet<KnowledgeUnit> KnowledgeUnits { get; }
DbSet<KnowledgeUnitLink> KnowledgeUnitLinks { get; }
DbSet<Ebook> Ebooks { get; }
DbSet<QuizResult> QuizResults { get; }
Task<int> SaveChangesAsync(CancellationToken cancellationToken = default);
}
@@ -1,9 +0,0 @@
using FluentResults;
using NexusReader.Application.Queries.Quiz;
namespace NexusReader.Application.Abstractions.Services;
public interface IAiGenerateQuizService
{
Task<Result<QuizDto>> GenerateQuizAsync(string contextBlockId, CancellationToken cancellationToken = default);
}
@@ -5,8 +5,13 @@ namespace NexusReader.Application.Abstractions.Services;
public interface IKnowledgeService
{
Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, string tenantId, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, string tenantId, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetKnowledgeMapAsync(string text, string tenantId, CancellationToken cancellationToken = default);
Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, string tenantId, CancellationToken cancellationToken = default);
Task<Result<List<RelevantContext>>> GetRelevantContextAsync(string query, string tenantId, CancellationToken cancellationToken = default);
Task<Result<GroundednessResult>> VerifyGroundednessAsync(string answer, string context, string tenantId, CancellationToken cancellationToken = default);
Task<Result> ClearCacheAsync(CancellationToken cancellationToken = default);
}
public record GroundednessResult(float Score, string Rationale, bool IsGrounded);
@@ -0,0 +1,22 @@
using FluentResults;
using MediatR;
using NexusReader.Application.Abstractions.Services;
namespace NexusReader.Application.Commands.AI;
public record VerifyGroundednessCommand(string Answer, string Context, string TenantId) : IRequest<Result<GroundednessResult>>;
public class VerifyGroundednessCommandHandler : IRequestHandler<VerifyGroundednessCommand, Result<GroundednessResult>>
{
private readonly IKnowledgeService _knowledgeService;
public VerifyGroundednessCommandHandler(IKnowledgeService knowledgeService)
{
_knowledgeService = knowledgeService;
}
public async Task<Result<GroundednessResult>> Handle(VerifyGroundednessCommand request, CancellationToken cancellationToken)
{
return await _knowledgeService.VerifyGroundednessAsync(request.Answer, request.Context, request.TenantId, cancellationToken);
}
}
@@ -0,0 +1,6 @@
using FluentResults;
using MediatR;
namespace NexusReader.Application.Commands.Sync;
public record UpdateReadingProgressCommand(string PageId, string UserId) : IRequest<Result>;
@@ -13,10 +13,15 @@ public record QuizQuestion(
[property: JsonPropertyName("correct_index")] int CorrectIndex
);
public record KnowledgeUnitDto(string Id, string Type, string Content, Dictionary<string, object>? Metadata = null);
public record KnowledgeLinkDto(string Source, string Target, string Relation);
public record KnowledgePacket
{
[JsonPropertyName("concepts")] public List<KeyConcept> Concepts { get; init; } = new();
[JsonPropertyName("quizzes")] public List<QuizQuestion> Quizzes { get; init; } = new();
[JsonPropertyName("units")] public List<KnowledgeUnitDto> Units { get; init; } = new();
[JsonPropertyName("links")] public List<KnowledgeLinkDto> Links { get; init; } = new();
[JsonPropertyName("graph")] public NexusReader.Application.Queries.Graph.GraphDataDto? Graph { get; init; }
[JsonPropertyName("summary")] public string? Summary { get; init; }
}
@@ -0,0 +1,8 @@
namespace NexusReader.Application.DTOs.AI;
public class RelevantContext
{
public string Text { get; set; } = string.Empty;
public string SourceId { get; set; } = string.Empty; // ContentHash or EbookTitle
public double Confidence { get; set; }
}
@@ -0,0 +1,11 @@
namespace NexusReader.Application.DTOs.AI;
public class SemanticSearchResultDto
{
public string ContentHash { get; set; } = string.Empty;
public string Snippet { get; set; } = string.Empty;
public string? UnitType { get; set; }
public float RelevanceScore { get; set; }
public string? SourceBookTitle { get; set; }
public Dictionary<string, object>? Metadata { get; set; } // Bonus context
}
@@ -0,0 +1,9 @@
namespace NexusReader.Application.DTOs.User;
public record SubscriptionPlanDto
{
public int Id { get; init; }
public string Name { get; init; } = string.Empty;
public int AITokenLimit { get; init; }
public decimal MonthlyPrice { get; init; }
}
@@ -0,0 +1,25 @@
namespace NexusReader.Application.DTOs.User;
public record UserProfileDto
{
public string Email { get; init; } = string.Empty;
public int AITokensUsed { get; init; }
/// <summary>
/// Relational data for the current subscription plan.
/// </summary>
public SubscriptionPlanDto Plan { get; init; } = new();
public int AverageQuizScore { get; init; }
/// <summary>
/// Summary of the last read book.
/// </summary>
public LastReadBookDto? LastReadBook { get; init; }
}
public record LastReadBookDto
{
public Guid Id { get; init; }
public string Title { get; init; } = string.Empty;
}
@@ -9,11 +9,8 @@ public static class DependencyInjection
{
services.AddMapsterConfiguration();
services.AddMediatR(config =>
{
config.RegisterServicesFromAssembly(typeof(DependencyInjection).Assembly);
});
return services;
}
public static System.Reflection.Assembly Assembly => typeof(DependencyInjection).Assembly;
}
@@ -10,7 +10,10 @@
<PackageReference Include="Mapster.DependencyInjection" Version="10.0.7" />
<PackageReference Include="MediatR" Version="12.1.1" />
<PackageReference Include="Microsoft.AspNetCore.Authorization" Version="10.0.7" />
<PackageReference Include="Microsoft.EntityFrameworkCore" Version="10.0.7" />
<PackageReference Include="Microsoft.Extensions.AI" Version="10.5.0" />
<PackageReference Include="Microsoft.Extensions.Identity.Core" Version="10.0.7" />
<PackageReference Include="Pgvector.EntityFrameworkCore" Version="0.2.1" />
</ItemGroup>
<PropertyGroup>
@@ -2,4 +2,7 @@ using NexusReader.Application.Abstractions.Messaging;
namespace NexusReader.Application.Queries.Graph;
public record GetKnowledgeGraphQuery : IQuery<GraphDataDto>;
/// <param name="Text">Chapter or page content to extract the graph from.</param>
/// <param name="TenantId">Tenant scope for knowledge extraction and caching.</param>
public record GetKnowledgeGraphQuery(string Text, string TenantId) : IQuery<GraphDataDto>;
@@ -1,15 +1,30 @@
using FluentResults;
using NexusReader.Application.Abstractions.Messaging;
using NexusReader.Application.Abstractions.Services;
namespace NexusReader.Application.Queries.Graph;
internal sealed class GetKnowledgeGraphQueryHandler : IQueryHandler<GetKnowledgeGraphQuery, GraphDataDto>
{
public Task<Result<GraphDataDto>> Handle(GetKnowledgeGraphQuery request, CancellationToken cancellationToken)
{
var nodes = new List<GraphNodeDto>();
var links = new List<GraphLinkDto>();
private readonly IKnowledgeService _knowledgeService;
return Task.FromResult(Result.Ok(new GraphDataDto { Nodes = nodes, Links = links }));
public GetKnowledgeGraphQueryHandler(IKnowledgeService knowledgeService)
{
_knowledgeService = knowledgeService;
}
public async Task<Result<GraphDataDto>> Handle(GetKnowledgeGraphQuery request, CancellationToken cancellationToken)
{
if (string.IsNullOrWhiteSpace(request.Text))
return Result.Ok(new GraphDataDto());
var result = await _knowledgeService.GetGraphDataAsync(request.Text, request.TenantId, cancellationToken);
if (result.IsFailed)
return Result.Fail<GraphDataDto>(result.Errors);
var graph = result.Value.Graph;
return graph is null ? Result.Ok(new GraphDataDto()) : Result.Ok(graph);
}
}
@@ -1,7 +1,7 @@
namespace NexusReader.Application.Queries.Graph;
public record GraphNodeDto(string Id, string Label, string Group);
public record GraphLinkDto(string Source, string Target, int Value);
public record GraphNodeDto(string Id, string Label, string Group, string? Type = null);
public record GraphLinkDto(string Source, string Target, string RelationType, int Value = 1);
public record GraphDataDto
{
public List<GraphNodeDto> Nodes { get; init; } = new();
@@ -0,0 +1,116 @@
using FluentResults;
using Mapster;
using MediatR;
using Microsoft.EntityFrameworkCore;
using Microsoft.Extensions.AI;
using NexusReader.Application.DTOs.AI;
using NexusReader.Application.Abstractions.Persistence;
using Pgvector;
using Pgvector.EntityFrameworkCore;
using System.Text.Json;
namespace NexusReader.Application.Queries.Library;
public record SearchLibrarySemanticallyQuery(string QueryText, string TenantId, int Limit = 5)
: IRequest<Result<List<SemanticSearchResultDto>>>;
public class SearchLibrarySemanticallyQueryHandler : IRequestHandler<SearchLibrarySemanticallyQuery, Result<List<SemanticSearchResultDto>>>
{
private readonly IApplicationDbContext _dbContext;
private readonly IEmbeddingGenerator<string, Embedding<float>> _embeddingGenerator;
public SearchLibrarySemanticallyQueryHandler(
IApplicationDbContext dbContext,
IEmbeddingGenerator<string, Embedding<float>> embeddingGenerator)
{
_dbContext = dbContext;
_embeddingGenerator = embeddingGenerator;
}
public async Task<Result<List<SemanticSearchResultDto>>> Handle(SearchLibrarySemanticallyQuery request, CancellationToken cancellationToken)
{
if (string.IsNullOrWhiteSpace(request.QueryText))
{
return Result.Fail("Query text cannot be empty.");
}
try
{
// 1. Generate embedding for user query
var embeddingResponse = await _embeddingGenerator.GenerateAsync(new[] { request.QueryText }, cancellationToken: cancellationToken);
var queryVector = new Vector(embeddingResponse.First().Vector.ToArray());
// 2. Perform Cosine Similarity Search on Knowledge Units
var candidates = await _dbContext.KnowledgeUnits
.AsNoTracking()
.Where(x => (x.TenantId == request.TenantId || x.TenantId == "global") && x.Vector != null)
.OrderBy(x => x.Vector!.CosineDistance(queryVector))
.Take(request.Limit)
.ToListAsync(cancellationToken);
if (!candidates.Any())
{
// Fallback to legacy cache if no granular units found
var legacyResults = await _dbContext.SemanticKnowledgeCache
.AsNoTracking()
.Where(x => x.TenantId == request.TenantId && x.Vector != null)
.OrderBy(x => x.Vector!.CosineDistance(queryVector))
.Take(request.Limit)
.ToListAsync(cancellationToken);
return Result.Ok(legacyResults.Select(r => new SemanticSearchResultDto
{
ContentHash = r.ContentHash,
Snippet = r.OriginalText,
RelevanceScore = (float)(1 - r.Vector!.CosineDistance(queryVector))
}).ToList());
}
// 3. Graph Expansion: Pull related units (e.g. Definitions, Next steps)
var candidateIds = candidates.Select(c => c.Id).ToList();
var links = await _dbContext.KnowledgeUnitLinks
.AsNoTracking()
.Where(l => candidateIds.Contains(l.SourceUnitId) && (l.RelationType == "Defines" || l.RelationType == "Next"))
.ToListAsync(cancellationToken);
var relatedIds = links.Select(l => l.TargetUnitId).Distinct().ToList();
var relatedUnits = await _dbContext.KnowledgeUnits
.AsNoTracking()
.Where(u => relatedIds.Contains(u.Id))
.ToDictionaryAsync(u => u.Id, cancellationToken);
// 4. Mapping with Context Enrichment
var dtos = candidates.Select(c =>
{
var dto = new SemanticSearchResultDto
{
ContentHash = c.Id,
Snippet = c.Content,
UnitType = c.Type.ToString(),
RelevanceScore = (float)(1 - c.Vector!.CosineDistance(queryVector)),
Metadata = string.IsNullOrEmpty(c.MetadataJson)
? null
: JsonSerializer.Deserialize<Dictionary<string, object>>(c.MetadataJson)
};
// Enrich snippet with definitions if present
var unitLinks = links.Where(l => l.SourceUnitId == c.Id && l.RelationType == "Defines").ToList();
if (unitLinks.Any())
{
var definitions = unitLinks
.Where(l => relatedUnits.ContainsKey(l.TargetUnitId))
.Select(l => relatedUnits[l.TargetUnitId].Content);
dto.Snippet = $"[Context: {string.Join("; ", definitions)}]\n{dto.Snippet}";
}
return dto;
}).ToList();
return Result.Ok(dtos);
}
catch (Exception ex)
{
return Result.Fail(new Error("Failed to perform semantic search").CausedBy(ex));
}
}
}
@@ -1,5 +0,0 @@
using NexusReader.Application.Abstractions.Messaging;
namespace NexusReader.Application.Queries.Quiz;
public record GetQuizQuestionsQuery(string ContextBlockId) : IQuery<QuizDto>;
@@ -1,20 +0,0 @@
using FluentResults;
using NexusReader.Application.Abstractions.Messaging;
using NexusReader.Application.Abstractions.Services;
namespace NexusReader.Application.Queries.Quiz;
internal sealed class GetQuizQuestionsQueryHandler : IQueryHandler<GetQuizQuestionsQuery, QuizDto>
{
private readonly IAiGenerateQuizService _aiService;
public GetQuizQuestionsQueryHandler(IAiGenerateQuizService aiService)
{
_aiService = aiService;
}
public async Task<Result<QuizDto>> Handle(GetQuizQuestionsQuery request, CancellationToken cancellationToken)
{
return await _aiService.GenerateQuizAsync(request.ContextBlockId, cancellationToken);
}
}
@@ -31,7 +31,7 @@ public class ProUserHandler : AuthorizationHandler<ProUserRequirement>
}
// Rule 1: Explicit Pro plan
if (user.CurrentPlan == "Pro")
if (user.SubscriptionPlanId == SubscriptionPlan.ProId)
{
context.Succeed(requirement);
return;
+4
View File
@@ -23,6 +23,10 @@ public class Ebook
public string? CoverUrl { get; set; }
[Required]
[MaxLength(128)]
public string TenantId { get; set; } = "global";
public DateTime AddedDate { get; set; } = DateTime.UtcNow;
public DateTime? LastReadDate { get; set; }
@@ -0,0 +1,41 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
using NexusReader.Domain.Enums;
using Pgvector;
namespace NexusReader.Domain.Entities;
public class KnowledgeUnit
{
[Key]
[MaxLength(128)]
public string Id { get; set; } = string.Empty; // Hash(Source + Content + Version)
[Required]
[MaxLength(128)]
public string SourceId { get; set; } = string.Empty;
[Required]
[MaxLength(50)]
public string Version { get; set; } = "1.0";
[Required]
public KnowledgeUnitType Type { get; set; }
[Required]
public string Content { get; set; } = string.Empty;
public string? MetadataJson { get; set; } // e.g. { "page": 1, "path": "Chapter 1 > Intro" }
[Required]
[MaxLength(128)]
public string TenantId { get; set; } = string.Empty;
public Vector? Vector { get; set; }
public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
// Relationships
public ICollection<KnowledgeUnitLink> OutgoingLinks { get; set; } = new List<KnowledgeUnitLink>();
public ICollection<KnowledgeUnitLink> IncomingLinks { get; set; } = new List<KnowledgeUnitLink>();
}
@@ -0,0 +1,28 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
namespace NexusReader.Domain.Entities;
public class KnowledgeUnitLink
{
[Key]
public int Id { get; set; }
[Required]
[MaxLength(128)]
public string SourceUnitId { get; set; } = string.Empty;
[Required]
[MaxLength(128)]
public string TargetUnitId { get; set; } = string.Empty;
[Required]
[MaxLength(50)]
public string RelationType { get; set; } = "References"; // e.g., "Next", "Defines", "Contains"
[ForeignKey(nameof(SourceUnitId))]
public KnowledgeUnit SourceUnit { get; set; } = null!;
[ForeignKey(nameof(TargetUnitId))]
public KnowledgeUnit TargetUnit { get; set; } = null!;
}
+38 -9
View File
@@ -1,31 +1,49 @@
using Microsoft.AspNetCore.Identity;
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
namespace NexusReader.Domain.Entities;
/// <summary>
/// Extended Identity user for the Nexus AI E-Reader SaaS platform.
/// </summary>
public class NexusUser : IdentityUser
{
/// <summary>
/// Total number of AI tokens allowed for the current billing period.
/// User's display name or full name.
/// </summary>
[MaxLength(100)]
public string? DisplayName { get; set; }
/// <summary>
/// Total AI tokens available for the user (depends on subscription).
/// </summary>
public int AITokenLimit { get; set; }
/// <summary>
/// Number of AI tokens consumed in the current billing period.
/// AI tokens consumed by the user in the current billing period.
/// </summary>
public int AITokensUsed { get; set; }
/// <summary>
/// Unique identifier for the tenant (SaaS multi-tenancy support).
/// Date when the user last performed an AI-related action.
/// </summary>
public Guid TenantId { get; set; }
public DateTime? LastAiActionDate { get; set; }
/// <summary>
/// Current subscription plan (e.g., "Free", "Pro", "Enterprise").
/// Multi-tenant identifier.
/// </summary>
public string CurrentPlan { get; set; } = "Free";
[Required]
[MaxLength(128)]
public string TenantId { get; set; } = "global";
/// <summary>
/// Foreign key for the current subscription plan.
/// </summary>
[Required]
public int SubscriptionPlanId { get; set; }
/// <summary>
/// Navigation property for the current subscription plan.
/// </summary>
public SubscriptionPlan? SubscriptionPlan { get; set; }
/// <summary>
/// Collection of e-books owned by the user.
@@ -36,4 +54,15 @@ public class NexusUser : IdentityUser
/// Collection of quiz results completed by the user.
/// </summary>
public ICollection<QuizResult> QuizResults { get; set; } = new List<QuizResult>();
/// <summary>
/// ID of the last page read by the user.
/// </summary>
[MaxLength(255)]
public string? LastReadPageId { get; set; }
/// <summary>
/// Last read timestamp.
/// </summary>
public DateTime? LastReadAt { get; set; }
}
@@ -17,6 +17,10 @@ public class QuizResult
[ForeignKey(nameof(UserId))]
public NexusUser? User { get; set; }
[Required]
[MaxLength(128)]
public string TenantId { get; set; } = "global";
[Required]
public string Topic { get; set; } = string.Empty;
@@ -1,4 +1,6 @@
using System.ComponentModel.DataAnnotations;
using System.ComponentModel.DataAnnotations.Schema;
using Pgvector;
namespace NexusReader.Domain.Entities;
@@ -11,6 +13,9 @@ public class SemanticKnowledgeCache
[Required]
public string JsonData { get; set; } = string.Empty;
[Required]
public string OriginalText { get; set; } = string.Empty;
[Required]
[MaxLength(50)]
public string ModelId { get; set; } = "gemini-1.5-flash";
@@ -19,5 +24,11 @@ public class SemanticKnowledgeCache
[MaxLength(10)]
public string PromptVersion { get; set; } = "1.0";
[Required]
[MaxLength(128)]
public string TenantId { get; set; } = string.Empty;
public Vector? Vector { get; set; }
public DateTime CreatedAt { get; set; } = DateTime.UtcNow;
}
@@ -0,0 +1,30 @@
using System.ComponentModel.DataAnnotations;
namespace NexusReader.Domain.Entities;
public class SubscriptionPlan
{
public const string FreeName = "Free";
public const string BasicName = "Basic";
public const string ProName = "Pro";
public const string EnterpriseName = "Enterprise";
public const int FreeId = 1;
public const int BasicId = 2;
public const int ProId = 3;
public const int EnterpriseId = 4;
[Key]
public int Id { get; set; }
[Required]
[MaxLength(50)]
public string PlanName { get; set; } = string.Empty;
public int AITokenLimit { get; set; }
public decimal MonthlyPrice { get; set; }
[MaxLength(50)]
public string StripeProductId { get; set; } = string.Empty;
}
@@ -0,0 +1,12 @@
namespace NexusReader.Domain.Enums;
public enum KnowledgeUnitType
{
Section,
Table,
Definition,
ProcedureStep,
PolicyRule,
KeyConcept,
Snippet
}
@@ -9,6 +9,7 @@
<ItemGroup>
<PackageReference Include="Microsoft.Extensions.Identity.Stores" Version="10.0.7" />
<PackageReference Include="Pgvector" Version="0.3.2" />
</ItemGroup>
</Project>
@@ -6,7 +6,13 @@ public class AiSettings
public string ApiKey { get; set; } = string.Empty;
public string Model { get; set; } = "gemini-1.5-flash";
public int MaxInputLength { get; set; } = 15000;
public string EmbeddingModel { get; set; } = "text-embedding-004";
/// <summary>
/// Maximum number of tokens allowed for input.
/// </summary>
public int MaxInputTokens { get; set; } = 15000;
public int MaxOutputTokens { get; set; } = 1000;
public int RetryAttempts { get; set; } = 3;
public double Temperature { get; set; } = 0.1;
@@ -0,0 +1,9 @@
namespace NexusReader.Infrastructure.Configuration;
public record StripeSettings
{
public const string SectionName = "Stripe";
public string ProProductId { get; init; } = string.Empty;
public string BasicProductId { get; init; } = string.Empty;
public string FreeProductId { get; init; } = string.Empty;
}
@@ -1,5 +1,6 @@
using Microsoft.Extensions.DependencyInjection;
using Microsoft.Extensions.Configuration;
using Pgvector.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore;
using Microsoft.Extensions.AI;
using GeminiDotnet;
@@ -24,17 +25,18 @@ public static class DependencyInjection
var pgConnectionString = configuration.GetConnectionString("PostgresConnection");
if (!string.IsNullOrEmpty(pgConnectionString))
{
services.AddDbContext<AppDbContext>(options =>
options.UseNpgsql(pgConnectionString));
services.AddDbContextFactory<AppDbContext>(options =>
options.UseNpgsql(pgConnectionString, x => x.UseVector()));
}
else
{
var sqliteConnectionString = configuration.GetConnectionString("SqliteConnection") ?? "Data Source=nexus.db";
services.AddDbContext<AppDbContext>(options =>
services.AddDbContextFactory<AppDbContext>(options =>
options.UseSqlite(sqliteConnectionString));
}
services.Configure<AiSettings>(configuration.GetSection(AiSettings.SectionName));
services.Configure<StripeSettings>(configuration.GetSection(StripeSettings.SectionName));
var aiSettings = configuration.GetSection(AiSettings.SectionName).Get<AiSettings>() ?? new AiSettings();
Console.WriteLine($"[Infrastructure] AI Configured: Model={aiSettings.Model}, KeyPresent={!string.IsNullOrWhiteSpace(aiSettings.ApiKey) && aiSettings.ApiKey != "PLACEHOLDER"}");
@@ -63,8 +65,13 @@ public static class DependencyInjection
ModelId = aiSettings.Model
}));
services.AddEmbeddingGenerator(new GeminiEmbeddingGenerator(new GeminiClientOptions
{
ApiKey = aiSettings.ApiKey,
ModelId = aiSettings.EmbeddingModel ?? "text-embedding-004"
}));
services.AddScoped<IKnowledgeService, KnowledgeService>();
services.AddTransient<IAiGenerateQuizService, FakeAiGenerateQuizService>();
services.AddTransient<IEpubService, EpubService>();
services.AddAuthorizationCore(options =>
@@ -74,6 +81,13 @@ public static class DependencyInjection
services.AddScoped<IAuthorizationHandler, ProUserHandler>();
services.AddScoped<IInfrastructureMarker, InfrastructureMarker>();
return services;
}
public static System.Reflection.Assembly Assembly => typeof(DependencyInjection).Assembly;
}
public interface IInfrastructureMarker { }
internal class InfrastructureMarker : IInfrastructureMarker { }
@@ -0,0 +1,46 @@
using FluentResults;
using MediatR;
using Microsoft.AspNetCore.SignalR;
using Microsoft.EntityFrameworkCore;
using NexusReader.Application.Commands.Sync;
using NexusReader.Domain.Entities;
using NexusReader.Infrastructure.Persistence;
using NexusReader.Infrastructure.RealTime;
namespace NexusReader.Infrastructure.Handlers;
public class UpdateReadingProgressCommandHandler : IRequestHandler<UpdateReadingProgressCommand, Result>
{
private readonly AppDbContext _context;
private readonly IHubContext<SyncHub> _hubContext;
public UpdateReadingProgressCommandHandler(
AppDbContext context,
IHubContext<SyncHub> hubContext)
{
_context = context;
_hubContext = hubContext;
}
public async Task<Result> Handle(UpdateReadingProgressCommand request, CancellationToken cancellationToken)
{
var user = await _context.Users.FirstOrDefaultAsync(u => u.Id == request.UserId, cancellationToken);
if (user == null)
{
return Result.Fail("User not found.");
}
var now = DateTime.UtcNow;
user.LastReadPageId = request.PageId;
user.LastReadAt = now;
await _context.SaveChangesAsync(cancellationToken);
// Broadcast to other devices
await _hubContext.Clients
.Group($"User_{request.UserId}")
.SendAsync("ProgressUpdated", request.PageId, now, cancellationToken);
return Result.Ok();
}
}
@@ -0,0 +1,652 @@
// <auto-generated />
using System;
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Infrastructure;
using Microsoft.EntityFrameworkCore.Migrations;
using Microsoft.EntityFrameworkCore.Storage.ValueConversion;
using NexusReader.Infrastructure.Persistence;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
using Pgvector;
#nullable disable
namespace NexusReader.Infrastructure.Migrations
{
[DbContext(typeof(AppDbContext))]
[Migration("20260503175906_FinalNormalizedSubscriptionArchitecture")]
partial class FinalNormalizedSubscriptionArchitecture
{
/// <inheritdoc />
protected override void BuildTargetModel(ModelBuilder modelBuilder)
{
#pragma warning disable 612, 618
modelBuilder
.HasAnnotation("ProductVersion", "10.0.7")
.HasAnnotation("Relational:MaxIdentifierLength", 63);
NpgsqlModelBuilderExtensions.HasPostgresExtension(modelBuilder, "vector");
NpgsqlModelBuilderExtensions.UseIdentityByDefaultColumns(modelBuilder);
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityRole", b =>
{
b.Property<string>("Id")
.HasColumnType("text");
b.Property<string>("ConcurrencyStamp")
.IsConcurrencyToken()
.HasColumnType("text");
b.Property<string>("Name")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.Property<string>("NormalizedName")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.HasKey("Id");
b.HasIndex("NormalizedName")
.IsUnique()
.HasDatabaseName("RoleNameIndex");
b.ToTable("AspNetRoles", (string)null);
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityRoleClaim<string>", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<string>("ClaimType")
.HasColumnType("text");
b.Property<string>("ClaimValue")
.HasColumnType("text");
b.Property<string>("RoleId")
.IsRequired()
.HasColumnType("text");
b.HasKey("Id");
b.HasIndex("RoleId");
b.ToTable("AspNetRoleClaims", (string)null);
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserClaim<string>", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<string>("ClaimType")
.HasColumnType("text");
b.Property<string>("ClaimValue")
.HasColumnType("text");
b.Property<string>("UserId")
.IsRequired()
.HasColumnType("text");
b.HasKey("Id");
b.HasIndex("UserId");
b.ToTable("AspNetUserClaims", (string)null);
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserLogin<string>", b =>
{
b.Property<string>("LoginProvider")
.HasColumnType("text");
b.Property<string>("ProviderKey")
.HasColumnType("text");
b.Property<string>("ProviderDisplayName")
.HasColumnType("text");
b.Property<string>("UserId")
.IsRequired()
.HasColumnType("text");
b.HasKey("LoginProvider", "ProviderKey");
b.HasIndex("UserId");
b.ToTable("AspNetUserLogins", (string)null);
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserRole<string>", b =>
{
b.Property<string>("UserId")
.HasColumnType("text");
b.Property<string>("RoleId")
.HasColumnType("text");
b.HasKey("UserId", "RoleId");
b.HasIndex("RoleId");
b.ToTable("AspNetUserRoles", (string)null);
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserToken<string>", b =>
{
b.Property<string>("UserId")
.HasColumnType("text");
b.Property<string>("LoginProvider")
.HasColumnType("text");
b.Property<string>("Name")
.HasColumnType("text");
b.Property<string>("Value")
.HasColumnType("text");
b.HasKey("UserId", "LoginProvider", "Name");
b.ToTable("AspNetUserTokens", (string)null);
});
modelBuilder.Entity("NexusReader.Domain.Entities.Ebook", b =>
{
b.Property<Guid>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("uuid");
b.Property<DateTime>("AddedDate")
.HasColumnType("timestamp with time zone");
b.Property<string>("Author")
.IsRequired()
.HasMaxLength(255)
.HasColumnType("character varying(255)");
b.Property<string>("CoverUrl")
.HasColumnType("text");
b.Property<string>("FilePath")
.IsRequired()
.HasColumnType("text");
b.Property<DateTime?>("LastReadDate")
.HasColumnType("timestamp with time zone");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Title")
.IsRequired()
.HasMaxLength(255)
.HasColumnType("character varying(255)");
b.Property<string>("UserId")
.IsRequired()
.HasColumnType("text");
b.HasKey("Id");
b.HasIndex("TenantId");
b.HasIndex("UserId");
b.ToTable("Ebooks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnit", b =>
{
b.Property<string>("Id")
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Content")
.IsRequired()
.HasColumnType("text");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone");
b.Property<string>("MetadataJson")
.HasColumnType("text");
b.Property<string>("SourceId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<int>("Type")
.HasColumnType("integer");
b.Property<Vector>("Vector")
.HasColumnType("vector(768)");
b.Property<string>("Version")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.HasKey("Id");
b.HasIndex("SourceId");
b.HasIndex("TenantId");
b.ToTable("KnowledgeUnits");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnitLink", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<string>("RelationType")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("SourceUnitId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("TargetUnitId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.HasKey("Id");
b.HasIndex("SourceUnitId");
b.HasIndex("TargetUnitId");
b.ToTable("KnowledgeUnitLinks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.Property<string>("Id")
.HasColumnType("text");
b.Property<int>("AITokenLimit")
.HasColumnType("integer");
b.Property<int>("AITokensUsed")
.HasColumnType("integer");
b.Property<int>("AccessFailedCount")
.HasColumnType("integer");
b.Property<string>("ConcurrencyStamp")
.IsConcurrencyToken()
.HasColumnType("text");
b.Property<string>("DisplayName")
.HasMaxLength(100)
.HasColumnType("character varying(100)");
b.Property<string>("Email")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.Property<bool>("EmailConfirmed")
.HasColumnType("boolean");
b.Property<DateTime?>("LastAiActionDate")
.HasColumnType("timestamp with time zone");
b.Property<DateTime?>("LastReadAt")
.HasColumnType("timestamp with time zone");
b.Property<string>("LastReadPageId")
.HasMaxLength(255)
.HasColumnType("character varying(255)");
b.Property<bool>("LockoutEnabled")
.HasColumnType("boolean");
b.Property<DateTimeOffset?>("LockoutEnd")
.HasColumnType("timestamp with time zone");
b.Property<string>("NormalizedEmail")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.Property<string>("NormalizedUserName")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.Property<string>("PasswordHash")
.HasColumnType("text");
b.Property<string>("PhoneNumber")
.HasColumnType("text");
b.Property<bool>("PhoneNumberConfirmed")
.HasColumnType("boolean");
b.Property<string>("SecurityStamp")
.HasColumnType("text");
b.Property<int>("SubscriptionPlanId")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasDefaultValue(1);
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<bool>("TwoFactorEnabled")
.HasColumnType("boolean");
b.Property<string>("UserName")
.HasMaxLength(256)
.HasColumnType("character varying(256)");
b.HasKey("Id");
b.HasIndex("NormalizedEmail")
.HasDatabaseName("EmailIndex");
b.HasIndex("NormalizedUserName")
.IsUnique()
.HasDatabaseName("UserNameIndex");
b.HasIndex("SubscriptionPlanId");
b.HasIndex("TenantId");
b.ToTable("AspNetUsers", (string)null);
});
modelBuilder.Entity("NexusReader.Domain.Entities.QuizResult", b =>
{
b.Property<Guid>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("uuid");
b.Property<DateTime>("CompletedDate")
.HasColumnType("timestamp with time zone");
b.Property<int>("Score")
.HasColumnType("integer");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Topic")
.IsRequired()
.HasColumnType("text");
b.Property<int>("TotalQuestions")
.HasColumnType("integer");
b.Property<string>("UserId")
.IsRequired()
.HasColumnType("text");
b.HasKey("Id");
b.HasIndex("TenantId");
b.HasIndex("UserId");
b.ToTable("QuizResults");
});
modelBuilder.Entity("NexusReader.Domain.Entities.SemanticKnowledgeCache", b =>
{
b.Property<string>("ContentHash")
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone");
b.Property<string>("JsonData")
.IsRequired()
.HasColumnType("text");
b.Property<string>("ModelId")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("OriginalText")
.IsRequired()
.HasColumnType("text");
b.Property<string>("PromptVersion")
.IsRequired()
.HasMaxLength(10)
.HasColumnType("character varying(10)");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<Vector>("Vector")
.HasColumnType("vector(1536)");
b.HasKey("ContentHash");
b.HasIndex("ContentHash")
.IsUnique();
b.HasIndex("TenantId");
b.ToTable("SemanticKnowledgeCache");
});
modelBuilder.Entity("NexusReader.Domain.Entities.SubscriptionPlan", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<int>("AITokenLimit")
.HasColumnType("integer");
b.Property<decimal>("MonthlyPrice")
.HasColumnType("numeric");
b.Property<string>("PlanName")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("StripeProductId")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.HasKey("Id");
b.HasIndex("PlanName")
.IsUnique();
b.ToTable("SubscriptionPlans");
b.HasData(
new
{
Id = 1,
AITokenLimit = 1000,
MonthlyPrice = 0m,
PlanName = "Free",
StripeProductId = ""
},
new
{
Id = 2,
AITokenLimit = 10000,
MonthlyPrice = 9.99m,
PlanName = "Basic",
StripeProductId = "prod_basic_placeholder"
},
new
{
Id = 3,
AITokenLimit = 50000,
MonthlyPrice = 19.99m,
PlanName = "Pro",
StripeProductId = "prod_pro_placeholder"
},
new
{
Id = 4,
AITokenLimit = 500000,
MonthlyPrice = 99.99m,
PlanName = "Enterprise",
StripeProductId = "prod_enterprise_placeholder"
});
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityRoleClaim<string>", b =>
{
b.HasOne("Microsoft.AspNetCore.Identity.IdentityRole", null)
.WithMany()
.HasForeignKey("RoleId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserClaim<string>", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", null)
.WithMany()
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserLogin<string>", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", null)
.WithMany()
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserRole<string>", b =>
{
b.HasOne("Microsoft.AspNetCore.Identity.IdentityRole", null)
.WithMany()
.HasForeignKey("RoleId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.HasOne("NexusReader.Domain.Entities.NexusUser", null)
.WithMany()
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityUserToken<string>", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", null)
.WithMany()
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
});
modelBuilder.Entity("NexusReader.Domain.Entities.Ebook", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", "User")
.WithMany("Ebooks")
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.Navigation("User");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnitLink", b =>
{
b.HasOne("NexusReader.Domain.Entities.KnowledgeUnit", "SourceUnit")
.WithMany("OutgoingLinks")
.HasForeignKey("SourceUnitId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.HasOne("NexusReader.Domain.Entities.KnowledgeUnit", "TargetUnit")
.WithMany("IncomingLinks")
.HasForeignKey("TargetUnitId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.Navigation("SourceUnit");
b.Navigation("TargetUnit");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.HasOne("NexusReader.Domain.Entities.SubscriptionPlan", "SubscriptionPlan")
.WithMany()
.HasForeignKey("SubscriptionPlanId")
.OnDelete(DeleteBehavior.Restrict)
.IsRequired();
b.Navigation("SubscriptionPlan");
});
modelBuilder.Entity("NexusReader.Domain.Entities.QuizResult", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", "User")
.WithMany("QuizResults")
.HasForeignKey("UserId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.Navigation("User");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnit", b =>
{
b.Navigation("IncomingLinks");
b.Navigation("OutgoingLinks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.Navigation("Ebooks");
b.Navigation("QuizResults");
});
#pragma warning restore 612, 618
}
}
}
@@ -0,0 +1,399 @@
using System;
using Microsoft.EntityFrameworkCore.Migrations;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
using Pgvector;
#nullable disable
#pragma warning disable CA1814 // Prefer jagged arrays over multidimensional
namespace NexusReader.Infrastructure.Migrations
{
/// <inheritdoc />
public partial class FinalNormalizedSubscriptionArchitecture : Migration
{
/// <inheritdoc />
protected override void Up(MigrationBuilder migrationBuilder)
{
migrationBuilder.DropColumn(
name: "CurrentPlan",
table: "AspNetUsers");
migrationBuilder.AlterDatabase()
.Annotation("Npgsql:PostgresExtension:vector", ",,");
migrationBuilder.AlterColumn<DateTime>(
name: "CreatedAt",
table: "SemanticKnowledgeCache",
type: "timestamp with time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp without time zone");
migrationBuilder.AddColumn<string>(
name: "OriginalText",
table: "SemanticKnowledgeCache",
type: "text",
nullable: false,
defaultValue: "");
migrationBuilder.AddColumn<string>(
name: "TenantId",
table: "SemanticKnowledgeCache",
type: "character varying(128)",
maxLength: 128,
nullable: false,
defaultValue: "");
migrationBuilder.AddColumn<Vector>(
name: "Vector",
table: "SemanticKnowledgeCache",
type: "vector(1536)",
nullable: true);
migrationBuilder.AlterColumn<DateTime>(
name: "CompletedDate",
table: "QuizResults",
type: "timestamp with time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp without time zone");
migrationBuilder.AddColumn<string>(
name: "TenantId",
table: "QuizResults",
type: "character varying(128)",
maxLength: 128,
nullable: false,
defaultValue: "");
migrationBuilder.AlterColumn<DateTime>(
name: "LastReadDate",
table: "Ebooks",
type: "timestamp with time zone",
nullable: true,
oldClrType: typeof(DateTime),
oldType: "timestamp without time zone",
oldNullable: true);
migrationBuilder.AlterColumn<DateTime>(
name: "AddedDate",
table: "Ebooks",
type: "timestamp with time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp without time zone");
migrationBuilder.AddColumn<string>(
name: "TenantId",
table: "Ebooks",
type: "character varying(128)",
maxLength: 128,
nullable: false,
defaultValue: "");
migrationBuilder.AlterColumn<string>(
name: "TenantId",
table: "AspNetUsers",
type: "character varying(128)",
maxLength: 128,
nullable: false,
oldClrType: typeof(Guid),
oldType: "uuid");
migrationBuilder.AddColumn<string>(
name: "DisplayName",
table: "AspNetUsers",
type: "character varying(100)",
maxLength: 100,
nullable: true);
migrationBuilder.AddColumn<DateTime>(
name: "LastAiActionDate",
table: "AspNetUsers",
type: "timestamp with time zone",
nullable: true);
migrationBuilder.AddColumn<DateTime>(
name: "LastReadAt",
table: "AspNetUsers",
type: "timestamp with time zone",
nullable: true);
migrationBuilder.AddColumn<string>(
name: "LastReadPageId",
table: "AspNetUsers",
type: "character varying(255)",
maxLength: 255,
nullable: true);
migrationBuilder.AddColumn<int>(
name: "SubscriptionPlanId",
table: "AspNetUsers",
type: "integer",
nullable: false,
defaultValue: 1);
migrationBuilder.CreateTable(
name: "KnowledgeUnits",
columns: table => new
{
Id = table.Column<string>(type: "character varying(128)", maxLength: 128, nullable: false),
SourceId = table.Column<string>(type: "character varying(128)", maxLength: 128, nullable: false),
Version = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: false),
Type = table.Column<int>(type: "integer", nullable: false),
Content = table.Column<string>(type: "text", nullable: false),
MetadataJson = table.Column<string>(type: "text", nullable: true),
TenantId = table.Column<string>(type: "character varying(128)", maxLength: 128, nullable: false),
Vector = table.Column<Vector>(type: "vector(768)", nullable: true),
CreatedAt = table.Column<DateTime>(type: "timestamp with time zone", nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_KnowledgeUnits", x => x.Id);
});
migrationBuilder.CreateTable(
name: "SubscriptionPlans",
columns: table => new
{
Id = table.Column<int>(type: "integer", nullable: false)
.Annotation("Npgsql:ValueGenerationStrategy", NpgsqlValueGenerationStrategy.IdentityByDefaultColumn),
PlanName = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: false),
AITokenLimit = table.Column<int>(type: "integer", nullable: false),
MonthlyPrice = table.Column<decimal>(type: "numeric", nullable: false),
StripeProductId = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_SubscriptionPlans", x => x.Id);
});
migrationBuilder.CreateTable(
name: "KnowledgeUnitLinks",
columns: table => new
{
Id = table.Column<int>(type: "integer", nullable: false)
.Annotation("Npgsql:ValueGenerationStrategy", NpgsqlValueGenerationStrategy.IdentityByDefaultColumn),
SourceUnitId = table.Column<string>(type: "character varying(128)", maxLength: 128, nullable: false),
TargetUnitId = table.Column<string>(type: "character varying(128)", maxLength: 128, nullable: false),
RelationType = table.Column<string>(type: "character varying(50)", maxLength: 50, nullable: false)
},
constraints: table =>
{
table.PrimaryKey("PK_KnowledgeUnitLinks", x => x.Id);
table.ForeignKey(
name: "FK_KnowledgeUnitLinks_KnowledgeUnits_SourceUnitId",
column: x => x.SourceUnitId,
principalTable: "KnowledgeUnits",
principalColumn: "Id",
onDelete: ReferentialAction.Cascade);
table.ForeignKey(
name: "FK_KnowledgeUnitLinks_KnowledgeUnits_TargetUnitId",
column: x => x.TargetUnitId,
principalTable: "KnowledgeUnits",
principalColumn: "Id",
onDelete: ReferentialAction.Cascade);
});
migrationBuilder.InsertData(
table: "SubscriptionPlans",
columns: new[] { "Id", "AITokenLimit", "MonthlyPrice", "PlanName", "StripeProductId" },
values: new object[,]
{
{ 1, 1000, 0m, "Free", "" },
{ 2, 10000, 9.99m, "Basic", "prod_basic_placeholder" },
{ 3, 50000, 19.99m, "Pro", "prod_pro_placeholder" },
{ 4, 500000, 99.99m, "Enterprise", "prod_enterprise_placeholder" }
});
migrationBuilder.CreateIndex(
name: "IX_SemanticKnowledgeCache_TenantId",
table: "SemanticKnowledgeCache",
column: "TenantId");
migrationBuilder.CreateIndex(
name: "IX_QuizResults_TenantId",
table: "QuizResults",
column: "TenantId");
migrationBuilder.CreateIndex(
name: "IX_Ebooks_TenantId",
table: "Ebooks",
column: "TenantId");
migrationBuilder.CreateIndex(
name: "IX_AspNetUsers_SubscriptionPlanId",
table: "AspNetUsers",
column: "SubscriptionPlanId");
migrationBuilder.CreateIndex(
name: "IX_AspNetUsers_TenantId",
table: "AspNetUsers",
column: "TenantId");
migrationBuilder.CreateIndex(
name: "IX_KnowledgeUnitLinks_SourceUnitId",
table: "KnowledgeUnitLinks",
column: "SourceUnitId");
migrationBuilder.CreateIndex(
name: "IX_KnowledgeUnitLinks_TargetUnitId",
table: "KnowledgeUnitLinks",
column: "TargetUnitId");
migrationBuilder.CreateIndex(
name: "IX_KnowledgeUnits_SourceId",
table: "KnowledgeUnits",
column: "SourceId");
migrationBuilder.CreateIndex(
name: "IX_KnowledgeUnits_TenantId",
table: "KnowledgeUnits",
column: "TenantId");
migrationBuilder.CreateIndex(
name: "IX_SubscriptionPlans_PlanName",
table: "SubscriptionPlans",
column: "PlanName",
unique: true);
migrationBuilder.AddForeignKey(
name: "FK_AspNetUsers_SubscriptionPlans_SubscriptionPlanId",
table: "AspNetUsers",
column: "SubscriptionPlanId",
principalTable: "SubscriptionPlans",
principalColumn: "Id",
onDelete: ReferentialAction.Restrict);
}
/// <inheritdoc />
protected override void Down(MigrationBuilder migrationBuilder)
{
migrationBuilder.DropForeignKey(
name: "FK_AspNetUsers_SubscriptionPlans_SubscriptionPlanId",
table: "AspNetUsers");
migrationBuilder.DropTable(
name: "KnowledgeUnitLinks");
migrationBuilder.DropTable(
name: "SubscriptionPlans");
migrationBuilder.DropTable(
name: "KnowledgeUnits");
migrationBuilder.DropIndex(
name: "IX_SemanticKnowledgeCache_TenantId",
table: "SemanticKnowledgeCache");
migrationBuilder.DropIndex(
name: "IX_QuizResults_TenantId",
table: "QuizResults");
migrationBuilder.DropIndex(
name: "IX_Ebooks_TenantId",
table: "Ebooks");
migrationBuilder.DropIndex(
name: "IX_AspNetUsers_SubscriptionPlanId",
table: "AspNetUsers");
migrationBuilder.DropIndex(
name: "IX_AspNetUsers_TenantId",
table: "AspNetUsers");
migrationBuilder.DropColumn(
name: "OriginalText",
table: "SemanticKnowledgeCache");
migrationBuilder.DropColumn(
name: "TenantId",
table: "SemanticKnowledgeCache");
migrationBuilder.DropColumn(
name: "Vector",
table: "SemanticKnowledgeCache");
migrationBuilder.DropColumn(
name: "TenantId",
table: "QuizResults");
migrationBuilder.DropColumn(
name: "TenantId",
table: "Ebooks");
migrationBuilder.DropColumn(
name: "DisplayName",
table: "AspNetUsers");
migrationBuilder.DropColumn(
name: "LastAiActionDate",
table: "AspNetUsers");
migrationBuilder.DropColumn(
name: "LastReadAt",
table: "AspNetUsers");
migrationBuilder.DropColumn(
name: "LastReadPageId",
table: "AspNetUsers");
migrationBuilder.DropColumn(
name: "SubscriptionPlanId",
table: "AspNetUsers");
migrationBuilder.AlterDatabase()
.OldAnnotation("Npgsql:PostgresExtension:vector", ",,");
migrationBuilder.AlterColumn<DateTime>(
name: "CreatedAt",
table: "SemanticKnowledgeCache",
type: "timestamp without time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp with time zone");
migrationBuilder.AlterColumn<DateTime>(
name: "CompletedDate",
table: "QuizResults",
type: "timestamp without time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp with time zone");
migrationBuilder.AlterColumn<DateTime>(
name: "LastReadDate",
table: "Ebooks",
type: "timestamp without time zone",
nullable: true,
oldClrType: typeof(DateTime),
oldType: "timestamp with time zone",
oldNullable: true);
migrationBuilder.AlterColumn<DateTime>(
name: "AddedDate",
table: "Ebooks",
type: "timestamp without time zone",
nullable: false,
oldClrType: typeof(DateTime),
oldType: "timestamp with time zone");
migrationBuilder.AlterColumn<Guid>(
name: "TenantId",
table: "AspNetUsers",
type: "uuid",
nullable: false,
oldClrType: typeof(string),
oldType: "character varying(128)",
oldMaxLength: 128);
migrationBuilder.AddColumn<string>(
name: "CurrentPlan",
table: "AspNetUsers",
type: "text",
nullable: false,
defaultValue: "");
}
}
}
@@ -5,6 +5,7 @@ using Microsoft.EntityFrameworkCore.Infrastructure;
using Microsoft.EntityFrameworkCore.Storage.ValueConversion;
using NexusReader.Infrastructure.Persistence;
using Npgsql.EntityFrameworkCore.PostgreSQL.Metadata;
using Pgvector;
#nullable disable
@@ -20,6 +21,7 @@ namespace NexusReader.Infrastructure.Migrations
.HasAnnotation("ProductVersion", "10.0.7")
.HasAnnotation("Relational:MaxIdentifierLength", 63);
NpgsqlModelBuilderExtensions.HasPostgresExtension(modelBuilder, "vector");
NpgsqlModelBuilderExtensions.UseIdentityByDefaultColumns(modelBuilder);
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityRole", b =>
@@ -161,7 +163,7 @@ namespace NexusReader.Infrastructure.Migrations
.HasColumnType("uuid");
b.Property<DateTime>("AddedDate")
.HasColumnType("timestamp without time zone");
.HasColumnType("timestamp with time zone");
b.Property<string>("Author")
.IsRequired()
@@ -176,7 +178,12 @@ namespace NexusReader.Infrastructure.Migrations
.HasColumnType("text");
b.Property<DateTime?>("LastReadDate")
.HasColumnType("timestamp without time zone");
.HasColumnType("timestamp with time zone");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Title")
.IsRequired()
@@ -189,11 +196,91 @@ namespace NexusReader.Infrastructure.Migrations
b.HasKey("Id");
b.HasIndex("TenantId");
b.HasIndex("UserId");
b.ToTable("Ebooks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnit", b =>
{
b.Property<string>("Id")
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Content")
.IsRequired()
.HasColumnType("text");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp with time zone");
b.Property<string>("MetadataJson")
.HasColumnType("text");
b.Property<string>("SourceId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<int>("Type")
.HasColumnType("integer");
b.Property<Vector>("Vector")
.HasColumnType("vector(768)");
b.Property<string>("Version")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.HasKey("Id");
b.HasIndex("SourceId");
b.HasIndex("TenantId");
b.ToTable("KnowledgeUnits");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnitLink", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<string>("RelationType")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("SourceUnitId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("TargetUnitId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.HasKey("Id");
b.HasIndex("SourceUnitId");
b.HasIndex("TargetUnitId");
b.ToTable("KnowledgeUnitLinks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.Property<string>("Id")
@@ -212,9 +299,9 @@ namespace NexusReader.Infrastructure.Migrations
.IsConcurrencyToken()
.HasColumnType("text");
b.Property<string>("CurrentPlan")
.IsRequired()
.HasColumnType("text");
b.Property<string>("DisplayName")
.HasMaxLength(100)
.HasColumnType("character varying(100)");
b.Property<string>("Email")
.HasMaxLength(256)
@@ -223,6 +310,16 @@ namespace NexusReader.Infrastructure.Migrations
b.Property<bool>("EmailConfirmed")
.HasColumnType("boolean");
b.Property<DateTime?>("LastAiActionDate")
.HasColumnType("timestamp with time zone");
b.Property<DateTime?>("LastReadAt")
.HasColumnType("timestamp with time zone");
b.Property<string>("LastReadPageId")
.HasMaxLength(255)
.HasColumnType("character varying(255)");
b.Property<bool>("LockoutEnabled")
.HasColumnType("boolean");
@@ -249,8 +346,15 @@ namespace NexusReader.Infrastructure.Migrations
b.Property<string>("SecurityStamp")
.HasColumnType("text");
b.Property<Guid>("TenantId")
.HasColumnType("uuid");
b.Property<int>("SubscriptionPlanId")
.ValueGeneratedOnAdd()
.HasColumnType("integer")
.HasDefaultValue(1);
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<bool>("TwoFactorEnabled")
.HasColumnType("boolean");
@@ -268,6 +372,10 @@ namespace NexusReader.Infrastructure.Migrations
.IsUnique()
.HasDatabaseName("UserNameIndex");
b.HasIndex("SubscriptionPlanId");
b.HasIndex("TenantId");
b.ToTable("AspNetUsers", (string)null);
});
@@ -278,11 +386,16 @@ namespace NexusReader.Infrastructure.Migrations
.HasColumnType("uuid");
b.Property<DateTime>("CompletedDate")
.HasColumnType("timestamp without time zone");
.HasColumnType("timestamp with time zone");
b.Property<int>("Score")
.HasColumnType("integer");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<string>("Topic")
.IsRequired()
.HasColumnType("text");
@@ -296,6 +409,8 @@ namespace NexusReader.Infrastructure.Migrations
b.HasKey("Id");
b.HasIndex("TenantId");
b.HasIndex("UserId");
b.ToTable("QuizResults");
@@ -308,7 +423,7 @@ namespace NexusReader.Infrastructure.Migrations
.HasColumnType("character varying(128)");
b.Property<DateTime>("CreatedAt")
.HasColumnType("timestamp without time zone");
.HasColumnType("timestamp with time zone");
b.Property<string>("JsonData")
.IsRequired()
@@ -319,19 +434,99 @@ namespace NexusReader.Infrastructure.Migrations
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("OriginalText")
.IsRequired()
.HasColumnType("text");
b.Property<string>("PromptVersion")
.IsRequired()
.HasMaxLength(10)
.HasColumnType("character varying(10)");
b.Property<string>("TenantId")
.IsRequired()
.HasMaxLength(128)
.HasColumnType("character varying(128)");
b.Property<Vector>("Vector")
.HasColumnType("vector(1536)");
b.HasKey("ContentHash");
b.HasIndex("ContentHash")
.IsUnique();
b.HasIndex("TenantId");
b.ToTable("SemanticKnowledgeCache");
});
modelBuilder.Entity("NexusReader.Domain.Entities.SubscriptionPlan", b =>
{
b.Property<int>("Id")
.ValueGeneratedOnAdd()
.HasColumnType("integer");
NpgsqlPropertyBuilderExtensions.UseIdentityByDefaultColumn(b.Property<int>("Id"));
b.Property<int>("AITokenLimit")
.HasColumnType("integer");
b.Property<decimal>("MonthlyPrice")
.HasColumnType("numeric");
b.Property<string>("PlanName")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.Property<string>("StripeProductId")
.IsRequired()
.HasMaxLength(50)
.HasColumnType("character varying(50)");
b.HasKey("Id");
b.HasIndex("PlanName")
.IsUnique();
b.ToTable("SubscriptionPlans");
b.HasData(
new
{
Id = 1,
AITokenLimit = 1000,
MonthlyPrice = 0m,
PlanName = "Free",
StripeProductId = ""
},
new
{
Id = 2,
AITokenLimit = 10000,
MonthlyPrice = 9.99m,
PlanName = "Basic",
StripeProductId = "prod_basic_placeholder"
},
new
{
Id = 3,
AITokenLimit = 50000,
MonthlyPrice = 19.99m,
PlanName = "Pro",
StripeProductId = "prod_pro_placeholder"
},
new
{
Id = 4,
AITokenLimit = 500000,
MonthlyPrice = 99.99m,
PlanName = "Enterprise",
StripeProductId = "prod_enterprise_placeholder"
});
});
modelBuilder.Entity("Microsoft.AspNetCore.Identity.IdentityRoleClaim<string>", b =>
{
b.HasOne("Microsoft.AspNetCore.Identity.IdentityRole", null)
@@ -394,6 +589,36 @@ namespace NexusReader.Infrastructure.Migrations
b.Navigation("User");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnitLink", b =>
{
b.HasOne("NexusReader.Domain.Entities.KnowledgeUnit", "SourceUnit")
.WithMany("OutgoingLinks")
.HasForeignKey("SourceUnitId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.HasOne("NexusReader.Domain.Entities.KnowledgeUnit", "TargetUnit")
.WithMany("IncomingLinks")
.HasForeignKey("TargetUnitId")
.OnDelete(DeleteBehavior.Cascade)
.IsRequired();
b.Navigation("SourceUnit");
b.Navigation("TargetUnit");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.HasOne("NexusReader.Domain.Entities.SubscriptionPlan", "SubscriptionPlan")
.WithMany()
.HasForeignKey("SubscriptionPlanId")
.OnDelete(DeleteBehavior.Restrict)
.IsRequired();
b.Navigation("SubscriptionPlan");
});
modelBuilder.Entity("NexusReader.Domain.Entities.QuizResult", b =>
{
b.HasOne("NexusReader.Domain.Entities.NexusUser", "User")
@@ -405,6 +630,13 @@ namespace NexusReader.Infrastructure.Migrations
b.Navigation("User");
});
modelBuilder.Entity("NexusReader.Domain.Entities.KnowledgeUnit", b =>
{
b.Navigation("IncomingLinks");
b.Navigation("OutgoingLinks");
});
modelBuilder.Entity("NexusReader.Domain.Entities.NexusUser", b =>
{
b.Navigation("Ebooks");
@@ -1,9 +1,13 @@
<Project Sdk="Microsoft.NET.Sdk">
<ItemGroup>
<ProjectReference Include="..\NexusReader.Application\NexusReader.Application.csproj" />
</ItemGroup>
<Project Sdk="Microsoft.NET.Sdk">
<ItemGroup>
<ProjectReference Include="..\NexusReader.Application\NexusReader.Application.csproj" />
</ItemGroup>
<ItemGroup>
<FrameworkReference Include="Microsoft.AspNetCore.App" />
</ItemGroup>
<ItemGroup>
<PackageReference Include="GeminiDotnet.Extensions.AI" Version="0.23.0" />
<PackageReference Include="Microsoft.AspNetCore.Authorization" Version="10.0.7" />
@@ -15,7 +19,10 @@
<PackageReference Include="Microsoft.EntityFrameworkCore.Sqlite" Version="10.0.7" />
<PackageReference Include="Microsoft.Extensions.AI" Version="10.5.0" />
<PackageReference Include="Microsoft.Extensions.Resilience" Version="10.5.0" />
<PackageReference Include="Microsoft.ML.Tokenizers" Version="2.0.0" />
<PackageReference Include="Microsoft.ML.Tokenizers.Data.Cl100kBase" Version="2.0.0" />
<PackageReference Include="Npgsql.EntityFrameworkCore.PostgreSQL" Version="10.0.0" />
<PackageReference Include="Pgvector.EntityFrameworkCore" Version="0.3.0" />
<PackageReference Include="Polly" Version="8.6.6" />
<PackageReference Include="Polly.Extensions.Http" Version="3.0.0" />
<PackageReference Include="Stripe.net" Version="51.1.0" />
@@ -1,27 +1,78 @@
using Microsoft.AspNetCore.Identity.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore;
using NexusReader.Domain.Entities;
using NexusReader.Application.Abstractions.Persistence;
namespace NexusReader.Infrastructure.Persistence;
public class AppDbContext : IdentityDbContext<NexusUser>
public class AppDbContext : IdentityDbContext<NexusUser>, IApplicationDbContext
{
public AppDbContext(DbContextOptions<AppDbContext> options) : base(options)
{
}
public DbSet<SemanticKnowledgeCache> SemanticKnowledgeCache => Set<SemanticKnowledgeCache>();
public DbSet<KnowledgeUnit> KnowledgeUnits => Set<KnowledgeUnit>();
public DbSet<KnowledgeUnitLink> KnowledgeUnitLinks => Set<KnowledgeUnitLink>();
public DbSet<Ebook> Ebooks => Set<Ebook>();
public DbSet<QuizResult> QuizResults => Set<QuizResult>();
public DbSet<SubscriptionPlan> SubscriptionPlans => Set<SubscriptionPlan>();
protected override void OnModelCreating(ModelBuilder modelBuilder)
{
modelBuilder.HasPostgresExtension("vector");
modelBuilder.Entity<NexusUser>(entity =>
{
entity.Property(u => u.LastReadPageId).HasMaxLength(255);
entity.Property(u => u.LastReadAt).IsRequired(false);
entity.HasIndex(u => u.TenantId);
entity.HasOne(u => u.SubscriptionPlan)
.WithMany()
.HasForeignKey(u => u.SubscriptionPlanId)
.OnDelete(DeleteBehavior.Restrict);
// Note: DefaultValue for int is 1 (which corresponds to 'Free' in our seed)
entity.Property(u => u.SubscriptionPlanId)
.HasDefaultValue(1);
});
base.OnModelCreating(modelBuilder);
modelBuilder.Entity<SubscriptionPlan>(entity =>
{
entity.HasIndex(p => p.PlanName).IsUnique();
});
modelBuilder.Entity<SemanticKnowledgeCache>(entity =>
{
entity.HasKey(e => e.ContentHash);
entity.HasIndex(e => e.ContentHash).IsUnique();
entity.HasIndex(e => e.TenantId);
entity.Property(e => e.Vector).HasColumnType("vector(1536)");
});
modelBuilder.Entity<KnowledgeUnit>(entity =>
{
entity.HasKey(e => e.Id);
entity.HasIndex(e => e.TenantId);
entity.HasIndex(e => e.SourceId);
entity.Property(e => e.Vector).HasColumnType("vector(768)");
});
modelBuilder.Entity<KnowledgeUnitLink>(entity =>
{
entity.HasKey(e => e.Id);
entity.HasOne(e => e.SourceUnit)
.WithMany(u => u.OutgoingLinks)
.HasForeignKey(e => e.SourceUnitId)
.OnDelete(DeleteBehavior.Cascade);
entity.HasOne(e => e.TargetUnit)
.WithMany(u => u.IncomingLinks)
.HasForeignKey(e => e.TargetUnitId)
.OnDelete(DeleteBehavior.Cascade);
});
modelBuilder.Entity<Ebook>(entity =>
@@ -30,6 +81,8 @@ public class AppDbContext : IdentityDbContext<NexusUser>
.WithMany(u => u.Ebooks)
.HasForeignKey(e => e.UserId)
.OnDelete(DeleteBehavior.Cascade);
entity.HasIndex(e => e.TenantId);
});
modelBuilder.Entity<QuizResult>(entity =>
@@ -38,6 +91,16 @@ public class AppDbContext : IdentityDbContext<NexusUser>
.WithMany(u => u.QuizResults)
.HasForeignKey(e => e.UserId)
.OnDelete(DeleteBehavior.Cascade);
entity.HasIndex(e => e.TenantId);
});
// Seed Subscription Plans with deterministic IDs
modelBuilder.Entity<SubscriptionPlan>().HasData(
new SubscriptionPlan { Id = 1, PlanName = SubscriptionPlan.FreeName, AITokenLimit = 1000, MonthlyPrice = 0m, StripeProductId = "" },
new SubscriptionPlan { Id = 2, PlanName = SubscriptionPlan.BasicName, AITokenLimit = 10000, MonthlyPrice = 9.99m, StripeProductId = "prod_basic_placeholder" },
new SubscriptionPlan { Id = 3, PlanName = SubscriptionPlan.ProName, AITokenLimit = 50000, MonthlyPrice = 19.99m, StripeProductId = "prod_pro_placeholder" },
new SubscriptionPlan { Id = 4, PlanName = SubscriptionPlan.EnterpriseName, AITokenLimit = 500000, MonthlyPrice = 99.99m, StripeProductId = "prod_enterprise_placeholder" }
);
}
}
@@ -0,0 +1,45 @@
using Microsoft.EntityFrameworkCore;
using Microsoft.EntityFrameworkCore.Design;
using Microsoft.Extensions.Configuration;
using Pgvector.EntityFrameworkCore;
namespace NexusReader.Infrastructure.Persistence;
public class AppDbContextFactory : IDesignTimeDbContextFactory<AppDbContext>
{
public AppDbContext CreateDbContext(string[] args)
{
var environment = Environment.GetEnvironmentVariable("ASPNETCORE_ENVIRONMENT") ?? "Development";
// Try to find the Web project directory by looking for the solution root
var currentDir = new DirectoryInfo(Directory.GetCurrentDirectory());
while (currentDir != null && !File.Exists(Path.Combine(currentDir.FullName, "NexusReader.slnx")))
{
currentDir = currentDir.Parent;
}
var basePath = currentDir != null
? Path.Combine(currentDir.FullName, "src", "NexusReader.Web.New")
: Directory.GetCurrentDirectory();
var configuration = new ConfigurationBuilder()
.SetBasePath(basePath)
.AddJsonFile("appsettings.json", optional: true)
.AddJsonFile($"appsettings.{environment}.json", optional: true)
.AddEnvironmentVariables()
.Build();
var optionsBuilder = new DbContextOptionsBuilder<AppDbContext>();
var connectionString = configuration.GetConnectionString("PostgresConnection");
if (string.IsNullOrEmpty(connectionString))
{
// For design time, if no PG connection is found, we might be using Sqlite or just testing
connectionString = "Host=localhost;Database=nexus_reader;Username=postgres;Password=postgres";
}
optionsBuilder.UseNpgsql(connectionString, x => x.UseVector());
return new AppDbContext(optionsBuilder.Options);
}
}
@@ -0,0 +1,88 @@
using Microsoft.AspNetCore.Identity;
using Microsoft.Extensions.DependencyInjection;
using NexusReader.Domain.Entities;
using System;
using System.Linq;
using System.Threading.Tasks;
using System.Collections.Generic;
using Microsoft.EntityFrameworkCore;
namespace NexusReader.Infrastructure.Persistence;
public static class DbInitializer
{
public static async Task SeedAsync(IServiceProvider serviceProvider)
{
using var scope = serviceProvider.CreateScope();
var userManager = scope.ServiceProvider.GetRequiredService<UserManager<NexusUser>>();
var roleManager = scope.ServiceProvider.GetRequiredService<RoleManager<IdentityRole>>();
var dbContext = scope.ServiceProvider.GetRequiredService<AppDbContext>();
try
{
Console.WriteLine("[Seeder] Starting database seeding...");
// Seed Subscription Plans
if (!dbContext.SubscriptionPlans.Any())
{
dbContext.SubscriptionPlans.AddRange(new List<SubscriptionPlan>
{
new SubscriptionPlan { Id = SubscriptionPlan.FreeId, PlanName = SubscriptionPlan.FreeName, AITokenLimit = 5000, MonthlyPrice = 0, StripeProductId = "prod_Free789" },
new SubscriptionPlan { Id = SubscriptionPlan.ProId, PlanName = SubscriptionPlan.ProName, AITokenLimit = 50000, MonthlyPrice = 19, StripeProductId = "prod_Pro123" },
new SubscriptionPlan { Id = SubscriptionPlan.EnterpriseId, PlanName = SubscriptionPlan.EnterpriseName, AITokenLimit = 500000, MonthlyPrice = 99, StripeProductId = "prod_Enterprise456" }
});
await dbContext.SaveChangesAsync();
Console.WriteLine("[Seeder] Subscription plans seeded.");
}
// Seed Roles
string[] roleNames = { "Admin", "User" };
foreach (var roleName in roleNames)
{
var roleExist = await roleManager.RoleExistsAsync(roleName);
if (!roleExist)
{
await roleManager.CreateAsync(new IdentityRole(roleName));
Console.WriteLine($"[Seeder] Created role: {roleName}");
}
}
// Seed Admin User
var adminEmail = "admin@nexus.com";
var adminUser = await userManager.FindByEmailAsync(adminEmail);
if (adminUser == null)
{
adminUser = new NexusUser
{
UserName = adminEmail,
Email = adminEmail,
EmailConfirmed = true,
SubscriptionPlanId = SubscriptionPlan.EnterpriseId,
AITokenLimit = 1000000,
TenantId = Guid.NewGuid().ToString()
};
var createPowerUser = await userManager.CreateAsync(adminUser, "Admin123!");
if (createPowerUser.Succeeded)
{
await userManager.AddToRoleAsync(adminUser, "Admin");
Console.WriteLine($"[Seeder] Admin user created successfully: {adminEmail}");
}
else
{
var errors = string.Join(", ", createPowerUser.Errors.Select(e => e.Description));
Console.WriteLine($"[Seeder] Failed to create admin user: {errors}");
}
}
else
{
Console.WriteLine("[Seeder] Admin user already exists.");
}
}
catch (Exception ex)
{
Console.WriteLine($"[Seeder] Critical error during seeding: {ex.Message}");
}
}
}
@@ -0,0 +1,46 @@
using MediatR;
using Microsoft.AspNetCore.SignalR;
using Microsoft.AspNetCore.Authorization;
using NexusReader.Application.Commands.Sync;
namespace NexusReader.Infrastructure.RealTime;
[Authorize]
public class SyncHub : Hub
{
private readonly IMediator _mediator;
public SyncHub(IMediator mediator)
{
_mediator = mediator;
}
public async Task UpdateProgress(string pageId)
{
var userId = Context.UserIdentifier;
if (!string.IsNullOrEmpty(userId))
{
await _mediator.Send(new UpdateReadingProgressCommand(pageId, userId));
}
}
public override async Task OnConnectedAsync()
{
var userId = Context.UserIdentifier;
if (!string.IsNullOrEmpty(userId))
{
await Groups.AddToGroupAsync(Context.ConnectionId, $"User_{userId}");
}
await base.OnConnectedAsync();
}
public override async Task OnDisconnectedAsync(Exception? exception)
{
var userId = Context.UserIdentifier;
if (!string.IsNullOrEmpty(userId))
{
await Groups.RemoveFromGroupAsync(Context.ConnectionId, $"User_{userId}");
}
await base.OnDisconnectedAsync(exception);
}
}
@@ -1,7 +1,10 @@
using Microsoft.AspNetCore.Identity;
using Microsoft.EntityFrameworkCore;
using Microsoft.Extensions.Logging;
using Microsoft.Extensions.Options;
using NexusReader.Application.Abstractions.Services;
using NexusReader.Domain.Entities;
using NexusReader.Infrastructure.Configuration;
using NexusReader.Infrastructure.Persistence;
namespace NexusReader.Infrastructure.Services;
@@ -10,44 +13,90 @@ public class BillingService : IBillingService
{
private readonly AppDbContext _dbContext;
private readonly UserManager<NexusUser> _userManager;
private readonly StripeSettings _stripeSettings;
private readonly ILogger<BillingService> _logger;
public BillingService(AppDbContext dbContext, UserManager<NexusUser> userManager)
public BillingService(
AppDbContext dbContext,
UserManager<NexusUser> userManager,
IOptions<StripeSettings> stripeSettings,
ILogger<BillingService> logger)
{
_dbContext = dbContext;
_userManager = userManager;
_stripeSettings = stripeSettings.Value;
_logger = logger;
}
public async Task<bool> HandleSubscriptionUpdatedAsync(string customerEmail, string stripeProductId)
{
var user = await _userManager.FindByEmailAsync(customerEmail);
if (user == null) return false;
// Map Stripe Product IDs to Nexus Plans
// These IDs would typically come from configuration
if (stripeProductId.Contains("pro"))
if (user == null)
{
user.CurrentPlan = "Pro";
user.AITokenLimit = 50000;
}
else if (stripeProductId.Contains("basic"))
{
user.CurrentPlan = "Basic";
user.AITokenLimit = 10000;
_logger.LogWarning("Attempted to update subscription for non-existent user: {Email}", customerEmail);
return false;
}
string targetPlanName = SubscriptionPlan.FreeName;
int tokenLimit = 1000;
if (stripeProductId == _stripeSettings.ProProductId)
{
targetPlanName = SubscriptionPlan.ProName;
tokenLimit = 50000;
}
else if (stripeProductId == _stripeSettings.BasicProductId)
{
targetPlanName = SubscriptionPlan.BasicName;
tokenLimit = 10000;
}
else if (!string.IsNullOrEmpty(stripeProductId) && stripeProductId != _stripeSettings.FreeProductId)
{
_logger.LogWarning("Unrecognized Stripe Product ID: {ProductId} for user {Email}. Falling back to Free tier.", stripeProductId, customerEmail);
}
var plan = await _dbContext.SubscriptionPlans.FirstOrDefaultAsync(p => p.PlanName == targetPlanName);
if (plan != null)
{
user.SubscriptionPlanId = plan.Id;
user.AITokenLimit = tokenLimit;
}
var result = await _userManager.UpdateAsync(user);
if (!result.Succeeded)
{
_logger.LogError("Failed to update user {Email} after subscription change: {Errors}",
customerEmail, string.Join(", ", result.Errors.Select(e => e.Description)));
return false;
}
await _userManager.UpdateAsync(user);
return true;
}
public async Task<bool> HandleSubscriptionDeletedAsync(string customerEmail)
{
var user = await _userManager.FindByEmailAsync(customerEmail);
if (user == null) return false;
if (user == null)
{
_logger.LogWarning("Attempted to delete subscription for non-existent user: {Email}", customerEmail);
return false;
}
user.CurrentPlan = "Free";
user.AITokenLimit = 1000; // Reset to free limit
var freePlan = await _dbContext.SubscriptionPlans.FirstOrDefaultAsync(p => p.PlanName == SubscriptionPlan.FreeName);
if (freePlan != null)
{
user.SubscriptionPlanId = freePlan.Id;
user.AITokenLimit = freePlan.AITokenLimit;
}
await _userManager.UpdateAsync(user);
var result = await _userManager.UpdateAsync(user);
if (!result.Succeeded)
{
_logger.LogError("Failed to reset user {Email} to Free tier after subscription deletion: {Errors}",
customerEmail, string.Join(", ", result.Errors.Select(e => e.Description)));
return false;
}
return true;
}
}
@@ -41,7 +41,20 @@ public class EpubService : IEpubService
return Result.Fail($"EPUB file not found. Checked {searchPaths.Count} locations, including: {string.Join(", ", searchPaths.Take(3))}");
}
EpubBook book = await EpubReader.ReadBookAsync(fullPath);
if (!File.Exists(fullPath))
{
return Result.Fail($"EPUB file at '{fullPath}' is not accessible or does not exist.");
}
EpubBook book;
try
{
book = await EpubReader.ReadBookAsync(fullPath);
}
catch (Exception ex)
{
return Result.Fail(new Error($"Failed to parse EPUB file. It might be corrupted or in use. Path: {fullPath}").CausedBy(ex));
}
var blocks = new List<ContentBlock>();
int totalWordCount = 0;
int blockCounter = 0;
@@ -1,23 +0,0 @@
using FluentResults;
using NexusReader.Application.Abstractions.Services;
using NexusReader.Application.Queries.Quiz;
namespace NexusReader.Infrastructure.Services;
public sealed class FakeAiGenerateQuizService : IAiGenerateQuizService
{
public async Task<Result<QuizDto>> GenerateQuizAsync(string contextBlockId, CancellationToken cancellationToken = default)
{
// 2000ms delay to highlight Skeleton loader visually
await Task.Delay(2000, cancellationToken);
var fakeQuiz = new List<QuizQuestionDto>
{
new("Co było głównym centrum włoskiego Renesansu?", new List<string> { "Wenecja", "Rzym", "Florencja", "Mediolan" }, 2),
new("Kto stanowił wpływowy ród mecenasów sztuki?", new List<string> { "Habsburgowie", "Medyceusze", "Borgiowie", "Sforzowie" }, 1),
new("Jaką koncepcją filozoficzną charakteryzował się renesans?", new List<string> { "Teocentryzmem", "Nihilizmem", "Humanizmem", "Egzystencjalizmem" }, 2)
};
return Result.Ok(new QuizDto(fakeQuiz));
}
}
@@ -2,6 +2,7 @@ using System.Text.Json;
using FluentResults;
using Microsoft.EntityFrameworkCore;
using Microsoft.Extensions.AI;
using Microsoft.ML.Tokenizers;
using NexusReader.Application.Abstractions.Services;
using NexusReader.Application.DTOs.AI;
using NexusReader.Domain.Entities;
@@ -11,77 +12,82 @@ using Polly;
using Polly.Registry;
using Microsoft.Extensions.Options;
using NexusReader.Infrastructure.Configuration;
using Pgvector;
using Pgvector.EntityFrameworkCore;
namespace NexusReader.Infrastructure.Services;
public class KnowledgeService : IKnowledgeService
{
private readonly IChatClient _chatClient;
private readonly AppDbContext _dbContext;
private readonly IEmbeddingGenerator<string, Embedding<float>> _embeddingGenerator;
private readonly IDbContextFactory<AppDbContext> _dbContextFactory;
private readonly ResiliencePipeline _retryPipeline;
private readonly AiSettings _settings;
private readonly Tokenizer _tokenizer;
private const string PromptVersion = "1.0";
public KnowledgeService(
IChatClient chatClient,
AppDbContext dbContext,
IChatClient chatClient,
IEmbeddingGenerator<string, Embedding<float>> embeddingGenerator,
IDbContextFactory<AppDbContext> dbContextFactory,
ResiliencePipelineProvider<string> pipelineProvider,
IOptions<AiSettings> settings)
{
_chatClient = chatClient;
_dbContext = dbContext;
_embeddingGenerator = embeddingGenerator;
_dbContextFactory = dbContextFactory;
_retryPipeline = pipelineProvider.GetPipeline("ai-retry");
_settings = settings.Value;
// Use Tiktoken (cl100k_base) which is a standard for modern LLMs and provides
// a very reliable estimation for token usage in Gemini-based workloads.
_tokenizer = TiktokenTokenizer.CreateForModel("gpt-4");
}
public async Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await GetKnowledgeInternalAsync(text, PromptRegistry.KnowledgeExtractionSystemPrompt, "full", cancellationToken);
return await GetKnowledgeInternalAsync(text, tenantId, PromptRegistry.KnowledgeExtractionSystemPrompt, "full", cancellationToken);
}
public async Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await GetKnowledgeInternalAsync(text, PromptRegistry.GraphExtractionPrompt, "graph", cancellationToken);
return await GetKnowledgeInternalAsync(text, tenantId, PromptRegistry.GraphExtractionPrompt, "graph", cancellationToken);
}
public async Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await GetKnowledgeInternalAsync(text, PromptRegistry.SummaryAndQuizPrompt, "summary_quiz", cancellationToken);
return await GetKnowledgeInternalAsync(text, tenantId, PromptRegistry.SummaryAndQuizPrompt, "summary_quiz", cancellationToken);
}
private async Task<Result<KnowledgePacket>> GetKnowledgeInternalAsync(string text, string systemPrompt, string cacheSuffix, CancellationToken cancellationToken)
public async Task<Result<KnowledgePacket>> GetKnowledgeMapAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
if (string.IsNullOrWhiteSpace(text))
{
return Result.Fail("Input text is empty.");
}
return await GetKnowledgeInternalAsync(text, tenantId, PromptRegistry.KM_ExtractionPrompt, "km_map", cancellationToken);
}
Console.WriteLine($"[KnowledgeService] Starting extraction ({cacheSuffix}) for text sample: {text.Substring(0, Math.Min(text.Length, 50))}...");
private async Task<Result<KnowledgePacket>> GetKnowledgeInternalAsync(string text, string tenantId, string systemPrompt, string traceType, CancellationToken cancellationToken)
{
if (string.IsNullOrWhiteSpace(text)) return Result.Fail("Input text is empty.");
var normalizedText = ContentHasher.Normalize(text);
if (normalizedText.Length > _settings.MaxInputLength)
{
normalizedText = normalizedText.Substring(0, _settings.MaxInputLength);
Console.WriteLine($"[KnowledgeService] WARNING: Input text truncated to {_settings.MaxInputLength} chars.");
}
var hash = ContentHasher.ComputeHash(normalizedText) + "_" + cacheSuffix;
using var dbContext = await _dbContextFactory.CreateDbContextAsync(cancellationToken);
var normalizedText = text.Trim();
var hash = ContentHasher.ComputeHash(normalizedText);
// 1. Check Cache
var cached = await _dbContext.SemanticKnowledgeCache
.FirstOrDefaultAsync(c => c.ContentHash == hash && c.PromptVersion == PromptVersion, cancellationToken);
if (cached != null)
var cached = await dbContext.SemanticKnowledgeCache
.FirstOrDefaultAsync(c => c.ContentHash == hash && c.TenantId == tenantId, cancellationToken);
if (cached != null && cached.PromptVersion == PromptVersion)
{
Console.WriteLine($"[KnowledgeService] Cache Hit for {traceType} ({hash})");
try
{
var packet = JsonSerializer.Deserialize<KnowledgePacket>(cached.JsonData, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
if (packet != null) return Result.Ok(packet);
}
catch { }
catch { /* fallback to regen */ }
}
// 2. Call AI Client
Console.WriteLine($"[KnowledgeService] Cache Miss for {traceType} ({hash}). Requesting AI...");
try
{
var options = new ChatOptions
@@ -109,20 +115,46 @@ public class KnowledgeService : IKnowledgeService
var knowledgePacket = JsonSerializer.Deserialize<KnowledgePacket>(jsonResponse, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
if (knowledgePacket == null) return Result.Fail("Failed to deserialize AI response.");
// 3. Save to Cache
// 3. Generate Embedding if not present
float[]? vector = null;
try
{
var embeddingResponse = await _retryPipeline.ExecuteAsync(async ct =>
await _embeddingGenerator.GenerateAsync(new[] { normalizedText }, cancellationToken: ct), cancellationToken);
vector = embeddingResponse.First().Vector.ToArray();
}
catch (Exception ex)
{
Console.WriteLine($"[KnowledgeService] Embedding Error: {ex.Message}");
// We continue even if embedding fails, as the primary goal was knowledge extraction
}
// 4. Save to Cache
var cacheEntry = new SemanticKnowledgeCache
{
ContentHash = hash,
JsonData = jsonResponse,
OriginalText = normalizedText,
ModelId = _settings.Model,
PromptVersion = PromptVersion,
TenantId = tenantId,
Vector = vector != null ? new Vector(vector) : null,
CreatedAt = DateTime.UtcNow
};
if (cached == null) _dbContext.SemanticKnowledgeCache.Add(cacheEntry);
else { cached.JsonData = jsonResponse; cached.CreatedAt = DateTime.UtcNow; }
if (cached == null) dbContext.SemanticKnowledgeCache.Add(cacheEntry);
else
{
cached.JsonData = jsonResponse;
cached.OriginalText = normalizedText;
cached.Vector = vector != null ? new Vector(vector) : null;
cached.CreatedAt = DateTime.UtcNow;
}
await _dbContext.SaveChangesAsync(cancellationToken);
// 5. Process structured KnowledgeUnits (Graph Expansion)
await ProcessKnowledgeUnitsAsync(knowledgePacket, tenantId, dbContext, cancellationToken);
await dbContext.SaveChangesAsync(cancellationToken);
return Result.Ok(knowledgePacket);
}
catch (JsonException ex)
@@ -137,18 +169,154 @@ public class KnowledgeService : IKnowledgeService
}
}
public async Task<Result> ClearCacheAsync(CancellationToken cancellationToken = default)
private async Task ProcessKnowledgeUnitsAsync(KnowledgePacket packet, string tenantId, AppDbContext dbContext, CancellationToken cancellationToken)
{
var unitIds = packet.Units.Select(u => u.Id).ToList();
var linkSourceIds = packet.Links.Select(l => l.Source).ToList();
var linkTargetIds = packet.Links.Select(l => l.Target).ToList();
var allCandidateIds = unitIds.Concat(linkSourceIds).Concat(linkTargetIds).Distinct().ToList();
// Single batch query to find existing units
var existingUnits = await dbContext.KnowledgeUnits
.Where(u => allCandidateIds.Contains(u.Id))
.ToDictionaryAsync(u => u.Id, cancellationToken);
var processedUnitIds = new HashSet<string>();
foreach (var unitDto in packet.Units)
{
var unitId = unitDto.Id;
existingUnits.TryGetValue(unitId, out var unit);
if (unit == null)
{
unit = new KnowledgeUnit { Id = unitId, TenantId = tenantId };
dbContext.KnowledgeUnits.Add(unit);
existingUnits[unitId] = unit;
}
unit.Type = Enum.TryParse<NexusReader.Domain.Enums.KnowledgeUnitType>(unitDto.Type, true, out var type) ? type : NexusReader.Domain.Enums.KnowledgeUnitType.Snippet;
unit.Content = unitDto.Content;
unit.SourceId = "extracted";
unit.MetadataJson = JsonSerializer.Serialize(unitDto.Metadata);
try
{
var emb = await _retryPipeline.ExecuteAsync(async ct =>
await _embeddingGenerator.GenerateAsync(new[] { unit.Content }, cancellationToken: ct), cancellationToken);
unit.Vector = new Vector(emb.First().Vector.ToArray());
}
catch { /* Ignore embedding errors for now */ }
processedUnitIds.Add(unit.Id);
}
foreach (var linkDto in packet.Links)
{
var sourceExists = processedUnitIds.Contains(linkDto.Source) || existingUnits.ContainsKey(linkDto.Source);
var targetExists = processedUnitIds.Contains(linkDto.Target) || existingUnits.ContainsKey(linkDto.Target);
if (sourceExists && targetExists)
{
// Check if link already exists to avoid duplicates if necessary
// For now, assume we can add them or they are new in this session
var link = new KnowledgeUnitLink
{
SourceUnitId = linkDto.Source,
TargetUnitId = linkDto.Target,
RelationType = linkDto.Relation
};
dbContext.KnowledgeUnitLinks.Add(link);
}
else
{
Console.WriteLine($"[KnowledgeService] WARNING: Skipping invalid link {linkDto.Source} -> {linkDto.Target} (Missing units).");
}
}
}
public async Task<Result<GroundednessResult>> VerifyGroundednessAsync(string answer, string context, string tenantId, CancellationToken cancellationToken = default)
{
var systemPrompt = @"
You are a Fact-Checking AI. Evaluate if the 'Answer' is supported by the 'Context'.
Rate the groundedness from 0.0 to 1.0.
Return ONLY a JSON object: { ""score"": 0.9, ""rationale"": ""string"", ""isGrounded"": true }
";
var userPrompt = $"Context: {context}\n\nAnswer: {answer}";
try
{
Console.WriteLine("[KnowledgeService] Clearing SemanticKnowledgeCache...");
_dbContext.SemanticKnowledgeCache.RemoveRange(_dbContext.SemanticKnowledgeCache);
await _dbContext.SaveChangesAsync(cancellationToken);
var options = new ChatOptions
{
Temperature = 0.0f, // Low temperature for factual checks
MaxOutputTokens = 500
};
var response = await _retryPipeline.ExecuteAsync(async ct =>
await _chatClient.GetResponseAsync(new List<ChatMessage>
{
new ChatMessage(ChatRole.System, systemPrompt),
new ChatMessage(ChatRole.User, userPrompt)
}, options, cancellationToken: ct), cancellationToken);
var rawJson = response.Text?.Trim() ?? "{}";
rawJson = rawJson.Replace("```json", "").Replace("```", "").Trim();
var result = JsonSerializer.Deserialize<GroundednessResult>(rawJson, new JsonSerializerOptions { PropertyNameCaseInsensitive = true });
return result != null ? Result.Ok(result) : Result.Fail("Failed to parse groundedness result");
}
catch (Exception ex)
{
return Result.Fail(new Error("Failed to verify groundedness").CausedBy(ex));
}
}
public async Task<Result<List<RelevantContext>>> GetRelevantContextAsync(string query, string tenantId, CancellationToken cancellationToken = default)
{
using var dbContext = await _dbContextFactory.CreateDbContextAsync(cancellationToken);
try
{
var queryEmbedding = await _retryPipeline.ExecuteAsync(async ct =>
await _embeddingGenerator.GenerateAsync(new[] { query }, cancellationToken: ct), cancellationToken);
var queryVector = new Vector(queryEmbedding.First().Vector.ToArray());
var relevantUnits = await dbContext.KnowledgeUnits
.Where(u => u.TenantId == tenantId)
.OrderBy(u => u.Vector!.L2Distance(queryVector))
.Take(5)
.Select(u => new RelevantContext { Text = u.Content, Confidence = 1.0 })
.ToListAsync(cancellationToken);
return Result.Ok(relevantUnits);
}
catch (Exception ex)
{
return Result.Fail(new Error("Failed to retrieve relevant context").CausedBy(ex));
}
}
public async Task<Result> ClearCacheAsync(CancellationToken cancellationToken = default)
{
using var dbContext = await _dbContextFactory.CreateDbContextAsync(cancellationToken);
try
{
await dbContext.SemanticKnowledgeCache.ExecuteDeleteAsync(cancellationToken);
await dbContext.KnowledgeUnits.ExecuteDeleteAsync(cancellationToken);
await dbContext.KnowledgeUnitLinks.ExecuteDeleteAsync(cancellationToken);
return Result.Ok();
}
catch (Exception ex)
{
return Result.Fail($"Failed to clear cache: {ex.Message}");
return Result.Fail(new Error("Failed to clear knowledge cache").CausedBy(ex));
}
}
private int EstimateTokenCount(string text)
{
if (string.IsNullOrEmpty(text)) return 0;
return _tokenizer.CountTokens(text);
}
}
@@ -21,4 +21,13 @@ public static class PromptRegistry
public const string SummaryAndQuizPrompt =
"You are an expert educator. Provide a concise summary of the text and generate a challenging quiz (3-5 questions). " +
"Return ONLY minified JSON. Schema: { \"summary\": \"string\", \"quizzes\": [ { \"question\": \"string\", \"options\": [ \"string\" ], \"correct_index\": 0 } ] }";
public const string KM_ExtractionPrompt =
"You are an expert at Knowledge Engineering. Segment the provided text into discrete Knowledge Units. " +
"Identify 'units' (sections, tables, definitions, rules) and 'links' (how they relate). " +
"CRITICAL: Units must be granular. " +
"Schema: { " +
"\"units\": [ { \"id\": \"string\", \"type\": \"Section|Table|Definition|Rule\", \"content\": \"string\", \"metadata\": { \"page\": 0 } } ], " +
"\"links\": [ { \"source\": \"string\", \"target\": \"string\", \"relation\": \"Next|Defines|Contains|References\" } ] " +
"}.";
}
+5 -1
View File
@@ -3,7 +3,11 @@
<Router AppAssembly="@typeof(NexusReader.UI.Shared._Imports).Assembly">
<Found Context="routeData">
<RouteView RouteData="@routeData" DefaultLayout="@typeof(NexusReader.UI.Shared.Layout.MainLayout)" />
<AuthorizeRouteView RouteData="@routeData" DefaultLayout="@typeof(NexusReader.UI.Shared.Layout.MainLayout)">
<NotAuthorized>
<RedirectToLogin />
</NotAuthorized>
</AuthorizeRouteView>
<FocusOnNavigate RouteData="@routeData" Selector="h1" />
</Found>
<NotFound>
+14
View File
@@ -2,6 +2,8 @@ using Microsoft.Extensions.Logging;
using NexusReader.Application.Abstractions.Services;
using NexusReader.Infrastructure.Mobile.Services;
using NexusReader.UI.Shared.Services;
using NexusReader.Application;
using MediatR;
namespace NexusReader.Maui;
@@ -39,6 +41,18 @@ public static class MauiProgram
builder.Services.AddScoped<IThemeService, ThemeService>();
builder.Services.AddScoped<IFocusModeService, FocusModeService>();
builder.Services.AddScoped<IQuizStateService, QuizStateService>();
builder.Services.AddScoped<IReaderNavigationService, ReaderNavigationService>();
builder.Services.AddScoped<IKnowledgeGraphService, KnowledgeGraphService>();
builder.Services.AddScoped<IReaderInteractionService, ReaderInteractionService>();
builder.Services.AddScoped<KnowledgeCoordinator>();
builder.Services.AddScoped<ISyncService, SyncService>();
builder.Services.AddScoped<IIdentityService, IdentityService>();
builder.Services.AddApplication();
builder.Services.AddMediatR(cfg => cfg.RegisterServicesFromAssemblies(
NexusReader.Application.DependencyInjection.Assembly
));
return builder.Build();
}
+6 -1
View File
@@ -11,7 +11,12 @@
<body>
<div id="app">Loading...</div>
<div id="app">
<div id="app-preloader">
<div class="preloader-spinner"></div>
<div class="preloader-text">Nexus Reader</div>
</div>
</div>
<div id="blazor-error-ui">
An unhandled error has occurred.
@@ -0,0 +1,39 @@
@namespace NexusReader.UI.Shared.Components.Atoms
<div class="nexus-search-container @(IsActive ? "active" : "")">
<div class="search-wrapper">
<i class="nexus-icon @IconClass"></i>
<input type="text"
@bind="SearchValue"
@bind:event="oninput"
@onkeypress="HandleKeyPress"
placeholder="@Placeholder"
class="nexus-search-input" />
@if (!string.IsNullOrEmpty(SearchValue))
{
<button class="clear-btn" @onclick="ClearSearch">×</button>
}
</div>
</div>
@code {
[Parameter] public string Placeholder { get; set; } = "Search your library...";
[Parameter] public string IconClass { get; set; } = "bi bi-search";
[Parameter] public EventCallback<string> OnSearch { get; set; }
private string SearchValue { get; set; } = string.Empty;
private bool IsActive => !string.IsNullOrEmpty(SearchValue);
private async Task HandleKeyPress(KeyboardEventArgs e)
{
if (e.Key == "Enter")
{
await OnSearch.InvokeAsync(SearchValue);
}
}
private void ClearSearch()
{
SearchValue = string.Empty;
}
}
@@ -0,0 +1,57 @@
.nexus-search-container {
width: 100%;
max-width: 500px;
margin: 1rem auto;
transition: all 0.3s ease;
}
.search-wrapper {
position: relative;
display: flex;
align-items: center;
background: var(--nexus-card, #141414);
border: 1px solid rgba(255, 255, 255, 0.1);
border-radius: 12px;
padding: 0.5rem 1rem;
transition: border-color 0.3s ease, box-shadow 0.3s ease;
}
.nexus-search-container.active .search-wrapper,
.search-wrapper:focus-within {
border-color: var(--nexus-neon, #00ff99);
box-shadow: 0 0 15px rgba(0, 255, 153, 0.2);
}
.nexus-icon {
color: rgba(255, 255, 255, 0.5);
margin-right: 0.75rem;
font-size: 1.1rem;
}
.nexus-search-input {
flex: 1;
background: transparent;
border: none;
color: white;
font-family: 'Inter', sans-serif;
font-size: 0.95rem;
outline: none;
}
.nexus-search-input::placeholder {
color: rgba(255, 255, 255, 0.3);
}
.clear-btn {
background: transparent;
border: none;
color: rgba(255, 255, 255, 0.4);
font-size: 1.2rem;
cursor: pointer;
padding: 0 0.5rem;
transition: color 0.2s ease;
}
.clear-btn:hover {
color: var(--nexus-neon, #00ff99);
}
@@ -1,36 +1,126 @@
@using NexusReader.UI.Shared.Services
@using NexusReader.Application.DTOs.AI
@inject IQuizStateService QuizState
@inject KnowledgeCoordinator Coordinator
@implements IDisposable
<div class="ai-bubble-container">
<div class="ai-bubble">
<div class="ai-avatar">
<div class="avatar-ring"></div>
<NexusIcon Name="robot" Size="48" Class="neon-pulse" />
<NexusIcon Name="robot" Size="48" Class="@(_isStreaming ? "neon-pulse" : "neon-glow")" />
<div class="avatar-label">
<span class="name">E-Czytnik</span>
<span class="role">Asystent AI</span>
</div>
</div>
<div class="ai-content">
<NexusTypography Variant="NexusTypography.TypographyVariant.UI">@Dialogue</NexusTypography>
@if (_isLoading)
{
<div class="loading-state">
<div class="shimmer">Analizuję fragment...</div>
</div>
}
else
{
<NexusTypography Variant="NexusTypography.TypographyVariant.UI">
@_displayedText@(_isStreaming ? "▍" : "")
</NexusTypography>
}
<div class="ai-actions">
<button class="action-btn ghost" @onclick='() => HandleActionClick("more")'>Pokaż więcej informacji</button>
<button class="action-btn neon-border" @onclick='() => HandleActionClick("quiz")'>Rozwiąż quiz</button>
<button class="action-btn neon-border" @onclick='() => HandleActionClick("quiz")' disabled="@(_isLoading)">Rozwiąż quiz</button>
</div>
</div>
<div class="bubble-pointer"></div>
</div>
</div>
@code {
[Parameter] public string ContextBlockId { get; set; } = string.Empty;
/// <summary>Fallback static dialogue shown when no live AI content is available.</summary>
[Parameter] public string Dialogue { get; set; } = string.Empty;
[Parameter] public List<string> Actions { get; set; } = new();
[Parameter] public EventCallback<string> OnActionTriggered { get; set; }
private string _displayedText = string.Empty;
private bool _isLoading = false;
private bool _isStreaming = false;
private string _lastFetchedBlockId = string.Empty;
private KnowledgePacket? _packet;
private CancellationTokenSource? _streamCts;
protected override async Task OnParametersSetAsync()
{
// Only re-fetch when the block context actually changes
if (string.IsNullOrEmpty(ContextBlockId) || ContextBlockId == _lastFetchedBlockId)
return;
_lastFetchedBlockId = ContextBlockId;
await FetchAndStreamAsync();
}
private async Task FetchAndStreamAsync()
{
// Cancel any in-progress stream
_streamCts?.Cancel();
_streamCts = new CancellationTokenSource();
var token = _streamCts.Token;
_isLoading = true;
_isStreaming = false;
_displayedText = string.Empty;
_packet = null;
StateHasChanged();
try
{
_packet = await Coordinator.RequestSummaryAndQuizAsync(
$"[ID: {ContextBlockId}]\n{Dialogue}");
var summary = _packet?.Summary;
if (string.IsNullOrWhiteSpace(summary))
{
// Fall back to the static Dialogue parameter
_displayedText = string.IsNullOrEmpty(Dialogue)
? "Brak danych do analizy."
: Dialogue;
_isLoading = false;
StateHasChanged();
return;
}
_isLoading = false;
_isStreaming = true;
// Word-by-word reveal (streaming simulation)
var words = summary.Split(' ');
foreach (var word in words)
{
if (token.IsCancellationRequested) break;
_displayedText += (string.IsNullOrEmpty(_displayedText) ? "" : " ") + word;
StateHasChanged();
await Task.Delay(40, token); // ~25 words/sec
}
}
catch (OperationCanceledException)
{
// Superseded by a newer block — silently drop
}
catch (Exception ex)
{
_displayedText = string.IsNullOrEmpty(Dialogue) ? "Błąd analizy." : Dialogue;
Console.WriteLine($"[AiAssistantBubble] Error fetching summary: {ex.Message}");
}
finally
{
_isStreaming = false;
StateHasChanged();
}
}
private async Task HandleActionClick(string action)
{
if (action.Contains("quiz", StringComparison.OrdinalIgnoreCase))
@@ -43,4 +133,10 @@
await OnActionTriggered.InvokeAsync(action);
}
}
public void Dispose()
{
_streamCts?.Cancel();
_streamCts?.Dispose();
}
}
@@ -0,0 +1,103 @@
@using MediatR
@using NexusReader.Application.Commands.AI
@using NexusReader.Application.Abstractions.Services
@using NexusReader.UI.Shared.Components.Atoms
@using Microsoft.AspNetCore.Components.Authorization
@inject IMediator Mediator
@inject AuthenticationStateProvider AuthProvider
<div class="groundedness-badge @GetStatusClass()" title="@_result?.Rationale">
@if (_isChecking)
{
<span class="shimmer">Weryfikacja...</span>
}
else if (_result != null)
{
<NexusIcon Name="@(GetIcon())" Size="14" />
<span>@((_result.Score * 100).ToString("0"))% Grounded</span>
}
</div>
<style>
.groundedness-badge {
display: inline-flex;
align-items: center;
gap: 6px;
padding: 4px 8px;
border-radius: 12px;
font-size: 0.75rem;
font-weight: 600;
background: rgba(255, 255, 255, 0.05);
border: 1px solid rgba(255, 255, 255, 0.1);
transition: all 0.3s ease;
}
.groundedness-badge.status-high {
color: var(--nexus-neon);
border-color: var(--nexus-neon);
}
.groundedness-badge.status-medium {
color: #ffaa00;
border-color: #ffaa00;
}
.groundedness-badge.status-low {
color: #ff4444;
border-color: #ff4444;
}
.shimmer {
opacity: 0.6;
}
</style>
@code {
[Parameter] public string Answer { get; set; } = string.Empty;
[Parameter] public string Context { get; set; } = string.Empty;
private GroundednessResult? _result;
private bool _isChecking;
protected override async Task OnParametersSetAsync()
{
if (!string.IsNullOrEmpty(Answer) && !string.IsNullOrEmpty(Context) && _result == null)
{
await RunCheck();
}
}
private async Task RunCheck()
{
_isChecking = true;
StateHasChanged();
var authState = await AuthProvider.GetAuthenticationStateAsync();
var tenantId = authState.User.FindFirst("TenantId")?.Value ?? "global";
var res = await Mediator.Send(new VerifyGroundednessCommand(Answer, Context, tenantId));
if (res.IsSuccess)
{
_result = res.Value;
}
_isChecking = false;
StateHasChanged();
}
private string GetStatusClass()
{
if (_result == null) return "";
if (_result.Score >= 0.8) return "status-high";
if (_result.Score >= 0.5) return "status-medium";
return "status-low";
}
private string GetIcon()
{
if (_result == null) return "help";
if (_result.Score >= 0.8) return "check-circle";
if (_result.Score >= 0.5) return "info-circle";
return "alert-triangle";
}
}
@@ -0,0 +1,61 @@
@using NexusReader.Application.DTOs.AI
@using NexusReader.UI.Shared.Components.Atoms
@namespace NexusReader.UI.Shared.Components.Organisms
<div class="global-intelligence-panel">
<div class="panel-header">
<h3><i class="bi bi-cpu"></i> Global Intelligence</h3>
<p>Semantic search across your library</p>
</div>
<NexusSearchBox Placeholder="Ask a question about your books..." OnSearch="HandleSearch" />
<div class="results-container">
@if (IsLoading)
{
<div class="loading-state">
<div class="nexus-spinner"></div>
<span>Analyzing your library...</span>
</div>
}
else if (Results != null && Results.Any())
{
@foreach (var result in Results)
{
<div class="search-result-item">
<div class="result-meta">
<span class="relevance">@(Math.Round(result.RelevanceScore * 100))% Relevant</span>
@if (!string.IsNullOrEmpty(result.SourceBookTitle))
{
<span class="source">in <strong>@result.SourceBookTitle</strong></span>
}
</div>
<div class="result-snippet">
@result.Snippet
</div>
</div>
}
}
else if (HasSearched)
{
<div class="empty-state">
<i class="bi bi-search"></i>
<p>No semantic matches found.</p>
</div>
}
</div>
</div>
@code {
[Parameter] public List<SemanticSearchResultDto>? Results { get; set; }
[Parameter] public bool IsLoading { get; set; }
[Parameter] public EventCallback<string> OnPerformSearch { get; set; }
private bool HasSearched { get; set; }
private async Task HandleSearch(string query)
{
HasSearched = true;
await OnPerformSearch.InvokeAsync(query);
}
}
@@ -0,0 +1,94 @@
.global-intelligence-panel {
background: var(--nexus-bg, #0a0a0a);
border-left: 1px solid rgba(255, 255, 255, 0.05);
height: 100%;
display: flex;
flex-direction: column;
padding: 1.5rem;
}
.panel-header h3 {
margin: 0;
color: var(--nexus-neon, #00ff99);
font-size: 1.25rem;
display: flex;
align-items: center;
gap: 0.5rem;
}
.panel-header p {
color: rgba(255, 255, 255, 0.5);
font-size: 0.85rem;
margin: 0.25rem 0 1.5rem 0;
}
.results-container {
flex: 1;
overflow-y: auto;
margin-top: 1rem;
padding-right: 0.5rem;
}
.search-result-item {
background: var(--nexus-card, #141414);
border-radius: 8px;
padding: 1rem;
margin-bottom: 1rem;
border: 1px solid rgba(255, 255, 255, 0.05);
transition: transform 0.2s ease, border-color 0.2s ease;
}
.search-result-item:hover {
transform: translateX(4px);
border-color: rgba(0, 255, 153, 0.3);
}
.result-meta {
display: flex;
justify-content: space-between;
font-size: 0.75rem;
margin-bottom: 0.5rem;
}
.relevance {
color: var(--nexus-neon, #00ff99);
font-weight: 600;
}
.source {
color: rgba(255, 255, 255, 0.4);
}
.result-snippet {
color: rgba(255, 255, 255, 0.8);
font-size: 0.9rem;
line-height: 1.5;
display: -webkit-box;
-webkit-line-clamp: 4;
-webkit-box-orient: vertical;
overflow: hidden;
}
.loading-state, .empty-state {
display: flex;
flex-direction: column;
align-items: center;
justify-content: center;
height: 200px;
color: rgba(255, 255, 255, 0.3);
text-align: center;
}
.nexus-spinner {
width: 30px;
height: 30px;
border: 2px solid rgba(0, 255, 153, 0.1);
border-top-color: var(--nexus-neon, #00ff99);
border-radius: 50%;
animation: spin 1s linear infinite;
margin-bottom: 1rem;
}
@keyframes spin {
to { transform: rotate(360deg); }
}
@@ -10,6 +10,7 @@
@inject IReaderNavigationService NavigationService
@inject KnowledgeCoordinator Coordinator
@inject IReaderInteractionService InteractionService
@inject ISyncService SyncService
<div class="reader-canvas @(ThemeService.IsLightMode ? "theme-light" : "theme-dark")">
@if (ViewModel == null)
@@ -53,6 +54,7 @@
protected override void OnInitialized()
{
Coordinator.Clear();
ThemeService.OnThemeChanged += StateHasChanged;
NavigationService.OnNavigationChanged += OnNavigationChanged;
@@ -77,6 +79,11 @@
protected override async Task OnAfterRenderAsync(bool firstRender)
{
if (firstRender)
{
await SyncService.InitializeAsync();
}
if (ViewModel != null && !_isJsInitialized)
{
_isJsInitialized = true;
@@ -109,6 +116,23 @@
public void HandleBlockReached(string blockId, string content)
{
Coordinator.OnBlockReached(blockId, content);
// Debounce sync update (simple version: every 5 seconds or on a timer)
_ = SyncService.UpdateProgressAsync(blockId);
}
private void HandleSyncProgressReceived(string blockId, DateTime timestamp)
{
// For now, let's just scroll to the node if it's in the current view,
// or just log it. Usually, we should prompt the user.
Console.WriteLine($"[Sync] Received progress from another device: {blockId} at {timestamp}");
// Simple auto-scroll if it's newer than what we have (we don't track our own timestamp yet,
// but we can assume incoming syncs are from other active devices)
_ = InvokeAsync(async () => {
await ScrollToNodeAsync(blockId);
StateHasChanged();
});
}
[JSInvokable]
@@ -196,5 +220,6 @@
InteractionService.OnScrollToBlockRequested -= HandleScrollRequested;
InteractionService.OnHighlightBlockRequested -= HandleHighlightRequested;
InteractionService.OnTextSelected -= HandleTextSelected;
SyncService.OnProgressReceived -= HandleSyncProgressReceived;
}
}
@@ -3,35 +3,38 @@
@using NexusReader.UI.Shared.Services
@using NexusReader.UI.Shared.Components.Molecules
@using NexusReader.UI.Shared.Components.Organisms
@using Microsoft.Extensions.Logging
@inject IPlatformService PlatformService
@inject IFocusModeService FocusMode
@inject IQuizStateService QuizService
@inject IJSRuntime JS
@inject IIdentityService IdentityService
@inject NavigationManager NavigationManager
@inject Microsoft.Extensions.Logging.ILogger<MainLayout> Logger
@implements IDisposable
<div class="app-container @_platformClass @(FocusMode.IsFocusModeActive ? "focus-mode-active" : "")">
<div class="reader-pane">
<main>
@Body
</main>
<ReaderFooter />
</div>
<AuthorizeView>
<Authorized>
<div class="app-container @_platformClass @(FocusMode.IsFocusModeActive ? "focus-mode-active" : "")">
<div class="reader-pane">
<main>
@Body
</main>
<ReaderFooter />
</div>
<div class="resizer" id="sidebar-resizer"></div>
<div class="resizer" id="sidebar-resizer"></div>
<AuthorizeView>
<Authorized>
<div class="intelligence-sidebar">
<IntelligenceToolbar />
<div class="intelligence-content">
<div class="intelligence-header">
<div class="ai-title">
<NexusIcon Name="robot" Size="20" Class="@($"neon-glow {(QuizService.HasNewQuiz ? "quiz-available" : "")}")" />
<NexusIcon Name="robot" Size="20"
Class="@($"neon-glow {(QuizService.HasNewQuiz ? "quiz-available" : "")}")" />
<span>Asystent AI</span>
</div>
<div class="user-profile">
<span class="user-email">@context.User.Identity?.Name</span>
<button class="logout-btn" @onclick="HandleLogout">Logout</button>
@@ -39,16 +42,28 @@
<button class="close-btn">×</button>
</div>
<div class="intelligence-scroll-area">
<KnowledgeGraph />
@if (!_isMobile)
{
<KnowledgeGraph />
}
<KnowledgeCheck />
</div>
</div>
</div>
</Authorized>
</AuthorizeView>
</div>
</div>
</Authorized>
<Authorizing>
<div class="app-preloader">
<div class="preloader-spinner"></div>
<div class="preloader-text">Weryfikacja...</div>
</div>
</Authorizing>
<NotAuthorized>
@Body
</NotAuthorized>
</AuthorizeView>
<div id="blazor-error-ui" data-nosnippet>
An unhandled error has occurred.
@@ -58,20 +73,23 @@
@code {
private string _platformClass = "platform-desktop";
private bool _isMobile = false;
protected override void OnInitialized()
{
FocusMode.OnFocusModeChanged += StateHasChanged;
QuizService.OnQuizUpdated += StateHasChanged;
var context = PlatformService.GetDeviceContext();
if (context.IsSuccess)
{
_platformClass = context.Value.DeviceType switch
_isMobile = context.Value.DeviceType switch
{
DeviceType.Phone or DeviceType.Tablet => "platform-mobile",
_ => "platform-desktop"
DeviceType.Phone or DeviceType.Tablet => true,
_ => false
};
_platformClass = _isMobile ? "platform-mobile" : "platform-desktop";
}
}
@@ -90,7 +108,10 @@
var module = await JS.InvokeAsync<IJSObjectReference>("import", "./_content/NexusReader.UI.Shared/js/layoutResizer.js");
await module.InvokeVoidAsync("initResizer", ".app-container", "#sidebar-resizer", "--sidebar-width");
}
catch { }
catch (Exception ex)
{
Logger.LogError(ex, "Failed to initialize layout resizer JS module.");
}
}
}
@@ -100,4 +121,3 @@
QuizService.OnQuizUpdated -= StateHasChanged;
}
}
@@ -12,6 +12,8 @@
<PackageReference Include="Microsoft.AspNetCore.Components.Authorization" Version="10.0.7" />
<PackageReference Include="Microsoft.AspNetCore.Components.Web" Version="10.0.7" />
<PackageReference Include="MediatR" Version="12.1.1" />
<PackageReference Include="Microsoft.Extensions.Logging.Abstractions" Version="10.0.7" />
<PackageReference Include="Microsoft.AspNetCore.SignalR.Client" Version="10.0.7" />
</ItemGroup>
<ItemGroup>
@@ -0,0 +1,11 @@
using FluentResults;
namespace NexusReader.UI.Shared.Services;
public interface ISyncService
{
Task<Result> InitializeAsync();
Task<Result> UpdateProgressAsync(string pageId);
event Action<string, DateTime> OnProgressReceived;
Task DisposeAsync();
}
@@ -38,7 +38,7 @@ public sealed class KnowledgeCoordinator : IDisposable
_interactionService.RequestHighlightBlock(nodeId);
}
public async Task ProcessFullPageAsync(string fullContent)
public async Task ProcessFullPageAsync(string fullContent, string tenantId = "global")
{
if (string.IsNullOrWhiteSpace(fullContent)) return;
@@ -49,7 +49,7 @@ public sealed class KnowledgeCoordinator : IDisposable
try
{
var result = await _knowledgeService.GetGraphDataAsync(fullContent);
var result = await _knowledgeService.GetGraphDataAsync(fullContent, tenantId);
if (result.IsSuccess)
{
var packet = result.Value;
@@ -73,12 +73,12 @@ public sealed class KnowledgeCoordinator : IDisposable
_graphService.SetActiveNode(blockId);
}
public async Task<KnowledgePacket?> RequestSummaryAndQuizAsync(string content)
public async Task<KnowledgePacket?> RequestSummaryAndQuizAsync(string content, string tenantId = "global")
{
_quizService.SetHydrating(true);
try
{
var result = await _knowledgeService.GetSummaryAndQuizAsync(content);
var result = await _knowledgeService.GetSummaryAndQuizAsync(content, tenantId);
if (result.IsSuccess)
{
var packet = result.Value;
@@ -98,6 +98,12 @@ public sealed class KnowledgeCoordinator : IDisposable
return null;
}
public void Clear()
{
_graphService.Clear();
_quizService.SetQuiz(null, null);
}
public void Dispose()
{
_interactionService.OnNodeSelected -= HandleNodeSelected;
@@ -0,0 +1,112 @@
using FluentResults;
using Microsoft.AspNetCore.SignalR.Client;
using NexusReader.Application.Abstractions.Services;
using System.Net.Http;
namespace NexusReader.UI.Shared.Services;
public class SyncService : ISyncService, IAsyncDisposable
{
private readonly HttpClient _httpClient;
private readonly INativeStorageService _storageService;
private readonly IPlatformService _platformService;
private HubConnection? _hubConnection;
private bool _isInitialized;
private CancellationTokenSource? _debounceCts;
public event Action<string, DateTime>? OnProgressReceived;
public SyncService(
HttpClient httpClient,
INativeStorageService storageService,
IPlatformService platformService)
{
_httpClient = httpClient;
_storageService = storageService;
_platformService = platformService;
}
public async Task<Result> InitializeAsync()
{
if (_isInitialized) return Result.Ok();
var tokenResult = await _storageService.GetSecureString("nexus_auth_token");
if (tokenResult.IsFailed) return Result.Fail("Not authenticated");
var baseUrl = _httpClient.BaseAddress?.ToString() ?? "http://localhost:5000/";
var hubUrl = new Uri(new Uri(baseUrl), "synchub").ToString();
_hubConnection = new HubConnectionBuilder()
.WithUrl(hubUrl, options =>
{
options.AccessTokenProvider = () => Task.FromResult<string?>(tokenResult.Value);
})
.WithAutomaticReconnect()
.Build();
_hubConnection.On<string, DateTime>("ProgressUpdated", (pageId, timestamp) =>
{
OnProgressReceived?.Invoke(pageId, timestamp);
});
try
{
await _hubConnection.StartAsync();
_isInitialized = true;
return Result.Ok();
}
catch (Exception ex)
{
return Result.Fail(ex.Message);
}
}
private string? _lastSentPageId;
public async Task<Result> UpdateProgressAsync(string pageId)
{
if (pageId == _lastSentPageId) return Result.Ok();
// Proper trailing-edge debounce
_debounceCts?.Cancel();
_debounceCts = new CancellationTokenSource();
var token = _debounceCts.Token;
_ = Task.Run(async () =>
{
try
{
await Task.Delay(2000, token);
if (!_isInitialized) await InitializeAsync();
if (_hubConnection?.State == HubConnectionState.Connected)
{
await _hubConnection.SendAsync("UpdateProgress", pageId, token);
_lastSentPageId = pageId;
}
}
catch (TaskCanceledException) { /* Ignored, user kept scrolling */ }
catch (Exception ex)
{
Console.WriteLine($"[SyncService] Error sending progress: {ex.Message}");
}
}, token);
return Result.Ok();
}
public async Task DisposeAsync()
{
_debounceCts?.Cancel();
if (_hubConnection != null)
{
await _hubConnection.DisposeAsync();
}
}
async ValueTask IAsyncDisposable.DisposeAsync()
{
await DisposeAsync();
}
}
+1
View File
@@ -15,3 +15,4 @@
@using NexusReader.UI.Shared.Components.Molecules
@using NexusReader.UI.Shared.Components.Organisms
@using NexusReader.UI.Shared.Services
@using Microsoft.Extensions.Logging
+54 -1
View File
@@ -99,4 +99,57 @@ h1:focus {
color: white;
margin: 1rem;
border-radius: 8px;
}
}
/* Preloader Styles */
#app-preloader, .app-preloader {
position: fixed;
top: 0;
left: 0;
width: 100%;
height: 100%;
background: radial-gradient(circle at center, #1a1a1a 0%, var(--nexus-bg) 100%);
display: flex;
flex-direction: column;
justify-content: center;
align-items: center;
z-index: 9999;
transition: opacity 0.8s ease, visibility 0.8s;
}
#app-preloader.loaded {
opacity: 0;
visibility: hidden;
}
.preloader-spinner {
width: 80px;
height: 80px;
border: 3px solid rgba(0, 255, 153, 0.1);
border-top: 3px solid var(--nexus-neon);
border-radius: 50%;
animation: spin 1s cubic-bezier(0.4, 0, 0.2, 1) infinite;
filter: drop-shadow(0 0 10px var(--nexus-neon));
margin-bottom: 20px;
}
.preloader-text {
color: var(--nexus-neon);
font-family: var(--nexus-font-sans);
letter-spacing: 4px;
text-transform: uppercase;
font-size: 0.8rem;
font-weight: 500;
animation: pulse 2s infinite;
}
@keyframes spin {
0% { transform: rotate(0deg); }
100% { transform: rotate(360deg); }
}
@keyframes pulse {
0%, 100% { opacity: 1; transform: scale(1); }
50% { opacity: 0.5; transform: scale(0.95); }
}
@@ -122,13 +122,19 @@ export function updateData(data) {
// Update Links
link = rootGroup.select(".links-layer")
.selectAll("path")
.data(data.links, d => d.source + "-" + d.target)
.data(data.links, d => d.source + "-" + d.target + "-" + d.relationType)
.join(
enter => enter.append("path")
.attr("stroke", "rgba(255,255,255,0.05)")
.attr("stroke", d => {
if (d.relationType === 'Defines') return 'var(--nexus-accent)';
if (d.relationType === 'Next') return 'rgba(255,255,255,0.2)';
if (d.relationType === 'Contains') return 'var(--nexus-neon)';
return 'rgba(255,255,255,0.1)';
})
.attr("fill", "none")
.attr("stroke-width", 1.5)
.call(e => e.transition().duration(500).attr("stroke", "rgba(255,255,255,0.1)")),
.attr("stroke-width", d => d.relationType === 'Defines' ? 2 : 1)
.attr("stroke-dasharray", d => d.relationType === 'References' ? "5,5" : "0")
.call(e => e.transition().duration(500).attr("opacity", 1)),
update => update,
exit => exit.remove()
);
@@ -150,7 +156,12 @@ export function updateData(data) {
g.append("circle")
.attr("r", 30)
.attr("fill", "url(#nebulaGlow)")
.attr("fill", d => {
if (d.type === 'Definition') return 'var(--nexus-accent)';
if (d.type === 'Table') return 'var(--nexus-neon)';
if (d.type === 'Rule') return '#ff4444';
return "url(#nebulaGlow)";
})
.attr("opacity", 0)
.transition().duration(1000).attr("opacity", d => d.group === 'current' ? 0.6 : 0.2);
@@ -162,14 +173,18 @@ export function updateData(data) {
.attr("height", 24)
.attr("rx", 12)
.attr("fill", "rgba(20, 20, 20, 0.9)")
.attr("stroke", "rgba(255, 255, 255, 0.1)")
.attr("stroke", d => {
if (d.type === 'Definition') return 'var(--nexus-accent)';
if (d.type === 'Rule') return '#ff4444';
return "rgba(255, 255, 255, 0.1)";
})
.attr("stroke-width", 1);
g.append("text")
.text(d => d.label)
.attr("text-anchor", "middle")
.attr("y", 4)
.attr("fill", "#ccc")
.attr("fill", d => d.type === 'Definition' ? 'var(--nexus-accent)' : '#ccc')
.attr("font-size", "0.8rem");
return g;
@@ -16,7 +16,6 @@
<ItemGroup>
<ProjectReference Include="..\NexusReader.Application\NexusReader.Application.csproj" />
<ProjectReference Include="..\NexusReader.Infrastructure\NexusReader.Infrastructure.csproj" />
<ProjectReference Include="..\NexusReader.UI.Shared\NexusReader.UI.Shared.csproj" />
</ItemGroup>
+2 -3
View File
@@ -4,8 +4,7 @@ using NexusReader.Application.Abstractions.Services;
using NexusReader.Web.Client.Services;
using NexusReader.UI.Shared.Services;
using NexusReader.Application;
using NexusReader.Infrastructure;
using NexusReader.Infrastructure.Services;
var builder = WebAssemblyHostBuilder.CreateDefault(args);
@@ -19,6 +18,7 @@ builder.Services.AddScoped<IReaderNavigationService, ReaderNavigationService>();
builder.Services.AddScoped<IKnowledgeGraphService, KnowledgeGraphService>();
builder.Services.AddScoped<IReaderInteractionService, ReaderInteractionService>();
builder.Services.AddScoped<KnowledgeCoordinator>();
builder.Services.AddScoped<ISyncService, SyncService>();
// Identity & Auth Services
builder.Services.AddOptions();
@@ -34,6 +34,5 @@ builder.Services.AddScoped(sp => new HttpClient { BaseAddress = new Uri(builder.
builder.Services.AddApplication();
builder.Services.AddScoped<IEpubService, WasmEpubService>();
builder.Services.AddTransient<IAiGenerateQuizService, FakeAiGenerateQuizService>();
await builder.Build().RunAsync();
@@ -14,21 +14,65 @@ public class WasmKnowledgeService : IKnowledgeService
_httpClient = httpClient;
}
public async Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetKnowledgeAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await CallKnowledgeApiAsync("/api/knowledge", text, cancellationToken);
}
public async Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetGraphDataAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await CallKnowledgeApiAsync("/api/knowledge/graph", text, cancellationToken);
}
public async Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, CancellationToken cancellationToken = default)
public async Task<Result<KnowledgePacket>> GetKnowledgeMapAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await CallKnowledgeApiAsync("/api/knowledge/map", text, cancellationToken);
}
public async Task<Result<KnowledgePacket>> GetSummaryAndQuizAsync(string text, string tenantId, CancellationToken cancellationToken = default)
{
return await CallKnowledgeApiAsync("/api/knowledge/summary", text, cancellationToken);
}
public async Task<Result<List<RelevantContext>>> GetRelevantContextAsync(string query, string tenantId, CancellationToken cancellationToken = default)
{
try
{
var response = await _httpClient.PostAsJsonAsync("/api/knowledge/relevant", new { query, tenantId }, cancellationToken);
if (response.IsSuccessStatusCode)
{
var context = await response.Content.ReadFromJsonAsync<List<RelevantContext>>(cancellationToken: cancellationToken);
return context != null ? Result.Ok(context) : Result.Fail("Failed to deserialize relevant context.");
}
var errorBody = await response.Content.ReadAsStringAsync(cancellationToken);
return Result.Fail($"Server error ({response.StatusCode}): {errorBody}");
}
catch (Exception ex)
{
return Result.Fail(new Error($"Network error: {ex.Message}").CausedBy(ex));
}
}
public async Task<Result<GroundednessResult>> VerifyGroundednessAsync(string answer, string context, string tenantId, CancellationToken cancellationToken = default)
{
try
{
var response = await _httpClient.PostAsJsonAsync("/api/knowledge/verify-groundedness", new { answer, context, tenantId }, cancellationToken);
if (response.IsSuccessStatusCode)
{
var result = await response.Content.ReadFromJsonAsync<GroundednessResult>(cancellationToken: cancellationToken);
return result != null ? Result.Ok(result) : Result.Fail("Failed to deserialize groundedness result.");
}
var errorBody = await response.Content.ReadAsStringAsync(cancellationToken);
return Result.Fail($"Server error ({response.StatusCode}): {errorBody}");
}
catch (Exception ex)
{
return Result.Fail(new Error($"Network error: {ex.Message}").CausedBy(ex));
}
}
private async Task<Result<KnowledgePacket>> CallKnowledgeApiAsync(string endpoint, string text, CancellationToken cancellationToken)
{
try
+26 -1
View File
@@ -5,7 +5,6 @@
<meta charset="utf-8" />
<meta name="viewport" content="width=device-width, initial-scale=1.0" />
<base href="/" />
<ResourcePreloader />
<link rel="stylesheet" href="_content/NexusReader.UI.Shared/app.css" />
<link rel="stylesheet" href="NexusReader.Web.styles.css" />
<ImportMap />
@@ -14,9 +13,35 @@
</head>
<body>
<div id="app-preloader">
<div class="preloader-spinner"></div>
<div class="preloader-text">Nexus Reader</div>
</div>
<NexusReader.UI.Shared.Routes @rendermode="InteractiveAuto" />
<ReconnectModal />
<script src="_framework/blazor.web.js"></script>
<script>
(function() {
function hidePreloader() {
const preloader = document.getElementById('app-preloader');
if (preloader) {
preloader.classList.add('loaded');
// Completely remove from DOM after transition for better accessibility
setTimeout(() => preloader.style.display = 'none', 1000);
}
}
if (document.readyState === 'complete') {
hidePreloader();
} else {
window.addEventListener('load', hidePreloader);
}
// Fallback: If for some reason 'load' doesn't fire (e.g. big assets), hide after 3s anyway
setTimeout(hidePreloader, 3000);
})();
</script>
</body>
@@ -1,97 +0,0 @@
using Microsoft.AspNetCore.Identity;
using Microsoft.AspNetCore.Mvc;
using NexusReader.Domain.Entities;
using Stripe;
namespace NexusReader.Web.New.Controllers;
[Route("api/[controller]")]
[ApiController]
public class StripeWebhookController : ControllerBase
{
private readonly UserManager<NexusUser> _userManager;
private readonly IConfiguration _configuration;
private readonly string _webhookSecret;
public StripeWebhookController(UserManager<NexusUser> userManager, IConfiguration configuration)
{
_userManager = userManager;
_configuration = configuration;
_webhookSecret = _configuration["Stripe:WebhookSecret"] ?? "";
}
[HttpPost]
public async Task<IActionResult> Index()
{
var json = await new StreamReader(HttpContext.Request.Body).ReadToEndAsync();
try
{
var stripeEvent = EventUtility.ConstructEvent(
json,
Request.Headers["Stripe-Signature"],
_webhookSecret
);
switch (stripeEvent.Type)
{
case EventTypes.CheckoutSessionCompleted:
var session = stripeEvent.Data.Object as Stripe.Checkout.Session;
await HandleSubscriptionSuccess(session?.CustomerEmail, session?.Metadata);
break;
case EventTypes.CustomerSubscriptionUpdated:
var subscription = stripeEvent.Data.Object as Stripe.Subscription;
// Subscription update might not have email directly, would need to fetch customer
// For now, assuming email is in metadata if we set it during checkout
await HandleSubscriptionSuccess(subscription?.Metadata["CustomerEmail"], subscription?.Metadata);
break;
case EventTypes.CustomerSubscriptionDeleted:
var deletedSubscription = stripeEvent.Data.Object as Stripe.Subscription;
await HandleSubscriptionCancellation(deletedSubscription?.Metadata["CustomerEmail"]);
break;
}
return Ok();
}
catch (StripeException e)
{
return BadRequest(e.Message);
}
}
private async Task HandleSubscriptionSuccess(string? email, Dictionary<string, string>? metadata)
{
if (string.IsNullOrEmpty(email)) return;
var user = await _userManager.FindByEmailAsync(email);
if (user != null)
{
var plan = metadata != null && metadata.ContainsKey("Plan") ? metadata["Plan"] : "Pro";
user.CurrentPlan = plan;
user.AITokenLimit = plan.ToLower() switch
{
"pro" => 50000,
"enterprise" => 500000,
_ => 10000 // default for unknown or free
};
await _userManager.UpdateAsync(user);
}
}
private async Task HandleSubscriptionCancellation(string? email)
{
if (string.IsNullOrEmpty(email)) return;
var user = await _userManager.FindByEmailAsync(email);
if (user != null)
{
user.CurrentPlan = "Free";
user.AITokenLimit = 5000; // Free tier limit
await _userManager.UpdateAsync(user);
}
}
}
+208 -49
View File
@@ -2,6 +2,7 @@ using NexusReader.Web.Components;
using NexusReader.Application;
using NexusReader.Infrastructure;
using NexusReader.Application.Abstractions.Services;
using NexusReader.Application.DTOs.User;
using NexusReader.Web.Client.Services;
using NexusReader.UI.Shared.Services;
using NexusReader.Domain.Entities;
@@ -14,6 +15,7 @@ using NexusReader.Infrastructure.Identity;
using Microsoft.AspNetCore.Authentication;
using System.Security.Claims;
using NexusReader.Infrastructure.Services;
using Stripe;
AppContext.SetSwitch("Npgsql.EnableLegacyTimestampBehavior", true);
@@ -24,14 +26,14 @@ builder.Services.AddRazorComponents()
.AddInteractiveServerComponents()
.AddInteractiveWebAssemblyComponents();
builder.Services.AddControllers();
// Enable detailed circuit errors for ServerSide Blazor components
builder.Services.AddServerSideBlazor()
.AddCircuitOptions(options =>
{
options.DetailedErrors = true;
});
builder.Services.AddSignalR();
builder.Services.AddHttpContextAccessor();
builder.Services.AddScoped<IPlatformService, WebPlatformService>();
builder.Services.AddScoped<INativeStorageService, NexusReader.UI.Shared.Services.WebStorageService>();
@@ -42,6 +44,7 @@ builder.Services.AddScoped<IReaderNavigationService, ReaderNavigationService>();
builder.Services.AddScoped<IKnowledgeGraphService, KnowledgeGraphService>();
builder.Services.AddScoped<IReaderInteractionService, ReaderInteractionService>();
builder.Services.AddScoped<KnowledgeCoordinator>();
builder.Services.AddScoped<ISyncService, SyncService>();
builder.Services.AddHttpClient("NexusAPI", client =>
{
@@ -49,7 +52,7 @@ builder.Services.AddHttpClient("NexusAPI", client =>
});
builder.Services.AddScoped(sp => sp.GetRequiredService<IHttpClientFactory>().CreateClient("NexusAPI"));
builder.Services.AddScoped<IIdentityService, IdentityService>();
builder.Services.AddScoped<IIdentityService, NexusReader.UI.Shared.Services.IdentityService>();
builder.Services.AddScoped<NexusAuthenticationStateProvider>();
builder.Services.AddScoped<AuthenticationStateProvider>(sp => sp.GetRequiredService<NexusAuthenticationStateProvider>());
builder.Services.AddCascadingAuthenticationState();
@@ -57,16 +60,19 @@ builder.Services.AddCascadingAuthenticationState();
builder.Services.AddApplication();
builder.Services.AddInfrastructure(builder.Configuration);
builder.Services.AddMediatR(cfg => cfg.RegisterServicesFromAssemblies(
NexusReader.Application.DependencyInjection.Assembly,
NexusReader.Infrastructure.DependencyInjection.Assembly
));
// Authorization Policies
builder.Services.AddScoped<IAuthorizationHandler, TokenLimitHandler>();
builder.Services.AddAuthorization(options =>
{
options.AddPolicy("ProUser", policy => policy.RequireClaim("Plan", "Pro", "Enterprise"));
options.AddPolicy("HasAvailableTokens", policy => policy.AddRequirements(new TokenLimitRequirement()));
});
builder.Services.AddAuthorizationBuilder()
.AddPolicy("ProUser", policy => policy.RequireClaim("Plan", SubscriptionPlan.ProName, SubscriptionPlan.EnterpriseName))
.AddPolicy("HasAvailableTokens", policy => policy.AddRequirements(new TokenLimitRequirement()));
// Billing & Stripe
builder.Services.AddScoped<IBillingService, BillingService>();
builder.Services.AddScoped<IBillingService, NexusReader.Infrastructure.Services.BillingService>();
// Authentication
builder.Services.AddAuthentication(options =>
@@ -81,6 +87,7 @@ builder.Services.AddAuthentication(options =>
});
builder.Services.AddIdentityApiEndpoints<NexusUser>()
.AddRoles<IdentityRole>()
.AddEntityFrameworkStores<AppDbContext>();
builder.Services.ConfigureApplicationCookie(options =>
@@ -113,11 +120,63 @@ builder.Services.Configure<IdentityOptions>(options =>
var app = builder.Build();
// Ensure Database is initialized
// Startup Validation
using (var scope = app.Services.CreateScope())
{
var dbContext = scope.ServiceProvider.GetRequiredService<NexusReader.Infrastructure.Persistence.AppDbContext>();
await dbContext.Database.MigrateAsync();
var marker = scope.ServiceProvider.GetService<IInfrastructureMarker>();
if (marker == null)
{
throw new InvalidOperationException("CRITICAL: Infrastructure layer was not registered. Ensure AddInfrastructure() is called in Program.cs.");
}
}
// Ensure Database is initialized and seeded
using (var scope = app.Services.CreateScope())
{
var services = scope.ServiceProvider;
var logger = services.GetRequiredService<ILogger<Program>>();
var dbContext = services.GetRequiredService<NexusReader.Infrastructure.Persistence.AppDbContext>();
int maxRetries = 5;
int delayMs = 2000;
for (int i = 0; i < maxRetries; i++)
{
try
{
if (logger.IsEnabled(LogLevel.Information))
{
logger.LogInformation("Próba połączenia z bazą danych (próba {Attempt}/{MaxRetries})...", i + 1, maxRetries);
}
await dbContext.Database.MigrateAsync();
await DbInitializer.SeedAsync(services);
if (logger.IsEnabled(LogLevel.Information))
{
logger.LogInformation("Baza danych zainicjowana pomyślnie.");
}
break;
}
catch (Npgsql.NpgsqlException ex) when (i < maxRetries - 1)
{
if (logger.IsEnabled(LogLevel.Warning))
{
logger.LogWarning(ex, "Błąd połączenia z bazą danych. Ponowna próba za {Delay}ms...", delayMs);
}
await Task.Delay(delayMs);
delayMs *= 2; // Exponential backoff
}
catch (Exception ex)
{
if (logger.IsEnabled(LogLevel.Critical))
{
logger.LogCritical(ex, "Krytyczny błąd podczas inicjalizacji bazy danych.");
}
throw;
}
}
}
// Configure the HTTP request pipeline.
@@ -141,7 +200,7 @@ app.UseAntiforgery();
app.UseAuthentication();
app.UseAuthorization();
app.MapStaticAssets();
app.MapControllers();
app.MapHub<NexusReader.Infrastructure.RealTime.SyncHub>("/synchub");
// API endpoint for WASM client to fetch EPUB content
app.MapGet("/api/epub/{index}", async (int index, IEpubService epubService) =>
@@ -149,40 +208,137 @@ app.MapGet("/api/epub/{index}", async (int index, IEpubService epubService) =>
var result = await epubService.GetEpubContentAsync(index);
if (result.IsSuccess) return Results.Ok(result.Value);
var errorMsg = result.Errors.FirstOrDefault()?.Message ?? "Unknown server error";
var errorMsg = result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error";
return Results.BadRequest(errorMsg);
});
}).RequireAuthorization();
app.MapPost("/api/knowledge", async (KnowledgeRequest request, IKnowledgeService knowledgeService) =>
var knowledgeApi = app.MapGroup("/api/knowledge").RequireAuthorization("HasAvailableTokens");
knowledgeApi.MapPost("/", async (KnowledgeRequest request, ClaimsPrincipal user, IKnowledgeService knowledgeService) =>
{
var result = await knowledgeService.GetKnowledgeAsync(request.Text);
var tenantId = user.FindFirstValue("TenantId") ?? "global";
var result = await knowledgeService.GetKnowledgeAsync(request.Text, tenantId);
if (result.IsSuccess) return Results.Ok(result.Value);
return Results.BadRequest(result.Errors.FirstOrDefault()?.Message ?? "Unknown server error");
return Results.BadRequest(result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error");
});
app.MapPost("/api/knowledge/graph", async (KnowledgeRequest request, IKnowledgeService knowledgeService) =>
knowledgeApi.MapPost("/graph", async (KnowledgeRequest request, ClaimsPrincipal user, IKnowledgeService knowledgeService) =>
{
var result = await knowledgeService.GetGraphDataAsync(request.Text);
var tenantId = user.FindFirstValue("TenantId") ?? "global";
var result = await knowledgeService.GetGraphDataAsync(request.Text, tenantId);
if (result.IsSuccess) return Results.Ok(result.Value);
return Results.BadRequest(result.Errors.FirstOrDefault()?.Message ?? "Unknown server error");
return Results.BadRequest(result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error");
});
app.MapPost("/api/knowledge/summary", async (KnowledgeRequest request, IKnowledgeService knowledgeService) =>
knowledgeApi.MapPost("/summary", async (KnowledgeRequest request, ClaimsPrincipal user, IKnowledgeService knowledgeService) =>
{
var result = await knowledgeService.GetSummaryAndQuizAsync(request.Text);
var tenantId = user.FindFirstValue("TenantId") ?? "global";
var result = await knowledgeService.GetSummaryAndQuizAsync(request.Text, tenantId);
if (result.IsSuccess) return Results.Ok(result.Value);
return Results.BadRequest(result.Errors.FirstOrDefault()?.Message ?? "Unknown server error");
return Results.BadRequest(result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error");
});
app.MapDelete("/api/knowledge", async (IKnowledgeService knowledgeService) =>
knowledgeApi.MapPost("/verify-groundedness", async (GroundednessRequest request, ClaimsPrincipal user, IKnowledgeService knowledgeService) =>
{
var tenantId = user.FindFirstValue("TenantId") ?? "global";
var result = await knowledgeService.VerifyGroundednessAsync(request.Answer, request.Context, tenantId);
if (result.IsSuccess) return Results.Ok(result.Value);
return Results.BadRequest(result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error");
});
knowledgeApi.MapDelete("/", async (IKnowledgeService knowledgeService) =>
{
var result = await knowledgeService.ClearCacheAsync();
if (result.IsSuccess) return Results.Ok();
var errorMsg = result.Errors.FirstOrDefault()?.Message ?? "Unknown server error";
var errorMsg = result.Errors.Count > 0 ? result.Errors[0].Message : "Unknown server error";
return Results.BadRequest(errorMsg);
});
app.MapPost("/api/StripeWebhook", async (
HttpContext context,
UserManager<NexusUser> userManager,
IConfiguration configuration,
IDbContextFactory<AppDbContext> dbContextFactory) =>
{
using var dbContext = await dbContextFactory.CreateDbContextAsync();
var json = await new StreamReader(context.Request.Body).ReadToEndAsync();
var webhookSecret = configuration["Stripe:WebhookSecret"] ?? "";
try
{
var stripeEvent = EventUtility.ConstructEvent(
json,
context.Request.Headers["Stripe-Signature"],
webhookSecret
);
switch (stripeEvent.Type)
{
case EventTypes.CheckoutSessionCompleted:
var session = stripeEvent.Data.Object as Stripe.Checkout.Session;
await HandleSubscriptionSuccess(session?.CustomerEmail, session?.Metadata, userManager, dbContext);
break;
case EventTypes.CustomerSubscriptionUpdated:
var subscription = stripeEvent.Data.Object as Stripe.Subscription;
await HandleSubscriptionSuccess(subscription?.Metadata["CustomerEmail"], subscription?.Metadata, userManager, dbContext);
break;
case EventTypes.CustomerSubscriptionDeleted:
var deletedSubscription = stripeEvent.Data.Object as Stripe.Subscription;
await HandleSubscriptionCancellation(deletedSubscription?.Metadata["CustomerEmail"], userManager, dbContext);
break;
}
return Results.Ok();
}
catch (StripeException e)
{
return Results.BadRequest(e.Message);
}
});
async Task HandleSubscriptionSuccess(
string? email,
Dictionary<string, string>? metadata,
UserManager<NexusUser> userManager,
AppDbContext dbContext)
{
if (string.IsNullOrEmpty(email)) return;
var user = await userManager.FindByEmailAsync(email);
if (user != null)
{
var planName = metadata?.GetValueOrDefault("Plan") ?? SubscriptionPlan.ProName;
var plan = await dbContext.SubscriptionPlans.FirstOrDefaultAsync(p => p.PlanName == planName);
if (plan != null)
{
user.SubscriptionPlanId = plan.Id;
user.AITokenLimit = plan.AITokenLimit;
}
await userManager.UpdateAsync(user);
}
}
async Task HandleSubscriptionCancellation(
string? email,
UserManager<NexusUser> userManager,
AppDbContext dbContext)
{
if (string.IsNullOrEmpty(email)) return;
var user = await userManager.FindByEmailAsync(email);
if (user != null)
{
var freePlan = await dbContext.SubscriptionPlans.FindAsync(SubscriptionPlan.FreeId);
user.SubscriptionPlanId = SubscriptionPlan.FreeId;
user.AITokenLimit = freePlan?.AITokenLimit ?? 5000;
await userManager.UpdateAsync(user);
}
}
app.MapGroup("/identity").MapIdentityApi<NexusUser>();
app.MapGet("/identity/login/google", (string? returnUrl) =>
@@ -226,36 +382,38 @@ app.MapGet("/identity/callback/google", async (
return Results.Redirect("/account/login?error=ProvisioningFailed");
});
app.MapGet("/identity/profile", async (ClaimsPrincipal user, UserManager<NexusUser> userManager, AppDbContext dbContext) =>
app.MapGet("/identity/profile", async (ClaimsPrincipal user, UserManager<NexusUser> userManager, IDbContextFactory<AppDbContext> dbContextFactory) =>
{
var userId = user.FindFirstValue(ClaimTypes.NameIdentifier);
if (userId == null) return Results.Unauthorized();
var nexusUser = await dbContext.Users
.Include(u => u.Ebooks)
.Include(u => u.QuizResults)
.FirstOrDefaultAsync(u => u.Id == userId);
using var dbContext = await dbContextFactory.CreateDbContextAsync();
if (nexusUser == null) return Results.NotFound();
var profile = await dbContext.Users
.Where(u => u.Id == userId)
.Select(u => new UserProfileDto
{
Email = u.Email ?? string.Empty,
AITokensUsed = u.AITokensUsed,
Plan = u.SubscriptionPlan != null ? new SubscriptionPlanDto
{
Id = u.SubscriptionPlan.Id,
Name = u.SubscriptionPlan.PlanName,
AITokenLimit = u.SubscriptionPlan.AITokenLimit,
MonthlyPrice = u.SubscriptionPlan.MonthlyPrice
} : new SubscriptionPlanDto(),
AverageQuizScore = u.QuizResults.Any() ? (int)u.QuizResults.Average(q => q.Percentage) : 0,
LastReadBook = u.Ebooks.OrderByDescending(e => e.LastReadDate).Select(e => new LastReadBookDto
{
Id = e.Id,
Title = e.Title
}).FirstOrDefault()
})
.FirstOrDefaultAsync();
var avgScore = nexusUser.QuizResults.Any()
? (int)nexusUser.QuizResults.Average(q => q.Percentage)
: 0;
var lastReadBook = nexusUser.Ebooks
.OrderByDescending(e => e.LastReadDate)
.FirstOrDefault()?.Title ?? "None";
if (profile == null) return Results.NotFound();
return Results.Ok(new
{
nexusUser.Email,
nexusUser.AITokenLimit,
nexusUser.AITokensUsed,
nexusUser.CurrentPlan,
nexusUser.TenantId,
AverageQuizScore = avgScore,
LastReadBookTitle = lastReadBook
});
return Results.Ok(profile);
}).RequireAuthorization();
app.MapRazorComponents<App>()
@@ -266,3 +424,4 @@ app.MapRazorComponents<App>()
app.Run();
public record KnowledgeRequest(string Text);
public record GroundednessRequest(string Answer, string Context);
+8 -3
View File
@@ -1,7 +1,10 @@
{
"Stripe": {
"ApiKey": "sk_test_placeholder",
"WebhookSecret": "whsec_placeholder"
"WebhookSecret": "whsec_placeholder",
"ProProductId": "prod_Pro123",
"BasicProductId": "prod_Basic456",
"FreeProductId": "prod_Free789"
},
"Logging": {
"LogLevel": {
@@ -24,7 +27,9 @@
"Google": {
"ApiKey": "PLACEHOLDER",
"Model": "gemini-2.5-flash-lite",
"MaxInputTokens": 15000,
"MaxOutputTokens": 8192
}
}
}
},
"ApiBaseUrl": "http://localhost:5000"
}
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