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Ecriture de tests unitaires coté java pour améliorer la stabilité de l'application

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IETM_FIXE\ietm6
2026-04-22 07:46:24 +02:00
parent 49a82d05f7
commit 63a3c21bd2
56 changed files with 5175 additions and 298 deletions
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270
core/src/main/java/com/loremind/infrastructure/ai/BrainAiChatClient.java
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@@ -1,17 +1,7 @@
package com.loremind.infrastructure.ai;
import com.loremind.domain.generationcontext.CampaignStructuralContext;
import com.loremind.domain.generationcontext.CampaignStructuralContext.ArcSummary;
import com.loremind.domain.generationcontext.CampaignStructuralContext.BranchHint;
import com.loremind.domain.generationcontext.CampaignStructuralContext.ChapterSummary;
import com.loremind.domain.generationcontext.CampaignStructuralContext.SceneSummary;
import com.loremind.domain.generationcontext.ChatMessage;
import com.loremind.domain.generationcontext.ChatRequest;
import com.loremind.domain.generationcontext.ChatUsage;
import com.loremind.domain.generationcontext.LoreStructuralContext;
import com.loremind.domain.generationcontext.LoreStructuralContext.PageSummary;
import com.loremind.domain.generationcontext.NarrativeEntityContext;
import com.loremind.domain.generationcontext.PageContext;
import com.loremind.domain.generationcontext.ports.AiChatProvider;
import com.loremind.domain.generationcontext.ports.AiProviderException;
import org.springframework.beans.factory.annotation.Value;
@@ -23,25 +13,21 @@ import org.springframework.web.reactive.function.client.WebClient;
import reactor.core.publisher.Flux;
import java.time.Duration;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.function.Consumer;
import java.util.stream.Collectors;
/**
* Adapter de sortie (Architecture Hexagonale) : implémente AiChatProvider
* en appelant le Brain Python via WebClient + SSE (Server-Sent Events).
* <p>
* Responsabilités :
* 1. Traduire ChatRequest (domaine) -> JSON attendu par /chat/stream.
* Sérialise lore_context, page_context, campaign_context et
* narrative_entity de façon conditionnelle selon le scénario d'appel
* (chat Lore / chat Lore focalisé page / chat Campagne / chat Campagne
* focalisé arc-chapter-scene).
* 2. Consommer le flux SSE token par token.
* 3. Invoquer onToken / onComplete / onError au bon moment.
* 4. Traduire toute erreur technique en AiProviderException.
* Responsabilités (après extraction) :
* 1. Transport HTTP + consommation du flux SSE.
* 2. Dispatch des évènements SSE (data / done / error / usage).
* 3. Traduction des erreurs techniques en AiProviderException.
* <p>
* Les responsabilités auxiliaires sont déléguées :
* - Construction du payload JSON : {@link BrainChatPayloadBuilder}.
* - Parsing des payloads SSE : {@link BrainSseParser}.
* <p>
* Le domaine ne voit JAMAIS WebClient, Flux, ni la moindre URL.
*/
@@ -53,11 +39,17 @@ public class BrainAiChatClient implements AiChatProvider {
new ParameterizedTypeReference<>() {};
private final WebClient webClient;
private final BrainChatPayloadBuilder payloadBuilder;
private final BrainSseParser sseParser;
public BrainAiChatClient(
WebClient.Builder builder,
@Value("${brain.base-url}") String baseUrl) {
@Value("${brain.base-url}") String baseUrl,
BrainChatPayloadBuilder payloadBuilder,
BrainSseParser sseParser) {
this.webClient = builder.baseUrl(baseUrl).build();
this.payloadBuilder = payloadBuilder;
this.sseParser = sseParser;
}
@Override
@@ -68,7 +60,7 @@ public class BrainAiChatClient implements AiChatProvider {
Runnable onComplete,
Consumer<Throwable> onError) {
Map<String, Object> payload = toPayload(request);
Map<String, Object> payload = payloadBuilder.build(request);
Flux<ServerSentEvent<String>> flux = webClient.post()
.uri(CHAT_STREAM_PATH)
@@ -92,13 +84,13 @@ public class BrainAiChatClient implements AiChatProvider {
}
}
/** Dispatch selon le type d'événement SSE (data par défaut, done, error, usage). */
/** Dispatch selon le type d'évènement SSE (data par défaut, done, error, usage). */
private void handleEvent(
ServerSentEvent<String> sse,
Consumer<ChatUsage> onUsage,
Consumer<String> onToken,
Consumer<Throwable> onError) {
String event = sse.event(); // null si pas d'event: xxx -> c'est un data par défaut
String event = sse.event(); // null si pas d'event: xxx -> data par défaut
String data = sse.data();
if ("error".equals(event)) {
@@ -107,235 +99,17 @@ public class BrainAiChatClient implements AiChatProvider {
return;
}
if ("done".equals(event)) {
return; // la fin est gérée par blockLast + onComplete
return; // fin gérée par blockLast + onComplete
}
if ("usage".equals(event)) {
ChatUsage usage = extractUsage(data);
ChatUsage usage = sseParser.parseUsage(data);
if (usage != null) onUsage.accept(usage);
return;
}
// Défaut : événement data avec JSON {"token":"..."}.
String token = extractToken(data);
// Défaut : évènement data avec JSON {"token":"..."}.
String token = sseParser.parseToken(data);
if (token != null && !token.isEmpty()) {
onToken.accept(token);
}
}
/**
* Parse un JSON {"system":N,"history":N,"current":N,"max":N} en ChatUsage.
* Renvoie null si le payload est illisible — dans ce cas on ne propage
* simplement pas d'usage, le stream token continue normalement.
*/
private ChatUsage extractUsage(String json) {
if (json == null) return null;
try {
int system = extractIntField(json, "system");
int history = extractIntField(json, "history");
int current = extractIntField(json, "current");
int max = extractIntField(json, "max");
return new ChatUsage(system, history, current, max);
} catch (Exception e) {
return null;
}
}
/** Parse minimaliste d'un champ entier JSON sans dépendre de Jackson. */
private int extractIntField(String json, String field) {
String needle = "\"" + field + "\"";
int idx = json.indexOf(needle);
if (idx < 0) return 0;
int colon = json.indexOf(':', idx);
if (colon < 0) return 0;
int start = colon + 1;
while (start < json.length() && Character.isWhitespace(json.charAt(start))) start++;
int end = start;
while (end < json.length() && (Character.isDigit(json.charAt(end)) || json.charAt(end) == '-')) end++;
if (end == start) return 0;
return Integer.parseInt(json.substring(start, end));
}
/**
* Parse minimaliste du JSON {"token":"..."} sans pull Jackson ici.
* Si le format se complexifie, on remplacera par un DTO Jackson.
*/
private String extractToken(String json) {
if (json == null) return null;
int idx = json.indexOf("\"token\"");
if (idx < 0) return null;
int colon = json.indexOf(':', idx);
int firstQuote = json.indexOf('"', colon + 1);
int lastQuote = json.lastIndexOf('"');
if (firstQuote < 0 || lastQuote <= firstQuote) return null;
return json.substring(firstQuote + 1, lastQuote)
.replace("\\n", "\n")
.replace("\\\"", "\"")
.replace("\\\\", "\\");
}
// --- Construction du payload JSON vers le Brain -------------------------
/**
* Construit le payload JSON. Chaque contexte optionnel est omis s'il est
* null, pour s'aligner sur le schéma Pydantic côté Brain (champs
* Optional qui restent absents du dict transmis au LLM).
*/
private Map<String, Object> toPayload(ChatRequest request) {
Map<String, Object> root = new LinkedHashMap<>();
root.put("messages", request.getMessages().stream()
.map(this::messageToMap)
.collect(Collectors.toList()));
if (request.getLoreContext() != null) {
root.put("lore_context", loreContextToMap(request.getLoreContext()));
}
if (request.getPageContext() != null) {
root.put("page_context", pageContextToMap(request.getPageContext()));
}
if (request.getCampaignContext() != null) {
root.put("campaign_context", campaignContextToMap(request.getCampaignContext()));
}
if (request.getNarrativeEntity() != null) {
root.put("narrative_entity", narrativeEntityToMap(request.getNarrativeEntity()));
}
return root;
}
private Map<String, Object> messageToMap(ChatMessage m) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("role", m.role());
map.put("content", m.content());
return map;
}
private Map<String, Object> loreContextToMap(LoreStructuralContext ctx) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("lore_name", ctx.getLoreName());
map.put("lore_description", ctx.getLoreDescription());
Map<String, Object> foldersMap = new LinkedHashMap<>();
for (Map.Entry<String, List<PageSummary>> e : ctx.getFolders().entrySet()) {
foldersMap.put(e.getKey(), e.getValue().stream()
.map(this::pageSummaryToMap)
.collect(Collectors.toList()));
}
map.put("folders", foldersMap);
map.put("tags", ctx.getTags());
return map;
}
private Map<String, Object> pageSummaryToMap(PageSummary ps) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("title", ps.getTitle());
map.put("template_name", ps.getTemplateName());
// values/tags/related_page_titles ne sont sérialisés que s'ils contiennent
// de l'info — payload réseau plus léger quand la page est vierge.
if (ps.getValues() != null && !ps.getValues().isEmpty()) {
map.put("values", ps.getValues());
}
if (ps.getTags() != null && !ps.getTags().isEmpty()) {
map.put("tags", ps.getTags());
}
if (ps.getRelatedPageTitles() != null && !ps.getRelatedPageTitles().isEmpty()) {
map.put("related_page_titles", ps.getRelatedPageTitles());
}
return map;
}
private Map<String, Object> pageContextToMap(PageContext pc) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("title", pc.getTitle());
map.put("template_name", pc.getTemplateName());
map.put("template_fields", pc.getTemplateFields());
map.put("values", pc.getValues());
return map;
}
private Map<String, Object> campaignContextToMap(CampaignStructuralContext ctx) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("campaign_name", ctx.getCampaignName());
map.put("campaign_description", ctx.getCampaignDescription());
map.put("arcs", ctx.getArcs().stream()
.map(this::arcSummaryToMap)
.collect(Collectors.toList()));
return map;
}
/**
* Helper generic pour serialiser les entites structurelles (Arc/Chapter/Scene)
* avec name, description et illustration_count conditionnel.
*/
private <T> Map<String, Object> structuralSummaryToMap(
T entity,
java.util.function.Function<T, String> nameExtractor,
java.util.function.Function<T, String> descriptionExtractor,
java.util.function.Function<T, Integer> illustrationCountExtractor,
java.util.function.BiConsumer<Map<String, Object>, T> childSerializer) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("name", nameExtractor.apply(entity));
map.put("description", descriptionExtractor.apply(entity));
// Envoye au Python pour enrichir le prompt ("N illustrations attachees").
// Serialise uniquement si > 0 pour economiser le payload sur les entites sans images.
if (illustrationCountExtractor.apply(entity) > 0) {
map.put("illustration_count", illustrationCountExtractor.apply(entity));
}
childSerializer.accept(map, entity);
return map;
}
private Map<String, Object> arcSummaryToMap(ArcSummary a) {
return structuralSummaryToMap(
a,
ArcSummary::getName,
ArcSummary::getDescription,
ArcSummary::getIllustrationCount,
(map, arc) -> map.put("chapters", arc.getChapters().stream()
.map(this::chapterSummaryToMap)
.collect(Collectors.toList())));
}
private Map<String, Object> chapterSummaryToMap(ChapterSummary c) {
return structuralSummaryToMap(
c,
ChapterSummary::getName,
ChapterSummary::getDescription,
ChapterSummary::getIllustrationCount,
(map, chapter) -> map.put("scenes", chapter.getScenes().stream()
.map(this::sceneSummaryToMap)
.collect(Collectors.toList())));
}
private Map<String, Object> sceneSummaryToMap(SceneSummary s) {
return structuralSummaryToMap(
s,
SceneSummary::getName,
SceneSummary::getDescription,
SceneSummary::getIllustrationCount,
(map, scene) -> {
// Branches narratives : serialise uniquement si presentes, pour garder
// un payload leger sur les scenes lineaires classiques.
if (s.getBranches() != null && !s.getBranches().isEmpty()) {
map.put("branches", s.getBranches().stream()
.map(this::branchHintToMap)
.collect(Collectors.toList()));
}
});
}
private Map<String, Object> branchHintToMap(BranchHint b) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("label", b.getLabel());
map.put("target_scene_name", b.getTargetSceneName());
if (b.getCondition() != null && !b.getCondition().isBlank()) {
map.put("condition", b.getCondition());
}
return map;
}
private Map<String, Object> narrativeEntityToMap(NarrativeEntityContext ne) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("entity_type", ne.getEntityType());
map.put("title", ne.getTitle());
map.put("fields", ne.getFields());
return map;
}
}

192
core/src/main/java/com/loremind/infrastructure/ai/BrainChatPayloadBuilder.java Normal file
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@@ -0,0 +1,192 @@
package com.loremind.infrastructure.ai;
import com.loremind.domain.generationcontext.CampaignStructuralContext;
import com.loremind.domain.generationcontext.CampaignStructuralContext.ArcSummary;
import com.loremind.domain.generationcontext.CampaignStructuralContext.BranchHint;
import com.loremind.domain.generationcontext.CampaignStructuralContext.ChapterSummary;
import com.loremind.domain.generationcontext.CampaignStructuralContext.SceneSummary;
import com.loremind.domain.generationcontext.ChatMessage;
import com.loremind.domain.generationcontext.ChatRequest;
import com.loremind.domain.generationcontext.LoreStructuralContext;
import com.loremind.domain.generationcontext.LoreStructuralContext.PageSummary;
import com.loremind.domain.generationcontext.NarrativeEntityContext;
import com.loremind.domain.generationcontext.PageContext;
import org.springframework.stereotype.Component;
import java.util.LinkedHashMap;
import java.util.List;
import java.util.Map;
import java.util.function.BiConsumer;
import java.util.function.Function;
import java.util.stream.Collectors;
/**
* Helper d'infrastructure : traduit un ChatRequest (domaine) vers le dict JSON
* attendu par le Brain Python (/chat/stream).
* <p>
* Extrait de BrainAiChatClient pour isoler la responsabilité "sérialisation
* de payload" (SRP) — le client HTTP se concentre désormais uniquement sur le
* transport et le streaming SSE.
* <p>
* Chaque contexte optionnel (lore, page, campaign, entité narrative) est omis
* si null, pour s'aligner sur le schéma Pydantic (champs Optional absents).
*/
@Component
public class BrainChatPayloadBuilder {
public Map<String, Object> build(ChatRequest request) {
Map<String, Object> root = new LinkedHashMap<>();
root.put("messages", request.getMessages().stream()
.map(this::messageToMap)
.collect(Collectors.toList()));
if (request.getLoreContext() != null) {
root.put("lore_context", loreContextToMap(request.getLoreContext()));
}
if (request.getPageContext() != null) {
root.put("page_context", pageContextToMap(request.getPageContext()));
}
if (request.getCampaignContext() != null) {
root.put("campaign_context", campaignContextToMap(request.getCampaignContext()));
}
if (request.getNarrativeEntity() != null) {
root.put("narrative_entity", narrativeEntityToMap(request.getNarrativeEntity()));
}
return root;
}
private Map<String, Object> messageToMap(ChatMessage m) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("role", m.role());
map.put("content", m.content());
return map;
}
private Map<String, Object> loreContextToMap(LoreStructuralContext ctx) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("lore_name", ctx.getLoreName());
map.put("lore_description", ctx.getLoreDescription());
Map<String, Object> foldersMap = new LinkedHashMap<>();
for (Map.Entry<String, List<PageSummary>> e : ctx.getFolders().entrySet()) {
foldersMap.put(e.getKey(), e.getValue().stream()
.map(this::pageSummaryToMap)
.collect(Collectors.toList()));
}
map.put("folders", foldersMap);
map.put("tags", ctx.getTags());
return map;
}
private Map<String, Object> pageSummaryToMap(PageSummary ps) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("title", ps.getTitle());
map.put("template_name", ps.getTemplateName());
// values/tags/related_page_titles : omis si vides pour alléger le payload.
if (ps.getValues() != null && !ps.getValues().isEmpty()) {
map.put("values", ps.getValues());
}
if (ps.getTags() != null && !ps.getTags().isEmpty()) {
map.put("tags", ps.getTags());
}
if (ps.getRelatedPageTitles() != null && !ps.getRelatedPageTitles().isEmpty()) {
map.put("related_page_titles", ps.getRelatedPageTitles());
}
return map;
}
private Map<String, Object> pageContextToMap(PageContext pc) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("title", pc.getTitle());
map.put("template_name", pc.getTemplateName());
map.put("template_fields", pc.getTemplateFields());
map.put("values", pc.getValues());
return map;
}
private Map<String, Object> campaignContextToMap(CampaignStructuralContext ctx) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("campaign_name", ctx.getCampaignName());
map.put("campaign_description", ctx.getCampaignDescription());
map.put("arcs", ctx.getArcs().stream()
.map(this::arcSummaryToMap)
.collect(Collectors.toList()));
return map;
}
/**
* Helper générique pour sérialiser les entités structurelles (Arc/Chapter/Scene)
* avec name, description et illustration_count conditionnel.
*/
private <T> Map<String, Object> structuralSummaryToMap(
T entity,
Function<T, String> nameExtractor,
Function<T, String> descriptionExtractor,
Function<T, Integer> illustrationCountExtractor,
BiConsumer<Map<String, Object>, T> childSerializer) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("name", nameExtractor.apply(entity));
map.put("description", descriptionExtractor.apply(entity));
if (illustrationCountExtractor.apply(entity) > 0) {
map.put("illustration_count", illustrationCountExtractor.apply(entity));
}
childSerializer.accept(map, entity);
return map;
}
private Map<String, Object> arcSummaryToMap(ArcSummary a) {
return structuralSummaryToMap(
a,
ArcSummary::getName,
ArcSummary::getDescription,
ArcSummary::getIllustrationCount,
(map, arc) -> map.put("chapters", arc.getChapters().stream()
.map(this::chapterSummaryToMap)
.collect(Collectors.toList())));
}
private Map<String, Object> chapterSummaryToMap(ChapterSummary c) {
return structuralSummaryToMap(
c,
ChapterSummary::getName,
ChapterSummary::getDescription,
ChapterSummary::getIllustrationCount,
(map, chapter) -> map.put("scenes", chapter.getScenes().stream()
.map(this::sceneSummaryToMap)
.collect(Collectors.toList())));
}
private Map<String, Object> sceneSummaryToMap(SceneSummary s) {
return structuralSummaryToMap(
s,
SceneSummary::getName,
SceneSummary::getDescription,
SceneSummary::getIllustrationCount,
(map, scene) -> {
// Branches narratives : omises si absentes (scènes linéaires classiques).
if (s.getBranches() != null && !s.getBranches().isEmpty()) {
map.put("branches", s.getBranches().stream()
.map(this::branchHintToMap)
.collect(Collectors.toList()));
}
});
}
private Map<String, Object> branchHintToMap(BranchHint b) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("label", b.getLabel());
map.put("target_scene_name", b.getTargetSceneName());
if (b.getCondition() != null && !b.getCondition().isBlank()) {
map.put("condition", b.getCondition());
}
return map;
}
private Map<String, Object> narrativeEntityToMap(NarrativeEntityContext ne) {
Map<String, Object> map = new LinkedHashMap<>();
map.put("entity_type", ne.getEntityType());
map.put("title", ne.getTitle());
map.put("fields", ne.getFields());
return map;
}
}

67
core/src/main/java/com/loremind/infrastructure/ai/BrainSseParser.java Normal file
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@@ -0,0 +1,67 @@
package com.loremind.infrastructure.ai;
import com.loremind.domain.generationcontext.ChatUsage;
import org.springframework.stereotype.Component;
/**
* Helper d'infrastructure : parse les payloads JSON véhiculés dans les
* évènements SSE reçus du Brain Python.
* <p>
* Implémentation volontairement minimaliste (pas de Jackson ici) car les
* schémas attendus sont figés et simples : {"token":"..."} et
* {"system":N,"history":N,"current":N,"max":N}. Si la complexité augmente,
* remplacer par un ObjectMapper + DTOs.
*/
@Component
public class BrainSseParser {
/**
* Parse un JSON {"system":N,"history":N,"current":N,"max":N} en ChatUsage.
* Renvoie null si le payload est illisible — l'appelant décidera de ne
* simplement pas propager l'usage (le stream token continue).
*/
public ChatUsage parseUsage(String json) {
if (json == null) return null;
try {
int system = extractIntField(json, "system");
int history = extractIntField(json, "history");
int current = extractIntField(json, "current");
int max = extractIntField(json, "max");
return new ChatUsage(system, history, current, max);
} catch (Exception e) {
return null;
}
}
/**
* Parse {"token":"..."} et renvoie la valeur du champ token (chaîne vide
* ou null si introuvable).
*/
public String parseToken(String json) {
if (json == null) return null;
int idx = json.indexOf("\"token\"");
if (idx < 0) return null;
int colon = json.indexOf(':', idx);
int firstQuote = json.indexOf('"', colon + 1);
int lastQuote = json.lastIndexOf('"');
if (firstQuote < 0 || lastQuote <= firstQuote) return null;
return json.substring(firstQuote + 1, lastQuote)
.replace("\\n", "\n")
.replace("\\\"", "\"")
.replace("\\\\", "\\");
}
private int extractIntField(String json, String field) {
String needle = "\"" + field + "\"";
int idx = json.indexOf(needle);
if (idx < 0) return 0;
int colon = json.indexOf(':', idx);
if (colon < 0) return 0;
int start = colon + 1;
while (start < json.length() && Character.isWhitespace(json.charAt(start))) start++;
int end = start;
while (end < json.length() && (Character.isDigit(json.charAt(end)) || json.charAt(end) == '-')) end++;
if (end == start) return 0;
return Integer.parseInt(json.substring(start, end));
}
}