profile: add progressive user profiles

Add cache-expiry profile maintenance and contextual injection, reorganize runtime code by responsibility, remove automatic favorability decay, and prepare version 1.15.0.
2026-09-15 02:56:10 +08:00 · 2026-08-02 21:45:34 +08:00
parent 2ed39e9fe8
commit 23299b2ae7
59 changed files with 4799 additions and 1340 deletions
@@ -0,0 +1,140 @@
+package top.jie65535.mirai.profile
+
+import com.aallam.openai.api.chat.ChatCompletionRequest
+import com.aallam.openai.api.chat.ChatMessage
+import com.aallam.openai.api.chat.ChatResponseFormat
+import com.aallam.openai.api.chat.StreamOptions
+import com.aallam.openai.api.core.Usage
+import com.aallam.openai.api.model.ModelId
+import kotlinx.serialization.SerializationException
+import kotlinx.serialization.json.Json
+import top.jie65535.mirai.llm.LargeLanguageModels
+import top.jie65535.mirai.llm.ModelService
+
+interface ProfileModel {
+    val modelName: String
+
+    suspend fun analyze(
+        profile: UserProfileSnapshot,
+        batch: ProfileHistoryBatch,
+    ): ProfileModelResult
+}
+
+interface ConversationProfileModel {
+    val modelName: String
+
+    suspend fun analyzeConversation(
+        profiles: Map<Long, UserProfileSnapshot>,
+        batch: ConversationProfileBatch,
+        eligibleUserIds: Set<Long>,
+    ): ConversationProfileModelResult
+}
+
+class ProfileModelClient(
+    private val endpoint: LargeLanguageModels.ProfileEndpoint,
+) : ProfileModel, ConversationProfileModel {
+    private val json = Json {
+        ignoreUnknownKeys = false
+        explicitNulls = false
+    }
+
+    override val modelName: String
+        get() = endpoint.model
+
+    override suspend fun analyze(
+        profile: UserProfileSnapshot,
+        batch: ProfileHistoryBatch,
+    ): ProfileModelResult {
+        val content = StringBuilder()
+        var lastUsage: Usage? = null
+        var cacheUsage: ModelService.CacheUsage? = null
+        endpoint.service.chatCompletions(
+            ChatCompletionRequest(
+                model = ModelId(endpoint.model),
+                temperature = endpoint.temperature,
+                responseFormat = ChatResponseFormat.JsonObject,
+                streamOptions = StreamOptions(includeUsage = true),
+                messages = listOf(
+                    ChatMessage.System(ProfilePromptStore.systemPrompt),
+                    ChatMessage.User(ProfilePromptStore.buildUserPrompt(profile, batch)),
+                ),
+            )
+        ) { cacheUsage = it }.collect { chunk ->
+            chunk.choices.firstOrNull()?.delta?.content?.let(content::append)
+            chunk.usage?.let { lastUsage = it }
+        }
+
+        val raw = content.toString().replace(THINK_REGEX, "").trim()
+        val response = parseResponse(raw)
+        return ProfileModelResult(
+            response = response,
+            rawResponse = raw,
+            usage = ProfileTokenUsage(
+                promptTokens = lastUsage?.promptTokens ?: 0,
+                completionTokens = lastUsage?.completionTokens ?: 0,
+                cachedTokens = cacheUsage?.hitTokens ?: 0,
+            ),
+        )
+    }
+
+    override suspend fun analyzeConversation(
+        profiles: Map<Long, UserProfileSnapshot>,
+        batch: ConversationProfileBatch,
+        eligibleUserIds: Set<Long>,
+    ): ConversationProfileModelResult {
+        val content = StringBuilder()
+        var lastUsage: Usage? = null
+        var cacheUsage: ModelService.CacheUsage? = null
+        endpoint.service.chatCompletions(
+            ChatCompletionRequest(
+                model = ModelId(endpoint.model),
+                temperature = endpoint.temperature,
+                responseFormat = ChatResponseFormat.JsonObject,
+                streamOptions = StreamOptions(includeUsage = true),
+                messages = listOf(
+                    ChatMessage.System(ProfilePromptStore.conversationSystemPrompt),
+                    ChatMessage.User(
+                        ProfilePromptStore.buildConversationUserPrompt(profiles, batch, eligibleUserIds)
+                    ),
+                ),
+            )
+        ) { cacheUsage = it }.collect { chunk ->
+            chunk.choices.firstOrNull()?.delta?.content?.let(content::append)
+            chunk.usage?.let { lastUsage = it }
+        }
+
+        val raw = content.toString().replace(THINK_REGEX, "").trim()
+        return ConversationProfileModelResult(
+            response = parseObject(raw),
+            rawResponse = raw,
+            usage = ProfileTokenUsage(
+                promptTokens = lastUsage?.promptTokens ?: 0,
+                completionTokens = lastUsage?.completionTokens ?: 0,
+                cachedTokens = cacheUsage?.hitTokens ?: 0,
+            ),
+        )
+    }
+
+    private fun parseResponse(raw: String): ProfileModelResponse {
+        return parseObject(raw)
+    }
+
+    private inline fun <reified T> parseObject(raw: String): T {
+        val unfenced = raw
+            .removePrefix("```json").removePrefix("```")
+            .removeSuffix("```").trim()
+        val objectText = if (unfenced.startsWith('{') && unfenced.endsWith('}')) {
+            unfenced
+        } else {
+            val start = unfenced.indexOf('{')
+            val end = unfenced.lastIndexOf('}')
+            if (start < 0 || end <= start) throw SerializationException("模型响应中没有完整 JSON object")
+            unfenced.substring(start, end + 1)
+        }
+        return json.decodeFromString(objectText)
+    }
+
+    companion object {
+        private val THINK_REGEX = Regex("<think>[\\s\\S]*?</think>")
+    }
+}