Initial Python rewrite

2026-02-19 17:50:14 +00:00
parent da95a64fb7
commit faa04a0d01
158 changed files with 5122 additions and 1144 deletions
--- a/src.bak/main/java/com/example/service/base/NotificationContextResolver.java
+++ b/src.bak/main/java/com/example/service/base/NotificationContextResolver.java
@@ -0,0 +1,128 @@
+/*
+* Copyright 2025 Google. This software is provided as-is, without warranty or representation for any use or purpose.
+* Your use of it is subject to your agreement with Google.
+*/
+
+package com.example.service.base;
+
+import com.example.service.notification.MemoryStoreNotificationService;
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+import org.springframework.beans.factory.annotation.Value;
+import org.springframework.stereotype.Service;
+import jakarta.annotation.PostConstruct;
+import java.io.IOException;
+import java.io.InputStream;
+import java.nio.charset.StandardCharsets;
+import java.util.Objects;
+
+/**
+ * Resolves the conversational context of a user query by leveraging a large
+ * language model (LLM). This service evaluates a user's question in the context
+ * of a specific notification and conversation history, then decides if the
+ * query
+ * can be answered by the LLM or if it should be handled by a standard
+ * Dialogflow agent.
+ * The class loads an LLM prompt from an external file and dynamically
+ * formats it with a user's query and other context to drive its decision-making
+ * process.
+ */
+@Service
+public class NotificationContextResolver {
+
+    private static final Logger logger = LoggerFactory.getLogger(NotificationContextResolver.class);
+    private final GeminiClientService geminiService;
+
+    @Value("${notificationcontext.geminimodel:gemini-2.0-flash-001}")
+    private String geminiModelNameResolver;
+
+    @Value("${notificationcontext.temperature:0.1f}")
+    private Float resolverTemperature;
+
+    @Value("${notificationcontext.maxOutputTokens:1024}")
+    private Integer resolverMaxOutputTokens;
+
+    @Value("${notificationcontext.topP:0.1f}")
+    private Float resolverTopP;
+
+    @Value("${notificationcontext.prompt:prompts/notification_context_resolver.txt}")
+    private String promptFilePath;
+
+    public static final String CATEGORY_DIALOGFLOW = "DIALOGFLOW";
+
+    private String promptTemplate;
+
+    public NotificationContextResolver(GeminiClientService geminiService,
+            MemoryStoreNotificationService memoryStoreNotificationService) {
+        this.geminiService = Objects.requireNonNull(geminiService,
+                "GeminiClientService cannot be null for NotificationContextResolver.");
+    }
+
+    @PostConstruct
+    public void loadPromptTemplate() {
+        try (InputStream inputStream = getClass().getClassLoader().getResourceAsStream(promptFilePath)) {
+            if (inputStream == null) {
+                throw new IOException("Resource not found: " + promptFilePath);
+            }
+            byte[] fileBytes = inputStream.readAllBytes();
+            this.promptTemplate = new String(fileBytes, StandardCharsets.UTF_8);
+            logger.info("Successfully loaded prompt template from '" + promptFilePath + "'.");
+        } catch (IOException e) {
+            logger.error("Failed to load prompt template from '" + promptFilePath
+                    + "'. Please ensure the file exists. Error: " + e.getMessage());
+            throw new IllegalStateException("Could not load prompt template.", e);
+        }
+    }
+
+    public String resolveContext(String queryInputText, String notificationsJson, String conversationJson,
+            String metadata, String userId, String sessionId, String userPhoneNumber) {
+        logger.debug("resolveContext -> queryInputText: {}, notificationsJson: {}, conversationJson: {}, metadata: {}",
+                queryInputText, notificationsJson, conversationJson, metadata);
+        if (queryInputText == null || queryInputText.isBlank()) {
+            logger.warn("Query input text for context resolution is null or blank.", CATEGORY_DIALOGFLOW);
+            return CATEGORY_DIALOGFLOW;
+        }
+
+        String notificationContent = (notificationsJson != null && !notificationsJson.isBlank()) ? notificationsJson
+                : "No metadata in notification.";
+
+        String conversationHistory = (conversationJson != null && !conversationJson.isBlank()) ? conversationJson
+                : "No conversation history.";
+
+        String contextPrompt = String.format(
+                this.promptTemplate,
+                conversationHistory,
+                notificationContent,
+                metadata,
+                queryInputText);
+
+        logger.debug("Sending context resolution request to Gemini for input (first 100 chars): '{}'...",
+                queryInputText.substring(0, Math.min(queryInputText.length(), 100)));
+
+        try {
+            String geminiResponse = geminiService.generateContent(
+                    contextPrompt,
+                    resolverTemperature,
+                    resolverMaxOutputTokens,
+                    geminiModelNameResolver,
+                    resolverTopP);
+
+            if (geminiResponse != null && !geminiResponse.isBlank()) {
+                if (geminiResponse.trim().equalsIgnoreCase(CATEGORY_DIALOGFLOW)) {
+                    logger.debug("Resolved to {}. Input: '{}'", CATEGORY_DIALOGFLOW, queryInputText);
+                    return CATEGORY_DIALOGFLOW;
+                } else {
+                    logger.debug("Resolved to a specific response. Input: '{}'", queryInputText);
+                    return geminiResponse;
+                }
+            } else {
+                logger.warn("Gemini returned a null or blank response",
+                        queryInputText, CATEGORY_DIALOGFLOW);
+                return CATEGORY_DIALOGFLOW;
+            }
+        } catch (Exception e) {
+            logger.error("An error occurred during Gemini content generation for context resolution.", e);
+            return CATEGORY_DIALOGFLOW;
+        }
+    }
+}