feat: enhance context handling by adding code context selection and implementing summary generation (#1091) #release

* feat: add context annotation types and enhance file handling in LLM processing

* feat: enhance context handling by adding chatId to annotations and implementing summary generation

* removed useless changes

* feat: updated token counts to include optimization requests

* prompt fix

* logging added

* useless logs removed

app/lib/.server/llm/create-summary.ts

@@ -0,0 +1,138 @@
+import { generateText, type CoreTool, type GenerateTextResult, type Message } from 'ai';
+import type { IProviderSetting } from '~/types/model';
+import { DEFAULT_MODEL, DEFAULT_PROVIDER, PROVIDER_LIST } from '~/utils/constants';
+import { extractCurrentContext, extractPropertiesFromMessage, simplifyBoltActions } from './utils';
+import { createScopedLogger } from '~/utils/logger';
+import { LLMManager } from '~/lib/modules/llm/manager';
+
+const logger = createScopedLogger('create-summary');
+
+export async function createSummary(props: {
+  messages: Message[];
+  env?: Env;
+  apiKeys?: Record<string, string>;
+  providerSettings?: Record<string, IProviderSetting>;
+  promptId?: string;
+  contextOptimization?: boolean;
+  onFinish?: (resp: GenerateTextResult<Record<string, CoreTool<any, any>>, never>) => void;
+}) {
+  const { messages, env: serverEnv, apiKeys, providerSettings, contextOptimization, onFinish } = props;
+  let currentModel = DEFAULT_MODEL;
+  let currentProvider = DEFAULT_PROVIDER.name;
+  const processedMessages = messages.map((message) => {
+    if (message.role === 'user') {
+      const { model, provider, content } = extractPropertiesFromMessage(message);
+      currentModel = model;
+      currentProvider = provider;
+
+      return { ...message, content };
+    } else if (message.role == 'assistant') {
+      let content = message.content;
+
+      if (contextOptimization) {
+        content = simplifyBoltActions(content);
+      }
+
+      return { ...message, content };
+    }
+
+    return message;
+  });
+
+  const provider = PROVIDER_LIST.find((p) => p.name === currentProvider) || DEFAULT_PROVIDER;
+  const staticModels = LLMManager.getInstance().getStaticModelListFromProvider(provider);
+  let modelDetails = staticModels.find((m) => m.name === currentModel);
+
+  if (!modelDetails) {
+    const modelsList = [
+      ...(provider.staticModels || []),
+      ...(await LLMManager.getInstance().getModelListFromProvider(provider, {
+        apiKeys,
+        providerSettings,
+        serverEnv: serverEnv as any,
+      })),
+    ];
+
+    if (!modelsList.length) {
+      throw new Error(`No models found for provider ${provider.name}`);
+    }
+
+    modelDetails = modelsList.find((m) => m.name === currentModel);
+
+    if (!modelDetails) {
+      // Fallback to first model
+      logger.warn(
+        `MODEL [${currentModel}] not found in provider [${provider.name}]. Falling back to first model. ${modelsList[0].name}`,
+      );
+      modelDetails = modelsList[0];
+    }
+  }
+
+  let slicedMessages = processedMessages;
+  const { summary } = extractCurrentContext(processedMessages);
+  let summaryText: string | undefined = undefined;
+  let chatId: string | undefined = undefined;
+
+  if (summary && summary.type === 'chatSummary') {
+    chatId = summary.chatId;
+    summaryText = `Below is the Chat Summary till now, this is chat summary before the conversation provided by the user 
+you should also use this as historical message while providing the response to the user.        
+${summary.summary}`;
+
+    if (chatId) {
+      let index = 0;
+
+      for (let i = 0; i < processedMessages.length; i++) {
+        if (processedMessages[i].id === chatId) {
+          index = i;
+          break;
+        }
+      }
+      slicedMessages = processedMessages.slice(index + 1);
+    }
+  }
+
+  const extractTextContent = (message: Message) =>
+    Array.isArray(message.content)
+      ? (message.content.find((item) => item.type === 'text')?.text as string) || ''
+      : message.content;
+
+  // select files from the list of code file from the project that might be useful for the current request from the user
+  const resp = await generateText({
+    system: `
+        You are a software engineer. You are working on a project. tou need to summarize the work till now and provide a summary of the chat till now.
+
+        ${summaryText} 
+        
+        RULES:
+        * Only provide the summary of the chat till now.
+        * Do not provide any new information.
+        `,
+    prompt: `
+please provide a summary of the chat till now.
+below is the latest chat:
+
+---
+${slicedMessages
+  .map((x) => {
+    return `---\n[${x.role}] ${extractTextContent(x)}\n---`;
+  })
+  .join('\n')}
+---
+`,
+    model: provider.getModelInstance({
+      model: currentModel,
+      serverEnv,
+      apiKeys,
+      providerSettings,
+    }),
+  });
+
+  const response = resp.text;
+
+  if (onFinish) {
+    onFinish(resp);
+  }
+
+  return response;
+}