feat(app): add suggestions route

ui/app/api/suggestions/route.ts

@@ -0,0 +1,81 @@
+import generateSuggestions from '@/lib/chains/suggestionGeneratorAgent';
+import {
+  getCustomOpenaiApiKey,
+  getCustomOpenaiApiUrl,
+  getCustomOpenaiModelName,
+} from '@/lib/config';
+import { getAvailableChatModelProviders } from '@/lib/providers';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { AIMessage, HumanMessage } from '@langchain/core/messages';
+import { ChatOpenAI } from '@langchain/openai';
+
+interface ChatModel {
+  provider: string;
+  model: string;
+}
+
+interface SuggestionsGenerationBody {
+  chatHistory: any[];
+  chatModel?: ChatModel;
+}
+
+export const POST = async (req: Request) => {
+  try {
+    const body: SuggestionsGenerationBody = await req.json();
+
+    const chatHistory = body.chatHistory
+      .map((msg: any) => {
+        if (msg.role === 'user') {
+          return new HumanMessage(msg.content);
+        } else if (msg.role === 'assistant') {
+          return new AIMessage(msg.content);
+        }
+      })
+      .filter((msg) => msg !== undefined);
+
+    const chatModelProviders = await getAvailableChatModelProviders();
+
+    const chatModelProvider =
+      chatModelProviders[
+        body.chatModel?.provider || Object.keys(chatModelProviders)[0]
+      ];
+    const chatModel =
+      chatModelProvider[
+        body.chatModel?.model || Object.keys(chatModelProvider)[0]
+      ];
+
+    let llm: BaseChatModel | undefined;
+
+    if (body.chatModel?.provider === 'custom_openai') {
+      llm = new ChatOpenAI({
+        openAIApiKey: getCustomOpenaiApiKey(),
+        modelName: getCustomOpenaiModelName(),
+        temperature: 0.7,
+        configuration: {
+          baseURL: getCustomOpenaiApiUrl(),
+        },
+      });
+    } else if (chatModelProvider && chatModel) {
+      llm = chatModel.model;
+    }
+
+    if (!llm) {
+      return Response.json({ error: 'Invalid chat model' }, { status: 400 });
+    }
+
+    const suggestions = await generateSuggestions(
+      {
+        chat_history: chatHistory,
+      },
+      llm,
+    );
+
+    return Response.json({ suggestions }, { status: 200 });
+  } catch (err) {
+    console.error(`An error ocurred while generating suggestions: ${err}`);
+    return Response.json(
+      { message: 'An error ocurred while generating suggestions' },
+      { status: 500 },
+    );
+  }
+};

ui/lib/chains/suggestionGeneratorAgent.ts

@@ -0,0 +1,55 @@
+import { RunnableSequence, RunnableMap } from '@langchain/core/runnables';
+import ListLineOutputParser from '../outputParsers/listLineOutputParser';
+import { PromptTemplate } from '@langchain/core/prompts';
+import formatChatHistoryAsString from '../utils/formatHistory';
+import { BaseMessage } from '@langchain/core/messages';
+import { BaseChatModel } from '@langchain/core/language_models/chat_models';
+import { ChatOpenAI } from '@langchain/openai';
+
+const suggestionGeneratorPrompt = `
+You are an AI suggestion generator for an AI powered search engine. You will be given a conversation below. You need to generate 4-5 suggestions based on the conversation. The suggestion should be relevant to the conversation that can be used by the user to ask the chat model for more information.
+You need to make sure the suggestions are relevant to the conversation and are helpful to the user. Keep a note that the user might use these suggestions to ask a chat model for more information. 
+Make sure the suggestions are medium in length and are informative and relevant to the conversation.
+
+Provide these suggestions separated by newlines between the XML tags <suggestions> and </suggestions>. For example:
+
+<suggestions>
+Tell me more about SpaceX and their recent projects
+What is the latest news on SpaceX?
+Who is the CEO of SpaceX?
+</suggestions>
+
+Conversation:
+{chat_history}
+`;
+
+type SuggestionGeneratorInput = {
+  chat_history: BaseMessage[];
+};
+
+const outputParser = new ListLineOutputParser({
+  key: 'suggestions',
+});
+
+const createSuggestionGeneratorChain = (llm: BaseChatModel) => {
+  return RunnableSequence.from([
+    RunnableMap.from({
+      chat_history: (input: SuggestionGeneratorInput) =>
+        formatChatHistoryAsString(input.chat_history),
+    }),
+    PromptTemplate.fromTemplate(suggestionGeneratorPrompt),
+    llm,
+    outputParser,
+  ]);
+};
+
+const generateSuggestions = (
+  input: SuggestionGeneratorInput,
+  llm: BaseChatModel,
+) => {
+  (llm as unknown as ChatOpenAI).temperature = 0;
+  const suggestionGeneratorChain = createSuggestionGeneratorChain(llm);
+  return suggestionGeneratorChain.invoke(input);
+};
+
+export default generateSuggestions;