Add Langgraph implementation

.gitignore

@@ -39,4 +39,6 @@ next-env.d.ts
 #Notion_db
 /Notion_DB
 
-.yarn/
+.yarn/
+# LangGraph API
+.langgraph_api

langgraph.json

@@ -0,0 +1,7 @@
+{
+    "dependencies": ["."],
+    "graphs": {
+      "agent": "./langgraph/graph.ts:graph"
+    },
+    "env": ".env"
+}

langgraph/graph.ts

@@ -0,0 +1,78 @@
+import { PINECONE_INDEX_NAME, PINECONE_NAME_SPACE } from "@/config/pinecone";
+import { makeChain } from "@/utils/makechain";
+import { pinecone } from "@/utils/pinecone-client";
+import { AIMessage, HumanMessage } from "@langchain/core/messages";
+import { StateGraph } from "@langchain/langgraph";
+import type { Document } from 'langchain/document';
+import { OpenAIEmbeddings } from "langchain/embeddings/openai";
+import { PineconeStore } from "langchain/vectorstores/pinecone";
+import { InputAnnotation, OutputAnnotation } from "./state";
+
+
+const assistant = async (state: typeof InputAnnotation.State) => {
+  const { question, messages } = state;
+
+  messages.push(new HumanMessage(question));
+
+  console.log('question', question);
+
+  console.log('history', messages);
+
+  const index = pinecone.Index(PINECONE_INDEX_NAME);
+
+    /* create vectorstore*/
+    const vectorStore = await PineconeStore.fromExistingIndex(
+      new OpenAIEmbeddings({}),
+      {
+        pineconeIndex: index,
+        textKey: 'text',
+        namespace: PINECONE_NAME_SPACE, //namespace comes from your config folder
+      },
+    );
+
+    // Use a callback to get intermediate sources from the middle of the chain
+    let resolveWithDocuments: (value: Document[]) => void;
+    const documentPromise = new Promise<Document[]>((resolve) => {
+      resolveWithDocuments = resolve;
+    });
+    const retriever = vectorStore.asRetriever({
+      callbacks: [
+        {
+          handleRetrieverEnd(documents) {
+            resolveWithDocuments(documents);
+          },
+        },
+      ],
+    });
+
+    //create chain
+    const chain = makeChain(retriever);
+
+    //Ask a question using chat history
+    const response = await chain.invoke({
+      question,
+      chat_history: JSON.stringify(messages),
+    });
+
+    const sourceDocuments = await documentPromise;
+
+    return { messages: [...messages, new AIMessage(response)], sourceDocuments, answer: response };
+};
+
+export const route = (state: typeof InputAnnotation.State): "__end__" | "assistant" => {
+  if (state.messages.length > 0) {
+    return "__end__";
+  }
+  // Loop back
+  return "assistant";
+};
+
+const builder = new StateGraph({ input: InputAnnotation, output: OutputAnnotation })
+                    .addNode("assistant", assistant)
+                    .addEdge("__start__", "assistant")
+                    .addConditionalEdges("assistant", route);
+
+export const graph = builder.compile();
+
+
+

langgraph/state.ts

@@ -0,0 +1,28 @@
+import { BaseMessage } from "@langchain/core/messages";
+import { Annotation } from "@langchain/langgraph";
+
+export const InputAnnotation = Annotation.Root({
+    question: Annotation<string>,
+    messages: Annotation<BaseMessage[]>({
+      reducer: (left: BaseMessage[], right: BaseMessage | BaseMessage[]) => {
+        if (Array.isArray(right)) {
+          return left.concat(right);
+        }
+        return left.concat([right]);
+      },
+      default: () => [],
+    }),
+  });
+
+export const OutputAnnotation = Annotation.Root({
+    sourceDocuments: Annotation<Document[]>({
+        reducer: (left: Document[], right: Document | Document[]) => {
+        if (Array.isArray(right)) {
+            return right;
+        }
+        return [right];
+        },
+        default: () => [],
+    }),
+    answer: Annotation<string>
+});

package.json

@@ -15,6 +15,8 @@
     "ingest": "tsx -r dotenv/config scripts/ingest-data.ts"
   },
   "dependencies": {
+    "@langchain/core": "^0.3.37",
+    "@langchain/langgraph": "^0.2.44",
     "@microsoft/fetch-event-source": "^2.0.1",
     "@pinecone-database/pinecone": "1.1.0",
     "@radix-ui/react-accordion": "^1.1.1",

pages/api/langgraph.ts

@@ -0,0 +1,44 @@
+import type { NextApiRequest, NextApiResponse } from 'next';
+import { AIMessage, HumanMessage } from '@langchain/core/messages';
+import { graph } from '@/langgraph/graph';
+
+export default async function handler(
+  req: NextApiRequest,
+  res: NextApiResponse,
+) {
+  const { question, history } = req.body;
+
+  console.log('question', question);
+  console.log('history', history);
+
+  //only accept post requests
+  if (req.method !== 'POST') {
+    res.status(405).json({ error: 'Method not allowed' });
+    return;
+  }
+
+  if (!question) {
+    return res.status(400).json({ message: 'No question in the request' });
+  }
+  // OpenAI recommends replacing newlines with spaces for best results
+  const sanitizedQuestion = question.trim().replaceAll('\n', ' ');
+
+  try {
+    const pastMessages = history
+      .map((message: [string, string]) => {
+        return [new HumanMessage(message[0]), new AIMessage(message[1])]
+      })
+    console.log(pastMessages);
+
+    //Ask a question using chat history
+    const response = await graph.invoke({ question: sanitizedQuestion, messages: pastMessages });
+
+    const sourceDocuments = response.sourceDocuments;
+
+    console.log('response', response);
+    res.status(200).json({ text: response.answer, sourceDocuments });
+  } catch (error: any) {
+    console.log('error', error);
+    res.status(500).json({ error: error.message || 'Something went wrong' });
+  }
+}