Alchemyst AI SDK in Langchain JS (Beta branch)

example1.ts

import { StringOutputParser } from "@langchain/core/output_parsers";
import { RunnableSequence } from "@langchain/core/runnables";
import dotenv from "dotenv";
import { AlchemystRetriever } from "langchainjs/libs/langchain-community/src/retrievers/alchemystai";
// filepath: /Users/anuran/Alchemyst/integrations/playground/example.ts

dotenv.config();

// Instantiate the retriever with your API key and optional config
const retriever = new AlchemystRetriever({
  apiKey: process.env.ALCHEMYST_AI_API_KEY!,
  similarityThreshold: 0.8,
  minimumSimilarityThreshold: 0.5,
  scope: "internal"
});

// Example: Use the retriever in a LangChain pipeline
export async function main() {
  // Create a simple pipeline that retrieves documents and outputs their content
  const pipeline = RunnableSequence.from([
    async (input: string) => {
      const docs = await retriever.getRelevantDocuments(input);
      return docs.map(doc => doc.pageContent).join("\n---\n");
    },
    new StringOutputParser()
  ]);

  const query = "Tell me about Quantum Entanglement"; // Put your query here
  const result = await pipeline.invoke(query);

  console.log("Retrieved Documents:\n", result);
}

// main().catch(console.error);

example2.ts

import { ChatPromptTemplate, MessagesPlaceholder } from "@langchain/core/prompts";
import { RunnablePassthrough, RunnableSequence } from "@langchain/core/runnables";
import { ChatOpenAI } from "@langchain/openai";
import { randomUUID } from "crypto";
import 'dotenv/config';
import { AlchemystMemory } from "langchainjs/libs/langchain-community/src/memory/alchemystai";

export async function main() {
  console.log("Boot: starting test with env:", {
    OPENAI_API_KEY: process.env.OPENAI_API_KEY ? "set" : "missing",
    ALCHEMYST_AI_API_KEY: process.env.ALCHEMYST_AI_API_KEY ? "set" : "missing",
  });
  const sessionId = randomUUID();
  console.log("Session:", sessionId);

  const memory = new AlchemystMemory({
    apiKey: process.env.ALCHEMYST_AI_API_KEY || "YOUR_ALCHEMYST_API_KEY",
    sessionId,
  });

  const model = new ChatOpenAI({
    model: "gpt-5-nano",
  });

  // Create a prompt template with message history
  const prompt = ChatPromptTemplate.fromMessages([
    ["system", "You are a helpful AI assistant. Have a conversation with the human, using the chat history for context."],
    new MessagesPlaceholder("history"),
    ["human", "{input}"],
  ]);

  // Create the chain using LCEL (LangChain Expression Language)
  const chain = RunnableSequence.from([
    RunnablePassthrough.assign({
      history: async () => {
        const memoryVars = await memory.loadMemoryVariables({});
        return memoryVars.history || [];
      },
    }),
    prompt,
    model,
  ]);

  console.log("Invoke #1 ->");
  const first = await chain.invoke({ input: "Hi, my name is Anuran. Anuran is from Bangalore." });

  // Save to memory
  await memory.saveContext(
    { input: "Hi, my name is Anuran. Anuran is from Bangalore." },
    { output: first.content }
  );

  console.log("First reply:", first.content);

  console.log("Invoke #2 ->");
  const second = await chain.invoke({ input: "Who is Anuran? Where is Anuran from?" });

  // Save to memory
  await memory.saveContext(
    { input: "Who is Anuran? Where is Anuran from?" },
    { output: second.content }
  );

  console.log("Second reply:", second.content);
}

// main().catch((err) => {
//   console.error(err);
//   process.exit(1);
// });

index.ts

import { main as exampleOneMain } from './example1';
import { main as exampleTwoMain } from './example2';

exampleOneMain().catch(console.error);
exampleTwoMain().catch(console.error);

package.json

{
  "name": "playground",
  "module": "index.ts",
  "type": "module",
  "private": true,
  "devDependencies": {
    "@types/bun": "latest"
  },
  "peerDependencies": {
    "typescript": "^5"
  },
  "dependencies": {
    "@alchemystai/sdk": "^0.5.0",
    "@langchain/core": "^0.3.78",
    "@langchain/openai": "^0.6.14",
    "dotenv": "^17.2.3",
    "langchain": "^0.3.35",
    "langchainjs": "https://github.com/Alchemyst-ai/langchainjs.git#add-alchemyst-sdk"
  }
}

tsconfig.json

{
  "compilerOptions": {
    // Environment setup & latest features
    "lib": ["ESNext"],
    "target": "ESNext",
    "module": "Preserve",
    "moduleDetection": "force",
    "jsx": "react-jsx",
    "allowJs": true,

    // Bundler mode
    "moduleResolution": "bundler",
    "allowImportingTsExtensions": true,
    "verbatimModuleSyntax": true,
    "noEmit": true,

    // Best practices
    "strict": true,
    "skipLibCheck": true,
    "noFallthroughCasesInSwitch": true,
    "noUncheckedIndexedAccess": true,
    "noImplicitOverride": true,

    // Some stricter flags (disabled by default)
    "noUnusedLocals": false,
    "noUnusedParameters": false,
    "noPropertyAccessFromIndexSignature": false
  }
}