Format

README.md

@@ -2,14 +2,13 @@
 
 This repository contains implementations of AI email assistants built using LangGraph.js, a library for building stateful, multi-actor applications with LLMs. It demonstrates how to create, test, and add features like Human-in-the-Loop (HITL) and persistent memory to an AI agent.
 
-
 ### Prerequisites
+
 - Install the latest version of [JupyterLab or Jupyter Notebook](https://jupyter.org/install)
 - Install [TS-Lab Typescript Kernel for Notebooks](https://github.com/yunabe/tslab#display-rich-objects)
 - Node.js (v18 or higher recommended)
 - A package manager (npm, yarn, or pnpm)
 
-
 ### 1. Install Dependencies
 
 Clone the repository and install the necessary packages:
@@ -24,11 +23,12 @@ pnpm install
 
 ### 2. Environment Setup
 
-Copy the `.env.example` file to  `.env` file in the root of the project and add your OpenAI API key:
+Copy the `.env.example` file to `.env` file in the root of the project and add your OpenAI API key:
 
 ```
 OPENAI_API_KEY=your_api_key_here
 ```
+
 it is recommended to also add your langsmith api key, and langsmith_project name to be able to analyze your graph traces in Langsmith.
 
 ### 3. Run the Agent
@@ -43,24 +43,25 @@ yarn agent
 pnpm agent
 ```
 
-
 ### Typescript Notebooks
- multiple interactive Typescript Jupyter notebooks to go through the process of creating these agentic features.
+
+multiple interactive Typescript Jupyter notebooks to go through the process of creating these agentic features.
+
 - `notebooks/langgraph_101.ipynb`
 - `notebooks/agent.ipynb`
-- `notebooks/hitl.ipynb` 
-- `notebooks/memory.ipynb`  
+- `notebooks/hitl.ipynb`
+- `notebooks/memory.ipynb`
+
+### Email Assistant Scripts
 
-### Email Assistant Scripts 
 Three versions of the email assistant are available in the `src/` directory:
+
 1.  `email_assistant.ts`: A basic email assistant for triage and response.
 2.  `email_assistant_hitl.ts`: Extends the basic assistant with Human-in-the-Loop capabilities for reviewing and intervening in the agent's actions.
 3.  `email_assistant_hitl_memory.ts`: Further extends the HITL assistant with persistent memory to learn from user feedback and preferences.
 
-
 There are also The notebooks assemble the agents in `src/` step by step. You can use **ts-lab kernel instead of the default python kernel** to execute the notebook code cells
 
-
 ## Table of Contents
 
 - [Getting Started](#getting-started)
@@ -79,9 +80,6 @@ There are also The notebooks assemble the agents in `src/` step by step. You can
   - [Testing Memory Features](#testing-memory-features)
 - [Development & Debugging](#development--debugging)
 
-
-
-
 ## Project Structure
 
 - `src/`: Contains the core TypeScript source code for the email assistants.
@@ -98,10 +96,10 @@ There are also The notebooks assemble the agents in `src/` step by step. You can
 - `tsconfig.json`: TypeScript configuration.
 - `.env`: Environment variables (gitignored).
 - `notebooks/` contains the interactive notebooks for the email assistants
-    `0_langgraph_101.ipynb` - langgraph fundamentals
-    `1_agent.ipynb` - agentic email assistant
-    `2_hitl.ipynb` - Human in the Loop, Interrupts notebook
-    `3_memory.ipynb` - Human in the loop, with memory notebook 
+  `0_langgraph_101.ipynb` - langgraph fundamentals
+  `1_agent.ipynb` - agentic email assistant
+  `2_hitl.ipynb` - Human in the Loop, Interrupts notebook
+  `3_memory.ipynb` - Human in the loop, with memory notebook
 
 ## Core Concepts & Workflow
 
@@ -151,6 +149,7 @@ The email assistants are built as stateful graphs using LangGraph.js.
 
 Implemented in `email_assistant_hitl.ts` and `email_assistant_hitl_memory.ts`.
 Interactive Notebooks available in `2_hitl.ipynb` and `3_memory.ipynb`
+
 - **Interrupts**: The graph execution pauses at critical junctures:
   - After triage if an email is marked `notify` (`triage_interrupt_handler` node).
   - Before executing certain tool calls within the `response_agent` (`interrupt_handler` node).
@@ -200,6 +199,7 @@ Use this JSON structure as input when testing your agent in the studio:
 ### Understanding Node Outputs
 
 #### Triage Router Node (`triage_router`)
+
 Classifies emails. Expect output like:
 
 ```json
@@ -216,6 +216,7 @@ Classifies emails. Expect output like:
 ```
 
 #### Response Agent Nodes (e.g., `llm_call`, `interrupt_handler`)
+
 Handles response generation.
 
 - `llm_call` output might include tool calls:

src/tools/default/email-tools.ts

@@ -32,7 +32,7 @@ ${content}
     description:
       "Write an email draft based on provided information. Use this when the user wants to compose a new email message.",
     schema: emailSchema,
-  }
+  },
 );
 
 /**
@@ -76,7 +76,7 @@ Recommended action: ${priority === "High" ? "Respond immediately" : "Review when
     description:
       "Analyze and categorize an email by importance and type. Use this when evaluating how to handle incoming messages.",
     schema: triageSchema,
-  }
+  },
 );
 
 /**
@@ -99,5 +99,5 @@ export const Done = tool(
     description:
       "Signal that you've completed the current task and no further actions are needed.",
     schema: doneSchema,
-  }
+  },
 );

src/tools/default/memory-tools.ts

@@ -20,7 +20,7 @@ export const backgroundTool = tool(
     name: "background",
     description: "Get background information about the user",
     schema: z.object({}).describe("This tool doesn't take any arguments"),
-  }
+  },
 );
 
 /**
@@ -36,7 +36,7 @@ export const calPreferencesTool = tool(
     name: "cal_preferences",
     description: "Get the user's calendar preferences",
     schema: z.object({}).describe("This tool doesn't take any arguments"),
-  }
+  },
 );
 
 /**
@@ -52,7 +52,7 @@ export const responsePreferencesTool = tool(
     name: "response_preferences",
     description: "Get the user's response style preferences",
     schema: z.object({}).describe("This tool doesn't take any arguments"),
-  }
+  },
 );
 
 /**
@@ -68,5 +68,5 @@ export const questionTool = tool(
     schema: z.object({
       content: z.string().describe("The question to ask the user"),
     }),
-  }
+  },
 );

src/utils.ts

@@ -58,7 +58,7 @@ export function formatEmailMarkdown(
   subject: string,
   author: string,
   to: string,
-  emailThread: string
+  emailThread: string,
 ): string {
   return `## Email: ${subject}
 
@@ -206,13 +206,13 @@ export function extractToolCalls(messages: any[]): string[] {
       // Handle plain objects
       if (message.tool_calls && Array.isArray(message.tool_calls)) {
         toolCallNames.push(
-          ...message.tool_calls.map((call: any) => call.name.toLowerCase())
+          ...message.tool_calls.map((call: any) => call.name.toLowerCase()),
         );
       }
       // Handle class instances with toolCalls property
       else if ("toolCalls" in message && Array.isArray(message.toolCalls)) {
         toolCallNames.push(
-          ...message.toolCalls.map((call: any) => call.name.toLowerCase())
+          ...message.toolCalls.map((call: any) => call.name.toLowerCase()),
         );
       }
     }
@@ -264,7 +264,7 @@ export function formatMessagesString(messages: BaseMessage[]): string {
           const toolCallsStr = aiMessage.tool_calls
             .map(
               (tc: ToolCall) =>
-                `\n  Tool: ${tc.name}\n  Args: ${JSON.stringify(tc.args, null, 2)}`
+                `\n  Tool: ${tc.name}\n  Args: ${JSON.stringify(tc.args, null, 2)}`,
             )
             .join("\n");
           content += `\n[Tool Calls: ${toolCallsStr}]`;
@@ -283,12 +283,12 @@ export function formatEmailOptional(
   subject?: string,
   author?: string,
   to?: string,
-  emailThread?: string
+  emailThread?: string,
 ): string {
   return formatEmailMarkdown(
     subject ?? "No Subject",
     author ?? "Unknown Sender",
     to ?? "Unknown Recipient",
-    emailThread ?? ""
+    emailThread ?? "",
   );
 }