format

templates/memory-agent/README.md

@@ -214,4 +214,4 @@ Configuration auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
     }
   }
 }
--->
+-->

templates/memory-agent/tests/integration/graph.int.test.ts

@@ -61,4 +61,4 @@ describe("Memory Graph", () => {
     },
     30000,
   );
-});
+});

templates/memory-agent/tests/unit/configuration.test.ts

@@ -8,4 +8,4 @@ describe("Configuration", () => {
     expect(result).toBeDefined();
     expect(typeof result).toBe("object");
   });
-});
+});

templates/monorepo/README.md

@@ -1,3 +1,3 @@
 # Agent App
 
-# TODO: ADD README
+# TODO: ADD README

templates/monorepo/langgraph.json

@@ -1,8 +1,6 @@
 {
   "node_version": "20",
-  "dependencies": [
-    "."
-  ],
+  "dependencies": ["."],
   "graphs": {},
   "env": ".env"
-}
+}

templates/monorepo/package.json

@@ -2,7 +2,9 @@
   "name": "agent-app",
   "author": "Your Name",
   "private": true,
-  "workspaces": ["apps/*"],
+  "workspaces": [
+    "apps/*"
+  ],
   "scripts": {
     "dev": "turbo dev --filter=web --filter=agents",
     "build": "turbo build",

templates/react-agent/README.md

@@ -233,4 +233,4 @@ Configuration auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
     }
   }
 }
--->
+-->

templates/research-agent/README.md

@@ -8,14 +8,18 @@ This is a starter project to help you get started with developing a RAG research
 
 This project has three graphs:
 
-* an "index" graph (`src/index_graph/graph.ts`)
-* a "retrieval" graph (`src/retrieval_graph/graph.ts`)
-* a "researcher" subgraph (part of the retrieval graph) (`src/retrieval_graph/researcher_graph/graph.ts`)
+- an "index" graph (`src/index_graph/graph.ts`)
+- a "retrieval" graph (`src/retrieval_graph/graph.ts`)
+- a "researcher" subgraph (part of the retrieval graph) (`src/retrieval_graph/researcher_graph/graph.ts`)
 
 The index graph takes in document objects indexes them.
 
 ```json
-[{ "page_content": "LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows." }]
+[
+  {
+    "page_content": "LangGraph is a library for building stateful, multi-actor applications with LLMs, used to create agent and multi-agent workflows."
+  }
+]
 ```
 
 If an empty list is provided (default), a list of sample documents from `src/sample_docs.json` is indexed instead. Those sample documents are based on the conceptual guides for LangChain and LangGraph.
@@ -24,12 +28,16 @@ The retrieval graph manages a chat history and responds based on the fetched doc
 
 1. Takes a user **query** as input
 2. Analyzes the query and determines how to route it:
+
 - if the query is about "LangChain", it creates a research plan based on the user's query and passes the plan to the researcher subgraph
 - if the query is ambiguous, it asks for more information
 - if the query is general (unrelated to LangChain), it lets the user know
+
 3. If the query is about "LangChain", the researcher subgraph runs for each step in the research plan, until no more steps are left:
+
 - it first generates a list of queries based on the step
 - it then retrieves the relevant documents in parallel for all queries and return the documents to the retrieval graph
+
 4. Finally, the retrieval graph generates a response based on the retrieved documents and the conversation context
 
 ## Getting Started
@@ -261,8 +269,8 @@ You can customize this retrieval agent template in several ways:
 
 5. **Modify prompts**: Update the prompts used for user query routing, research planning, query generation and more in `src/retrieval_graph/prompts.ts` to better suit your specific use case or to improve the agent's performance. You can also modify these directly in LangGraph Studio. For example, you can:
 
-  * Modify system prompt for creating research plan (`research_plan_system_prompt`)
-  * Modify system prompt for generating search queries based on the research plan (`generate_queries_system_prompt`)
+- Modify system prompt for creating research plan (`research_plan_system_prompt`)
+- Modify system prompt for generating search queries based on the research plan (`generate_queries_system_prompt`)
 
 6. **Change the language model**: Update the `response_model` in the configuration to use different language models for response generation. Options include various Claude models from Anthropic, as well as models from other providers like Fireworks AI.
 
@@ -712,4 +720,4 @@ Configuration auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
     }
   }
 }
--->
+-->

templates/research-agent/retrieval-graph/graph.ts

@@ -175,4 +175,3 @@ const builder = new StateGraph(
 export const graph = builder
   .compile()
   .withConfig({ runName: "RetrievalGraph" });
-  

templates/research-agent/retrieval-graph/researcher-graph/graph.ts

@@ -66,4 +66,3 @@ const builder = new StateGraph({
 export const graph = builder
   .compile()
   .withConfig({ runName: "ResearcherGraph" });
-  

templates/research-agent/retrieval-graph/state.ts

@@ -37,7 +37,7 @@ type Router = {
   type: "more-info" | "langchain" | "general";
 };
 
-/** 
+/**
  * Represents the state of the retrieval graph / agent.
  */
 export const AgentStateAnnotation = Annotation.Root({

templates/retrieval-agent/README.md

@@ -697,4 +697,4 @@ Configuration auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
     }
   }
 }
--->
+-->