fix ch4 to ch8

ch4/js/b-state-graph.js

@@ -3,9 +3,10 @@ import {
   Annotation,
   messagesStateReducer,
   START,
-} from "@langchain/langgraph";
-import { ChatOpenAI } from "@langchain/openai";
-import { HumanMessage } from "@langchain/core/messages";
+  END,
+} from '@langchain/langgraph';
+import { ChatOpenAI } from '@langchain/openai';
+import { HumanMessage } from '@langchain/core/messages';
 
 const State = {
   messages: Annotation({
@@ -23,14 +24,14 @@ async function chatbot(state) {
   return { messages: answer };
 }
 
-builder = builder.addNode("chatbot", chatbot);
+builder = builder.addNode('chatbot', chatbot);
 
-builder = builder.addEdge(START, "chatbot").addEdge("chatbot", END);
+builder = builder.addEdge(START, 'chatbot').addEdge('chatbot', END);
 
 let graph = builder.compile();
 
 // Run the graph
-const input = { messages: [new HumanMessage("hi!")] };
+const input = { messages: [new HumanMessage('hi!')] };
 for await (const chunk of await graph.stream(input)) {
   console.log(chunk);
 }

ch4/js/e-filter-messages.js

@@ -3,27 +3,39 @@ import {
   SystemMessage,
   AIMessage,
   filterMessages,
-} from "@langchain/core/messages";
+} from '@langchain/core/messages';
 
 const messages = [
-  new SystemMessage({ content: "you are a good assistant", id: "1" }),
-  new HumanMessage({ content: "example input", id: "2", name: "example_user" }),
+  new SystemMessage({ content: 'you are a good assistant', id: '1' }),
+  new HumanMessage({ content: 'example input', id: '2', name: 'example_user' }),
   new AIMessage({
-    content: "example output",
-    id: "3",
-    name: "example_assistant",
+    content: 'example output',
+    id: '3',
+    name: 'example_assistant',
   }),
-  new HumanMessage({ content: "real input", id: "4", name: "bob" }),
-  new AIMessage({ content: "real output", id: "5", name: "alice" }),
+  new HumanMessage({ content: 'real input', id: '4', name: 'bob' }),
+  new AIMessage({ content: 'real output', id: '5', name: 'alice' }),
 ];
 
 // Filter for human messages
-filterMessages(messages, { includeTypes: ["human"] });
+const filterByHumanMessages = filterMessages(messages, {
+  includeTypes: ['human'],
+});
+console.log(`Human messages: ${JSON.stringify(filterByHumanMessages)}`);
 
 // Filter to exclude names
-filterMessages(messages, {
-  excludeNames: ["example_user", "example_assistant"],
+const filterByExcludedNames = filterMessages(messages, {
+  excludeNames: ['example_user', 'example_assistant'],
 });
+console.log(
+  `\nExcluding example names: ${JSON.stringify(filterByExcludedNames)}`
+);
 
 // Filter by types and IDs
-filterMessages(messages, { includeTypes: ["human", "ai"], excludeIds: ["3"] });
+const filterByTypesAndIDs = filterMessages(messages, {
+  includeTypes: ['human', 'ai'],
+  excludeIds: ['3'],
+});
+console.log(
+  `\nFiltered by types and IDs: ${JSON.stringify(filterByTypesAndIDs)}`
+);

ch4/js/f-merge-messages.js

@@ -3,22 +3,23 @@ import {
   SystemMessage,
   AIMessage,
   mergeMessageRuns,
-} from "@langchain/core/messages";
+} from '@langchain/core/messages';
 
 const messages = [
   new SystemMessage("you're a good assistant."),
-  new SystemMessage("you always respond with a joke."),
+  new SystemMessage('you always respond with a joke.'),
   new HumanMessage({
-    content: [{ type: "text", text: "i wonder why it's called langchain" }],
+    content: [{ type: 'text', text: "i wonder why it's called langchain" }],
   }),
-  new HumanMessage("and who is harrison chasing anyways"),
+  new HumanMessage('and who is harrison chasing anyways'),
   new AIMessage(
-    'Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!',
+    'Well, I guess they thought "WordRope" and "SentenceString" just didn\'t have the same ring to it!'
   ),
   new AIMessage(
-    "Why, he's probably chasing after the last cup of coffee in the office!",
+    "Why, he's probably chasing after the last cup of coffee in the office!"
   ),
 ];
 
 // Merge consecutive messages
-mergeMessageRuns(messages);
+const mergedMessages = mergeMessageRuns(messages);
+console.log(mergedMessages);

ch5/js/a-chatbot.js

@@ -1,13 +1,13 @@
 import {
   StateGraph,
-  StateType,
   Annotation,
   messagesStateReducer,
   START,
-} from "@langchain/langgraph";
+  END,
+} from '@langchain/langgraph';
 
-import { ChatOpenAI } from "@langchain/openai";
-import { HumanMessage } from "@langchain/core/messages";
+import { ChatOpenAI } from '@langchain/openai';
+import { HumanMessage } from '@langchain/core/messages';
 
 const model = new ChatOpenAI();
 
@@ -28,14 +28,14 @@ async function chatbot(state) {
 }
 
 const builder = new StateGraph(State)
-  .addNode("chatbot", chatbot)
-  .addEdge(START, "chatbot")
-  .addEdge("chatbot", END);
+  .addNode('chatbot', chatbot)
+  .addEdge(START, 'chatbot')
+  .addEdge('chatbot', END);
 
 const graph = builder.compile();
 
 // Example usage
-const input = { messages: [new HumanMessage("hi!")] };
+const input = { messages: [new HumanMessage('hi!')] };
 for await (const chunk of await graph.stream(input)) {
   console.log(chunk);
 }

ch6/js/c-many-tools.js

@@ -1,17 +1,17 @@
-import { DuckDuckGoSearch } from "@langchain/community/tools/duckduckgo_search";
-import { Calculator } from "@langchain/community/tools/calculator";
-import { ChatOpenAI } from "@langchain/openai";
-import { OpenAIEmbeddings } from "@langchain/openai";
-import { Document } from "@langchain/core/documents";
-import { MemoryVectorStore } from "@langchain/community/vectorstores/memory";
+import { DuckDuckGoSearch } from '@langchain/community/tools/duckduckgo_search';
+import { Calculator } from '@langchain/community/tools/calculator';
+import { ChatOpenAI } from '@langchain/openai';
+import { OpenAIEmbeddings } from '@langchain/openai';
+import { Document } from '@langchain/core/documents';
+import { MemoryVectorStore } from 'langchain/vectorstores/memory';
 import {
   StateGraph,
   Annotation,
   messagesStateReducer,
   START,
-} from "@langchain/langgraph";
-import { ToolNode, toolsCondition } from "@langchain/langgraph/prebuilt";
-import { HumanMessage } from "@langchain/core/messages";
+} from '@langchain/langgraph';
+import { ToolNode, toolsCondition } from '@langchain/langgraph/prebuilt';
+import { HumanMessage } from '@langchain/core/messages';
 
 const search = new DuckDuckGoSearch();
 const calculator = new Calculator();
@@ -27,9 +27,9 @@ const toolsStore = await MemoryVectorStore.fromDocuments(
       new Document({
         pageContent: tool.description,
         metadata: { name: tool.constructor.name },
-      }),
+      })
   ),
-  embeddings,
+  embeddings
 );
 const toolsRetriever = toolsStore.asRetriever();
 
@@ -40,7 +40,7 @@ const annotation = Annotation.Root({
 
 async function modelNode(state) {
   const selectedTools = tools.filter((tool) =>
-    state.selected_tools.includes(tool.constructor.name),
+    state.selected_tools.includes(tool.constructor.name)
   );
   const res = await model.bindTools(selectedTools).invoke(state.messages);
   return { messages: res };
@@ -55,13 +55,13 @@ async function selectTools(state) {
 }
 
 const builder = new StateGraph(annotation)
-  .addNode("select_tools", selectTools)
-  .addNode("model", modelNode)
-  .addNode("tools", new ToolNode(tools))
-  .addEdge(START, "select_tools")
-  .addEdge("select_tools", "model")
-  .addConditionalEdges("model", toolsCondition)
-  .addEdge("tools", "model");
+  .addNode('select_tools', selectTools)
+  .addNode('model', modelNode)
+  .addNode('tools', new ToolNode(tools))
+  .addEdge(START, 'select_tools')
+  .addEdge('select_tools', 'model')
+  .addConditionalEdges('model', toolsCondition)
+  .addEdge('tools', 'model');
 
 const graph = builder.compile();
 
@@ -69,7 +69,7 @@ const graph = builder.compile();
 const input = {
   messages: [
     new HumanMessage(
-      "How old was the 30th president of the United States when he died?",
+      'How old was the 30th president of the United States when he died?'
     ),
   ],
 };

ch7/js/a-reflection.js

@@ -2,15 +2,15 @@ import {
   AIMessage,
   SystemMessage,
   HumanMessage,
-} from "@langchain/core/messages";
-import { ChatOpenAI } from "@langchain/openai";
+} from '@langchain/core/messages';
+import { ChatOpenAI } from '@langchain/openai';
 import {
   StateGraph,
   Annotation,
   messagesStateReducer,
   START,
   END,
-} from "@langchain/langgraph";
+} from '@langchain/langgraph';
 
 const model = new ChatOpenAI();
 
@@ -21,7 +21,7 @@ const annotation = Annotation.Root({
 const generatePrompt = new SystemMessage(
   `You are an essay assistant tasked with writing excellent 3-paragraph essays.
 Generate the best essay possible for the user's request.
-If the user provides critique, respond with a revised version of your previous attempts.`,
+If the user provides critique, respond with a revised version of your previous attempts.`
 );
 
 async function generate(state) {
@@ -31,7 +31,7 @@ async function generate(state) {
 
 const reflectionPrompt = new SystemMessage(
   `You are a teacher grading an essay submission. Generate critique and recommendations for the user's submission.
-Provide detailed recommendations, including requests for length, depth, style, etc.`,
+Provide detailed recommendations, including requests for length, depth, style, etc.`
 );
 
 async function reflect(state) {
@@ -58,16 +58,16 @@ function shouldContinue(state) {
     // End after 3 iterations, each with 2 messages
     return END;
   } else {
-    return "reflect";
+    return 'reflect';
   }
 }
 
 const builder = new StateGraph(annotation)
-  .addNode("generate", generate)
-  .addNode("reflect", reflect)
-  .addEdge(START, "generate")
-  .addConditionalEdges("generate", shouldContinue)
-  .addEdge("reflect", "generate");
+  .addNode('generate', generate)
+  .addNode('reflect', reflect)
+  .addEdge(START, 'generate')
+  .addConditionalEdges('generate', shouldContinue)
+  .addEdge('reflect', 'generate');
 
 const graph = builder.compile();
 
@@ -75,15 +75,18 @@ const graph = builder.compile();
 const initialState = {
   messages: [
     new HumanMessage(
-      "Write an essay about the relevance of 'The Little Prince' today.",
+      "Write an essay about the relevance of 'The Little Prince' today."
     ),
   ],
 };
 
-for await (const output of graph.stream(initialState)) {
+for await (const output of await graph.stream(initialState)) {
+  const messageType = output.generate ? 'generate' : 'reflect';
   console.log(
-    "\nNew message:",
-    output.messages[output.messages.length - 1].content.slice(0, 100),
-    "...",
+    '\nNew message:',
+    output[messageType].messages[
+      output[messageType].messages.length - 1
+    ].content.slice(0, 100),
+    '...'
   );
 }

ch7/js/b-subgraph-direct.js

@@ -1,4 +1,4 @@
-import { StateGraph, START, Annotation } from "@langchain/langgraph";
+import { StateGraph, START, Annotation } from '@langchain/langgraph';
 
 const StateAnnotation = Annotation.Root({
   foo: Annotation(), // string type
@@ -13,22 +13,23 @@ const SubgraphStateAnnotation = Annotation.Root({
 const subgraphNode = async (state) => {
   // note that this subgraph node can communicate with
   // the parent graph via the shared "foo" key
-  return { foo: state.foo + "bar" };
+  return { foo: state.foo + 'bar' };
 };
 
 const subgraph = new StateGraph(SubgraphStateAnnotation)
-  .addNode("subgraph", subgraphNode)
+  .addNode('subgraph', subgraphNode)
+  .addEdge(START, 'subgraph')
   // Additional subgraph setup would go here
   .compile();
 
 // Define parent graph
 const parentGraph = new StateGraph(StateAnnotation)
-  .addNode("subgraph", subgraph)
-  .addEdge(START, "subgraph")
+  .addNode('subgraph', subgraph)
+  .addEdge(START, 'subgraph')
   // Additional parent graph setup would go here
   .compile();
 
 // Example usage
-const initialState = { foo: "hello" };
+const initialState = { foo: 'hello' };
 const result = await parentGraph.invoke(initialState);
 console.log(`Result: ${JSON.stringify(result)}`); // Should append "bar" to the foo value

ch7/js/c-subgraph-function.js

@@ -1,4 +1,4 @@
-import { StateGraph, START, Annotation } from "@langchain/langgraph";
+import { StateGraph, START, Annotation } from '@langchain/langgraph';
 
 const StateAnnotation = Annotation.Root({
   foo: Annotation(),
@@ -12,11 +12,12 @@ const SubgraphStateAnnotation = Annotation.Root({
 
 // Define subgraph
 const subgraphNode = async (state) => {
-  return { bar: state.bar + "baz" };
+  return { bar: state.bar + 'baz' };
 };
 
 const subgraph = new StateGraph(SubgraphStateAnnotation)
-  .addNode("subgraph", subgraphNode)
+  .addNode('subgraph', subgraphNode)
+  .addEdge(START, 'subgraph')
   // Additional subgraph setup would go here
   .compile();
 
@@ -33,13 +34,13 @@ const subgraphWrapperNode = async (state) => {
 };
 
 const parentGraph = new StateGraph(StateAnnotation)
-  .addNode("subgraph", subgraphWrapperNode)
-  .addEdge(START, "subgraph")
+  .addNode('subgraph', subgraphWrapperNode)
+  .addEdge(START, 'subgraph')
   // Additional parent graph setup would go here
   .compile();
 
 // Example usage
 
-const initialState = { foo: "hello" };
+const initialState = { foo: 'hello' };
 const result = await parentGraph.invoke(initialState);
 console.log(`Result: ${JSON.stringify(result)}`); // Should transform foo->bar, append "baz", then transform bar->foo

ch7/py/a-reflection.py

@@ -78,4 +78,6 @@ initial_state = {
 
 # Run the graph
 for output in graph.stream(initial_state):
-    print("\nNew message:", output["messages"][-1].content[:100], "...")
+    message_type = "generate" if "generate" in output else "reflect"
+    print("\nNew message:", output[message_type]
+          ["messages"][-1].content[:100], "...")

ch7/py/c-subgraph-function.py

@@ -19,6 +19,7 @@ def subgraph_node(state: SubgraphState):
 
 subgraph_builder = StateGraph(SubgraphState)
 subgraph_builder.add_node("subgraph_node", subgraph_node)
+subgraph_builder.add_edge(START, "subgraph_node")
 # Additional subgraph setup would go here
 subgraph = subgraph_builder.compile()
 

ch8/py/a-structured-output.py

@@ -7,7 +7,7 @@ class Joke(BaseModel):
     punchline: str = Field(description="The punchline to the joke")
 
 
-model = ChatOpenAI(model="gpt-3.5-turbo-0125", temperature=0)
+model = ChatOpenAI(model="gpt-4o", temperature=0)
 model = model.with_structured_output(Joke)
 
 result = model.invoke("Tell me a joke about cats")