Adds support for memory and prompt passing to a ChatConversationalAgent

docs/docs/getting-started/guide-llm.mdx

@@ -169,17 +169,15 @@ Now we can get started!
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 
 const model = new OpenAI({ temperature: 0 });
 const tools = [new SerpAPI(), new Calculator()];
 
-const executor = await initializeAgentExecutor(
-  tools,
-  model,
-  "zero-shot-react-description"
-);
+const executor = await initializeAgentExecutorWithOptions(tools, model, {
+  agentType: "zero-shot-react-description",
+});
 console.log("Loaded agent.");
 
 const input =

docs/docs/modules/agents/executor/getting-started.md

@@ -31,17 +31,15 @@ Now we can get started!
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 
 const model = new OpenAI({ temperature: 0 });
 const tools = [new SerpAPI(), new Calculator()];
 
-const executor = await initializeAgentExecutor(
-  tools,
-  model,
-  "zero-shot-react-description"
-);
+const executor = await initializeAgentExecutorWithOptions(tools, model, {
+  agentType: "zero-shot-react-description",
+});
 console.log("Loaded agent.");
 
 const input =

docs/docs/modules/agents/tools/agents_with_vectorstores.md

@@ -8,7 +8,7 @@ First, you want to import the relevant modules
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator, ChainTool } from "langchain/tools";
 import { VectorDBQAChain } from "langchain/chains";
 import { HNSWLib } from "langchain/vectorstores";
@@ -48,11 +48,9 @@ Now we can go about constructing and using the tool as we would any other tool!
 ```typescript
 const tools = [new SerpAPI(), new Calculator(), qaTool];
 
-const executor = await initializeAgentExecutor(
-  tools,
-  model,
-  "zero-shot-react-description"
-);
+const executor = await initializeAgentExecutorWithOptions(tools, model, {
+  agentType: "zero-shot-react-description",
+});
 console.log("Loaded agent.");
 
 const input = `What did biden say about ketanji brown jackson is the state of the union address?`;

docs/docs/modules/agents/tools/index.mdx

@@ -48,7 +48,7 @@ See below for an example of defining and using `DynamicTool`s.
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { DynamicTool } from "langchain/tools";
 
 export const run = async () => {
@@ -68,11 +68,9 @@ export const run = async () => {
     }),
   ];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description"
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+  });
 
   console.log("Loaded agent.");
 

docs/docs/modules/agents/tools/zapier_agent.md

@@ -2,7 +2,7 @@
 
 Full docs here: https://nla.zapier.com/api/v1/dynamic/docs
 
-**Zapier Natural Language Actions** gives you access to the 5k+ apps, 20k+ actions on Zapier's platform through a natural language API interface.
+**Zapier Natural Language Actions** gives you access to the 5k+ apps and 20k+ actions on Zapier's platform through a natural language API interface.
 
 NLA supports apps like Gmail, Salesforce, Trello, Slack, Asana, HubSpot, Google Sheets, Microsoft Teams, and thousands more apps: https://zapier.com/apps
 
@@ -16,23 +16,28 @@ User-facing (Oauth): for production scenarios where you are deploying an end-use
 
 This quick start will focus on the server-side use case for brevity. Review full docs or reach out to nla@zapier.com for user-facing oauth developer support.
 
-This example goes over how to use the Zapier integration an Agent. In code, below:
+The example below demonstrates how to use the Zapier integration as an Agent:
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor, ZapierToolKit } from "langchain/agents";
+import {
+  initializeAgentExecutorWithOptions,
+  ZapierToolKit,
+} from "langchain/agents";
 import { ZapierNLAWrapper } from "langchain/tools";
 
 export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const zapier = new ZapierNLAWrapper();
   const toolkit = await ZapierToolKit.fromZapierNLAWrapper(zapier);
 
-  const executor = await initializeAgentExecutor(
+  const executor = await initializeAgentExecutorWithOptions(
     toolkit.tools,
     model,
-    "zero-shot-react-description",
-    true
+    {
+      agentType: "zero-shot-react-description",
+      verbose: true,
+    }
   );
   console.log("Loaded agent.");
 

docs/docs/production/tracing.md

@@ -10,7 +10,7 @@ Here's an example of how to use tracing in `langchain.js`. All that needs to be
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 import process from "process";
 
@@ -19,12 +19,10 @@ export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;
@@ -41,7 +39,7 @@ We are actively working on improving tracing to work better with concurrency. Fo
 
 ```typescript
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 import process from "process";
 import {
@@ -55,12 +53,10 @@ export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;
@@ -92,13 +88,11 @@ export const run = async () => {
     for (const tool of tools) {
       tool.callbackManager = callbackManager;
     }
-    const executor = await initializeAgentExecutor(
-      tools,
-      model,
-      "zero-shot-react-description",
-      true,
-      callbackManager
-    );
+    const executor = await initializeAgentExecutorWithOptions(tools, model, {
+      agentType: "zero-shot-react-description",
+      verbose: true,
+      callbackManager,
+    });
     executor.agent.llmChain.callbackManager = callbackManager;
     executors.push(executor);
   }

examples/src/agents/chat_convo_with_tracing.ts

@@ -1,5 +1,5 @@
 import { ChatOpenAI } from "langchain/chat_models";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 import { BufferMemory } from "langchain/memory";
 
@@ -8,16 +8,14 @@ export const run = async () => {
   const model = new ChatOpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "chat-conversational-react-description",
-    true
-  );
-  executor.memory = new BufferMemory({
-    returnMessages: true,
-    memoryKey: "chat_history",
-    inputKey: "input",
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "chat-conversational-react-description",
+    verbose: true,
+    memory: new BufferMemory({
+      returnMessages: true,
+      memoryKey: "chat_history",
+      inputKey: "input",
+    }),
   });
   console.log("Loaded agent.");
 

examples/src/agents/chat_mrkl.ts

@@ -1,16 +1,14 @@
 import { ChatOpenAI } from "langchain/chat_models";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 
 export const run = async () => {
   const model = new ChatOpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "chat-zero-shot-react-description"
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "chat-zero-shot-react-description",
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;

examples/src/agents/chat_mrkl_with_tracing.ts

@@ -1,18 +1,16 @@
 import { ChatOpenAI } from "langchain/chat_models";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 
 export const run = async () => {
   process.env.LANGCHAIN_HANDLER = "langchain";
   const model = new ChatOpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "chat-zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "chat-zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;

examples/src/agents/concurrent_mrkl.ts

@@ -1,5 +1,5 @@
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 import process from "process";
 import {
@@ -13,12 +13,10 @@ export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;
@@ -50,13 +48,11 @@ export const run = async () => {
     for (const tool of tools) {
       tool.callbackManager = callbackManager;
     }
-    const executor = await initializeAgentExecutor(
-      tools,
-      model,
-      "zero-shot-react-description",
-      true,
-      callbackManager
-    );
+    const executor = await initializeAgentExecutorWithOptions(tools, model, {
+      agentType: "zero-shot-react-description",
+      verbose: true,
+      callbackManager,
+    });
     executor.agent.llmChain.callbackManager = callbackManager;
     executors.push(executor);
   }

examples/src/agents/custom_tool.ts

@@ -1,5 +1,5 @@
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { DynamicTool } from "langchain/tools";
 
 export const run = async () => {
@@ -25,11 +25,9 @@ export const run = async () => {
     }),
   ];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description"
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+  });
 
   console.log("Loaded agent.");
 

examples/src/agents/mrkl.ts

@@ -1,17 +1,15 @@
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 
 export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;

examples/src/agents/mrkl_with_tracing.ts

@@ -1,5 +1,5 @@
 import { OpenAI } from "langchain";
-import { initializeAgentExecutor } from "langchain/agents";
+import { initializeAgentExecutorWithOptions } from "langchain/agents";
 import { SerpAPI, Calculator } from "langchain/tools";
 import process from "process";
 
@@ -8,12 +8,10 @@ export const run = async () => {
   const model = new OpenAI({ temperature: 0 });
   const tools = [new SerpAPI(), new Calculator()];
 
-  const executor = await initializeAgentExecutor(
-    tools,
-    model,
-    "zero-shot-react-description",
-    true
-  );
+  const executor = await initializeAgentExecutorWithOptions(tools, model, {
+    agentType: "zero-shot-react-description",
+    verbose: true,
+  });
   console.log("Loaded agent.");
 
   const input = `Who is Olivia Wilde's boyfriend? What is his current age raised to the 0.23 power?`;