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‎docs/core_docs/docs/how_to/trim_messages.ipynb

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"source": [
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"# How to trim messages\n",
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"\n",
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":::note\n",
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"The `trimMessages` function is available in `@langchain/core` version `0.2.8` and above.\n",
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":::info Prerequisites\n",
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"\n",
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"This guide assumes familiarity with the following concepts:\n",
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"\n",
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"- [Messages](/docs/concepts/#messages)\n",
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"- [Chat models](/docs/concepts/#chat-models)\n",
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"- [Chaining](/docs/how_to/sequence/)\n",
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"- [Chat history](/docs/concepts/#chat-history)\n",
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"\n",
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"The methods in this guide also require `@langchain/core>=0.2.8`.\n",
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"Please see here for a [guide on upgrading](/docs/how_to/installation/#installing-integration-packages).\n",
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"\n",
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":::\n",
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"\n",
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"All models have finite context windows, meaning there's a limit to how many tokens they can take as input. If you have very long messages or a chain/agent that accumulates a long message is history, you'll need to manage the length of the messages you're passing in to the model.\n",

‎docs/core_docs/docs/integrations/platforms/microsoft.mdx

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```typescript
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import { AzureBlobStorageFileLoader } from "@langchain/community/document_loaders/web/azure_blob_storage_file";
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```
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## Tools
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### Azure Container Apps Dynamic Sessions
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> [Azure Container Apps dynamic sessions](https://learn.microsoft.com/azure/container-apps/sessions) provide fast access to secure sandboxed environments that are ideal for running code or applications that require strong isolation from other workloads.
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<IntegrationInstallTooltip></IntegrationInstallTooltip>
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```bash npm2yarn
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npm install @langchain/azure-dynamic-sessions
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```
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See a [usage example](/docs/integrations/tools/azure_dynamic_sessions).
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```typescript
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import { SessionsPythonREPLTool } from "@langchain/azure-dynamic-sessions";
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```

‎docs/core_docs/docs/integrations/tools/azure_dynamic_sessions.mdx

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# Azure Container Apps Dynamic Sessions
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> [Azure Container Apps dynamic sessions](https://learn.microsoft.com/azure/container-apps/sessions) provide fast access to secure sandboxed environments that are ideal for running code or applications that require strong isolation from other workloads.
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You can learn more about Azure Container Apps dynamic sessions and its code interpretation capabilities on [this page](https://learn.microsoft.com/azure/container-apps/sessions). If you don't have an Azure account, you can [create a free account](https://azure.microsoft.com/free/) to get started.
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## Setup
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You'll first need to install the [`@langchain/azure-dynamic-sessions`](https://www.npmjs.com/package/@langchain/azure-dynamic-sessions) package:
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import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
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<IntegrationInstallTooltip></IntegrationInstallTooltip>
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```bash npm2yarn
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npm install @langchain/azure-dynamic-sessions
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```
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You'll also need to have a code interpreter session pool instance running. You can deploy a version using [Azure CLI](https://learn.microsoft.com/cli/azure/install-azure-cli) following [this guide](https://learn.microsoft.com/azure/container-apps/sessions-code-interpreter).
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Once you have your instance running, you need to make sure you have properly set up the Azure Entra authentication for it. You can find the instructions on how to do that [here](https://learn.microsoft.com/azure/container-apps/sessions?tabs=azure-cli#authentication).
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After you've added the role for your identity, you need to retrieve the **session pool management endpoint**. You can find it in the Azure Portal, under the "Overview" section of your instance. Then you need to set the following environment variable:
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import CodeBlock from "@theme/CodeBlock";
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import EnvVars from "@examples/tools/azure_dynamic_sessions/.env.example";
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<CodeBlock language="text">{EnvVars}</CodeBlock>
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## Usage example
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Below is a simple example that creates a new Python code interpreter session, invoke the tool and prints the result.
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import Example from "@examples/tools/azure_dynamic_sessions/azure_dynamic_sessions.ts";
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<CodeBlock language="typescript">{Example}</CodeBlock>
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Here is a complete example where we use an Azure OpenAI chat model to call the Python code interpreter session tool to execute the code and get the result:
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import AgentExample from "@examples/tools/azure_dynamic_sessions/azure_dynamic_sessions-agent.ts";
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<CodeBlock language="typescript">{AgentExample}</CodeBlock>

‎environment_tests/test-exports-bun/src/entrypoints.js

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@@ -28,10 +28,10 @@ export * from "langchain/memory";
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export * from "langchain/memory/index";
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export * from "langchain/memory/chat_memory";
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export * from "langchain/document";
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export * from "@langchain/community/document_loaders/base";
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export * from "@langchain/community/document_loaders/web/searchapi";
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export * from "@langchain/community/document_loaders/web/serpapi";
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export * from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_loaders/base";
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export * from "langchain/document_loaders/web/searchapi";
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export * from "langchain/document_loaders/web/serpapi";
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export * from "langchain/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_transformers/openai_functions";
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export * from "langchain/callbacks";
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export * from "langchain/output_parsers";

‎environment_tests/test-exports-cf/src/entrypoints.js

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export * from "langchain/memory/index";
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export * from "langchain/memory/chat_memory";
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export * from "langchain/document";
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export * from "@langchain/community/document_loaders/base";
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export * from "@langchain/community/document_loaders/web/searchapi";
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export * from "@langchain/community/document_loaders/web/serpapi";
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export * from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_loaders/base";
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export * from "langchain/document_loaders/web/searchapi";
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export * from "langchain/document_loaders/web/serpapi";
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export * from "langchain/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_transformers/openai_functions";
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export * from "langchain/callbacks";
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export * from "langchain/output_parsers";

‎environment_tests/test-exports-cjs/src/entrypoints.js

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const memory_index = require("langchain/memory/index");
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const memory_chat_memory = require("langchain/memory/chat_memory");
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const document = require("langchain/document");
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const document_loaders_base = require("@langchain/community/document_loaders/base");
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const document_loaders_web_searchapi = require("@langchain/community/document_loaders/web/searchapi");
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const document_loaders_web_serpapi = require("@langchain/community/document_loaders/web/serpapi");
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const document_loaders_web_sort_xyz_blockchain = require("@langchain/community/document_loaders/web/sort_xyz_blockchain");
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const document_loaders_base = require("langchain/document_loaders/base");
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const document_loaders_web_searchapi = require("langchain/document_loaders/web/searchapi");
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const document_loaders_web_serpapi = require("langchain/document_loaders/web/serpapi");
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const document_loaders_web_sort_xyz_blockchain = require("langchain/document_loaders/web/sort_xyz_blockchain");
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const document_transformers_openai_functions = require("langchain/document_transformers/openai_functions");
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const callbacks = require("langchain/callbacks");
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const output_parsers = require("langchain/output_parsers");

‎environment_tests/test-exports-esbuild/src/entrypoints.js

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import * as memory_index from "langchain/memory/index";
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import * as memory_chat_memory from "langchain/memory/chat_memory";
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import * as document from "langchain/document";
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import * as document_loaders_base from "@langchain/community/document_loaders/base";
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import * as document_loaders_web_searchapi from "@langchain/community/document_loaders/web/searchapi";
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import * as document_loaders_web_serpapi from "@langchain/community/document_loaders/web/serpapi";
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import * as document_loaders_web_sort_xyz_blockchain from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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import * as document_loaders_base from "langchain/document_loaders/base";
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import * as document_loaders_web_searchapi from "langchain/document_loaders/web/searchapi";
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import * as document_loaders_web_serpapi from "langchain/document_loaders/web/serpapi";
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import * as document_loaders_web_sort_xyz_blockchain from "langchain/document_loaders/web/sort_xyz_blockchain";
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import * as document_transformers_openai_functions from "langchain/document_transformers/openai_functions";
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import * as callbacks from "langchain/callbacks";
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import * as output_parsers from "langchain/output_parsers";

‎environment_tests/test-exports-esm/src/entrypoints.js

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import * as memory_index from "langchain/memory/index";
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import * as memory_chat_memory from "langchain/memory/chat_memory";
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import * as document from "langchain/document";
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import * as document_loaders_base from "@langchain/community/document_loaders/base";
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import * as document_loaders_web_searchapi from "@langchain/community/document_loaders/web/searchapi";
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import * as document_loaders_web_serpapi from "@langchain/community/document_loaders/web/serpapi";
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import * as document_loaders_web_sort_xyz_blockchain from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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import * as document_loaders_base from "langchain/document_loaders/base";
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import * as document_loaders_web_searchapi from "langchain/document_loaders/web/searchapi";
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import * as document_loaders_web_serpapi from "langchain/document_loaders/web/serpapi";
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import * as document_loaders_web_sort_xyz_blockchain from "langchain/document_loaders/web/sort_xyz_blockchain";
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import * as document_transformers_openai_functions from "langchain/document_transformers/openai_functions";
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import * as callbacks from "langchain/callbacks";
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import * as output_parsers from "langchain/output_parsers";

‎environment_tests/test-exports-vercel/src/entrypoints.js

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export * from "langchain/memory/index";
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export * from "langchain/memory/chat_memory";
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export * from "langchain/document";
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export * from "@langchain/community/document_loaders/base";
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export * from "@langchain/community/document_loaders/web/searchapi";
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export * from "@langchain/community/document_loaders/web/serpapi";
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export * from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_loaders/base";
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export * from "langchain/document_loaders/web/searchapi";
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export * from "langchain/document_loaders/web/serpapi";
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export * from "langchain/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_transformers/openai_functions";
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export * from "langchain/callbacks";
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export * from "langchain/output_parsers";

‎environment_tests/test-exports-vite/src/entrypoints.js

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export * from "langchain/memory/index";
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export * from "langchain/memory/chat_memory";
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export * from "langchain/document";
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export * from "@langchain/community/document_loaders/base";
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export * from "@langchain/community/document_loaders/web/searchapi";
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export * from "@langchain/community/document_loaders/web/serpapi";
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export * from "@langchain/community/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_loaders/base";
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export * from "langchain/document_loaders/web/searchapi";
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export * from "langchain/document_loaders/web/serpapi";
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export * from "langchain/document_loaders/web/sort_xyz_blockchain";
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export * from "langchain/document_transformers/openai_functions";
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export * from "langchain/callbacks";
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export * from "langchain/output_parsers";

‎examples/.env.example

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AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME=ADD_YOURS_HERE # Azure Portal -> Cognitive Services -> OpenAI -> Choose your instance -> Go to Azure OpenAI Studio -> Deployments
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AZURE_OPENAI_API_VERSION=ADD_YOURS_HERE # Azure Portal -> Cognitive Services -> OpenAI -> Choose your instance -> Go to Azure OpenAI Studio -> Completions/Chat -> Choose Deployment -> View Code
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AZURE_OPENAI_BASE_PATH=ADD_YOURS_HERE # Azure Portal -> Cognitive Services -> OpenAI -> Choose your instance -> Endpoint (optional)
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AZURE_OPENAI_BASE_PATH=ADD_YOURS_HERE # Azure Portal -> Cognitive Services -> OpenAI -> Choose your instance -> Endpoint (optional)
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AZURE_CONTAINER_APP_SESSION_POOL_MANAGEMENT_ENDPOINT=ADD_YOURS_HERE # Azure Portal -> Container App Session Pools -> Choose your app -> Pool management endpoint -> Copy the URL
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CONNERY_RUNNER_URL=ADD_YOURS_HERE
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CONNERY_RUNNER_API_KEY=ADD_YOURS_HERE
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ELASTIC_URL=ADD_YOURS_HERE # http://127.0.0.1:9200

‎examples/package.json

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"@gomomento/sdk": "^1.51.1",
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"@google/generative-ai": "^0.7.0",
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"@langchain/anthropic": "workspace:*",
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"@langchain/azure-dynamic-sessions": "workspace:^",
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"@langchain/azure-openai": "workspace:*",
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"@langchain/cloudflare": "workspace:*",
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"@langchain/cohere": "workspace:*",

‎examples/src/tools/azure_dynamic_sessions/.env.example

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AZURE_CONTAINER_APP_SESSION_POOL_MANAGEMENT_ENDPOINT=<your_endpoint>

‎examples/src/tools/azure_dynamic_sessions/azure_dynamic_sessions-agent.ts

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import type { ChatPromptTemplate } from "@langchain/core/prompts";
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import { pull } from "langchain/hub";
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import { AgentExecutor, createToolCallingAgent } from "langchain/agents";
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import { SessionsPythonREPLTool } from "@langchain/azure-dynamic-sessions";
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import { AzureChatOpenAI } from "@langchain/openai";
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const tools = [
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new SessionsPythonREPLTool({
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poolManagementEndpoint:
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process.env.AZURE_CONTAINER_APP_SESSION_POOL_MANAGEMENT_ENDPOINT || "",
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}),
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];
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// Note: you need a model deployment that supports function calling,
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// like `gpt-35-turbo` version `1106`.
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const llm = new AzureChatOpenAI({
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temperature: 0,
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});
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// Get the prompt to use - you can modify this!
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// If you want to see the prompt in full, you can at:
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// https://smith.langchain.com/hub/jacob/tool-calling-agent
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const prompt = await pull<ChatPromptTemplate>("jacob/tool-calling-agent");
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const agent = await createToolCallingAgent({
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llm,
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tools,
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prompt,
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});
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const agentExecutor = new AgentExecutor({
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agent,
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tools,
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});
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const result = await agentExecutor.invoke({
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input:
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"Create a Python program that prints the Python version and return the result.",
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});
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console.log(result);

‎examples/src/tools/azure_dynamic_sessions/azure_dynamic_sessions.ts

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import { SessionsPythonREPLTool } from "@langchain/azure-dynamic-sessions";
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const tool = new SessionsPythonREPLTool({
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poolManagementEndpoint:
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process.env.AZURE_CONTAINER_APP_SESSION_POOL_MANAGEMENT_ENDPOINT || "",
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});
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const result = await tool.invoke("print('Hello, World!')\n1+2");
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console.log(result);
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// {
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// stdout: "Hello, World!\n",
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// stderr: "",
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// result: 3,
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// }

‎langchain-core/package.json

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{
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"name": "@langchain/core",
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"version": "0.2.8",
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"version": "0.2.9",
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"description": "Core LangChain.js abstractions and schemas",
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"type": "module",
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"engines": {

‎langchain-core/src/language_models/base.ts

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}
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};
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/**
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* Whether or not the input matches the OpenAI tool definition.
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* @param {unknown} tool The input to check.
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* @returns {boolean} Whether the input is an OpenAI tool definition.
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*/
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export function isOpenAITool(tool: unknown): tool is ToolDefinition {
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if (typeof tool !== "object" || !tool) return false;
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if (
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"type" in tool &&
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tool.type === "function" &&
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"function" in tool &&
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typeof tool.function === "object" &&
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tool.function &&
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"name" in tool.function &&
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"parameters" in tool.function
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) {
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return true;
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}
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return false;
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}
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interface CalculateMaxTokenProps {
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prompt: string;
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modelName: TiktokenModel;

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