diff --git a/docs/core_docs/docs/integrations/llms/azure.mdx b/docs/core_docs/docs/integrations/llms/azure.mdx
index 6f29f04a97b2..eeb34320814d 100644
--- a/docs/core_docs/docs/integrations/llms/azure.mdx
+++ b/docs/core_docs/docs/integrations/llms/azure.mdx
@@ -6,56 +6,6 @@ LangChain.js supports integration with [Azure OpenAI](https://azure.microsoft.co
You can learn more about Azure OpenAI and its difference with the OpenAI API on [this page](https://learn.microsoft.com/azure/ai-services/openai/overview). If you don't have an Azure account, you can [create a free account](https://azure.microsoft.com/free/) to get started.
-## Using the OpenAI SDK
-
-You can also use the `OpenAI` class to call OpenAI models hosted on Azure.
-
-For example, if your Azure instance is hosted under `https://{MY_INSTANCE_NAME}.openai.azure.com/openai/deployments/{DEPLOYMENT_NAME}`, you could initialize your instance like this:
-
-import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
-
-<IntegrationInstallTooltip></IntegrationInstallTooltip>
-
-```bash npm2yarn
-npm install @langchain/openai
-```
-
-```typescript
-import { OpenAI } from "@langchain/openai";
-
-const model = new OpenAI({
- temperature: 0.9,
- azureOpenAIApiKey: "YOUR-API-KEY",
- azureOpenAIApiVersion: "YOUR-API-VERSION",
- azureOpenAIApiInstanceName: "{MY_INSTANCE_NAME}",
- azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
-});
-const res = await model.invoke(
- "What would be a good company name for a company that makes colorful socks?"
-);
-console.log({ res });
-```
-
-If your instance is hosted under a domain other than the default `openai.azure.com`, you'll need to use the alternate `AZURE_OPENAI_BASE_PATH` environment variable.
-For example, here's how you would connect to the domain `https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}`:
-
-```typescript
-import { OpenAI } from "@langchain/openai";
-
-const model = new OpenAI({
- temperature: 0.9,
- azureOpenAIApiKey: "YOUR-API-KEY",
- azureOpenAIApiVersion: "YOUR-API-VERSION",
- azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
- azureOpenAIBasePath:
- "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH
-});
-const res = await model.invoke(
- "What would be a good company name for a company that makes colorful socks?"
-);
-console.log({ res });
-```
-
## Using the Azure OpenAI SDK
You'll first need to install the [`@langchain/azure-openai`](https://www.npmjs.com/package/@langchain/azure-openai) package:
@@ -87,7 +37,21 @@ const model = new AzureOpenAI({
azureOpenAIEndpoint: "<your_endpoint>",
azureOpenAIApiKey: "<your_key>",
azureOpenAIApiDeploymentName: "<your_deployment_name",
- modelName: "<your_model>",
+});
+```
+
+If you're using Azure Managed Identity, you can also pass the credentials directly to the constructor:
+
+```typescript
+import { DefaultAzureCredential } from "@azure/identity";
+import { AzureOpenAI } from "@langchain/azure-openai";
+
+const credentials = new DefaultAzureCredential();
+
+const model = new AzureOpenAI({
+ credentials,
+ azureOpenAIEndpoint: "<your_endpoint>",
+ azureOpenAIApiDeploymentName: "<your_deployment_name",
});
```
@@ -113,3 +77,59 @@ import CodeBlock from "@theme/CodeBlock";
import LLMExample from "@examples/llms/azure_openai.ts";
<CodeBlock language="text">{LLMExample}</CodeBlock>
+
+### Chat usage example
+
+import ChatExample from "@examples/llms/azure_openai-chat.ts";
+
+<CodeBlock language="text">{ChatExample}</CodeBlock>
+
+## Using OpenAI SDK
+
+You can also use the `OpenAI` class to call OpenAI models hosted on Azure.
+
+For example, if your Azure instance is hosted under `https://{MY_INSTANCE_NAME}.openai.azure.com/openai/deployments/{DEPLOYMENT_NAME}`, you could initialize your instance like this:
+
+import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
+
+<IntegrationInstallTooltip></IntegrationInstallTooltip>
+
+```bash npm2yarn
+npm install @langchain/openai
+```
+
+```typescript
+import { OpenAI } from "@langchain/openai";
+
+const model = new OpenAI({
+ temperature: 0.9,
+ azureOpenAIApiKey: "YOUR-API-KEY",
+ azureOpenAIApiVersion: "YOUR-API-VERSION",
+ azureOpenAIApiInstanceName: "{MY_INSTANCE_NAME}",
+ azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
+});
+const res = await model.invoke(
+ "What would be a good company name for a company that makes colorful socks?"
+);
+console.log({ res });
+```
+
+If your instance is hosted under a domain other than the default `openai.azure.com`, you'll need to use the alternate `AZURE_OPENAI_BASE_PATH` environment variable.
+For example, here's how you would connect to the domain `https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}`:
+
+```typescript
+import { OpenAI } from "@langchain/openai";
+
+const model = new OpenAI({
+ temperature: 0.9,
+ azureOpenAIApiKey: "YOUR-API-KEY",
+ azureOpenAIApiVersion: "YOUR-API-VERSION",
+ azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
+ azureOpenAIBasePath:
+ "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH
+});
+const res = await model.invoke(
+ "What would be a good company name for a company that makes colorful socks?"
+);
+console.log({ res });
+```
diff --git a/docs/core_docs/docs/integrations/text_embedding/azure_openai.mdx b/docs/core_docs/docs/integrations/text_embedding/azure_openai.mdx
index fd8e062882d7..04de92f656b5 100644
--- a/docs/core_docs/docs/integrations/text_embedding/azure_openai.mdx
+++ b/docs/core_docs/docs/integrations/text_embedding/azure_openai.mdx
@@ -10,57 +10,14 @@ LangChain.js supports integration with [Azure OpenAI](https://azure.microsoft.co
You can learn more about Azure OpenAI and its difference with the OpenAI API on [this page](https://learn.microsoft.com/azure/ai-services/openai/overview). If you don't have an Azure account, you can [create a free account](https://azure.microsoft.com/free/) to get started.
-## Using the OpenAI SDK
+## Using Azure OpenAI SDK
-The `OpenAIEmbeddings` class can also use the OpenAI API on Azure to generate embeddings for a given text. By default it strips new line characters from the text, as recommended by OpenAI, but you can disable this by passing `stripNewLines: false` to the constructor.
-
-For example, if your Azure instance is hosted under `https://{MY_INSTANCE_NAME}.openai.azure.com/openai/deployments/{DEPLOYMENT_NAME}`, you
-could initialize your instance like this:
+You'll first need to install the [`@langchain/azure-openai`](https://www.npmjs.com/package/@langchain/azure-openai) package:
import IntegrationInstallTooltip from "@mdx_components/integration_install_tooltip.mdx";
<IntegrationInstallTooltip></IntegrationInstallTooltip>
-```bash npm2yarn
-npm install @langchain/openai
-```
-
-```typescript
-import { OpenAIEmbeddings } from "@langchain/openai";
-
-const embeddings = new OpenAIEmbeddings({
- azureOpenAIApiKey: "YOUR-API-KEY", // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
- azureOpenAIApiVersion: "YOUR-API-VERSION", // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
- azureOpenAIApiInstanceName: "{MY_INSTANCE_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME
- azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME
-});
-```
-
-If you'd like to initialize using environment variable defaults, the `process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME`
-will be used first, then `process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME`. This can be useful if you're using these embeddings
-with another Azure OpenAI model.
-
-If your instance is hosted under a domain other than the default `openai.azure.com`, you'll need to use the alternate `AZURE_OPENAI_BASE_PATH` environment variable.
-For example, here's how you would connect to the domain `https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}`:
-
-```typescript
-import { OpenAIEmbeddings } from "@langchain/openai";
-
-const embeddings = new OpenAIEmbeddings({
- azureOpenAIApiKey: "YOUR-API-KEY",
- azureOpenAIApiVersion: "YOUR-API-VERSION",
- azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
- azureOpenAIBasePath:
- "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH
-});
-```
-
-## Using the Azure OpenAI SDK
-
-You'll first need to install the [`@langchain/azure-openai`](https://www.npmjs.com/package/@langchain/azure-openai) package:
-
-<IntegrationInstallTooltip></IntegrationInstallTooltip>
-
```bash npm2yarn
npm install -S @langchain/azure-openai
```
@@ -86,7 +43,6 @@ const model = new AzureOpenAI({
azureOpenAIEndpoint: "<your_endpoint>",
azureOpenAIApiKey: "<your_key>",
azureOpenAIApiDeploymentName: "<your_embedding_deployment_name",
- modelName: "<your_model>",
});
```
@@ -102,13 +58,55 @@ const model = new AzureOpenAI({
credentials,
azureOpenAIEndpoint: "<your_endpoint>",
azureOpenAIApiDeploymentName: "<your_embedding_deployment_name",
- modelName: "<your_model>",
});
```
### Usage example
import CodeBlock from "@theme/CodeBlock";
-import Example from "@examples/llms/azure_openai.ts";
+import Example from "@examples/embeddings/azure_openai.ts";
<CodeBlock language="text">{Example}</CodeBlock>
+
+## Using OpenAI SDK
+
+The `OpenAIEmbeddings` class can also use the OpenAI API on Azure to generate embeddings for a given text. By default it strips new line characters from the text, as recommended by OpenAI, but you can disable this by passing `stripNewLines: false` to the constructor.
+
+For example, if your Azure instance is hosted under `https://{MY_INSTANCE_NAME}.openai.azure.com/openai/deployments/{DEPLOYMENT_NAME}`, you
+could initialize your instance like this:
+
+<IntegrationInstallTooltip></IntegrationInstallTooltip>
+
+```bash npm2yarn
+npm install @langchain/openai
+```
+
+```typescript
+import { OpenAIEmbeddings } from "@langchain/openai";
+
+const embeddings = new OpenAIEmbeddings({
+ azureOpenAIApiKey: "YOUR-API-KEY", // In Node.js defaults to process.env.AZURE_OPENAI_API_KEY
+ azureOpenAIApiVersion: "YOUR-API-VERSION", // In Node.js defaults to process.env.AZURE_OPENAI_API_VERSION
+ azureOpenAIApiInstanceName: "{MY_INSTANCE_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_INSTANCE_NAME
+ azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}", // In Node.js defaults to process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME
+});
+```
+
+If you'd like to initialize using environment variable defaults, the `process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME`
+will be used first, then `process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME`. This can be useful if you're using these embeddings
+with another Azure OpenAI model.
+
+If your instance is hosted under a domain other than the default `openai.azure.com`, you'll need to use the alternate `AZURE_OPENAI_BASE_PATH` environment variable.
+For example, here's how you would connect to the domain `https://westeurope.api.microsoft.com/openai/deployments/{DEPLOYMENT_NAME}`:
+
+```typescript
+import { OpenAIEmbeddings } from "@langchain/openai";
+
+const embeddings = new OpenAIEmbeddings({
+ azureOpenAIApiKey: "YOUR-API-KEY",
+ azureOpenAIApiVersion: "YOUR-API-VERSION",
+ azureOpenAIApiDeploymentName: "{DEPLOYMENT_NAME}",
+ azureOpenAIBasePath:
+ "https://westeurope.api.microsoft.com/openai/deployments", // In Node.js defaults to process.env.AZURE_OPENAI_BASE_PATH
+});
+```
diff --git a/examples/src/llms/azure_openai-chat.ts b/examples/src/llms/azure_openai-chat.ts
new file mode 100644
index 000000000000..f98bdd605e64
--- /dev/null
+++ b/examples/src/llms/azure_openai-chat.ts
@@ -0,0 +1,18 @@
+import { AzureChatOpenAI } from "@langchain/azure-openai";
+
+export const run = async () => {
+ const model = new AzureChatOpenAI({
+ modelName: "gpt-4",
+ prefixMessages: [
+ {
+ role: "system",
+ content: "You are a helpful assistant that answers in pirate language",
+ },
+ ],
+ maxTokens: 50,
+ });
+ const res = await model.invoke(
+ "What would be a good company name for a company that makes colorful socks?"
+ );
+ console.log({ res });
+};
diff --git a/libs/langchain-azure-openai/README.md b/libs/langchain-azure-openai/README.md
index 44988dcf74d2..5c09cc02ea52 100644
--- a/libs/langchain-azure-openai/README.md
+++ b/libs/langchain-azure-openai/README.md
@@ -19,7 +19,7 @@ You can do so by adding appropriate fields to your project's `package.json` like
"name": "your-project",
"version": "0.0.0",
"dependencies": {
- "@langchain/openai": "^0.0.9",
+ "@langchain/azure-openai": "^0.0.4",
"langchain": "0.0.207"
},
"resolutions": {
@@ -56,7 +56,6 @@ Then initialize the model and make the calls:
import { AzureChatOpenAI } from "@langchain/azure-openai";
const model = new AzureChatOpenAI({
- modelName: "gpt-4-1106-preview",
// Note that the following are optional, and will default to the values below
// if not provided.
azureOpenAIEndpoint: process.env.AZURE_OPENAI_API_ENDPOINT,
@@ -72,7 +71,6 @@ const response = await model.invoke(new HumanMessage("Hello world!"));
import { AzureChatOpenAI } from "@langchain/azure-openai";
const model = new AzureChatOpenAI({
- modelName: "gpt-4-1106-preview",
// Note that the following are optional, and will default to the values below
// if not provided.
azureOpenAIEndpoint: process.env.AZURE_OPENAI_API_ENDPOINT,
@@ -94,11 +92,41 @@ const embeddings = new AzureOpenAIEmbeddings({
// if not provided.
azureOpenAIEndpoint: process.env.AZURE_OPENAI_API_ENDPOINT,
azureOpenAIApiKey: process.env.AZURE_OPENAI_API_KEY,
- azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
+ azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_EMBEDDINGS_DEPLOYMENT_NAME,
});
const res = await embeddings.embedQuery("Hello world");
```
+## Using Azure managed identity
+
+If you're using [Azure Managed Identity](https://learn.microsoft.com/azure/ai-services/openai/how-to/managed-identity), you can also pass the credentials directly to the constructor:
+
+```typescript
+import { DefaultAzureCredential } from "@azure/identity";
+import { AzureOpenAI } from "@langchain/azure-openai";
+
+const credentials = new DefaultAzureCredential();
+
+const model = new AzureOpenAI({
+ credentials,
+ azureOpenAIEndpoint: process.env.AZURE_OPENAI_API_ENDPOINT,
+ azureOpenAIApiDeploymentName: process.env.AZURE_OPENAI_API_DEPLOYMENT_NAME,
+});
+```
+
+## Compatibility with OpenAI API
+
+This library is provides compatibility with the OpenAI API. You can use an API key from OpenAI's developer portal like in the example below:
+
+```typescript
+import { AzureOpenAI, OpenAIKeyCredential } from "@langchain/azure-openai";
+
+const model = new AzureOpenAI({
+ modelName: "gpt-3.5-turbo",
+ credentials: new OpenAIKeyCredential("<your_openai_api_key>"),
+});
+```
+
## Development
To develop the Azure OpenAI package, you'll need to follow these instructions:
diff --git a/libs/langchain-azure-openai/src/chat_models.ts b/libs/langchain-azure-openai/src/chat_models.ts
index 6acda2300b23..ffa7c8030adb 100644
--- a/libs/langchain-azure-openai/src/chat_models.ts
+++ b/libs/langchain-azure-openai/src/chat_models.ts
@@ -266,15 +266,27 @@ export class AzureChatOpenAI
(getEnvironmentVariable("AZURE_OPENAI_API_KEY") ||
getEnvironmentVariable("OPENAI_API_KEY"));
+ const azureCredential =
+ fields?.credentials ??
+ (fields?.azureOpenAIApiKey ||
+ getEnvironmentVariable("AZURE_OPENAI_API_KEY")
+ ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
+ : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+
+ const isOpenAIApiKey =
+ fields?.azureOpenAIApiKey ||
+ // eslint-disable-next-line no-instanceof/no-instanceof
+ azureCredential instanceof OpenAIKeyCredential;
+
if (!this.azureOpenAIApiKey && !fields?.credentials) {
throw new Error("Azure OpenAI API key not found");
}
- if (!this.azureOpenAIEndpoint) {
+ if (!this.azureOpenAIEndpoint && !isOpenAIApiKey) {
throw new Error("Azure OpenAI Endpoint not found");
}
- if (!this.azureOpenAIApiDeploymentName) {
+ if (!this.azureOpenAIApiDeploymentName && !isOpenAIApiKey) {
throw new Error("Azure OpenAI Deployment name not found");
}
@@ -294,28 +306,25 @@ export class AzureChatOpenAI
this.streaming = fields?.streaming ?? false;
- const azureCredential =
- fields?.credentials ??
- (fields?.azureOpenAIApiKey ||
- getEnvironmentVariable("AZURE_OPENAI_API_KEY")
- ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
- : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+ const options = {
+ userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
+ };
- if (isTokenCredential(azureCredential)) {
+ if (isOpenAIApiKey) {
+ this.client = new AzureOpenAIClient(
+ azureCredential as OpenAIKeyCredential
+ );
+ } else if (isTokenCredential(azureCredential)) {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as TokenCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
} else {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as KeyCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
}
}
@@ -339,11 +348,11 @@ export class AzureChatOpenAI
options: this["ParsedCallOptions"]
): Promise<EventStream<ChatCompletions>> {
return this.caller.call(async () => {
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Deployment name not found");
- }
+ const deploymentName =
+ this.azureOpenAIApiDeploymentName || this.modelName;
+
const res = await this.client.streamChatCompletions(
- this.azureOpenAIApiDeploymentName,
+ deploymentName,
azureOpenAIMessages,
{
functions: options?.functions,
@@ -434,10 +443,7 @@ export class AzureChatOpenAI
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<ChatResult> {
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Deployment name not found");
- }
- const deploymentName = this.azureOpenAIApiDeploymentName;
+ const deploymentName = this.azureOpenAIApiDeploymentName || this.modelName;
const tokenUsage: TokenUsage = {};
const azureOpenAIMessages: ChatRequestMessage[] =
this.formatMessages(messages);
diff --git a/libs/langchain-azure-openai/src/embeddings.ts b/libs/langchain-azure-openai/src/embeddings.ts
index e7ae702b4378..c62817f5baf4 100644
--- a/libs/langchain-azure-openai/src/embeddings.ts
+++ b/libs/langchain-azure-openai/src/embeddings.ts
@@ -23,8 +23,7 @@ export class AzureOpenAIEmbeddings
batchSize = 512;
- // TODO: Update to `false` on next minor release (see: https://github.com/langchain-ai/langchainjs/pull/3612)
- stripNewLines = true;
+ stripNewLines = false;
timeout?: number;
@@ -64,16 +63,28 @@ export class AzureOpenAIEmbeddings
(getEnvironmentVariable("AZURE_OPENAI_API_KEY") ||
getEnvironmentVariable("OPENAI_API_KEY"));
+ const azureCredential =
+ fields?.credentials ??
+ (fields?.azureOpenAIApiKey ||
+ getEnvironmentVariable("AZURE_OPENAI_API_KEY")
+ ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
+ : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+
+ const isOpenAIApiKey =
+ fields?.azureOpenAIApiKey ||
+ // eslint-disable-next-line no-instanceof/no-instanceof
+ azureCredential instanceof OpenAIKeyCredential;
+
if (!this.azureOpenAIApiKey && !fields?.credentials) {
throw new Error("Azure OpenAI API key not found");
}
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Completion Deployment name not found");
+ if (!this.azureOpenAIEndpoint && !isOpenAIApiKey) {
+ throw new Error("Azure OpenAI Endpoint not found");
}
- if (!this.azureOpenAIEndpoint) {
- throw new Error("Azure OpenAI Endpoint not found");
+ if (!this.azureOpenAIApiDeploymentName && !isOpenAIApiKey) {
+ throw new Error("Azure OpenAI Deployment name not found");
}
this.modelName = fieldsWithDefaults?.modelName ?? this.modelName;
@@ -87,28 +98,25 @@ export class AzureOpenAIEmbeddings
this.timeout = fieldsWithDefaults?.timeout;
- const azureCredential =
- fields?.credentials ??
- (fields?.azureOpenAIApiKey ||
- getEnvironmentVariable("AZURE_OPENAI_API_KEY")
- ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
- : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+ const options = {
+ userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
+ };
- if (isTokenCredential(azureCredential)) {
+ if (isOpenAIApiKey) {
+ this.client = new AzureOpenAIClient(
+ azureCredential as OpenAIKeyCredential
+ );
+ } else if (isTokenCredential(azureCredential)) {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as TokenCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
} else {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as KeyCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
}
}
@@ -133,22 +141,16 @@ export class AzureOpenAIEmbeddings
}
private async getEmbeddings(input: string[]) {
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Deployment name not found");
- }
+ const deploymentName = this.azureOpenAIApiDeploymentName || this.modelName;
const res = await this.caller.call(() =>
- this.client.getEmbeddings(
- this.azureOpenAIApiDeploymentName ?? "",
- input,
- {
- user: this.user,
- model: this.modelName,
- requestOptions: {
- timeout: this.timeout,
- },
- }
- )
+ this.client.getEmbeddings(deploymentName, input, {
+ user: this.user,
+ model: this.modelName,
+ requestOptions: {
+ timeout: this.timeout,
+ },
+ })
);
return res.data[0].embedding;
diff --git a/libs/langchain-azure-openai/src/llms.ts b/libs/langchain-azure-openai/src/llms.ts
index e735b54161ed..05e8e0b255a5 100644
--- a/libs/langchain-azure-openai/src/llms.ts
+++ b/libs/langchain-azure-openai/src/llms.ts
@@ -133,15 +133,27 @@ export class AzureOpenAI<
(getEnvironmentVariable("AZURE_OPENAI_API_KEY") ||
getEnvironmentVariable("OPENAI_API_KEY"));
+ const azureCredential =
+ fields?.credentials ??
+ (fields?.azureOpenAIApiKey ||
+ getEnvironmentVariable("AZURE_OPENAI_API_KEY")
+ ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
+ : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+
+ const isOpenAIApiKey =
+ fields?.azureOpenAIApiKey ||
+ // eslint-disable-next-line no-instanceof/no-instanceof
+ azureCredential instanceof OpenAIKeyCredential;
+
if (!this.azureOpenAIApiKey && !fields?.credentials) {
throw new Error("Azure OpenAI API key not found");
}
- if (!this.azureOpenAIEndpoint) {
+ if (!this.azureOpenAIEndpoint && !isOpenAIApiKey) {
throw new Error("Azure OpenAI Endpoint not found");
}
- if (!this.azureOpenAIApiDeploymentName) {
+ if (!this.azureOpenAIApiDeploymentName && !isOpenAIApiKey) {
throw new Error("Azure OpenAI Deployment name not found");
}
@@ -166,28 +178,25 @@ export class AzureOpenAI<
throw new Error("Cannot stream results when bestOf > 1");
}
- const azureCredential =
- fields?.credentials ??
- (fields?.azureOpenAIApiKey ||
- getEnvironmentVariable("AZURE_OPENAI_API_KEY")
- ? new AzureKeyCredential(this.azureOpenAIApiKey ?? "")
- : new OpenAIKeyCredential(this.azureOpenAIApiKey ?? ""));
+ const options = {
+ userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
+ };
- if (isTokenCredential(azureCredential)) {
+ if (isOpenAIApiKey) {
+ this.client = new AzureOpenAIClient(
+ azureCredential as OpenAIKeyCredential
+ );
+ } else if (isTokenCredential(azureCredential)) {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as TokenCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
} else {
this.client = new AzureOpenAIClient(
this.azureOpenAIEndpoint ?? "",
azureCredential as KeyCredential,
- {
- userAgentOptions: { userAgentPrefix: USER_AGENT_PREFIX },
- }
+ options
);
}
}
@@ -197,11 +206,7 @@ export class AzureOpenAI<
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): AsyncGenerator<GenerationChunk> {
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Completion Deployment name not found");
- }
-
- const deploymentName = this.azureOpenAIApiDeploymentName;
+ const deploymentName = this.azureOpenAIApiDeploymentName || this.modelName;
const stream = await this.caller.call(() =>
this.client.streamCompletions(deploymentName, [input], {
@@ -251,11 +256,7 @@ export class AzureOpenAI<
options: this["ParsedCallOptions"],
runManager?: CallbackManagerForLLMRun
): Promise<LLMResult> {
- if (!this.azureOpenAIApiDeploymentName) {
- throw new Error("Azure OpenAI Completion Deployment name not found");
- }
-
- const deploymentName = this.azureOpenAIApiDeploymentName;
+ const deploymentName = this.azureOpenAIApiDeploymentName || this.modelName;
if (this.maxTokens === -1) {
if (prompts.length !== 1) {
diff --git a/libs/langchain-azure-openai/src/tests/chat_models.int.test.ts b/libs/langchain-azure-openai/src/tests/chat_models.int.test.ts
index 2a4d7e01d717..e5c48c1e13fc 100644
--- a/libs/langchain-azure-openai/src/tests/chat_models.int.test.ts
+++ b/libs/langchain-azure-openai/src/tests/chat_models.int.test.ts
@@ -16,6 +16,8 @@ import {
import { CallbackManager } from "@langchain/core/callbacks/manager";
import { NewTokenIndices } from "@langchain/core/callbacks/base";
import { InMemoryCache } from "@langchain/core/caches";
+import { getEnvironmentVariable } from "@langchain/core/utils/env";
+import { OpenAIKeyCredential } from "@azure/openai";
import { AzureChatOpenAI } from "../chat_models.js";
test("Test ChatOpenAI", async () => {
@@ -790,3 +792,19 @@ test("Test ChatOpenAI token usage reporting for streaming calls", async () => {
expect(streamingTokenUsed).toEqual(nonStreamingTokenUsed);
}
});
+
+test("Test ChatOpenAI with OpenAI API key credentials", async () => {
+ const openAiKey: string = getEnvironmentVariable("OPENAI_API_KEY") ?? "";
+ const credentials = new OpenAIKeyCredential(openAiKey);
+
+ const chat = new AzureChatOpenAI({
+ modelName: "gpt-3.5-turbo",
+ maxTokens: 5,
+ credentials,
+ azureOpenAIEndpoint: "",
+ azureOpenAIApiDeploymentName: "",
+ });
+ const message = new HumanMessage("Hello!");
+ const res = await chat.invoke([["system", "Say hi"], message]);
+ console.log(res);
+});
diff --git a/libs/langchain-azure-openai/src/tests/embeddings.int.test.ts b/libs/langchain-azure-openai/src/tests/embeddings.int.test.ts
index 49d230cec189..90babbcc8410 100644
--- a/libs/langchain-azure-openai/src/tests/embeddings.int.test.ts
+++ b/libs/langchain-azure-openai/src/tests/embeddings.int.test.ts
@@ -1,6 +1,7 @@
import { test, expect } from "@jest/globals";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
import { ClientSecretCredential, TokenCredential } from "@azure/identity";
+import { OpenAIKeyCredential } from "@azure/openai";
import { AzureOpenAIEmbeddings } from "../embeddings.js";
test("Test OpenAIEmbeddings.embedQuery", async () => {
@@ -68,3 +69,16 @@ test("Test OpenAIEmbeddings.embedQuery with TokenCredentials", async () => {
const res = await embeddings.embedQuery("Hello world");
expect(typeof res[0]).toBe("number");
});
+
+test("Test OpenAIEmbeddings.embedQuery with OpenAI API key credentials", async () => {
+ const openAiKey: string = getEnvironmentVariable("OPENAI_API_KEY") ?? "";
+ const credentials = new OpenAIKeyCredential(openAiKey);
+
+ const embeddings = new AzureOpenAIEmbeddings({
+ credentials,
+ azureOpenAIEndpoint: "",
+ azureOpenAIApiDeploymentName: "",
+ });
+ const res = await embeddings.embedQuery("Hello world");
+ expect(typeof res[0]).toBe("number");
+});
diff --git a/libs/langchain-azure-openai/src/tests/llms.int.test.ts b/libs/langchain-azure-openai/src/tests/llms.int.test.ts
index 6a03c9c5152d..58bcbc80677e 100644
--- a/libs/langchain-azure-openai/src/tests/llms.int.test.ts
+++ b/libs/langchain-azure-openai/src/tests/llms.int.test.ts
@@ -6,6 +6,7 @@ import { NewTokenIndices } from "@langchain/core/callbacks/base";
import { ClientSecretCredential } from "@azure/identity";
import { TokenCredential } from "@azure/core-auth";
import { getEnvironmentVariable } from "@langchain/core/utils/env";
+import { OpenAIKeyCredential } from "@azure/openai";
import { AzureOpenAI } from "../llms.js";
test("Test OpenAI", async () => {
@@ -325,3 +326,18 @@ test("Test OpenAI with Token credentials ", async () => {
const res = await model.invoke("Print hello world");
console.log({ res });
});
+
+test("Test OpenAI with OpenAI API key credentials ", async () => {
+ const openAiKey: string = getEnvironmentVariable("OPENAI_API_KEY") ?? "";
+ const credentials = new OpenAIKeyCredential(openAiKey);
+
+ const model = new AzureOpenAI({
+ maxTokens: 5,
+ modelName: "davinci-002",
+ credentials,
+ azureOpenAIEndpoint: "",
+ azureOpenAIApiDeploymentName: "",
+ });
+ const res = await model.invoke("Print hello world");
+ console.log({ res });
+});