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Add documentation for get embedding operation in Azure OpenAI (#3658) 

* Add documentation for get embedding

Signed-off-by: Shivam Singh <shivamhere247@gmail.com>

* Resolve comments

Signed-off-by: Shivam Singh <shivamhere247@gmail.com>

---------

Signed-off-by: Shivam Singh <shivamhere247@gmail.com>
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Shivam Kumar Singh 2023-08-08 23:12:18 +05:30 committed by GitHub
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62
daprdocs/content/en/reference/components-reference/supported-bindings/openai.md
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@ -26,8 +26,6 @@ spec:
value: "1234567890abcdef"
- name: endpoint # Required
value: "https://myopenai.openai.azure.com"
- name: deploymentId # Required
value: "my-model"
```
{{% alert title="Warning" color="warning" %}}
The above example uses `apiKey` as a plain string. It is recommended to use a secret store for the secrets as described [here]({{< ref component-secrets.md >}}).
@ -39,7 +37,6 @@ The above example uses `apiKey` as a plain string. It is recommended to use a s
|--------------------|:--------:|--------|---------|---------|
| `endpoint` | Y | Output | Azure OpenAI service endpoint URL. | `"https://myopenai.openai.azure.com"` |
| `apiKey` | Y* | Output | The access key of the Azure OpenAI service. Only required when not using Azure AD authentication. | `"1234567890abcdef"` |
| `deploymentId` | Y | Output | The name of the model deployment. | `"my-model"` |
| `azureTenantId` | Y* | Input | The tenant ID of the Azure OpenAI resource. Only required when `apiKey` is not provided. | `"tenentID"` |
| `azureClientId` | Y* | Input | The client ID that should be used by the binding to create or update the Azure OpenAI Subscription and to authenticate incoming messages. Only required when `apiKey` is not provided.| `"clientId"` |
| `azureClientSecret` | Y* | Input | The client secret that should be used by the binding to create or update the Azure OpenAI Subscription and to authenticate incoming messages. Only required when `apiKey` is not provided. | `"clientSecret"` |
@ -61,8 +58,6 @@ spec:
metadata:
- name: endpoint
value: "https://myopenai.openai.azure.com"
- name: deploymentId
value: "my-model"
- name: azureTenantId
value: "***"
- name: azureClientId
@ -76,6 +71,7 @@ This component supports **output binding** with the following operations:
- `completion` : [Completion API](#completion-api)
- `chat-completion` : [Chat Completion API](#chat-completion-api)
- `get-embedding` : [Embedding API](#get-embedding-api)
### Completion API
@ -83,8 +79,9 @@ To call the completion API with a prompt, invoke the Azure OpenAI binding with a
```json
{
"operation": "create",
"operation": "completion",
"data": {
"deploymentId": "my-model",
"prompt": "A dog is",
"maxTokens":5
}
@ -93,6 +90,7 @@ To call the completion API with a prompt, invoke the Azure OpenAI binding with a
The data parameters are:
- `deploymentId` - string that specifies the model deployment ID to use.
- `prompt` - string that specifies the prompt to generate completions for.
- `maxTokens` - (optional) defines the max number of tokens to generate. Defaults to 16 for completion API.
- `temperature` - (optional) defines the sampling temperature between 0 and 2. Higher values like 0.8 make the output more random, while lower values like 0.2 make it more focused and deterministic. Defaults to 1.0 for completion API.
@ -107,7 +105,7 @@ Read more about the importance and usage of these parameters in the [Azure OpenA
{{< tabs Linux >}}
{{% codetab %}}
```bash
curl -d '{ "data": {"prompt": "A dog is ", "maxTokens":15}, "operation": "completion" }' \
curl -d '{ "data": {"deploymentId: "my-model" , "prompt": "A dog is ", "maxTokens":15}, "operation": "completion" }' \
http://localhost:<dapr-port>/v1.0/bindings/<binding-name>
```
{{% /codetab %}}
@ -142,6 +140,7 @@ To perform a chat-completion operation, invoke the Azure OpenAI binding with a `
{
"operation": "chat-completion",
"data": {
"deploymentId": "my-model",
"messages": [
{
"role": "system",
@ -161,6 +160,7 @@ To perform a chat-completion operation, invoke the Azure OpenAI binding with a `
The data parameters are:
- `deploymentId` - string that specifies the model deployment ID to use.
- `messages` - array of messages that will be used to generate chat completions.
Each message is of the form:
- `role` - string that specifies the role of the message. Can be either `user`, `system` or `assistant`.
@ -180,6 +180,7 @@ Each message is of the form:
```bash
curl -d '{
"data": {
"deploymentId": "my-model",
"messages": [
{
"role": "system",
@ -228,6 +229,53 @@ The response body contains the following JSON:
```
### Get Embedding API
The `get-embedding` operation returns a vector representation of a given input that can be easily consumed by machine learning models and other algorithms.
To perform a `get-embedding` operation, invoke the Azure OpenAI binding with a `POST` method and the following JSON body:
```json
{
"operation": "get-embedding",
"data": {
"deploymentId": "my-model",
"message": "The capital of France is Paris."
}
}
```
The data parameters are:
- `deploymentId` - string that specifies the model deployment ID to use.
- `message` - string that specifies the text to embed.
#### Example
{{< tabs Linux >}}
{{% codetab %}}
```bash
curl -d '{
"data": {
"deploymentId": "embeddings",
"message": "The capital of France is Paris."
},
"operation": "get-embedding"
}' \
http://localhost:<dapr-port>/v1.0/bindings/<binding-name>
```
{{% /codetab %}}
{{< /tabs >}}
#### Response
The response body contains the following JSON:
```json
[0.018574921,-0.00023652936,-0.0057790717,.... (1536 floats total for ada)]
```
## Related links