Conversation component specs on Dapr Docs

Anthropic

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: anthropic
spec:
 type: conversation.anthropic
 metadata:
 - name: key
 value: "mykey"
 - name: model
 value: claude-3-5-sonnet-20240620
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for Anthropic.	`"mykey"`
`model`	N	The Anthropic LLM to use. Defaults to `claude-3-5-sonnet-20240620`	`claude-3-5-sonnet-20240620`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`

Conversation API overview

AWS Bedrock

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: awsbedrock
spec:
 type: conversation.aws.bedrock
 metadata:
 - name: endpoint
 value: "http://localhost:4566"
 - name: model
 value: amazon.titan-text-express-v1
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`region`	N	AWS region for the Bedrock service.	`us-east-1`
`endpoint`	N	AWS endpoint for the component to use and connect to emulators. Not recommended for production AWS use.	`http://localhost:4566`
`accessKey`	N	AWS access key for authentication. It is recommended to use a secret store for this value.	`"AKIAIOSFODNN7EXAMPLE"`
`secretKey`	N	AWS secret key for authentication. It is recommended to use a secret store for this value.	`"wJalrXUtnFEMI/K7MDENG/bPxRfiCYEXAMPLEKEY"`
`sessionToken`	N	AWS session token for temporary credentials. It is recommended to use a secret store for this value.	`"session-token-example"`
`model`	N	The LLM to use. Defaults to Bedrock’s default provider model from Amazon.	`amazon.titan-text-express-v1`
`responseCacheTTL`	N	A time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`
`assumeRoleArn`	N	ARN of the role to assume for authentication.	`arn:aws:iam::123456789012:role/MyRole`
`trustAnchorArn`	N	ARN of the trust anchor for authentication.	`arn:aws:rolesanywhere:us-east-1:123456789012:trust-anchor/12345678-1234-1234-1234-123456789012`
`trustProfileArn`	N	ARN of the trust profile for authentication.	`arn:aws:rolesanywhere:us-east-1:123456789012:profile/12345678-1234-1234-1234-123456789012`

Authenticating AWS

Instead of using a key parameter, AWS Bedrock authenticates using Dapr’s standard method of IAM or static credentials. Learn more about authenticating with AWS.

DeepSeek

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: deepseek
spec:
 type: conversation.deepseek
 metadata:
 - name: key
 value: mykey
 - name: maxTokens
 value: 2048

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for DeepSeek.	`mykey`
`maxTokens`	N	The max amount of tokens for each request.	`2048`

Conversation API overview

Local Testing

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: echo
spec:
 type: conversation.echo
 version: v1

Information

This component is only meant for local validation and testing of a Conversation component implementation. It does not actually send the data to any LLM but rather echos the input back directly.

Conversation API overview

GoogleAI

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: googleai
spec:
 type: conversation.googleai
 metadata:
 - name: key
 value: mykey
 - name: model
 value: gemini-1.5-flash
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for GoogleAI.	`mykey`
`model`	N	The GoogleAI LLM to use. Defaults to `gemini-1.5-flash`.	`gemini-2.0-flash`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`

Conversation API overview

Huggingface

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: huggingface
spec:
 type: conversation.huggingface
 metadata:
 - name: key
 value: mykey
 - name: model
 value: meta-llama/Meta-Llama-3-8B
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for Huggingface.	`mykey`
`model`	N	The Huggingface LLM to use. Defaults to `meta-llama/Meta-Llama-3-8B`.	`meta-llama/Meta-Llama-3-8B`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`

Conversation API overview

Mistral

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: mistral
spec:
 type: conversation.mistral
 metadata:
 - name: key
 value: mykey
 - name: model
 value: open-mistral-7b
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for Mistral.	`mykey`
`model`	N	The Mistral LLM to use. Defaults to `open-mistral-7b`.	`open-mistral-7b`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`

Conversation API overview

Ollama

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: ollama
spec:
 type: conversation.ollama
 metadata:
 - name: model
 value: llama3.2:latest
 - name: responseCacheTTL
 value: 10m

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`model`	N	The Ollama LLM to use. Defaults to `llama3.2:latest`.	`phi4:latest`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`

OpenAI Compatibility

Ollama is compatible with OpenAI’s API. You can use the OpenAI component with Ollama models with the following changes:

OpenAI

Mon, 01 Jan 0001 00:00:00 +0000

Component format

A Dapr conversation.yaml component file has the following structure:

apiVersion: dapr.io/v1alpha1
kind: Component
metadata:
 name: openai
spec:
 type: conversation.openai
 metadata:
 - name: key
 value: mykey
 - name: model
 value: gpt-4-turbo
 - name: endpoint
 value: 'https://api.openai.com/v1'
 - name: responseCacheTTL
 value: 10m
 # - name: apiType # Optional
 # value: 'azure'
 # - name: apiVersion # Optional
 # value: '2025-01-01-preview'

Warning

The above example uses secrets as plain strings. It is recommended to use a secret store for the secrets, as described here.

Spec metadata fields

Field	Required	Details	Example
`key`	Y	API key for OpenAI.	`mykey`
`model`	N	The OpenAI LLM to use. Defaults to `gpt-4-turbo`.	`gpt-4-turbo`
`endpoint`	N	Custom API endpoint URL for OpenAI API-compatible services. If not specified, the default OpenAI API endpoint is used. Required when `apiType` is set to `azure`.	`https://api.openai.com/v1`, `https://example.openai.azure.com/`
`responseCacheTTL`	N	Time-to-live for the in-memory response cache. When set, identical requests are served from cache until they expire.	`10m`
`apiType`	N	Specifies the API provider type. Required when using a provider that does not follow the default OpenAI API endpoint conventions.	`azure`
`apiVersion`	N	The API version to use. Required when the `apiType` is set to `azure`.	`2025-04-01-preview`

Azure OpenAI Configuration

To configure the OpenAI component to connect to Azure OpenAI, you need to set the following metadata fields which are required for Azure’s API format.

Conversation component specs on Dapr Docs

Anthropic

Component format

Warning

Spec metadata fields

Related links

AWS Bedrock

Component format

Warning

Spec metadata fields

Authenticating AWS

DeepSeek

Component format

Warning

Spec metadata fields

Related links

Local Testing

Component format

Information

Related links

GoogleAI

Component format

Warning

Spec metadata fields

Related links

Huggingface

Component format

Warning

Spec metadata fields

Related links

Mistral

Component format

Warning

Spec metadata fields

Related links

Ollama

Component format

Warning

Spec metadata fields

OpenAI Compatibility

OpenAI

Component format

Warning

Spec metadata fields

Azure OpenAI Configuration