The Mistral AI chat completion API lets create conversational applications.
Tip
You can use the Mistral AI chat completion API with the base inference operations (InvokeModel or InvokeModelWithResponseStream). However, we recommend that you use the Converse API to implement messages in your application. The Converse API provides a unified set of parameters that work across all models that support messages. For more information, see Carry out a conversation with the Converse API operations.
Mistral AI models are available under the Apache 2.0 license
Supported models
You can use following Mistral AI models.
Mistral Large
You need the model ID for the model that you want to use. To get the model ID, see Supported foundation models in Amazon Bedrock.
Request and Response
The Mistral AI models have the following inference parameters.
{
"messages": [
{
"role": "system"|"user"|"assistant",
"content": str
},
{
"role": "assistant",
"content": "",
"tool_calls": [
{
"id": str,
"function": {
"name": str,
"arguments": str
}
}
]
},
{
"role": "tool",
"tool_call_id": str,
"content": str
}
],
"tools": [
{
"type": "function",
"function": {
"name": str,
"description": str,
"parameters": dict
}
}
],
"tool_choice": "auto"|"any"|"none",
"max_tokens": int,
"top_p": float,
"temperature": float
}The following are required parameters.
-
messages – (Required) The messages that you want to pass to the model.
-
role – The role for the message. Valid values are:
system – Sets the behavior and context for the model in the conversation.
user – The user message to send to the model.
assistant – The response from the model.
-
content – The content for the message.
[ { "role": "user", "content": "What is the most popular song on WZPZ?" } ]To pass a tool result, use JSON with the following fields.
-
role – The role for the message. The value must be
tool. -
tool_call_id – The ID of the tool request. You get the ID from the
tool_callsfields in the response from the previous request. -
content – The result from the tool.
The following example is the result from a tool that gets the most popular song on a radio station.
{ "role": "tool", "tool_call_id": "v6RMMiRlT7ygYkT4uULjtg", "content": "{\"song\": \"Elemental Hotel\", \"artist\": \"8 Storey Hike\"}" } -
The following are optional parameters.
-
tools – Definitions of tools that the model may use.
If you include
toolsin your request, the model may return atool_callsfield in the message that represent the model's use of those tools. You can then run those tools using the tool input generated by the model and then optionally return results back to the model usingtool_resultcontent blocks.The following example is for a tool that gets the most popular songs on a radio station.
[ { "type": "function", "function": { "name": "top_song", "description": "Get the most popular song played on a radio station.", "parameters": { "type": "object", "properties": { "sign": { "type": "string", "description": "The call sign for the radio station for which you want the most popular song. Example calls signs are WZPZ and WKRP." } }, "required": [ "sign" ] } } } ] -
tool_choice – Specifies how functions are called. If set to
nonethe model won't call a function and will generate a message instead. If set toautothe model can choose to either generate a message or call a function. If set toanythe model is forced to call a function.
-
max_tokens – Specify the maximum number of tokens to use in the generated response. The model truncates the response once the generated text exceeds
max_tokens.Default Minimum Maximum Mistral Large – 8,192
1
Mistral Large – 8,192
-
temperature – Controls the randomness of predictions made by the model. For more information, see Influence response generation with inference parameters.
Default Minimum Maximum Mistral Large – 0.7
0
1
-
top_p – Controls the diversity of text that the model generates by setting the percentage of most-likely candidates that the model considers for the next token. For more information, see Influence response generation with inference parameters.
Default Minimum Maximum Mistral Large – 1
0
1
