Update to latest Mistral AI API (v1.0.0)

- Replace closed Model enum with flexible string-based Model type
  with constructor methods for all current models (Mistral Large 3,
  Small 4, Magistral, Codestral, Devstral, Pixtral, Voxtral, etc.)
- Add new API endpoints: FIM completions, Files, Fine-tuning, Batch
  jobs, OCR, Audio transcription, Moderations/Classifications, and
  Agent completions (sync + async for all)
- Add new chat fields: frequency_penalty, presence_penalty, stop,
  n, parallel_tool_calls, reasoning_effort, min_tokens, json_schema
  response format
- Add embedding fields: output_dimension, output_dtype
- Tool parameters now accept raw JSON Schema (serde_json::Value)
  instead of limited enum types
- Add tool call IDs and Required tool choice variant
- Add DELETE HTTP method support and multipart file upload
- Bump thiserror to v2, add reqwest multipart feature
- Remove strum dependency (no longer needed)
- Update all tests and examples for new API

examples/embeddings_async.rs

@@ -1,11 +1,11 @@
-use mistralai_client::v1::{client::Client, constants::EmbedModel};
+use mistralai_client::v1::{client::Client, constants::Model};
 
 #[tokio::main]
 async fn main() {
     // This example suppose you have set the `MISTRAL_API_KEY` environment variable.
     let client: Client = Client::new(None, None, None, None).unwrap();
 
-    let model = EmbedModel::MistralEmbed;
+    let model = Model::mistral_embed();
     let input = vec!["Embed this sentence.", "As well as this one."]
         .iter()
         .map(|s| s.to_string())
@@ -17,5 +17,4 @@ async fn main() {
         .await
         .unwrap();
     println!("First Embedding: {:?}", response.data[0]);
-    // => "First Embedding: {...}"
 }