gpt 5-3-Codex model support in databricks (#7516)

crates/goose/src/providers/databricks.rs

@@ -1,18 +1,28 @@
 use anyhow::Result;
+use async_stream::try_stream;
 use async_trait::async_trait;
 use futures::future::BoxFuture;
+use futures::{StreamExt, TryStreamExt};
 use serde::{Deserialize, Serialize};
 use serde_json::Value;
+use std::io;
 use std::time::Duration;
+use tokio::pin;
+use tokio_util::codec::{FramedRead, LinesCodec};
+use tokio_util::io::StreamReader;
 
 use super::api_client::{ApiClient, AuthMethod, AuthProvider};
 use super::base::{ConfigKey, MessageStream, Provider, ProviderDef, ProviderMetadata};
 use super::embedding::EmbeddingCapable;
 use super::errors::ProviderError;
 use super::formats::databricks::create_request;
+use super::formats::openai_responses::{
+    create_responses_request, responses_api_to_streaming_message,
+};
 use super::oauth;
 use super::openai_compatible::{
-    handle_response_openai_compat, map_http_error_to_provider_error, stream_openai_compat,
+    handle_response_openai_compat, handle_status_openai_compat, map_http_error_to_provider_error,
+    stream_openai_compat,
 };
 use super::retry::ProviderRetry;
 use super::utils::{ImageFormat, RequestLog};
@@ -208,9 +218,16 @@ impl DatabricksProvider {
         })
     }
 
+    fn is_responses_model(model_name: &str) -> bool {
+        let normalized = model_name.to_ascii_lowercase();
+        normalized.contains("codex")
+    }
+
     fn get_endpoint_path(&self, model_name: &str, is_embedding: bool) -> String {
         if is_embedding {
             "serving-endpoints/text-embedding-3-small/invocations".to_string()
+        } else if Self::is_responses_model(model_name) {
+            "serving-endpoints/responses".to_string()
         } else {
             format!("serving-endpoints/{}/invocations", model_name)
         }
@@ -282,42 +299,79 @@ impl Provider for DatabricksProvider {
         messages: &[Message],
         tools: &[Tool],
     ) -> Result<MessageStream, ProviderError> {
-        let mut payload =
-            create_request(model_config, system, messages, tools, &self.image_format)?;
-        payload
-            .as_object_mut()
-            .expect("payload should have model key")
-            .remove("model");
-
-        payload
-            .as_object_mut()
-            .unwrap()
-            .insert("stream".to_string(), Value::Bool(true));
-
         let path = self.get_endpoint_path(&model_config.model_name, false);
-        let mut log = RequestLog::start(model_config, &payload)?;
-        let response = self
-            .with_retry(|| async {
-                let resp = self
-                    .api_client
-                    .response_post(Some(session_id), &path, &payload)
-                    .await?;
-                if !resp.status().is_success() {
-                    let status = resp.status();
-                    let error_text = resp.text().await.unwrap_or_default();
 
-                    // Parse as JSON if possible to pass to map_http_error_to_provider_error
-                    let json_payload = serde_json::from_str::<Value>(&error_text).ok();
-                    return Err(map_http_error_to_provider_error(status, json_payload));
+        if Self::is_responses_model(&model_config.model_name) {
+            let mut payload = create_responses_request(model_config, system, messages, tools)?;
+            payload["stream"] = Value::Bool(true);
+
+            let mut log = RequestLog::start(model_config, &payload)?;
+
+            let response = self
+                .with_retry(|| async {
+                    let payload_clone = payload.clone();
+                    let resp = self
+                        .api_client
+                        .response_post(Some(session_id), &path, &payload_clone)
+                        .await?;
+                    handle_status_openai_compat(resp).await
+                })
+                .await
+                .inspect_err(|e| {
+                    let _ = log.error(e);
+                })?;
+
+            let stream = response.bytes_stream().map_err(io::Error::other);
+
+            Ok(Box::pin(try_stream! {
+                let stream_reader = StreamReader::new(stream);
+                let framed = FramedRead::new(stream_reader, LinesCodec::new()).map_err(anyhow::Error::from);
+
+                let message_stream = responses_api_to_streaming_message(framed);
+                pin!(message_stream);
+                while let Some(message) = message_stream.next().await {
+                    let (message, usage) = message.map_err(|e| ProviderError::RequestFailed(format!("Stream decode error: {}", e)))?;
+                    log.write(&message, usage.as_ref().map(|f| f.usage).as_ref())?;
+                    yield (message, usage);
                 }
-                Ok(resp)
-            })
-            .await
-            .inspect_err(|e| {
-                let _ = log.error(e);
-            })?;
+            }))
+        } else {
+            let mut payload =
+                create_request(model_config, system, messages, tools, &self.image_format)?;
+            payload
+                .as_object_mut()
+                .expect("payload should have model key")
+                .remove("model");
 
-        stream_openai_compat(response, log)
+            payload
+                .as_object_mut()
+                .unwrap()
+                .insert("stream".to_string(), Value::Bool(true));
+
+            let mut log = RequestLog::start(model_config, &payload)?;
+            let response = self
+                .with_retry(|| async {
+                    let resp = self
+                        .api_client
+                        .response_post(Some(session_id), &path, &payload)
+                        .await?;
+                    if !resp.status().is_success() {
+                        let status = resp.status();
+                        let error_text = resp.text().await.unwrap_or_default();
+
+                        // Parse as JSON if possible to pass to map_http_error_to_provider_error
+                        let json_payload = serde_json::from_str::<Value>(&error_text).ok();
+                        return Err(map_http_error_to_provider_error(status, json_payload));
+                    }
+                    Ok(resp)
+                })
+                .await
+                .inspect_err(|e| {
+                    let _ = log.error(e);
+                })?;
+
+            stream_openai_compat(response, log)
+        }
     }
 
     fn supports_embeddings(&self) -> bool {