fix(openai): implement error probing and gpt-5-nano support

- Added error probing to capture detailed 400 Bad Request error bodies.
- Explicitly added gpt-5-nano to supports_model.
- Used parse_openai_stream_chunk helper for robust stream parsing.
This commit is contained in:
2026-03-05 19:17:22 +00:00
parent 6a324c08c7
commit d0d64e2064

View File

@@ -1,6 +1,7 @@
use anyhow::Result;
use async_trait::async_trait;
use futures::stream::BoxStream;
use futures::StreamExt;
use super::helpers;
use super::{ProviderResponse, ProviderStreamChunk};
@@ -44,7 +45,7 @@ impl super::Provider for OpenAIProvider {
}
fn supports_model(&self, model: &str) -> bool {
model.starts_with("gpt-") || model.starts_with("o1-") || model.starts_with("o3-") || model.starts_with("o4-")
model.starts_with("gpt-") || model.starts_with("o1-") || model.starts_with("o3-") || model.starts_with("o4-") || model == "gpt-5-nano"
}
fn supports_multimodal(&self) -> bool {
@@ -65,9 +66,11 @@ impl super::Provider for OpenAIProvider {
.map_err(|e| AppError::ProviderError(e.to_string()))?;
if !response.status().is_success() {
let status = response.status();
let error_text = response.text().await.unwrap_or_default();
// Read error body to diagnose. If the model requires the Responses
// API (v1/responses), retry against that endpoint.
let error_text = response.text().await.unwrap_or_default();
if error_text.to_lowercase().contains("v1/responses") || error_text.to_lowercase().contains("only supported in v1/responses") {
// Build a simple `input` string by concatenating message parts.
let messages_json = helpers::messages_to_openai_json(&request.messages).await?;
@@ -106,16 +109,13 @@ impl super::Provider for OpenAIProvider {
}
// Responses API: try to extract text from `output` or `candidates`
// output -> [{"content": [{"type":..., "text": "..."}, ...]}]
let mut content_text = String::new();
if let Some(output) = resp_json.get("output").and_then(|o| o.as_array()) {
if let Some(first) = output.get(0) {
if let Some(contents) = first.get("content").and_then(|c| c.as_array()) {
for item in contents {
if let Some(text) = item.get("text").and_then(|t| t.as_str()) {
if !content_text.is_empty() {
content_text.push_str("\n");
}
if !content_text.is_empty() { content_text.push_str("\n"); }
content_text.push_str(text);
} else if let Some(parts) = item.get("parts").and_then(|p| p.as_array()) {
for p in parts {
@@ -130,7 +130,6 @@ impl super::Provider for OpenAIProvider {
}
}
// Fallback: check `candidates` -> candidate.content.parts.text
if content_text.is_empty() {
if let Some(cands) = resp_json.get("candidates").and_then(|c| c.as_array()) {
if let Some(c0) = cands.get(0) {
@@ -148,7 +147,6 @@ impl super::Provider for OpenAIProvider {
}
}
// Extract simple usage if present
let prompt_tokens = resp_json.get("usage").and_then(|u| u.get("prompt_tokens")).and_then(|v| v.as_u64()).unwrap_or(0) as u32;
let completion_tokens = resp_json.get("usage").and_then(|u| u.get("completion_tokens")).and_then(|v| v.as_u64()).unwrap_or(0) as u32;
let total_tokens = resp_json.get("usage").and_then(|u| u.get("total_tokens")).and_then(|v| v.as_u64()).unwrap_or(0) as u32;
@@ -166,7 +164,8 @@ impl super::Provider for OpenAIProvider {
});
}
return Err(AppError::ProviderError(format!("OpenAI API error: {}", error_text)));
tracing::error!("OpenAI API error ({}): {}", status, error_text);
return Err(AppError::ProviderError(format!("OpenAI API error ({}): {}", status, error_text)));
}
let resp_json: serde_json::Value = response
@@ -297,46 +296,70 @@ impl super::Provider for OpenAIProvider {
request: UnifiedRequest,
) -> Result<BoxStream<'static, Result<ProviderStreamChunk, AppError>>, AppError> {
let messages_json = helpers::messages_to_openai_json(&request.messages).await?;
let body = helpers::build_openai_body(&request, messages_json, true);
let mut body = helpers::build_openai_body(&request, messages_json, true);
// Try to create an EventSource for streaming; if creation fails or
// the stream errors, fall back to a single synchronous request and
// emit its result as a single chunk.
let es_result = reqwest_eventsource::EventSource::new(
// Standard OpenAI cleanup
if let Some(obj) = body.as_object_mut() {
obj.remove("stream_options");
}
let url = format!("{}/chat/completions", self.config.base_url);
let api_key = self.api_key.clone();
let probe_client = self.client.clone();
let probe_body = body.clone();
let model = request.model.clone();
let es = reqwest_eventsource::EventSource::new(
self.client
.post(format!("{}/chat/completions", self.config.base_url))
.post(&url)
.header("Authorization", format!("Bearer {}", self.api_key))
.json(&body),
);
)
.map_err(|e| AppError::ProviderError(format!("Failed to create EventSource: {}", e)))?;
if es_result.is_err() {
// Fallback to non-streaming request which itself may retry to
// Responses API if necessary (handled in chat_completion).
let resp = self.chat_completion(request.clone()).await?;
let single_stream = async_stream::try_stream! {
let chunk = ProviderStreamChunk {
content: resp.content,
reasoning_content: resp.reasoning_content,
finish_reason: Some("stop".to_string()),
tool_calls: None,
model: resp.model.clone(),
usage: Some(super::StreamUsage {
prompt_tokens: resp.prompt_tokens,
completion_tokens: resp.completion_tokens,
total_tokens: resp.total_tokens,
cache_read_tokens: resp.cache_read_tokens,
cache_write_tokens: resp.cache_write_tokens,
}),
};
yield chunk;
};
return Ok(Box::pin(single_stream));
let stream = async_stream::try_stream! {
let mut es = es;
while let Some(event) = es.next().await {
match event {
Ok(reqwest_eventsource::Event::Message(msg)) => {
if msg.data == "[DONE]" {
break;
}
let es = es_result.map_err(|e| AppError::ProviderError(format!("Failed to create EventSource: {}", e)))?;
let chunk: serde_json::Value = serde_json::from_str(&msg.data)
.map_err(|e| AppError::ProviderError(format!("Failed to parse stream chunk: {}", e)))?;
Ok(helpers::create_openai_stream(es, request.model, None))
if let Some(p_chunk) = helpers::parse_openai_stream_chunk(&chunk, &model, None) {
yield p_chunk?;
}
}
Ok(_) => continue,
Err(e) => {
// Attempt to probe for the actual error body
let probe_resp = probe_client
.post(&url)
.header("Authorization", format!("Bearer {}", api_key))
.json(&probe_body)
.send()
.await;
match probe_resp {
Ok(r) if !r.status().is_success() => {
let status = r.status();
let error_body = r.text().await.unwrap_or_default();
tracing::error!("OpenAI Stream Error Probe ({}): {}", status, error_body);
tracing::debug!("Offending OpenAI Request Body: {}", serde_json::to_string(&probe_body).unwrap_or_default());
Err(AppError::ProviderError(format!("OpenAI API error ({}): {}", status, error_body)))?;
}
_ => {
Err(AppError::ProviderError(format!("Stream error: {}", e)))?;
}
}
}
}
}
};
Ok(Box::pin(stream))
}
}