refactor: extract stream parsing helper and enable deepseek error probing
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This commit is contained in:
2026-03-05 18:16:56 +00:00
parent c2bad90a8f
commit e3c1b9fa20
2 changed files with 82 additions and 98 deletions

View File

@@ -237,6 +237,79 @@ pub fn parse_openai_response(resp_json: &Value, model: String) -> Result<Provide
})
}
/// Parse a single OpenAI-compatible stream chunk into a ProviderStreamChunk.
/// Returns None if the chunk should be skipped (e.g. promptFeedback).
pub fn parse_openai_stream_chunk(
chunk: &Value,
model: &str,
reasoning_field: Option<&'static str>,
) -> Option<Result<ProviderStreamChunk, AppError>> {
// Parse usage from the final chunk (sent when stream_options.include_usage is true).
// This chunk may have an empty `choices` array.
let stream_usage = chunk.get("usage").and_then(|u| {
if u.is_null() {
return None;
}
let prompt_tokens = u["prompt_tokens"].as_u64().unwrap_or(0) as u32;
let completion_tokens = u["completion_tokens"].as_u64().unwrap_or(0) as u32;
let total_tokens = u["total_tokens"].as_u64().unwrap_or(0) as u32;
let cache_read_tokens = u["prompt_tokens_details"]["cached_tokens"]
.as_u64()
.or_else(|| u["prompt_cache_hit_tokens"].as_u64())
.unwrap_or(0) as u32;
let cache_write_tokens = u["prompt_cache_miss_tokens"]
.as_u64()
.unwrap_or(0) as u32;
Some(StreamUsage {
prompt_tokens,
completion_tokens,
total_tokens,
cache_read_tokens,
cache_write_tokens,
})
});
if let Some(choice) = chunk["choices"].get(0) {
let delta = &choice["delta"];
let content = delta["content"].as_str().unwrap_or_default().to_string();
let reasoning_content = delta["reasoning_content"]
.as_str()
.or_else(|| reasoning_field.and_then(|f| delta[f].as_str()))
.map(|s| s.to_string());
let finish_reason = choice["finish_reason"].as_str().map(|s| s.to_string());
// Parse tool_calls deltas from the stream chunk
let tool_calls: Option<Vec<ToolCallDelta>> = delta
.get("tool_calls")
.and_then(|tc| serde_json::from_value(tc.clone()).ok());
Some(Ok(ProviderStreamChunk {
content,
reasoning_content,
finish_reason,
tool_calls,
model: model.to_string(),
usage: stream_usage,
}))
} else if stream_usage.is_some() {
// Final usage-only chunk (empty choices array) — yield it so
// AggregatingStream can capture the real token counts.
Some(Ok(ProviderStreamChunk {
content: String::new(),
reasoning_content: None,
finish_reason: None,
tool_calls: None,
model: model.to_string(),
usage: stream_usage,
}))
} else {
None
}
}
/// Create an SSE stream that parses OpenAI-compatible streaming chunks.
///
/// The optional `reasoning_field` allows overriding the field name for
@@ -264,67 +337,8 @@ pub fn create_openai_stream(
let chunk: Value = serde_json::from_str(&msg.data)
.map_err(|e| AppError::ProviderError(format!("Failed to parse stream chunk: {}", e)))?;
// Parse usage from the final chunk (sent when stream_options.include_usage is true).
// This chunk may have an empty `choices` array.
let stream_usage = chunk.get("usage").and_then(|u| {
if u.is_null() {
return None;
}
let prompt_tokens = u["prompt_tokens"].as_u64().unwrap_or(0) as u32;
let completion_tokens = u["completion_tokens"].as_u64().unwrap_or(0) as u32;
let total_tokens = u["total_tokens"].as_u64().unwrap_or(0) as u32;
let cache_read_tokens = u["prompt_tokens_details"]["cached_tokens"]
.as_u64()
.or_else(|| u["prompt_cache_hit_tokens"].as_u64())
.unwrap_or(0) as u32;
let cache_write_tokens = u["prompt_cache_miss_tokens"]
.as_u64()
.unwrap_or(0) as u32;
Some(StreamUsage {
prompt_tokens,
completion_tokens,
total_tokens,
cache_read_tokens,
cache_write_tokens,
})
});
if let Some(choice) = chunk["choices"].get(0) {
let delta = &choice["delta"];
let content = delta["content"].as_str().unwrap_or_default().to_string();
let reasoning_content = delta["reasoning_content"]
.as_str()
.or_else(|| reasoning_field.and_then(|f| delta[f].as_str()))
.map(|s| s.to_string());
let finish_reason = choice["finish_reason"].as_str().map(|s| s.to_string());
// Parse tool_calls deltas from the stream chunk
let tool_calls: Option<Vec<ToolCallDelta>> = delta
.get("tool_calls")
.and_then(|tc| serde_json::from_value(tc.clone()).ok());
yield ProviderStreamChunk {
content,
reasoning_content,
finish_reason,
tool_calls,
model: model.clone(),
usage: stream_usage,
};
} else if stream_usage.is_some() {
// Final usage-only chunk (empty choices array) — yield it so
// AggregatingStream can capture the real token counts.
yield ProviderStreamChunk {
content: String::new(),
reasoning_content: None,
finish_reason: None,
tool_calls: None,
model: model.clone(),
usage: stream_usage,
};
if let Some(p_chunk) = parse_openai_stream_chunk(&chunk, &model, reasoning_field) {
yield p_chunk?;
}
}
Ok(_) => continue,