refactor: extract stream parsing helper and enable deepseek error probing

2026-03-05 18:16:56 +00:00
parent c2bad90a8f
commit e3c1b9fa20
2 changed files with 82 additions and 98 deletions
--- a/src/providers/deepseek.rs
+++ b/src/providers/deepseek.rs
@@ -58,22 +58,7 @@ impl super::Provider for DeepSeekProvider {

    async fn chat_completion(&self, request: UnifiedRequest) -> Result<ProviderResponse, AppError> {
        let messages_json = helpers::messages_to_openai_json(&request.messages).await?;
-        let mut body = helpers::build_openai_body(&request, messages_json, false);
-
-        // Sanitize for deepseek-reasoner
-        if request.model == "deepseek-reasoner" {
-            if let Some(obj) = body.as_object_mut() {
-                obj.remove("tools");
-                obj.remove("tool_choice");
-                obj.remove("temperature");
-                obj.remove("top_p");
-                obj.remove("presence_penalty");
-                obj.remove("frequency_penalty");
-                obj.remove("logit_bias");
-                obj.remove("logprobs");
-                obj.remove("top_logprobs");
-            }
-        }
+        let body = helpers::build_openai_body(&request, messages_json, false);

        let response = self
            .client
@@ -85,8 +70,10 @@ impl super::Provider for DeepSeekProvider {
            .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();
-            return Err(AppError::ProviderError(format!("DeepSeek API error: {}", error_text)));
+            tracing::error!("DeepSeek API error ({}): {}", status, error_text);
+            return Err(AppError::ProviderError(format!("DeepSeek API error ({}): {}", status, error_text)));
        }

        let resp_json: serde_json::Value = response
@@ -131,26 +118,9 @@ impl super::Provider for DeepSeekProvider {
        let messages_json = helpers::messages_to_openai_json_text_only(&request.messages).await?;
        let mut body = helpers::build_openai_body(&request, messages_json, true);

-        // Sanitize for deepseek-reasoner or general deepseek-chat
-        if request.model == "deepseek-reasoner" {
-            if let Some(obj) = body.as_object_mut() {
-                obj.remove("stream_options");
-                // Also does not support these parameters
-                obj.remove("tools");
-                obj.remove("tool_choice");
-                obj.remove("temperature");
-                obj.remove("top_p");
-                obj.remove("presence_penalty");
-                obj.remove("frequency_penalty");
-                obj.remove("logit_bias");
-                obj.remove("logprobs");
-                obj.remove("top_logprobs");
-            }
-        } else {
-            // For standard deepseek-chat, keep it clean
-            if let Some(obj) = body.as_object_mut() {
-                obj.remove("stream_options");
-            }
+        // Standard OpenAI cleanup
+        if let Some(obj) = body.as_object_mut() {
+            obj.remove("stream_options");
        }

        let url = format!("{}/chat/completions", self.config.base_url);
--- a/src/providers/helpers.rs
+++ b/src/providers/helpers.rs
@@ -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,