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fix(llm): add GLM compatibility for reasoning_content field #55

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fix(llm): add GLM compatibility for reasoning_content field #55

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23 changes: 19 additions & 4 deletions packages/core/src/llm/provider.ts
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Original file line number Diff line number Diff line change
Expand Up @@ -345,10 +345,19 @@ async function chatCompletionOpenAIChat(
try {
for await (const chunk of stream) {
const delta = chunk.choices[0]?.delta?.content;
if (delta) {
const reasoningDelta = (chunk.choices[0]?.delta as { reasoning_content?: string } | undefined)?.reasoning_content;

// GLM models (glm-4, glm-5) return content in reasoning_content field
if (reasoningDelta) {
// For GLM models, treat reasoning_content as main content
chunks.push(reasoningDelta);
monitor.onChunk(reasoningDelta);
} else if (delta) {
// Standard OpenAI format
chunks.push(delta);
monitor.onChunk(delta);
}

if (chunk.usage) {
inputTokens = chunk.usage.prompt_tokens ?? 0;
outputTokens = chunk.usage.completion_tokens ?? 0;
Expand Down Expand Up @@ -393,11 +402,17 @@ async function chatCompletionOpenAIChatSync(
stream: false,
});

const content = response.choices[0]?.message?.content ?? "";
if (!content) throw new Error("LLM returned empty response");
// GLM models (glm-4, glm-5) return content in reasoning_content field
const choice = response.choices[0]?.message;
const content = choice?.content ?? "";
const reasoningContent = (choice as { reasoning_content?: string } | undefined)?.reasoning_content ?? "";

// For GLM models, use reasoning_content when content is empty
const finalContent = content || reasoningContent;
if (!finalContent) throw new Error("LLM returned empty response");

return {
content,
content: finalContent,
usage: {
promptTokens: response.usage?.prompt_tokens ?? 0,
completionTokens: response.usage?.completion_tokens ?? 0,
Expand Down