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server/_core/llm.ts

@@ -57,6 +57,7 @@ export type ToolChoice =
 
 export type InvokeParams = {
   messages: Message[];
+  model?: string;
   tools?: Tool[];
   toolChoice?: ToolChoice;
   tool_choice?: ToolChoice;
@@ -286,7 +287,7 @@ export async function invokeLLM(params: InvokeParams): Promise<InvokeResult> {
   } = params;
 
   const payload: Record<string, unknown> = {
-    model: process.env.HF_TOKEN && !process.env.BUILT_IN_FORGE_API_KEY ? "Qwen/Qwen2.5-72B-Instruct" : "gemini-2.5-flash",
+    model: params.model || (process.env.HF_TOKEN && !process.env.BUILT_IN_FORGE_API_KEY ? "huihui-ai/Qwen2.5-72B-Instruct-abliterated" : "gemini-2.5-flash"),
     messages: messages.map(normalizeMessage),
   };
 

server/routers/chat.ts

@@ -20,6 +20,7 @@ export const chatRouter = router({
 
         if (input.mode === "qwen" || input.mode === "auto") {
           response = await invokeLLM({
+            model: "huihui-ai/Qwen2.5-72B-Instruct-abliterated",
             messages: [
               {
                 role: "system",
@@ -35,6 +36,7 @@ Focus on: security, efficiency, and reliability.`,
           });
         } else if (input.mode === "deepseek") {
           response = await invokeLLM({
+            model: "huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated",
             messages: [
               {
                 role: "system",
@@ -139,6 +141,7 @@ ${input.context ? `Context: ${input.context}` : ""}`,
 
         // 2. Static Analysis & Multi-Criteria Scoring via LLM
         const response = await invokeLLM({
+          model: "huihui-ai/DeepSeek-R1-Distill-Qwen-32B-abliterated",
           messages: [
             {
               role: "system",