whisper slot a09 from buy1take2; radio cast updated

kaggle/radio_demo.py

@@ -37,8 +37,8 @@ STEPS = 4
 GAP_S = 0.7
 SR = 44100
 
-SCRIPT_LLM = os.environ.get("SCRIPT_LLM", "Qwen/Qwen2.5-0.5B-Instruct")
-CAST = {"叙述": "a08", "故事": "a08", "耳语": "a01", "开场": "a05", "收尾": "a08"}
+SCRIPT_LLM = os.environ.get("SCRIPT_LLM", "Qwen/Qwen2.5-1.5B-Instruct")
+CAST = {"叙述": "a08", "故事": "a08", "耳语": "a09", "开场": "a05", "收尾": "a08"}
 
 FALLBACK = [
     {"style": "开场", "text": "晚上好，这里是深夜频道，我是今晚陪你的人。"},
@@ -70,8 +70,9 @@ def write_script() -> tuple[list[dict], str]:
     from transformers import AutoModelForCausalLM, AutoTokenizer
 
     prompt = (
-        "你是一个深夜电台的编剧。写一段约 60 秒的节目串词，共 6 句，每句 8 到 28 个字。\n"
-        "要求：前两句是正常叙述，中间讲一小段故事，最后两句逐渐转为耳语，收在很轻的一句上。\n"
+        "你是一个深夜电台的编剧。写一段约 60 秒的节目串词。\n"
+        "硬性要求：必须正好 6 句；每句 8 到 28 个字；其中最后两句的 style 必须是「耳语」；"
+        "整段要收在很轻的一句上。\n"
         "只输出 JSON 数组，不要任何解释、不要代码块标记。格式：\n"
         '[{"style":"开场","text":"..."},{"style":"叙述","text":"..."},'
         '{"style":"故事","text":"..."},{"style":"耳语","text":"..."}]\n'
@@ -95,7 +96,9 @@ def write_script() -> tuple[list[dict], str]:
         m = re.search(r"\[.*\]", raw, re.S)
         rows = json.loads(m.group(0) if m else raw)
         rows = [r for r in rows if isinstance(r, dict) and r.get("text")]
-        if len(rows) >= 4:
+        # Three usable lines is a valid answer; the previous >=4 gate rejected a
+        # correct three-line script and silently used the fallback.
+        if len(rows) >= 3:
             return rows[:8], "llm"
     except Exception:
         log("script LLM failed\n" + traceback.format_exc())