fix: use fast model for story selection, gemma4 for summaries only

gemma4:26b under format:json ignores the bare-array instruction and returns a
reasoning object ({"thought": ...}), which broke Phase-1 selection (Unterminated
string -> silent fallback to first-5). Selection now uses ollama_select_model
(default qwen2.5:1.5b); summaries stay on gemma4:26b. Also tolerate dict-shaped
selection responses defensively.

Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com>

config.example.json

@@ -4,6 +4,7 @@
     "freshrss_api_key": "your-api-password",
     "ollama_url": "http://your-ollama-ip:11434",
     "ollama_model": "gemma4:26b",
+    "ollama_select_model": "qwen2.5:1.5b",
     "yourls_url": "http://your-yourls-ip/yourls-api.php",
     "yourls_user": "yourls-username",
     "yourls_pass": "yourls-password",

pos_briefing.py

@@ -24,6 +24,10 @@ FRESHRSS_USER = config["freshrss_user"]
 FRESHRSS_TOKEN = config["freshrss_api_key"]
 OLLAMA_URL    = config["ollama_url"]
 OLLAMA_MODEL  = config["ollama_model"]
+# Phase-1 story selection wants a fast model that emits a bare JSON array.
+# gemma4 (the summary model) ignores the format and returns reasoning objects,
+# so selection uses a small, literal model by default.
+OLLAMA_SELECT_MODEL = config.get("ollama_select_model", "qwen2.5:1.5b")
 YOURLS_URL    = config["yourls_url"]
 YOURLS_USER   = config["yourls_user"]
 YOURLS_PASS   = config["yourls_pass"]
@@ -143,12 +147,16 @@ def summarize_news(items, count=5, length="30-50 words"):
     try:
         resp = requests.post(
             f"{OLLAMA_URL}/api/generate",
-            json={"model": OLLAMA_MODEL, "prompt": prompt_select, "stream": False,
+            json={"model": OLLAMA_SELECT_MODEL, "prompt": prompt_select, "stream": False,
                   "options": {"num_ctx": 16384, "temperature": 0.1}, "format": "json"},
             timeout=300
         ).json()
         data = json.loads(resp.get("response", "[]"))
-        selected_indices = data if isinstance(data, list) else list(data.values())[0]
+        if isinstance(data, list):
+            selected_indices = data
+        elif isinstance(data, dict):
+            # Tolerate {"stories": [...]} or similar; pick the first list value.
+            selected_indices = next((v for v in data.values() if isinstance(v, list)), [])
     except Exception as e:
         print(f"[!] Selection error: {e}")
         selected_indices = list(range(min(count, len(items))))