feat: configure LLM generation parameters and implement text truncation for summarization inputs

rag/rag.py

@@ -135,6 +135,9 @@ def get_llm():
         model=settings.model_name,
         base_url=settings.openrouter_base_url,
         api_key=settings.openrouter_api_key,
+        temperature=0.3,
+        max_tokens=2000,
+        timeout=120,
     )
 
 

summary_generator/summary.py

@@ -68,8 +68,23 @@ def clean_summary(text: str) -> str:
     return '\n'.join(cleaned)
 
 
+MAX_INPUT_CHARS = 15000
+
+
+def _truncate_text(text: str, max_chars: int = MAX_INPUT_CHARS) -> str:
+    if len(text) <= max_chars:
+        return text
+    first_len = int(max_chars * 0.6)
+    last_len = max_chars - first_len
+    first_part = text[:first_len]
+    last_part = text[-last_len:]
+    logger.info(f"Text truncated from {len(text)} to {max_chars} chars")
+    return f"{first_part}\n\n...[content truncated]...\n\n{last_part}"
+
+
 def summarizer(text: str) -> str:
     logger.info(f"Summarizer started for text of length {len(text)}")
+    text = _truncate_text(text)
     try:
         prompt = summarizer_prompt()
         llm = get_llm()