Video tutorial fixes

.github/workflows/run_bot_on_quarterly_cup.yaml

@@ -1,4 +1,4 @@
-name: Regularly forecast new questions
+name: Forecast on Quarterly Cup
 
 on:
   workflow_dispatch:

.github/workflows/run_bot_on_tournament.yaml

@@ -1,4 +1,4 @@
-name: Regularly forecast new questions
+name: Forecast on new AI tournament questions
 
 on:
   workflow_dispatch:

main.py

@@ -61,7 +61,7 @@ class Q1TemplateBot(ForecastBot):
     """
 
     _max_concurrent_questions = (
-        2  # Set this to whatever works for your search-provider/ai-model rate limits
+        10  # Set this to whatever works for your search-provider/ai-model rate limits
     )
     _concurrency_limiter = asyncio.Semaphore(_max_concurrent_questions)
 
@@ -74,26 +74,34 @@ async def run_research(self, question: MetaculusQuestion) -> str:
                 research = await self._call_exa_smart_searcher(question.question_text)
             elif os.getenv("PERPLEXITY_API_KEY"):
                 research = await self._call_perplexity(question.question_text)
+            elif os.getenv("OPENROUTER_API_KEY"):
+                research = await self._call_perplexity(question.question_text, use_open_router=True)
             else:
                 research = ""
             logger.info(f"Found Research for {question.page_url}:\n{research}")
             return research
 
-    async def _call_perplexity(self, question: str) -> str:
-        system_prompt = clean_indents(
-            """
+    async def _call_perplexity(self, question: str, use_open_router: bool = False) -> str:
+        prompt = clean_indents(
+            f"""
             You are an assistant to a superforecaster.
             The superforecaster will give you a question they intend to forecast on.
             To be a great assistant, you generate a concise but detailed rundown of the most relevant news, including if the question would resolve Yes or No based on current information.
             You do not produce forecasts yourself.
+
+            Question:
+            {question}
             """
         )
+        if use_open_router:
+            model_name = "openrouter/perplexity/sonar-reasoning"
+        else:
+            model_name = "perplexity/sonar-pro" # perplexity/sonar-reasoning and perplexity/sonar are cheaper, but do only 1 search.
         model = GeneralLlm(
-            model="perplexity/sonar-pro",  # perplexity/sonar is cheaper, but does only 1 search.
+            model=model_name,
             temperature=0.1,
-            system_prompt=system_prompt,
         )
-        response = await model.invoke(question)
+        response = await model.invoke(prompt)
         return response
 
     async def _call_exa_smart_searcher(self, question: str) -> str: