Added benchmarks for Claude Sonnet 3.5

forecasting_tools/ai_models/claude35sonnet.py

@@ -7,9 +7,12 @@
 
 class Claude35Sonnet(AnthropicTextToTextModel):
     # See Anthropic Limit on the account dashboard for most up-to-date limit
+    # Latest as of Nov 6 2024 is claude-2-5-sonnet-20241022
+    # Latest in general is claude-3-5-sonnet-latest
+    # See models here https://docs.anthropic.com/en/docs/about-claude/models
     MODEL_NAME: Final[str] = "claude-3-5-sonnet-20240620"
-    REQUESTS_PER_PERIOD_LIMIT: Final[int] = 50
+    REQUESTS_PER_PERIOD_LIMIT: Final[int] = 1_750
     REQUEST_PERIOD_IN_SECONDS: Final[int] = 60
     TIMEOUT_TIME: Final[int] = 40
-    TOKENS_PER_PERIOD_LIMIT: Final[int] = 40000
+    TOKENS_PER_PERIOD_LIMIT: Final[int] = 140_000
     TOKEN_PERIOD_IN_SECONDS: Final[int] = 60

forecasting_tools/ai_models/exa_searcher.py

@@ -62,10 +62,10 @@ class SearchInput(BaseModel, Jsonable):
         description="The query to search within each document using semantic similarity"
     )
     include_domains: list[str] = Field(
-        description="List of domains to require in the search results for example: ['youtube.com', 'en.wikipedia.org']. An empty list means no filter."
+        description="List of domains to require in the search results for example: ['youtube.com', 'en.wikipedia.org']. An empty list means no filter. This will constrain search to ONLY results from these domains."
     )
     exclude_domains: list[str] = Field(
-        description="List of domains to exclude from the search results: ['youtube.com', 'en.wikipedia.org']. An empty list means no filter."
+        description="List of domains to exclude from the search results: ['youtube.com', 'en.wikipedia.org']. An empty list means no filter. This will constrain search to exclude results from these domains."
     )
     include_text: str | None = Field(
         description="A 1-5 word phrase that must be exactly present in the text of the search results"

forecasting_tools/forecasting/llms/smart_searcher.py

@@ -94,6 +94,7 @@ async def __come_up_with_search_queries(
             {self.llm.get_schema_format_instructions_for_pydantic_type(SearchInput)}
 
             Make sure to return a list of the search inputs as a list of JSON objects in this schema.
+            Do not give the json in separate chunks. It needs to be in one combined list.
             """
         )
         search_terms = await self.llm.invoke_and_return_verified_type(

front_end/app_pages/benchmark_page.py

@@ -16,15 +16,17 @@ class BenchmarkPage(AppPage):
     URL_PATH: str = "/benchmark"
     BENCHMARK_FILE_SELECTBOX_KEY: str = "benchmark_file_selectbox"
     BENCHMARK_FILES_TO_SHOW: dict[str, str] = {
-        "GPT-4O for research and GPT-O1 for reasoning": "2024-11-06_00-05-28__q4_initial_bot__score_0.0079__git_b666874.json",
+        "GPT-4O for research and GPT-O1 for final decision": "2024-11-06_00-05-28__q4_initial_bot__score_0.0079__git_b666874.json",
+        "Claude 3.5 Sonnet for all tasks": "2024-11-06_19-32-35__q4_initial_bot_anthropic__score_0.024__git_a7572c1.json",
+        # "Claude 3.5 Sonnet Incomplete (5 questions)": "2024-11-06_11-05-17__q4_initial_bot_with_anthropic__score_0.0092.json",
         # "Research Format Update": "2024-08-30_17-22-42__research_format_update__score_0.0802.json",
         # "Original Bot": "2024-08-30_16-46-19__original_bot__score_0.0657.json",
     }
     BENCHMARK_FOLDER: str = "front_end/benchmarks"
 
     @classmethod
     async def _async_main(cls) -> None:
-        st.title("Benchmarks")
+        st.title("📈 Benchmarking Forecast Bot")
         st.write("")
         selected_file = st.selectbox(
             "Select a benchmark file:",