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python-versions = ">=3.7.2" files = [ - {file = "web3-6.20.0-py3-none-any.whl", hash = "sha256:ec09882d21378b688210cf29385e82b604bdc18fe5c2e238bf3b5fe2a6e6dbbc"}, - {file = "web3-6.20.0.tar.gz", hash = "sha256:b04725517502cad4f15e39356eaf7c4fcb0127c7728f83eec8cbafb5b6455f33"}, + {file = "web3-6.20.1-py3-none-any.whl", hash = "sha256:16fe72aeb48bbd5f7e7e64b323a0d3a16522a28eb4f19ef9f9dd6ce7ee813c82"}, + {file = "web3-6.20.1.tar.gz", hash = "sha256:a29bc1863734e1c05f128ddbc56878f299ea71776806e667b581a83b5d5be0ed"}, ] [package.dependencies] @@ -7167,4 +7223,4 @@ test = ["big-O", "importlib-resources", "jaraco.functools", "jaraco.itertools", [metadata] lock-version = "2.0" python-versions = "~3.10" -content-hash = "9bca1c0f9aa2f7634bedf2200287ee74795389fc74bbdc34aba671da06dc84e7" +content-hash = "a7b2df3caeae67827b4451dc06be957d819c2164292c0617802a2863913db1ad" diff --git a/prediction_prophet/functions/research.py b/prediction_prophet/functions/research.py index 470e24e4..63fe3f2f 100644 --- a/prediction_prophet/functions/research.py +++ b/prediction_prophet/functions/research.py @@ -10,6 +10,7 @@ from prediction_prophet.functions.scrape_results import scrape_results from prediction_prophet.functions.search import search from pydantic.types import SecretStr +from prediction_market_agent_tooling.tools.tavily_cached.tavily_models import TavilyResponseCache if t.TYPE_CHECKING: from loguru import Logger @@ -26,7 +27,8 @@ def research( use_tavily_raw_content: bool = False, openai_api_key: SecretStr | None = None, tavily_api_key: SecretStr | None = None, - logger: t.Union[logging.Logger, "Logger"] = logging.getLogger() + logger: t.Union[logging.Logger, "Logger"] = logging.getLogger(), + tavily_cache: TavilyResponseCache | None = None, ) -> str: logger.info("Started subqueries generation") queries = generate_subqueries(query=goal, limit=initial_subqueries_limit, model=model, api_key=openai_api_key) @@ -44,7 +46,8 @@ def research( search_results_with_queries = search( queries, lambda result: not result.url.startswith("https://www.youtube"), - tavily_api_key=tavily_api_key + tavily_api_key=tavily_api_key, + tavily_cache=tavily_cache, ) if not search_results_with_queries: diff --git a/prediction_prophet/functions/search.py b/prediction_prophet/functions/search.py index de4a9b93..9be679dc 100644 --- a/prediction_prophet/functions/search.py +++ b/prediction_prophet/functions/search.py @@ -3,23 +3,24 @@ from prediction_prophet.functions.web_search import WebSearchResult, web_search from concurrent.futures import ThreadPoolExecutor, as_completed from pydantic.types import SecretStr +from prediction_market_agent_tooling.tools.tavily_cached.tavily_models import TavilyResponseCache -def safe_web_search(query: str, max_results: int = 5, tavily_api_key: SecretStr | None = None) -> t.Optional[list[WebSearchResult]]: +def safe_web_search(query: str, max_results: int = 5, tavily_api_key: SecretStr | None = None, tavily_cache: TavilyResponseCache | None = None) -> t.Optional[list[WebSearchResult]]: try: - return web_search(query, max_results, tavily_api_key) + return web_search(query, max_results, tavily_api_key, tavily_cache) except requests.exceptions.HTTPError as e: print(f"Error in web_search: {e}") return None -def search(queries: list[str], filter: t.Callable[[WebSearchResult], bool] = lambda x: True, tavily_api_key: SecretStr | None = None) -> list[tuple[str, WebSearchResult]]: +def search(queries: list[str], filter: t.Callable[[WebSearchResult], bool] = lambda x: True, tavily_api_key: SecretStr | None = None, tavily_cache: TavilyResponseCache | None = None) -> list[tuple[str, WebSearchResult]]: maybe_results: list[t.Optional[list[WebSearchResult]]] = [] # Each result will have a query associated with it # We only want to keep the results that are unique with ThreadPoolExecutor(max_workers=5) as executor: - futures = {executor.submit(safe_web_search, query, 5, tavily_api_key) for query in queries} + futures = {executor.submit(safe_web_search, query, 5, tavily_api_key, tavily_cache) for query in queries} for future in as_completed(futures): maybe_results.append(future.result()) diff --git a/prediction_prophet/functions/web_search.py b/prediction_prophet/functions/web_search.py index a13e0cc0..dc85bd7f 100644 --- a/prediction_prophet/functions/web_search.py +++ b/prediction_prophet/functions/web_search.py @@ -1,45 +1,32 @@ -import tenacity -import typing as t -from tavily import TavilyClient from pydantic.types import SecretStr -from prediction_market_agent_tooling.tools.utils import secret_str_from_env from prediction_prophet.models.WebSearchResult import WebSearchResult -from prediction_prophet.functions.cache import persistent_inmemory_cache +from prediction_market_agent_tooling.config import APIKeys +from prediction_market_agent_tooling.tools.tavily_cached.tavily_models import TavilyResponseCache +from prediction_market_agent_tooling.tools.tavily_cached.tavily_cached import tavily_search -def web_search(query: str, max_results: int = 5, tavily_api_key: SecretStr | None = None) -> list[WebSearchResult]: - response = _web_search(query=query, max_results=max_results, tavily_api_key=tavily_api_key) - - transformed_results = [ - WebSearchResult( - title=result['title'], - url=result['url'], - description=result['content'], - raw_content=result['raw_content'], - relevancy=result['score'], - query=query - ) - for result in response['results'] - ] - - return transformed_results - - -@tenacity.retry(stop=tenacity.stop_after_attempt(3), wait=tenacity.wait_fixed(1), reraise=True) -@persistent_inmemory_cache -def _web_search(query: str, max_results: int = 5, tavily_api_key: SecretStr | None = None) -> dict[str, t.Any]: - if tavily_api_key == None: - tavily_api_key = secret_str_from_env("TAVILY_API_KEY") - - tavily = TavilyClient(api_key=tavily_api_key.get_secret_value() if tavily_api_key else None) - response: dict[str, t.Any] = tavily.search( +def web_search(query: str, max_results: int = 5, tavily_api_key: SecretStr | None = None, tavily_cache: TavilyResponseCache | None = None) -> list[WebSearchResult]: + response = tavily_search( query=query, search_depth="advanced", max_results=max_results, include_raw_content=True, + response_cache=tavily_cache, + api_keys=APIKeys(TAVILY_API_KEY=tavily_api_key) if tavily_api_key else None, ) - return response + transformed_results = [ + WebSearchResult( + title=result.title, + url=result.url, + description=result.content, + raw_content=result.raw_content, + relevancy=result.score, + query=query, + ) + for result in response.results + ] + return transformed_results diff --git a/pyproject.toml b/pyproject.toml index 75e0080a..70fc1620 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -31,7 +31,8 @@ scikit-learn = "^1.4.0" typer = ">=0.9.0,<1.0.0" types-requests = "^2.31.0.20240125" types-python-dateutil = "^2.9.0" -prediction-market-agent-tooling = { version = ">=0.43.0,<1", extras = ["langchain", "google"] } +# prediction-market-agent-tooling = { version = ">=0.47.0,<1", extras = ["langchain", "google"] } +prediction-market-agent-tooling = { git = "https://github.com/gnosis/prediction-market-agent-tooling.git", rev="29e4e0254d5ad2ce4be687a4d0d4bccdb644675a", extras = ["langchain", "google"] } langchain-community = "^0.2.6" memory-profiler = "^0.61.0" matplotlib = "^3.8.3"