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Documentation Index

Fetch the complete documentation index at: https://docs.camel-ai.org/llms.txt

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_process_response

def _process_response(response, return_type: str):
Process the response based on the specified return type. This helper method processes the API response and returns the content in the specified format, which could be a string, a dictionary, or both. Parameters:
  • response: The response object returned by the API call.
  • return_type (str): Specifies the format of the return value. It can be “string” to return the response as a string, “dicts” to return it as a dictionary, or “both” to return both formats as a tuple.
Returns: Union[str, dict, Tuple[str, dict]]: The processed response, formatted according to the return_type argument. If “string”, returns the response as a string. If “dicts”, returns the response as a dictionary. If “both”, returns a tuple containing both formats. Raises:
  • ValueError: If the return_type provided is invalid.

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AskNewsToolkit

class AskNewsToolkit(BaseToolkit):
A class representing a toolkit for interacting with the AskNews API. This class provides methods for fetching news, stories, and other content based on user queries using the AskNews API.

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init

def __init__(self, timeout: Optional[float] = None):
Initialize the AskNewsToolkit with API clients.The API keys and credentials are retrieved from environment variables.

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get_news

def get_news(
    self,
    query: str,
    n_articles: int = 10,
    return_type: Literal['string', 'dicts', 'both'] = 'string',
    method: Literal['nl', 'kw'] = 'kw'
):
Fetch news or stories based on a user query. Parameters:
  • query (str): The search query for fetching relevant news.
  • n_articles (int): Number of articles to include in the response. (default: :obj:10)
  • return_type (Literal["string", "dicts", "both"]): The format of the return value. (default: :obj:"string")
  • method (Literal["nl", "kw"]): The search method, either “nl” for natural language or “kw” for keyword search. (default: :obj:"kw")
Returns: Union[str, dict, Tuple[str, dict]]: A string, dictionary, or both containing the news or story content, or error message if the process fails.

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get_stories

def get_stories(
    self,
    query: str,
    categories: List[Literal['Politics', 'Economy', 'Finance', 'Science', 'Technology', 'Sports', 'Climate', 'Environment', 'Culture', 'Entertainment', 'Business', 'Health', 'International']],
    reddit: int = 3,
    expand_updates: bool = True,
    max_updates: int = 2,
    max_articles: int = 10
):
Fetch stories based on the provided parameters. Parameters:
  • query (str): The search query for fetching relevant stories.
  • categories (list): The categories to filter stories by.
  • reddit (int): Number of Reddit threads to include. (default: :obj:3)
  • expand_updates (bool): Whether to include detailed updates. (default: :obj:True)
  • max_updates (int): Maximum number of recent updates per story. (default: :obj:2)
  • max_articles (int): Maximum number of articles associated with each update. (default: :obj:10)
Returns: Union[dict, str]: A dictionary containing the stories and their associated data, or error message if the process fails. 
def get_web_search(
    self,
    queries: List[str],
    return_type: Literal['string', 'dicts', 'both'] = 'string'
):
Perform a live web search based on the given queries. Parameters:
  • queries (List[str]): A list of search queries.
  • return_type (Literal["string", "dicts", "both"]): The format of the return value. (default: :obj:"string")
Returns: Union[str, dict, Tuple[str, dict]]: A string, dictionary, or both containing the search results, or error message if the process fails.

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search_reddit

def search_reddit(
    self,
    keywords: List[str],
    n_threads: int = 5,
    return_type: Literal['string', 'dicts', 'both'] = 'string',
    method: Literal['nl', 'kw'] = 'kw'
):
Search Reddit based on the provided keywords. Parameters:
  • keywords (List[str]): The keywords to search for on Reddit.
  • n_threads (int): Number of Reddit threads to summarize and return. (default: :obj:5)
  • return_type (Literal["string", "dicts", "both"]): The format of the return value. (default: :obj:"string")
  • method (Literal["nl", "kw"]): The search method, either “nl” for natural language or “kw” for keyword search. (default: :obj:"kw")
Returns: Union[str, dict, Tuple[str, dict]]: The Reddit search results as a string, dictionary, or both, or error message if the process fails.

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query_finance

def query_finance(
    self,
    asset: Literal['bitcoin', 'ethereum', 'cardano', 'uniswap', 'ripple', 'solana', 'polkadot', 'polygon', 'chainlink', 'tether', 'dogecoin', 'monero', 'tron', 'binance', 'aave', 'tesla', 'microsoft', 'amazon'],
    metric: Literal['news_positive', 'news_negative', 'news_total', 'news_positive_weighted', 'news_negative_weighted', 'news_total_weighted'] = 'news_positive',
    return_type: Literal['list', 'string'] = 'string',
    date_from: Optional[datetime] = None,
    date_to: Optional[datetime] = None
):
Fetch asset sentiment data for a given asset, metric, and date range. Parameters:
  • asset (Literal): The asset for which to fetch sentiment data.
  • metric (Literal): The sentiment metric to analyze.
  • return_type (Literal["list", "string"]): The format of the return value. (default: :obj:"string")
  • date_from (datetime, optional): The start date and time for the data in ISO 8601 format.
  • date_to (datetime, optional): The end date and time for the data in ISO 8601 format.
Returns: Union[list, str]: A list of dictionaries containing the datetime and value or a string describing all datetime and value pairs for providing quantified time-series data for news sentiment on topics of interest, or an error message if the process fails.

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get_tools

def get_tools(self):
Returns: List[FunctionTool]: A list of FunctionTool objects representing the functions in the toolkit.

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AsyncAskNewsToolkit

class AsyncAskNewsToolkit(BaseToolkit):
A class representing a toolkit for interacting with the AskNews API asynchronously. This class provides methods for fetching news, stories, and other content based on user queries using the AskNews API.

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init

def __init__(self):
Initialize the AsyncAskNewsToolkit with API clients.The API keys and credentials are retrieved from environment variables.

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get_tools

def get_tools(self):
Returns: List[FunctionTool]: A list of FunctionTool objects representing the functions in the toolkit.