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Talk2Scholars state

State management for the Talk2Scholars agent.

This module defines the state class Talk2Scholars, which maintains the conversation context, retrieved papers, and other relevant metadata. The state ensures consistency across agent interactions.

Talk2Scholars

Bases: AgentState

Represents the state of the Talk2Scholars agent.

This class extends AgentState to maintain conversation history, retrieved papers, and interactions with the language model.

Attributes:

Name Type Description
last_displayed_papers Dict[str, Any]

Stores the most recently displayed papers.
papers Dict[str, Any]

Stores the research papers retrieved from the agent's queries.
multi_papers Dict[str, Any]

Stores multiple recommended papers from various sources.
zotero_read Dict[str, Any]

Stores the papers retrieved from Zotero.
llm_model BaseChatModel

The language model instance used for generating responses.
Source code in aiagents4pharma/talk2scholars/state/state_talk2scholars.py 
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class Talk2Scholars(AgentState):
    """
    Represents the state of the Talk2Scholars agent.

    This class extends `AgentState` to maintain conversation history, retrieved papers,
    and interactions with the language model.

    Attributes:
        last_displayed_papers (Dict[str, Any]): Stores the most recently displayed papers.
        papers (Dict[str, Any]): Stores the research papers retrieved from the agent's queries.
        multi_papers (Dict[str, Any]): Stores multiple recommended papers from various sources.
        zotero_read (Dict[str, Any]): Stores the papers retrieved from Zotero.
        llm_model (BaseChatModel): The language model instance used for generating responses.
    """

    # Agent state fields
    last_displayed_papers: Annotated[Dict[str, Any], replace_dict]
    papers: Annotated[Dict[str, Any], replace_dict]
    multi_papers: Annotated[Dict[str, Any], replace_dict]
    zotero_read: Annotated[Dict[str, Any], replace_dict]
    llm_model: BaseChatModel

replace_dict(existing, new)

Replaces the existing dictionary with a new dictionary.

This function logs the state update and ensures that the old state is replaced with the new one.

Parameters:

Name Type Description Default
existing Dict[str, Any]

The current dictionary state.

 required
new Dict[str, Any]

The new dictionary state to replace the existing one.

 required

Returns:

Type Description
Dict[str, Any]

Dict[str, Any]: The updated dictionary state.
Example

old_state = {"papers": {"id1": "Paper 1"}} new_state = {"papers": {"id2": "Paper 2"}} updated_state = replace_dict(old_state, new_state) print(updated_state) {"papers": {"id2": "Paper 2"}}

Source code in aiagents4pharma/talk2scholars/state/state_talk2scholars.py 
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def replace_dict(existing: Dict[str, Any], new: Dict[str, Any]) -> Dict[str, Any]:
    """
    Replaces the existing dictionary with a new dictionary.

    This function logs the state update and ensures that the old state is replaced
    with the new one.

    Args:
        existing (Dict[str, Any]): The current dictionary state.
        new (Dict[str, Any]): The new dictionary state to replace the existing one.

    Returns:
        Dict[str, Any]: The updated dictionary state.

    Example:
        >>> old_state = {"papers": {"id1": "Paper 1"}}
        >>> new_state = {"papers": {"id2": "Paper 2"}}
        >>> updated_state = replace_dict(old_state, new_state)
        >>> print(updated_state)
        {"papers": {"id2": "Paper 2"}}
    """
    logger.info("Updating existing state %s with the state dict: %s", existing, new)
    return new