Module zep_python.memory

Expand source code
from zep_python.memory.models import (
    Memory,
    MemorySearchPayload,
    MemorySearchResult,
    Message,
    Session,
    Summary,
)

__all__ = [
    "Memory",
    "Message",
    "MemorySearchPayload",
    "MemorySearchResult",
    "Summary",
    "Session",
]

Sub-modules

zep_python.memory.client
zep_python.memory.models

Classes

class Memory (**data: Any)

Represents a memory object with messages, metadata, and other attributes.

Attributes

messages : Optional[List[Message]]
A list of message objects, where each message contains a role and content.
metadata : Optional[Dict[str, Any]]
A dictionary containing metadata associated with the memory.
summary : Optional[Summary]
A Summary object.
uuid : Optional[str]
A unique identifier for the memory.
created_at : Optional[str]
The timestamp when the memory was created.
token_count : Optional[int]
The token count of the memory.

Methods

to_dict() -> Dict[str, Any]: Returns a dictionary representation of the message.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class Memory(BaseModel):
    """
    Represents a memory object with messages, metadata, and other attributes.

    Attributes
    ----------
    messages : Optional[List[Message]]
        A list of message objects, where each message contains a role and content.
    metadata : Optional[Dict[str, Any]]
        A dictionary containing metadata associated with the memory.
    summary : Optional[Summary]
        A Summary object.
    uuid : Optional[str]
        A unique identifier for the memory.
    created_at : Optional[str]
        The timestamp when the memory was created.
    token_count : Optional[int]
        The token count of the memory.

    Methods
    -------
    to_dict() -> Dict[str, Any]:
        Returns a dictionary representation of the message.
    """

    messages: Optional[List[Message]] = Field(
        default=[],
        description="A List of Messages or empty List is required",
    )
    metadata: Optional[Dict[str, Any]] = Field(default=None)
    summary: Optional[Summary] = Field(default=None)
    uuid: Optional[str] = Field(default=None)
    created_at: Optional[str] = Field(default=None)
    token_count: Optional[int] = Field(default=None)

    def to_dict(self) -> Dict[str, Any]:
        return self.model_dump(exclude_unset=True, exclude_none=True)

Ancestors

  • pydantic.main.BaseModel

Class variables

var created_at : Optional[str]
var messages : Optional[List[Message]]
var metadata : Optional[Dict[str, Any]]
var model_config
var model_fields
var summary : Optional[Summary]
var token_count : Optional[int]
var uuid : Optional[str]

Methods

def to_dict(self) ‑> Dict[str, Any]
Expand source code
def to_dict(self) -> Dict[str, Any]:
    return self.model_dump(exclude_unset=True, exclude_none=True)
class MemorySearchPayload (**data: Any)

Represents a search payload for querying memory.

Attributes

metadata : Dict[str, Any]
Metadata associated with the search query.
text : str
The text of the search query.
search_scope : Optional[str]
Search over messages or summaries. Defaults to "messages". Must be one of "messages" or "summary".
search_type : Optional[str]
The type of search to perform. Defaults to "similarity". Must be one of "similarity" or "mmr".
mmr_lambda : Optional[float]
The lambda parameter for the MMR Reranking Algorithm.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class MemorySearchPayload(BaseModel):
    """
    Represents a search payload for querying memory.

    Attributes
    ----------
    metadata : Dict[str, Any]
        Metadata associated with the search query.
    text : str
        The text of the search query.
    search_scope : Optional[str]
        Search over messages or summaries. Defaults to "messages".
        Must be one of "messages" or "summary".
    search_type : Optional[str]
        The type of search to perform. Defaults to "similarity".
        Must be one of "similarity" or "mmr".
    mmr_lambda : Optional[float]
        The lambda parameter for the MMR Reranking Algorithm.
    """

    text: Optional[str] = Field(default=None)
    metadata: Optional[Dict[str, Any]] = Field(default=None)
    search_scope: Optional[str] = Field(default="messages")
    search_type: Optional[str] = Field(default="similarity")
    mmr_lambda: Optional[float] = Field(default=None)

Ancestors

  • pydantic.main.BaseModel

Class variables

var metadata : Optional[Dict[str, Any]]
var mmr_lambda : Optional[float]
var model_config
var model_fields
var search_scope : Optional[str]
var search_type : Optional[str]
var text : Optional[str]
class MemorySearchResult (**data: Any)

Represents a search result from querying memory.

Attributes

message : Optional[Message]
The message matched by search.
summary : Optional[Summary]
The summary matched by search.
metadata : Optional[Dict[str, Any]]
Metadata associated with the search result.
score : Optional[float]
The score of the search result.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class MemorySearchResult(BaseModel):
    """
    Represents a search result from querying memory.

    Attributes
    ----------
    message : Optional[Message]
        The message matched by search.
    summary : Optional[Summary]
        The summary matched by search.
    metadata : Optional[Dict[str, Any]]
        Metadata associated with the search result.
    score : Optional[float]
        The score of the search result.
    """

    message: Optional[Message] = None
    summary: Optional[Summary] = None
    metadata: Optional[Dict[str, Any]] = None
    score: Optional[float] = None

Ancestors

  • pydantic.main.BaseModel

Class variables

var message : Optional[Message]
var metadata : Optional[Dict[str, Any]]
var model_config
var model_fields
var score : Optional[float]
var summary : Optional[Summary]
class Message (**data: Any)

Represents a message in a conversation.

Attributes

uuid : str, optional
The unique identifier of the message.
created_at : str, optional
The timestamp of when the message was created.
role : str
The role of the sender of the message (e.g., "user", "assistant").
content : str
The content of the message.
token_count : int, optional
The number of tokens in the message.

Methods

to_dict() -> Dict[str, Any]: Returns a dictionary representation of the message.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class Message(BaseModel):
    """
    Represents a message in a conversation.

    Attributes
    ----------
    uuid : str, optional
        The unique identifier of the message.
    created_at : str, optional
        The timestamp of when the message was created.
    role : str
        The role of the sender of the message (e.g., "user", "assistant").
    content : str
        The content of the message.
    token_count : int, optional
        The number of tokens in the message.

    Methods
    -------
    to_dict() -> Dict[str, Any]:
        Returns a dictionary representation of the message.
    """

    role: str = Field("A role is required")
    content: str = Field("Content is required")
    uuid: Optional[str] = Field(default=None)
    created_at: Optional[str] = Field(default=None)
    token_count: Optional[int] = Field(default=None)
    metadata: Optional[Dict[str, Any]] = Field(default=None)

    def to_dict(self) -> Dict[str, Any]:
        """
        Returns a dictionary representation of the message.

        Returns
        -------
        Dict[str, Any]
            A dictionary containing the attributes of the message.
        """
        return self.model_dump(exclude_unset=True, exclude_none=True)

Ancestors

  • pydantic.main.BaseModel

Class variables

var content : str
var created_at : Optional[str]
var metadata : Optional[Dict[str, Any]]
var model_config
var model_fields
var role : str
var token_count : Optional[int]
var uuid : Optional[str]

Methods

def to_dict(self) ‑> Dict[str, Any]

Returns a dictionary representation of the message.

Returns

Dict[str, Any]
A dictionary containing the attributes of the message.
Expand source code
def to_dict(self) -> Dict[str, Any]:
    """
    Returns a dictionary representation of the message.

    Returns
    -------
    Dict[str, Any]
        A dictionary containing the attributes of the message.
    """
    return self.model_dump(exclude_unset=True, exclude_none=True)
class Session (**data: Any)

Represents a session object with a unique identifier, metadata, and other attributes.

Attributes

uuid : Optional[str]
A unique identifier for the session. This is generated server-side and is not expected to be present on creation.
created_at : str
The timestamp when the session was created. Generated by the server.
updated_at : str
The timestamp when the session was last updated. Generated by the server.
deleted_at : Optional[datetime]
The timestamp when the session was deleted. Generated by the server.
session_id : str
The unique identifier of the session.
metadata : Dict[str, Any]
The metadata associated with the session.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class Session(BaseModel):
    """
    Represents a session object with a unique identifier, metadata,
    and other attributes.

    Attributes
    ----------
    uuid : Optional[str]
        A unique identifier for the session.
        This is generated server-side and is not expected to be present on creation.
    created_at : str
        The timestamp when the session was created.
        Generated by the server.
    updated_at : str
        The timestamp when the session was last updated.
        Generated by the server.
    deleted_at : Optional[datetime]
        The timestamp when the session was deleted.
        Generated by the server.
    session_id : str
        The unique identifier of the session.
    metadata : Dict[str, Any]
        The metadata associated with the session.
    """

    uuid: Optional[str] = None
    id: Optional[int] = None
    created_at: Optional[str] = None
    updated_at: Optional[str] = None
    deleted_at: Optional[str] = None
    session_id: str
    user_id: Optional[str] = None
    metadata: Optional[Dict[str, Any]] = None

Ancestors

  • pydantic.main.BaseModel

Class variables

var created_at : Optional[str]
var deleted_at : Optional[str]
var id : Optional[int]
var metadata : Optional[Dict[str, Any]]
var model_config
var model_fields
var session_id : str
var updated_at : Optional[str]
var user_id : Optional[str]
var uuid : Optional[str]
class Summary (**data: Any)

Represents a summary of a conversation.

Attributes

uuid : str
The unique identifier of the summary.
created_at : str
The timestamp of when the summary was created.
content : str
The content of the summary.
recent_message_uuid : str
The unique identifier of the most recent message in the conversation.
token_count : int
The number of tokens in the summary.

Methods

to_dict() -> Dict[str, Any]: Returns a dictionary representation of the summary.

Create a new model by parsing and validating input data from keyword arguments.

Raises [ValidationError][pydantic_core.ValidationError] if the input data cannot be validated to form a valid model.

__init__ uses __pydantic_self__ instead of the more common self for the first arg to allow self as a field name.

Expand source code
class Summary(BaseModel):
    """
    Represents a summary of a conversation.

    Attributes
    ----------
    uuid : str
        The unique identifier of the summary.
    created_at : str
        The timestamp of when the summary was created.
    content : str
        The content of the summary.
    recent_message_uuid : str
        The unique identifier of the most recent message in the conversation.
    token_count : int
        The number of tokens in the summary.

    Methods
    -------
    to_dict() -> Dict[str, Any]:
        Returns a dictionary representation of the summary.
    """

    uuid: str = Field("A uuid is required")
    created_at: str = Field("A created_at is required")
    content: str = Field("Content is required")
    recent_message_uuid: str = Field("A recent_message_uuid is required")
    token_count: int = Field("A token_count is required")

    def to_dict(self) -> Dict[str, Any]:
        """
        Returns a dictionary representation of the summary.

        Returns
        -------
        Dict[str, Any]
            A dictionary containing the attributes of the summary.
        """
        return self.model_dump(exclude_unset=True, exclude_none=True)

Ancestors

  • pydantic.main.BaseModel

Class variables

var content : str
var created_at : str
var model_config
var model_fields
var recent_message_uuid : str
var token_count : int
var uuid : str

Methods

def to_dict(self) ‑> Dict[str, Any]

Returns a dictionary representation of the summary.

Returns

Dict[str, Any]
A dictionary containing the attributes of the summary.
Expand source code
def to_dict(self) -> Dict[str, Any]:
    """
    Returns a dictionary representation of the summary.

    Returns
    -------
    Dict[str, Any]
        A dictionary containing the attributes of the summary.
    """
    return self.model_dump(exclude_unset=True, exclude_none=True)