camel.memories.context_creators package

camel.memories.context_creators package#

Submodules#

camel.memories.context_creators.score_based module#

class camel.memories.context_creators.score_based.ScoreBasedContextCreator(token_counter: BaseTokenCounter, token_limit: int)[source]#

Bases: BaseContextCreator

A default implementation of context creation strategy, which inherits from BaseContextCreator.

This class provides a strategy to generate a conversational context from a list of chat history records while ensuring the total token count of the context does not exceed a specified limit. It prunes messages based on their score if the total token count exceeds the limit.

Parameters:

  • token_counter (BaseTokenCounter) – An instance responsible for counting tokens in a message.

  • token_limit (int) – The maximum number of tokens allowed in the generated context.

create_context(records: List[ContextRecord]) → Tuple[List[ChatCompletionDeveloperMessageParam | ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam | ChatCompletionAssistantMessageParam | ChatCompletionToolMessageParam | ChatCompletionFunctionMessageParam], int][source]#

Constructs conversation context from chat history while respecting token limits.

Key strategies: 1. System message is always prioritized and preserved 2. Truncation removes low-score messages first 3. Final output maintains chronological order and in history memory,

the score of each message decreases according to keep_rate. The newer the message, the higher the score.

Parameters:

records (List[ContextRecord]) – List of context records with scores and timestamps.

Returns:

  • Ordered list of OpenAI messages

  • Total token count of the final context

Return type:

Tuple[List[OpenAIMessage], int]

Raises:

RuntimeError – If system message alone exceeds token limit

property token_counter: BaseTokenCounter#
property token_limit: int#

Module contents#

class camel.memories.context_creators.ScoreBasedContextCreator(token_counter: BaseTokenCounter, token_limit: int)[source]#

Bases: BaseContextCreator

A default implementation of context creation strategy, which inherits from BaseContextCreator.

This class provides a strategy to generate a conversational context from a list of chat history records while ensuring the total token count of the context does not exceed a specified limit. It prunes messages based on their score if the total token count exceeds the limit.

Parameters:

  • token_counter (BaseTokenCounter) – An instance responsible for counting tokens in a message.

  • token_limit (int) – The maximum number of tokens allowed in the generated context.

create_context(records: List[ContextRecord]) → Tuple[List[ChatCompletionDeveloperMessageParam | ChatCompletionSystemMessageParam | ChatCompletionUserMessageParam | ChatCompletionAssistantMessageParam | ChatCompletionToolMessageParam | ChatCompletionFunctionMessageParam], int][source]#

Constructs conversation context from chat history while respecting token limits.

Key strategies: 1. System message is always prioritized and preserved 2. Truncation removes low-score messages first 3. Final output maintains chronological order and in history memory,

the score of each message decreases according to keep_rate. The newer the message, the higher the score.

Parameters:

records (List[ContextRecord]) – List of context records with scores and timestamps.

Returns:

  • Ordered list of OpenAI messages

  • Total token count of the final context

Return type:

Tuple[List[OpenAIMessage], int]

Raises:

RuntimeError – If system message alone exceeds token limit

property token_counter: BaseTokenCounter#
property token_limit: int#
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