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@ -1,8 +1,8 @@
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import traceback
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import concurrent.futures
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import datetime
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import json
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import os
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import threading
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import uuid
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from typing import (
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TYPE_CHECKING,
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@ -15,10 +15,9 @@ from typing import (
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)
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import yaml
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import inspect
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from swarms.structs.base_structure import BaseStructure
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from swarms.utils.any_to_str import any_to_str
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from swarms.utils.formatter import formatter
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from swarms.utils.litellm_tokenizer import count_tokens
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if TYPE_CHECKING:
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@ -143,7 +142,7 @@ def _create_backend_conversation(backend: str, **kwargs):
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raise
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class Conversation(BaseStructure):
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class Conversation:
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"""
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A class to manage a conversation history, allowing for the addition, deletion,
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and retrieval of messages, as well as saving and loading the conversation
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@ -167,13 +166,12 @@ class Conversation(BaseStructure):
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time_enabled (bool): Flag to enable time tracking for messages.
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autosave (bool): Flag to enable automatic saving of conversation history.
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save_filepath (str): File path for saving the conversation history.
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tokenizer (Any): Tokenizer for counting tokens in messages.
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context_length (int): Maximum number of tokens allowed in the conversation history.
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rules (str): Rules for the conversation.
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custom_rules_prompt (str): Custom prompt for rules.
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user (str): The user identifier for messages.
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auto_save (bool): Flag to enable auto-saving of conversation history.
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save_as_yaml (bool): Flag to save conversation history as YAML.
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save_as_yaml_on (bool): Flag to save conversation history as YAML.
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save_as_json_bool (bool): Flag to save conversation history as JSON.
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token_count (bool): Flag to enable token counting for messages.
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conversation_history (list): List to store the history of messages.
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@ -182,7 +180,7 @@ class Conversation(BaseStructure):
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def __init__(
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self,
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id: str = generate_conversation_id(),
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name: str = None,
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name: str = "conversation-test",
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system_prompt: Optional[str] = None,
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time_enabled: bool = False,
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autosave: bool = False, # Changed default to False
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@ -193,7 +191,7 @@ class Conversation(BaseStructure):
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rules: str = None,
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custom_rules_prompt: str = None,
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user: str = "User",
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save_as_yaml: bool = False,
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save_as_yaml_on: bool = False,
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save_as_json_bool: bool = False,
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token_count: bool = False,
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message_id_on: bool = False,
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@ -201,6 +199,7 @@ class Conversation(BaseStructure):
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backend: Optional[str] = None,
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supabase_url: Optional[str] = None,
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supabase_key: Optional[str] = None,
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tokenizer_model_name: str = "gpt-4.1",
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redis_host: str = "localhost",
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redis_port: int = 6379,
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redis_db: int = 0,
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@ -212,26 +211,28 @@ class Conversation(BaseStructure):
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auto_persist: bool = True,
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redis_data_dir: Optional[str] = None,
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conversations_dir: Optional[str] = None,
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export_method: str = "json",
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*args,
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**kwargs,
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):
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super().__init__()
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# Initialize all attributes first
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self.id = id
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self.name = name or id
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self.name = name
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self.save_filepath = save_filepath
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self.system_prompt = system_prompt
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self.time_enabled = time_enabled
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self.autosave = autosave
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self.save_enabled = save_enabled
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self.conversations_dir = conversations_dir
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self.tokenizer_model_name = tokenizer_model_name
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self.message_id_on = message_id_on
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self.load_filepath = load_filepath
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self.context_length = context_length
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self.rules = rules
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self.custom_rules_prompt = custom_rules_prompt
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self.user = user
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self.save_as_yaml = save_as_yaml
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self.save_as_yaml_on = save_as_yaml_on
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self.save_as_json_bool = save_as_json_bool
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self.token_count = token_count
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self.provider = provider # Keep for backwards compatibility
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@ -249,23 +250,75 @@ class Conversation(BaseStructure):
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self.persist_redis = persist_redis
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self.auto_persist = auto_persist
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self.redis_data_dir = redis_data_dir
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self.export_method = export_method
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if self.name is None:
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self.name = id
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self.conversation_history = []
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# Handle save filepath
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if save_enabled and save_filepath:
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self.save_filepath = save_filepath
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elif save_enabled and conversations_dir:
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self.save_filepath = os.path.join(
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conversations_dir, f"{self.id}.json"
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self.setup_file_path()
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self.backend_setup(backend, provider)
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def setup_file_path(self):
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"""Set up the file path for saving the conversation and load existing data if available."""
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# Validate export method
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if self.export_method not in ["json", "yaml"]:
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raise ValueError(
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f"Invalid export_method: {self.export_method}. Must be 'json' or 'yaml'"
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)
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# Set default save filepath if not provided
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if not self.save_filepath:
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# Ensure extension matches export method
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extension = (
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".json" if self.export_method == "json" else ".yaml"
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)
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self.save_filepath = (
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f"conversation_{self.name}{extension}"
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)
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logger.debug(
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f"Setting default save filepath to: {self.save_filepath}"
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)
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else:
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self.save_filepath = None
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# Validate that provided filepath extension matches export method
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file_ext = os.path.splitext(self.save_filepath)[1].lower()
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expected_ext = (
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".json" if self.export_method == "json" else ".yaml"
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)
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if file_ext != expected_ext:
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logger.warning(
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f"Save filepath extension ({file_ext}) does not match export_method ({self.export_method}). "
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f"Updating filepath extension to match export method."
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)
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base_name = os.path.splitext(self.save_filepath)[0]
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self.save_filepath = f"{base_name}{expected_ext}"
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# Support both 'provider' and 'backend' parameters for backwards compatibility
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# 'backend' takes precedence if both are provided
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self.created_at = datetime.datetime.now().strftime(
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"%Y-%m-%d_%H-%M-%S"
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)
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self.backend_setup(backend, provider)
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# Check if file exists and load it
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if os.path.exists(self.save_filepath):
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logger.debug(
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f"Found existing conversation file at: {self.save_filepath}"
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)
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try:
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self.load(self.save_filepath)
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logger.info(
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f"Loaded existing conversation from {self.save_filepath}"
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)
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except Exception as e:
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logger.error(
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f"Failed to load existing conversation from {self.save_filepath}: {str(e)}"
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)
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# Keep the empty conversation_history initialized in __init__
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else:
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logger.debug(
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f"No existing conversation file found at: {self.save_filepath}"
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)
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def backend_setup(
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self, backend: str = None, provider: str = None
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@ -341,7 +394,7 @@ class Conversation(BaseStructure):
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"rules": self.rules,
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"custom_rules_prompt": self.custom_rules_prompt,
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"user": self.user,
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"save_as_yaml": self.save_as_yaml,
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"save_as_yaml_on": self.save_as_yaml_on,
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"save_as_json_bool": self.save_as_json_bool,
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"token_count": self.token_count,
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}
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@ -466,13 +519,7 @@ class Conversation(BaseStructure):
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def _autosave(self):
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"""Automatically save the conversation if autosave is enabled."""
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if self.autosave and self.save_filepath:
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try:
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self.save_as_json(self.save_filepath)
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except Exception as e:
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logger.error(
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f"Failed to autosave conversation: {str(e)}"
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)
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return self.export()
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def mem0_provider(self):
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try:
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@ -503,6 +550,7 @@ class Conversation(BaseStructure):
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Args:
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role (str): The role of the speaker (e.g., 'User', 'System').
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content (Union[str, dict, list]): The content of the message to be added.
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category (Optional[str]): Optional category for the message.
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"""
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# Base message with role and timestamp
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message = {
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@ -522,20 +570,18 @@ class Conversation(BaseStructure):
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# Add message to conversation history
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self.conversation_history.append(message)
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# Handle token counting in a separate thread if enabled
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if self.token_count is True:
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self._count_tokens(content, message)
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tokens = count_tokens(
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text=any_to_str(content),
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model=self.tokenizer_model_name,
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)
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message["token_count"] = tokens
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# Autosave after adding message, but only if saving is enabled
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if self.autosave and self.save_enabled and self.save_filepath:
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try:
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self.save_as_json(self.save_filepath)
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except Exception as e:
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logger.error(
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f"Failed to autosave conversation: {str(e)}"
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)
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return message
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def export_and_count_categories(
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self, tokenizer_model_name: Optional[str] = "gpt-4.1-mini"
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self,
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) -> Dict[str, int]:
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"""Export all messages with category 'input' and 'output' and count their tokens.
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@ -580,12 +626,16 @@ class Conversation(BaseStructure):
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# Count tokens only if there is text
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input_tokens = (
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count_tokens(all_input_text, tokenizer_model_name)
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count_tokens(
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all_input_text, self.tokenizer_model_name
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)
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if all_input_text.strip()
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else 0
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)
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output_tokens = (
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count_tokens(all_output_text, tokenizer_model_name)
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count_tokens(
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all_output_text, self.tokenizer_model_name
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)
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if all_output_text.strip()
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else 0
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)
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@ -637,56 +687,57 @@ class Conversation(BaseStructure):
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metadata: Optional[dict] = None,
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category: Optional[str] = None,
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):
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"""Add a message to the conversation history."""
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"""Add a message to the conversation history.
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Args:
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role (str): The role of the speaker (e.g., 'User', 'System').
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content (Union[str, dict, list]): The content of the message to be added.
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metadata (Optional[dict]): Optional metadata for the message.
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category (Optional[str]): Optional category for the message.
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"""
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result = None
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# If using a persistent backend, delegate to it
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if self.backend_instance:
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try:
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return self.backend_instance.add(
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result = self.backend_instance.add(
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role=role, content=content, metadata=metadata
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)
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except Exception as e:
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logger.error(
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f"Backend add failed: {e}. Falling back to in-memory."
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)
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return self.add_in_memory(role, content)
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result = self.add_in_memory(
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role=role, content=content, category=category
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)
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elif self.provider == "in-memory":
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return self.add_in_memory(
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result = self.add_in_memory(
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role=role, content=content, category=category
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)
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elif self.provider == "mem0":
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return self.add_mem0(
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result = self.add_mem0(
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role=role, content=content, metadata=metadata
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)
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else:
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raise ValueError(f"Invalid provider: {self.provider}")
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raise ValueError(
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f"Error: Conversation: {self.name} Invalid provider: {self.provider} Traceback: {traceback.format_exc()}"
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)
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# Ensure autosave happens after the message is added
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if self.autosave:
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self._autosave()
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return result
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def add_multiple_messages(
|
|
|
|
|
self, roles: List[str], contents: List[Union[str, dict, list]]
|
|
|
|
|
):
|
|
|
|
|
return self.add_multiple(roles, contents)
|
|
|
|
|
|
|
|
|
|
def _count_tokens(self, content: str, message: dict):
|
|
|
|
|
# If token counting is enabled, do it in a separate thread
|
|
|
|
|
if self.token_count is True:
|
|
|
|
|
|
|
|
|
|
# Define a function to count tokens and update the message
|
|
|
|
|
def count_tokens_thread():
|
|
|
|
|
tokens = count_tokens(any_to_str(content))
|
|
|
|
|
# Update the message that's already in the conversation history
|
|
|
|
|
message["token_count"] = int(tokens)
|
|
|
|
|
added = self.add_multiple(roles, contents)
|
|
|
|
|
|
|
|
|
|
# If autosave is enabled, save after token count is updated
|
|
|
|
|
if self.autosave:
|
|
|
|
|
self.save_as_json(self.save_filepath)
|
|
|
|
|
if self.autosave:
|
|
|
|
|
self._autosave()
|
|
|
|
|
|
|
|
|
|
# Start a new thread for token counting
|
|
|
|
|
token_thread = threading.Thread(
|
|
|
|
|
target=count_tokens_thread
|
|
|
|
|
)
|
|
|
|
|
token_thread.daemon = (
|
|
|
|
|
True # Make thread terminate when main program exits
|
|
|
|
|
)
|
|
|
|
|
token_thread.start()
|
|
|
|
|
return added
|
|
|
|
|
|
|
|
|
|
def add_multiple(
|
|
|
|
|
self,
|
|
|
|
|
@ -785,45 +836,6 @@ class Conversation(BaseStructure):
|
|
|
|
|
if keyword in str(message["content"])
|
|
|
|
|
]
|
|
|
|
|
|
|
|
|
|
def display_conversation(self, detailed: bool = False):
|
|
|
|
|
"""Display the conversation history.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
detailed (bool, optional): Flag to display detailed information. Defaults to False.
|
|
|
|
|
"""
|
|
|
|
|
if self.backend_instance:
|
|
|
|
|
try:
|
|
|
|
|
return self.backend_instance.display_conversation(
|
|
|
|
|
detailed
|
|
|
|
|
)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"Backend display failed: {e}")
|
|
|
|
|
# Fallback to in-memory display
|
|
|
|
|
pass
|
|
|
|
|
|
|
|
|
|
# In-memory display implementation with proper formatting
|
|
|
|
|
for message in self.conversation_history:
|
|
|
|
|
content = message.get("content", "")
|
|
|
|
|
role = message.get("role", "Unknown")
|
|
|
|
|
|
|
|
|
|
# Format the message content
|
|
|
|
|
if isinstance(content, (dict, list)):
|
|
|
|
|
content = json.dumps(content, indent=2)
|
|
|
|
|
|
|
|
|
|
# Create the display string
|
|
|
|
|
display_str = f"{role}: {content}"
|
|
|
|
|
|
|
|
|
|
# Add details if requested
|
|
|
|
|
if detailed:
|
|
|
|
|
display_str += f"\nTimestamp: {message.get('timestamp', 'Unknown')}"
|
|
|
|
|
display_str += f"\nMessage ID: {message.get('message_id', 'Unknown')}"
|
|
|
|
|
if "token_count" in message:
|
|
|
|
|
display_str += (
|
|
|
|
|
f"\nTokens: {message['token_count']}"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
formatter.print_panel(display_str)
|
|
|
|
|
|
|
|
|
|
def export_conversation(self, filename: str, *args, **kwargs):
|
|
|
|
|
"""Export the conversation history to a file.
|
|
|
|
|
|
|
|
|
|
@ -844,7 +856,7 @@ class Conversation(BaseStructure):
|
|
|
|
|
# In-memory export implementation
|
|
|
|
|
# If the filename ends with .json, use save_as_json
|
|
|
|
|
if filename.endswith(".json"):
|
|
|
|
|
self.save_as_json(filename)
|
|
|
|
|
self.save_as_json(force=True)
|
|
|
|
|
else:
|
|
|
|
|
# Simple text export for non-JSON files
|
|
|
|
|
with open(filename, "w", encoding="utf-8") as f:
|
|
|
|
|
@ -946,99 +958,307 @@ class Conversation(BaseStructure):
|
|
|
|
|
pass
|
|
|
|
|
return self.return_history_as_string()
|
|
|
|
|
|
|
|
|
|
def save_as_json(self, filename: str = None):
|
|
|
|
|
"""Save the conversation history as a JSON file.
|
|
|
|
|
def to_dict(self) -> Dict[str, Any]:
|
|
|
|
|
"""
|
|
|
|
|
Converts all attributes of the class into a dictionary, including all __init__ parameters
|
|
|
|
|
and conversation history. Automatically extracts parameters from __init__ signature.
|
|
|
|
|
|
|
|
|
|
Returns:
|
|
|
|
|
Dict[str, Any]: A dictionary containing:
|
|
|
|
|
- metadata: All initialization parameters and their current values
|
|
|
|
|
- conversation_history: The list of conversation messages
|
|
|
|
|
"""
|
|
|
|
|
# Get all parameters from __init__ signature
|
|
|
|
|
init_signature = inspect.signature(self.__class__.__init__)
|
|
|
|
|
init_params = [
|
|
|
|
|
param
|
|
|
|
|
for param in init_signature.parameters
|
|
|
|
|
if param not in ["self", "args", "kwargs"]
|
|
|
|
|
]
|
|
|
|
|
|
|
|
|
|
# Build metadata dictionary from init parameters
|
|
|
|
|
metadata = {}
|
|
|
|
|
for param in init_params:
|
|
|
|
|
# Get the current value of the parameter from instance
|
|
|
|
|
value = getattr(self, param, None)
|
|
|
|
|
# Special handling for certain types
|
|
|
|
|
if value is not None:
|
|
|
|
|
if isinstance(
|
|
|
|
|
value, (str, int, float, bool, list, dict)
|
|
|
|
|
):
|
|
|
|
|
metadata[param] = value
|
|
|
|
|
elif hasattr(value, "to_dict"):
|
|
|
|
|
metadata[param] = value.to_dict()
|
|
|
|
|
else:
|
|
|
|
|
try:
|
|
|
|
|
# Try to convert to string if not directly serializable
|
|
|
|
|
metadata[param] = str(value)
|
|
|
|
|
except:
|
|
|
|
|
# Skip if we can't serialize
|
|
|
|
|
continue
|
|
|
|
|
|
|
|
|
|
# Add created_at if it exists
|
|
|
|
|
if hasattr(self, "created_at"):
|
|
|
|
|
metadata["created_at"] = self.created_at
|
|
|
|
|
|
|
|
|
|
return {
|
|
|
|
|
"metadata": metadata,
|
|
|
|
|
"conversation_history": self.conversation_history,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
def save_as_json(self, force: bool = True):
|
|
|
|
|
"""Save the conversation history and metadata to a JSON file.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
filename (str): Filename to save the conversation history.
|
|
|
|
|
force (bool, optional): If True, saves regardless of autosave setting. Defaults to True.
|
|
|
|
|
"""
|
|
|
|
|
# Check backend instance first
|
|
|
|
|
if self.backend_instance:
|
|
|
|
|
try:
|
|
|
|
|
return self.backend_instance.save_as_json(filename)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"Backend save_as_json failed: {e}")
|
|
|
|
|
# Fallback to local save implementation below
|
|
|
|
|
try:
|
|
|
|
|
# Check if saving is allowed
|
|
|
|
|
if not self.autosave and not force:
|
|
|
|
|
logger.warning(
|
|
|
|
|
"Autosave is disabled. To save anyway, call save_as_json(force=True) "
|
|
|
|
|
"or enable autosave by setting autosave=True when creating the Conversation."
|
|
|
|
|
)
|
|
|
|
|
return
|
|
|
|
|
|
|
|
|
|
# Don't save if saving is disabled
|
|
|
|
|
if not self.save_enabled:
|
|
|
|
|
logger.warning(
|
|
|
|
|
"An attempt to save the conversation failed: save_enabled is False."
|
|
|
|
|
"Please set save_enabled=True when creating a Conversation object to enable saving."
|
|
|
|
|
# Don't save if saving is disabled (你的PR代码)
|
|
|
|
|
if not self.save_enabled:
|
|
|
|
|
logger.warning(
|
|
|
|
|
"An attempt to save the conversation failed: save_enabled is False."
|
|
|
|
|
"Please set save_enabled=True when creating a Conversation object to enable saving."
|
|
|
|
|
)
|
|
|
|
|
return
|
|
|
|
|
# Get the full data including metadata and conversation history
|
|
|
|
|
data = self.get_init_params()
|
|
|
|
|
|
|
|
|
|
# Ensure we have a valid save path
|
|
|
|
|
if not self.save_filepath:
|
|
|
|
|
self.save_filepath = os.path.join(
|
|
|
|
|
self.conversations_dir or os.getcwd(),
|
|
|
|
|
f"conversation_{self.name}.json",
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
# Create directory if it doesn't exist
|
|
|
|
|
save_dir = os.path.dirname(self.save_filepath)
|
|
|
|
|
if save_dir:
|
|
|
|
|
os.makedirs(save_dir, exist_ok=True)
|
|
|
|
|
|
|
|
|
|
# Save with proper formatting
|
|
|
|
|
with open(self.save_filepath, "w", encoding="utf-8") as f:
|
|
|
|
|
json.dump(data, f, indent=4, default=str)
|
|
|
|
|
|
|
|
|
|
logger.info(f"Conversation saved to {self.save_filepath}")
|
|
|
|
|
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to save conversation: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
return
|
|
|
|
|
raise # Re-raise to ensure the error is visible to the caller
|
|
|
|
|
|
|
|
|
|
def get_init_params(self):
|
|
|
|
|
data = {
|
|
|
|
|
"metadata": {
|
|
|
|
|
"id": self.id,
|
|
|
|
|
"name": self.name,
|
|
|
|
|
"system_prompt": self.system_prompt,
|
|
|
|
|
"time_enabled": self.time_enabled,
|
|
|
|
|
"autosave": self.autosave,
|
|
|
|
|
"save_filepath": self.save_filepath,
|
|
|
|
|
"load_filepath": self.load_filepath,
|
|
|
|
|
"context_length": self.context_length,
|
|
|
|
|
"rules": self.rules,
|
|
|
|
|
"custom_rules_prompt": self.custom_rules_prompt,
|
|
|
|
|
"user": self.user,
|
|
|
|
|
"save_as_yaml_on": self.save_as_yaml_on,
|
|
|
|
|
"save_as_json_bool": self.save_as_json_bool,
|
|
|
|
|
"token_count": self.token_count,
|
|
|
|
|
"message_id_on": self.message_id_on,
|
|
|
|
|
"provider": self.provider,
|
|
|
|
|
"backend": self.backend,
|
|
|
|
|
"tokenizer_model_name": self.tokenizer_model_name,
|
|
|
|
|
"conversations_dir": self.conversations_dir,
|
|
|
|
|
"export_method": self.export_method,
|
|
|
|
|
"created_at": self.created_at,
|
|
|
|
|
},
|
|
|
|
|
"conversation_history": self.conversation_history,
|
|
|
|
|
}
|
|
|
|
|
|
|
|
|
|
save_path = filename or self.save_filepath
|
|
|
|
|
if save_path is not None:
|
|
|
|
|
try:
|
|
|
|
|
# Prepare metadata
|
|
|
|
|
metadata = {
|
|
|
|
|
"id": self.id,
|
|
|
|
|
"name": self.name,
|
|
|
|
|
"created_at": datetime.datetime.now().isoformat(),
|
|
|
|
|
"system_prompt": self.system_prompt,
|
|
|
|
|
"rules": self.rules,
|
|
|
|
|
"custom_rules_prompt": self.custom_rules_prompt,
|
|
|
|
|
}
|
|
|
|
|
return data
|
|
|
|
|
|
|
|
|
|
# Prepare save data
|
|
|
|
|
save_data = {
|
|
|
|
|
"metadata": metadata,
|
|
|
|
|
"history": self.conversation_history,
|
|
|
|
|
}
|
|
|
|
|
def save_as_yaml(self, force: bool = True):
|
|
|
|
|
"""Save the conversation history and metadata to a YAML file.
|
|
|
|
|
|
|
|
|
|
# Create directory if it doesn't exist
|
|
|
|
|
os.makedirs(
|
|
|
|
|
os.path.dirname(save_path),
|
|
|
|
|
mode=0o755,
|
|
|
|
|
exist_ok=True,
|
|
|
|
|
Args:
|
|
|
|
|
force (bool, optional): If True, saves regardless of autosave setting. Defaults to True.
|
|
|
|
|
"""
|
|
|
|
|
try:
|
|
|
|
|
# Check if saving is allowed
|
|
|
|
|
if not self.autosave and not force:
|
|
|
|
|
logger.warning(
|
|
|
|
|
"Autosave is disabled. To save anyway, call save_as_yaml(force=True) "
|
|
|
|
|
"or enable autosave by setting autosave=True when creating the Conversation."
|
|
|
|
|
)
|
|
|
|
|
return
|
|
|
|
|
|
|
|
|
|
# Get the full data including metadata and conversation history
|
|
|
|
|
data = self.get_init_params()
|
|
|
|
|
|
|
|
|
|
# Create directory if it doesn't exist
|
|
|
|
|
save_dir = os.path.dirname(self.save_filepath)
|
|
|
|
|
if save_dir:
|
|
|
|
|
os.makedirs(save_dir, exist_ok=True)
|
|
|
|
|
|
|
|
|
|
# Save with proper formatting
|
|
|
|
|
with open(self.save_filepath, "w", encoding="utf-8") as f:
|
|
|
|
|
yaml.dump(
|
|
|
|
|
data,
|
|
|
|
|
f,
|
|
|
|
|
indent=4,
|
|
|
|
|
default_flow_style=False,
|
|
|
|
|
sort_keys=False,
|
|
|
|
|
)
|
|
|
|
|
logger.info(
|
|
|
|
|
f"Conversation saved to {self.save_filepath}"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
# Write directly to file
|
|
|
|
|
with open(save_path, "w") as f:
|
|
|
|
|
json.dump(save_data, f, indent=2)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to save conversation to {self.save_filepath}: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
raise # Re-raise the exception to handle it in the calling method
|
|
|
|
|
|
|
|
|
|
# Only log explicit saves, not autosaves
|
|
|
|
|
if not self.autosave:
|
|
|
|
|
logger.info(
|
|
|
|
|
f"Successfully saved conversation to {save_path}"
|
|
|
|
|
)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"Failed to save conversation: {str(e)}")
|
|
|
|
|
def export(self, force: bool = True):
|
|
|
|
|
"""Export the conversation to a file based on the export method.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
force (bool, optional): If True, saves regardless of autosave setting. Defaults to True.
|
|
|
|
|
"""
|
|
|
|
|
try:
|
|
|
|
|
# Validate export method
|
|
|
|
|
if self.export_method not in ["json", "yaml"]:
|
|
|
|
|
raise ValueError(
|
|
|
|
|
f"Invalid export_method: {self.export_method}. Must be 'json' or 'yaml'"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
# Create directory if it doesn't exist
|
|
|
|
|
save_dir = os.path.dirname(self.save_filepath)
|
|
|
|
|
if save_dir:
|
|
|
|
|
os.makedirs(save_dir, exist_ok=True)
|
|
|
|
|
|
|
|
|
|
# Ensure filepath extension matches export method
|
|
|
|
|
file_ext = os.path.splitext(self.save_filepath)[1].lower()
|
|
|
|
|
expected_ext = (
|
|
|
|
|
".json" if self.export_method == "json" else ".yaml"
|
|
|
|
|
)
|
|
|
|
|
if file_ext != expected_ext:
|
|
|
|
|
base_name = os.path.splitext(self.save_filepath)[0]
|
|
|
|
|
self.save_filepath = f"{base_name}{expected_ext}"
|
|
|
|
|
logger.warning(
|
|
|
|
|
f"Updated save filepath to match export method: {self.save_filepath}"
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
if self.export_method == "json":
|
|
|
|
|
self.save_as_json(force=force)
|
|
|
|
|
elif self.export_method == "yaml":
|
|
|
|
|
self.save_as_yaml(force=force)
|
|
|
|
|
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to export conversation to {self.save_filepath}: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
raise # Re-raise to ensure the error is visible
|
|
|
|
|
|
|
|
|
|
def load_from_json(self, filename: str):
|
|
|
|
|
"""Load the conversation history from a JSON file.
|
|
|
|
|
"""Load the conversation history and metadata from a JSON file.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
filename (str): Filename to load from.
|
|
|
|
|
"""
|
|
|
|
|
if filename is not None and os.path.exists(filename):
|
|
|
|
|
try:
|
|
|
|
|
with open(filename) as f:
|
|
|
|
|
with open(filename, "r", encoding="utf-8") as f:
|
|
|
|
|
data = json.load(f)
|
|
|
|
|
|
|
|
|
|
# Load metadata
|
|
|
|
|
metadata = data.get("metadata", {})
|
|
|
|
|
self.id = metadata.get("id", self.id)
|
|
|
|
|
self.name = metadata.get("name", self.name)
|
|
|
|
|
self.system_prompt = metadata.get(
|
|
|
|
|
"system_prompt", self.system_prompt
|
|
|
|
|
# Update all metadata attributes
|
|
|
|
|
for key, value in metadata.items():
|
|
|
|
|
if hasattr(self, key):
|
|
|
|
|
setattr(self, key, value)
|
|
|
|
|
|
|
|
|
|
# Load conversation history
|
|
|
|
|
self.conversation_history = data.get(
|
|
|
|
|
"conversation_history", []
|
|
|
|
|
)
|
|
|
|
|
self.rules = metadata.get("rules", self.rules)
|
|
|
|
|
self.custom_rules_prompt = metadata.get(
|
|
|
|
|
"custom_rules_prompt", self.custom_rules_prompt
|
|
|
|
|
|
|
|
|
|
logger.info(
|
|
|
|
|
f"Successfully loaded conversation from {filename}"
|
|
|
|
|
)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to load conversation: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
raise
|
|
|
|
|
|
|
|
|
|
def load_from_yaml(self, filename: str):
|
|
|
|
|
"""Load the conversation history and metadata from a YAML file.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
filename (str): Filename to load from.
|
|
|
|
|
"""
|
|
|
|
|
if filename is not None and os.path.exists(filename):
|
|
|
|
|
try:
|
|
|
|
|
with open(filename, "r", encoding="utf-8") as f:
|
|
|
|
|
data = yaml.safe_load(f)
|
|
|
|
|
|
|
|
|
|
# Load metadata
|
|
|
|
|
metadata = data.get("metadata", {})
|
|
|
|
|
# Update all metadata attributes
|
|
|
|
|
for key, value in metadata.items():
|
|
|
|
|
if hasattr(self, key):
|
|
|
|
|
setattr(self, key, value)
|
|
|
|
|
|
|
|
|
|
# Load conversation history
|
|
|
|
|
self.conversation_history = data.get("history", [])
|
|
|
|
|
self.conversation_history = data.get(
|
|
|
|
|
"conversation_history", []
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
logger.info(
|
|
|
|
|
f"Successfully loaded conversation from {filename}"
|
|
|
|
|
)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"Failed to load conversation: {str(e)}")
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to load conversation: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
raise
|
|
|
|
|
|
|
|
|
|
def load(self, filename: str):
|
|
|
|
|
"""Load the conversation history and metadata from a file.
|
|
|
|
|
Automatically detects the file format based on extension.
|
|
|
|
|
|
|
|
|
|
Args:
|
|
|
|
|
filename (str): Filename to load from.
|
|
|
|
|
"""
|
|
|
|
|
if filename is None or not os.path.exists(filename):
|
|
|
|
|
logger.warning(f"File not found: {filename}")
|
|
|
|
|
return
|
|
|
|
|
|
|
|
|
|
file_ext = os.path.splitext(filename)[1].lower()
|
|
|
|
|
try:
|
|
|
|
|
if file_ext == ".json":
|
|
|
|
|
self.load_from_json(filename)
|
|
|
|
|
elif file_ext == ".yaml" or file_ext == ".yml":
|
|
|
|
|
self.load_from_yaml(filename)
|
|
|
|
|
else:
|
|
|
|
|
raise ValueError(
|
|
|
|
|
f"Unsupported file format: {file_ext}. Must be .json, .yaml, or .yml"
|
|
|
|
|
)
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(
|
|
|
|
|
f"Failed to load conversation from {filename}: {str(e)}\nTraceback: {traceback.format_exc()}"
|
|
|
|
|
)
|
|
|
|
|
raise
|
|
|
|
|
|
|
|
|
|
def search_keyword_in_conversation(self, keyword: str):
|
|
|
|
|
"""Search for a keyword in the conversation history.
|
|
|
|
|
|
|
|
|
|
@ -1067,7 +1287,7 @@ class Conversation(BaseStructure):
|
|
|
|
|
for message in self.conversation_history:
|
|
|
|
|
role = message.get("role")
|
|
|
|
|
content = message.get("content")
|
|
|
|
|
tokens = count_tokens(content)
|
|
|
|
|
tokens = count_tokens(content, self.tokenizer_model_name)
|
|
|
|
|
count = tokens # Assign the token count
|
|
|
|
|
total_tokens += count
|
|
|
|
|
|
|
|
|
|
@ -1130,21 +1350,6 @@ class Conversation(BaseStructure):
|
|
|
|
|
pass
|
|
|
|
|
return self.conversation_history
|
|
|
|
|
|
|
|
|
|
def to_yaml(self):
|
|
|
|
|
"""Convert the conversation history to a YAML string.
|
|
|
|
|
|
|
|
|
|
Returns:
|
|
|
|
|
str: The conversation history as a YAML string.
|
|
|
|
|
"""
|
|
|
|
|
if self.backend_instance:
|
|
|
|
|
try:
|
|
|
|
|
return self.backend_instance.to_yaml()
|
|
|
|
|
except Exception as e:
|
|
|
|
|
logger.error(f"Backend to_yaml failed: {e}")
|
|
|
|
|
# Fallback to in-memory implementation
|
|
|
|
|
pass
|
|
|
|
|
return yaml.dump(self.conversation_history)
|
|
|
|
|
|
|
|
|
|
def get_visible_messages(self, agent: "Agent", turn: int):
|
|
|
|
|
"""
|
|
|
|
|
Get the visible messages for a given agent and turn.
|
|
|
|
|
@ -1359,10 +1564,6 @@ class Conversation(BaseStructure):
|
|
|
|
|
pass
|
|
|
|
|
self.conversation_history.extend(messages)
|
|
|
|
|
|
|
|
|
|
def clear_memory(self):
|
|
|
|
|
"""Clear the memory of the conversation."""
|
|
|
|
|
self.conversation_history = []
|
|
|
|
|
|
|
|
|
|
@classmethod
|
|
|
|
|
def load_conversation(
|
|
|
|
|
cls,
|
|
|
|
|
@ -1381,35 +1582,33 @@ class Conversation(BaseStructure):
|
|
|
|
|
Conversation: The loaded conversation object
|
|
|
|
|
"""
|
|
|
|
|
if load_filepath:
|
|
|
|
|
return cls(
|
|
|
|
|
name=name,
|
|
|
|
|
load_filepath=load_filepath,
|
|
|
|
|
save_enabled=False, # Don't enable saving when loading specific file
|
|
|
|
|
)
|
|
|
|
|
conversation = cls(name=name)
|
|
|
|
|
conversation.load(load_filepath)
|
|
|
|
|
return conversation
|
|
|
|
|
|
|
|
|
|
conv_dir = conversations_dir or get_conversation_dir()
|
|
|
|
|
# Try loading by name first
|
|
|
|
|
filepath = os.path.join(conv_dir, f"{name}.json")
|
|
|
|
|
|
|
|
|
|
# If not found by name, try loading by ID
|
|
|
|
|
if not os.path.exists(filepath):
|
|
|
|
|
filepath = os.path.join(conv_dir, f"{name}")
|
|
|
|
|
if not os.path.exists(filepath):
|
|
|
|
|
logger.warning(
|
|
|
|
|
f"No conversation found with name or ID: {name}"
|
|
|
|
|
# Try loading by name with different extensions
|
|
|
|
|
for ext in [".json", ".yaml", ".yml"]:
|
|
|
|
|
filepath = os.path.join(conv_dir, f"{name}{ext}")
|
|
|
|
|
if os.path.exists(filepath):
|
|
|
|
|
conversation = cls(
|
|
|
|
|
name=name, conversations_dir=conv_dir
|
|
|
|
|
)
|
|
|
|
|
return cls(
|
|
|
|
|
name=name,
|
|
|
|
|
conversations_dir=conv_dir,
|
|
|
|
|
save_enabled=True,
|
|
|
|
|
)
|
|
|
|
|
|
|
|
|
|
return cls(
|
|
|
|
|
name=name,
|
|
|
|
|
conversations_dir=conv_dir,
|
|
|
|
|
load_filepath=filepath,
|
|
|
|
|
save_enabled=True,
|
|
|
|
|
conversation.load(filepath)
|
|
|
|
|
return conversation
|
|
|
|
|
|
|
|
|
|
# If not found by name with extensions, try loading by ID
|
|
|
|
|
filepath = os.path.join(conv_dir, name)
|
|
|
|
|
if os.path.exists(filepath):
|
|
|
|
|
conversation = cls(name=name, conversations_dir=conv_dir)
|
|
|
|
|
conversation.load(filepath)
|
|
|
|
|
return conversation
|
|
|
|
|
|
|
|
|
|
logger.warning(
|
|
|
|
|
f"No conversation found with name or ID: {name}"
|
|
|
|
|
)
|
|
|
|
|
return cls(name=name, conversations_dir=conv_dir)
|
|
|
|
|
|
|
|
|
|
def return_dict_final(self):
|
|
|
|
|
"""Return the final message as a dictionary."""
|
|
|
|
|
|
王祥宇
2 months ago