CoACT initialize (#292)

mm_agents/coact/autogen/agentchat/group/llm_condition.py

@@ -0,0 +1,93 @@
+# Copyright (c) 2023 - 2025, AG2ai, Inc., AG2ai open-source projects maintainers and core contributors
+#
+# SPDX-License-Identifier: Apache-2.0
+
+from typing import TYPE_CHECKING, Any
+
+from pydantic import BaseModel
+
+from .context_str import ContextStr
+
+if TYPE_CHECKING:
+    # Avoid circular import
+    from ..conversable_agent import ConversableAgent
+
+__all__ = ["ContextStrLLMCondition", "LLMCondition", "StringLLMCondition"]
+
+
+class LLMCondition(BaseModel):
+    """Protocol for conditions evaluated by an LLM."""
+
+    def get_prompt(self, agent: "ConversableAgent", messages: list[dict[str, Any]]) -> str:
+        """Get the prompt text for LLM evaluation.
+
+        Args:
+            agent: The agent evaluating the condition
+            messages: The conversation history
+
+        Returns:
+            The prompt text to be evaluated by the LLM
+        """
+        raise NotImplementedError("Requires subclasses to implement.")
+
+
+class StringLLMCondition(LLMCondition):
+    """Simple string-based LLM condition.
+
+    This condition provides a static string prompt to be evaluated by an LLM.
+    """
+
+    prompt: str
+
+    def __init__(self, prompt: str, **data: Any) -> None:
+        """Initialize with a prompt string as a positional parameter.
+
+        Args:
+            prompt: The static prompt string to evaluate
+            data: Additional data for the parent class
+        """
+        super().__init__(prompt=prompt, **data)
+
+    def get_prompt(self, agent: "ConversableAgent", messages: list[dict[str, Any]]) -> str:
+        """Return the static prompt string.
+
+        Args:
+            agent: The agent evaluating the condition (not used)
+            messages: The conversation history (not used)
+
+        Returns:
+            The static prompt string
+        """
+        return self.prompt
+
+
+class ContextStrLLMCondition(LLMCondition):
+    """Context variable-based LLM condition.
+
+    This condition uses a ContextStr object with context variable placeholders that
+    will be substituted before being evaluated by an LLM.
+    """
+
+    context_str: ContextStr
+
+    def __init__(self, context_str: ContextStr, **data: Any) -> None:
+        """Initialize with a context string as a positional parameter.
+
+        Args:
+            context_str: The ContextStr object with variable placeholders
+            data: Additional data for the parent class
+        """
+        super().__init__(context_str=context_str, **data)
+
+    def get_prompt(self, agent: "ConversableAgent", messages: list[dict[str, Any]]) -> str:
+        """Return the prompt with context variables substituted.
+
+        Args:
+            agent: The agent evaluating the condition (provides context variables)
+            messages: The conversation history (not used)
+
+        Returns:
+            The prompt with context variables substituted
+        """
+        result = self.context_str.format(agent.context_variables)
+        return result if result is not None else ""