多场景对架构一期

pilot/prompts/base.py

@@ -0,0 +1,51 @@
+
+
+import json
+from abc import ABC, abstractmethod
+from pathlib import Path
+from typing import Any, Callable, Dict, List, Mapping, Optional, Set, Union
+
+import yaml
+from pydantic import BaseModel, Extra, Field, root_validator
+
+from pilot.scene.base_message import BaseMessage,HumanMessage,AIMessage, SystemMessage
+
+
+def get_buffer_string(
+    messages: List[BaseMessage], human_prefix: str = "Human", ai_prefix: str = "AI"
+) -> str:
+    """Get buffer string of messages."""
+    string_messages = []
+    for m in messages:
+        if isinstance(m, HumanMessage):
+            role = human_prefix
+        elif isinstance(m, AIMessage):
+            role = ai_prefix
+        elif isinstance(m, SystemMessage):
+            role = "System"
+        else:
+            raise ValueError(f"Got unsupported message type: {m}")
+        string_messages.append(f"{role}: {m.content}")
+    return "\n".join(string_messages)
+
+
+
+class PromptValue(BaseModel, ABC):
+    @abstractmethod
+    def to_string(self) -> str:
+        """Return prompt as string."""
+
+    @abstractmethod
+    def to_messages(self) -> List[BaseMessage]:
+        """Return prompt as messages."""
+
+class ChatPromptValue(PromptValue):
+    messages: List[BaseMessage]
+
+    def to_string(self) -> str:
+        """Return prompt as string."""
+        return get_buffer_string(self.messages)
+
+    def to_messages(self) -> List[BaseMessage]:
+        """Return prompt as messages."""
+        return self.messages