core/agent+config: soft context budget in estimated tokens

Replace max_context_chars with max_context_tokens (default 200k est.
tokens via char/4); compact and /status use the token budget.

src/plyngent/agent/chat.py

@@ -4,7 +4,7 @@ from typing import TYPE_CHECKING
 
 from plyngent.lmproto.openai_compatible.model import SystemChatMessage, UserChatMessage
 
-from .budget import DEFAULT_CONTEXT_MAX_CHARS, DEFAULT_TOOL_RESULT_MAX_CHARS
+from .budget import DEFAULT_CONTEXT_MAX_TOKENS, DEFAULT_TOOL_RESULT_MAX_CHARS
 from .events import UsageEvent
 from .loop import DEFAULT_MAX_ROUNDS, run_chat_loop
 from .usage import TokenUsage
@@ -37,7 +37,7 @@ class ChatAgent:
     system_prompt: str | None
     max_tool_result_chars: int
     parallel_tools: bool
-    max_context_chars: int
+    max_context_tokens: int
     messages: list[AnyChatMessage]
     pending_retry_text: str | None
     session_usage: TokenUsage
@@ -59,7 +59,7 @@ class ChatAgent:
         system_prompt: str | None = None,
         max_tool_result_chars: int = DEFAULT_TOOL_RESULT_MAX_CHARS,
         parallel_tools: bool = True,
-        max_context_chars: int = DEFAULT_CONTEXT_MAX_CHARS,
+        max_context_tokens: int = DEFAULT_CONTEXT_MAX_TOKENS,
     ) -> None:
         self.client = client
         self.model = model
@@ -73,7 +73,7 @@ class ChatAgent:
         self.system_prompt = system_prompt
         self.max_tool_result_chars = max_tool_result_chars
         self.parallel_tools = parallel_tools
-        self.max_context_chars = max_context_chars
+        self.max_context_tokens = max_context_tokens
         self.messages = list(messages) if messages is not None else []
         self.pending_retry_text = None
         self.session_usage = TokenUsage()
@@ -135,7 +135,7 @@ class ChatAgent:
                 stream=self.stream,
                 max_tool_result_chars=self.max_tool_result_chars,
                 parallel_tools=self.parallel_tools,
-                max_context_chars=self.max_context_chars,
+                max_context_tokens=self.max_context_tokens,
             ):
                 if isinstance(event, UsageEvent):
                     turn_usage = turn_usage.add(event.usage)