fix: more refactor, support summarizing conversations with `gptme-uti…

…l chats list --summarize`

gptme/logmanager.py

@@ -340,9 +340,16 @@ class ConversationMeta:
     messages: int
     branches: int
 
-    def format(self) -> str:
-        """Format a conversation for display."""
-        return f"{self.name}: {self.messages} messages, last modified {self.modified}"
+    def format(self, metadata=False) -> str:
+        """Format conversation metadata for display."""
+        output = f"{self.name}"
+        if metadata:
+            output += f"\nMessages: {self.messages}"
+            output += f"\nCreated:  {datetime.fromtimestamp(self.created)}"
+            output += f"\nModified: {datetime.fromtimestamp(self.modified)}"
+            if self.branches > 1:
+                output += f"\n({self.branches} branches)"
+        return output
 
 
 def get_conversations() -> Generator[ConversationMeta, None, None]:

gptme/tools/chats.py

@@ -3,6 +3,7 @@
 """
 
 import logging
+import textwrap
 from pathlib import Path
 
 from ..message import Message
@@ -21,7 +22,9 @@ def _get_matching_messages(log_manager, query: str, system=False) -> list[Messag
     ]
 
 
-def list_chats(max_results: int = 5, include_summary: bool = False) -> None:
+def list_chats(
+    max_results: int = 5, metadata=False, include_summary: bool = False
+) -> None:
     """
     List recent chat conversations and optionally summarize them using an LLM.
 
@@ -41,16 +44,20 @@ def list_chats(max_results: int = 5, include_summary: bool = False) -> None:
 
     print(f"Recent conversations (showing up to {max_results}):")
     for i, conv in enumerate(conversations, 1):
-        print(f"\n{i}. {conv.format()}")
-        print(f"   Created: {conv.created}")
+        if metadata:
+            print()  # Add a newline between conversations
+        print(f"{i:2}. {textwrap.indent(conv.format(metadata=True), '    ')[4:]}")
 
         log_path = Path(conv.path)
         log_manager = LogManager.load(log_path)
 
         # Use the LLM to generate a summary if requested
         if include_summary:
             summary = summarize(log_manager.log.messages)
-            print(f"   Summary: {summary.content}")
+            print(
+                f"\n    Summary:\n{textwrap.indent(summary.content, '    > ', predicate=lambda _: True)}"
+            )
+            print()
 
 
 def search_chats(query: str, max_results: int = 5, system=False) -> None:

gptme/util/cli.py

@@ -8,8 +8,9 @@
 import click
 
 from ..dirs import get_logs_dir
-from ..logmanager import LogManager, list_conversations
+from ..logmanager import LogManager
 from ..message import Message
+from ..tools.chats import list_chats
 
 
 @click.group()
@@ -26,16 +27,17 @@ def chats():
 
 @chats.command("ls")
 @click.option("-n", "--limit", default=20, help="Maximum number of chats to show.")
-def chats_list(limit: int):
+@click.option(
+    "--summarize", is_flag=True, help="Generate LLM-based summaries for chats"
+)
+def chats_list(limit: int, summarize: bool):
     """List conversation logs."""
+    if summarize:
+        from gptme.init import init  # fmt: skip
 
-    conversations = list_conversations(limit)
-    if not conversations:
-        print("No conversations found.")
-        return
-
-    for conv in conversations:
-        print(conv.format())
+        # This isn't the best way to initialize the model for summarization, but it works for now
+        init("openai/gpt-4o", interactive=False, tool_allowlist=[])
+    list_chats(max_results=limit, include_summary=summarize)
 
 
 @chats.command("read")