progresss

gui.py

@@ -1,4 +1,4 @@
-# gui.py
+# gui.py
 import dearpygui.dearpygui as dpg
 import tomllib
 import tomli_w
@@ -283,6 +283,41 @@ class ConfirmDialog:
         return self._approved, self._script
 
 
+DISC_ROLES = ["User", "AI", "Vendor API", "System"]
+
+
+def _parse_history_entries(history: list[str]) -> list[dict]:
+    """
+    Convert the raw TOML string array into a flat list of {role, content} dicts.
+    Each TOML string is one excerpt (may contain multiple role blocks separated
+    by lines like "Role:" or "[Role]").  We detect the common patterns:
+      "User:\n..."  "AI:\n..."  "[User]\n..."  "[AI]\n..."
+    and split accordingly.  Unrecognised text becomes a User entry.
+    """
+    import re
+    entries: list[dict] = []
+    role_pattern = re.compile(
+        r'^(?:\[)?(' + '|'.join(re.escape(r) for r in DISC_ROLES) + r')(?:\])?:?\s*$',
+        re.IGNORECASE | re.MULTILINE,
+    )
+    for excerpt in history:
+        # Find all role header positions
+        splits = [(m.start(), m.end(), m.group(1).capitalize()) for m in role_pattern.finditer(excerpt)]
+        if not splits:
+            # No role headers found - treat whole excerpt as User content
+            text = excerpt.strip()
+            if text:
+                entries.append({"role": "User", "content": text})
+            continue
+        # Extract content between headers
+        for idx, (start, end, role) in enumerate(splits):
+            next_start = splits[idx + 1][0] if idx + 1 < len(splits) else len(excerpt)
+            content = excerpt[end:next_start].strip()
+            # Normalise role capitalisation to match DISC_ROLES
+            matched = next((r for r in DISC_ROLES if r.lower() == role.lower()), role)
+            entries.append({"role": matched, "content": content})
+    return entries
+
 class App:
     def __init__(self):
         self.config = load_config()