feat(context): Interactive Text Slice Highlighting with Fuzzy Anchors

src/fuzzy_anchor.py

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+import hashlib
+import re
+from typing import Optional, Tuple
+
+class FuzzyAnchor:
+    @staticmethod
+    def get_context(lines: list[str], index: int, count: int, direction: int) -> list[str]:
+        context = []
+        curr = index
+        while len(context) < count and 0 <= curr < len(lines):
+            line = lines[curr].strip()
+            if line:
+                context.append(line)
+            curr += direction
+        return context
+
+    @classmethod
+    def create_slice(cls, text: str, start_line: int, end_line: int) -> dict:
+        """start_line and end_line are 1-based."""
+        lines = text.splitlines()
+        s_idx = max(0, start_line - 1)
+        e_idx = min(len(lines), end_line)
+        slice_lines = lines[s_idx:e_idx]
+        slice_text = "\n".join(slice_lines)
+        
+        return {
+            "start_line": start_line,
+            "end_line": end_line,
+            "start_context": cls.get_context(lines, s_idx, 3, 1),
+            "end_context": cls.get_context(lines, e_idx - 1, 3, -1)[::-1], # Reverse back to normal order
+            "content_hash": hashlib.mdsafe(slice_text.encode()).hexdigest() if hasattr(hashlib, 'mdsafe') else hashlib.md5(slice_text.encode()).hexdigest()
+        }
+
+    @classmethod
+    def resolve_slice(cls, text: str, slice_data: dict) -> Optional[Tuple[int, int]]:
+        lines = text.splitlines()
+        # 1. Try exact match
+        s_idx = slice_data["start_line"] - 1
+        e_idx = slice_data["end_line"]
+        if 0 <= s_idx < len(lines) and e_idx <= len(lines):
+            current_text = "\n".join(lines[s_idx:e_idx])
+            curr_hash = hashlib.md5(current_text.encode()).hexdigest()
+            if curr_hash == slice_data["content_hash"]:
+                return (slice_data["start_line"], slice_data["end_line"])
+
+        # 2. Fuzzy match
+        start_ctx = slice_data["start_context"]
+        end_ctx = slice_data["end_context"]
+        if not start_ctx or not end_ctx: return None
+
+        # Search for start_ctx
+        best_s = -1
+        for i in range(len(lines)):
+            match = True
+            for j, ctx_line in enumerate(start_ctx):
+                if i+j >= len(lines) or lines[i+j].strip() != ctx_line:
+                    match = False
+                    break
+            if match:
+                best_s = i
+                break
+        
+        if best_s == -1: return None
+
+        # Search for end_ctx after start_ctx
+        best_e = -1
+        for i in range(best_s, len(lines)):
+            match = True
+            for j, ctx_line in enumerate(end_ctx):
+                # end_ctx is the LAST 3 lines. So we match backwards from i.
+                idx = i - (len(end_ctx) - 1) + j
+                if idx < 0 or idx >= len(lines) or lines[idx].strip() != ctx_line:
+                    match = False
+                    break
+            if match:
+                best_e = i + 1
+                break
+        
+        if best_e != -1:
+            return (best_s + 1, best_e)
+        
+        return None