SkillOpt v0.1.0: initial release

- Skill optimization framework with training loop analogy
- 11 benchmarks, 4 model backends (Azure OpenAI, Claude, Codex, Qwen)
- WebUI for browser-based training control
- Pluggable architecture for extending benchmarks and backends

skillopt/utils/json_utils.py

@@ -0,0 +1,42 @@
+"""JSON extraction helpers for LLM responses."""
+from __future__ import annotations
+
+import json
+import re
+
+
+def extract_json(text: str) -> dict | None:
+    """Extract a JSON object from LLM response text.
+
+    Tries ```json fences first, then bare {...} patterns.
+    """
+    m = re.search(r"```json\s*(.*?)```", text, re.DOTALL)
+    if m:
+        try:
+            return json.loads(m.group(1))
+        except json.JSONDecodeError:
+            pass
+    m = re.search(r"\{.*\}", text, re.DOTALL)
+    if m:
+        try:
+            return json.loads(m.group(0))
+        except json.JSONDecodeError:
+            pass
+    return None
+
+
+def extract_json_array(text: str) -> list | None:
+    """Extract a JSON array from LLM response text."""
+    m = re.search(r"```json\s*(.*?)```", text, re.DOTALL)
+    if m:
+        try:
+            return json.loads(m.group(1))
+        except json.JSONDecodeError:
+            pass
+    m = re.search(r"\[.*\]", text, re.DOTALL)
+    if m:
+        try:
+            return json.loads(m.group(0))
+        except json.JSONDecodeError:
+            pass
+    return None