Delete 题目生成.py

题目生成.py

@@ -1,133 +0,0 @@
-import json
-import random
-from collections import defaultdict, deque
-
-def generate_localization_samples(n):
-    all_data = []
-    global_index = 1
-
-    def is_all_steps_connected(steps):
-        # 构建依赖图
-        graph = defaultdict(list)
-        reverse_graph = defaultdict(list)
-        all_ids = set()
-
-        for step in steps:
-            step_id = step["id"]
-            inputs = step["inputs"]
-            all_ids.add(step_id)
-            for inp in inputs:
-                if isinstance(inp, int):  # 如果引用了前一个 step
-                    graph[inp].append(step_id)
-                    reverse_graph[step_id].append(inp)
-
-        # 最后一个 step ID
-        print(steps)
-        last_id = steps[-1]["id"]
-
-        # 从最后一个 step 开始反向遍历，看能否覆盖所有 step
-        visited = set()
-        queue = deque([last_id])
-        while queue:
-            curr = queue.popleft()
-            visited.add(curr)
-            for parent in reverse_graph[curr]:
-                if parent not in visited:
-                    queue.append(parent)
-
-        return all_ids.issubset(visited)
-
-    while len(all_data) < n:
-        sample = {"index": global_index, "instruction": "", "steps": []}
-        num_locations = random.randint(1, 3)
-        locations = [f"LOC_{i+1}" for i in range(num_locations)]
-        used_locations = set()
-        steps = []
-        current_id = 1
-        all_refs = locations.copy()  # step inputs can be LOCs or previous step IDs
-        step_definitions = []
-
-        num_steps = random.randint(2, 5)
-
-        for _ in range(num_steps):
-            func = random.choice(["Relative", "Azimuth", "Between"])
-            if func in ["Relative", "Azimuth"]:
-                base = random.choice(all_refs)
-                if isinstance(base, str):
-                    used_locations.add(base)
-
-                if func == "Relative":
-                    direction = random.choice([
-                        "north", "south", "east", "west",
-                        "northeast", "northwest", "southeast", "southwest"
-                    ])
-                    distance = f"{random.randint(1, 10)} km"
-                    step_definitions.append({
-                        "id": current_id,
-                        "function": "Relative",
-                        "inputs": [base, direction, distance]
-                    })
-                else:
-                    angle = f"{random.randint(0, 359)}°"
-                    distance = f"{random.randint(1, 10)} km"
-                    step_definitions.append({
-                        "id": current_id,
-                        "function": "Azimuth",
-                        "inputs": [base, angle, distance]
-                    })
-
-                all_refs.append(current_id)
-                current_id += 1
-
-            elif func == "Between" and len(all_refs) >= 2:
-                base1, base2 = random.sample(all_refs, 2)
-                for b in (base1, base2):
-                    if isinstance(b, str):
-                        used_locations.add(b)
-                step_definitions.append({
-                    "id": current_id,
-                    "function": "Between",
-                    "inputs": [base1, base2]
-                })
-                all_refs.append(current_id)
-                current_id += 1
-
-        if len(step_definitions) == 0:
-            continue  # 无有效步骤，跳过重新生成
-
-        all_locs_used = all(loc in used_locations for loc in locations)
-        steps_connected = is_all_steps_connected(step_definitions)
-
-        if all_locs_used and steps_connected:
-            sample["steps"] = step_definitions
-            all_data.append(sample)
-            global_index += 1
-
-        # 否则重新生成
-
-    return all_data
-
-
-def write_custom_json(data, filename):
-    def format_step(step):
-        inputs = json.dumps(step["inputs"], ensure_ascii=False)
-        return f'{{"id": {step["id"]}, "function": "{step["function"]}", "inputs": {inputs}}}'
-
-    with open(filename, "w", encoding="utf-8") as f:
-        f.write("[\n")
-        for i, item in enumerate(data):
-            f.write("  {\n")
-            f.write(f'    "index": {item["index"]},\n')
-            f.write('    "instruction": "",\n')
-            f.write('    "steps": [\n')
-            step_lines = [f"      {format_step(step)}" for step in item["steps"]]
-            f.write(",\n".join(step_lines))
-            f.write("\n    ]\n")
-            f.write("  }" + (",\n" if i < len(data) - 1 else "\n"))
-        f.write("]\n")
-
-# 运行
-if __name__ == "__main__":
-    samples = generate_localization_samples(100)
-    write_custom_json(samples, "localization_samples.json")
-    print("✅ Saved to localization_samples.json with all steps contributing.")