File size: 7,717 Bytes
d48479e
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
import re

with open("inference.py", "r") as f:
    code = f.read()

# -----------------------------------------------------------------------------
# 1. Dispatch Updates in main()
# -----------------------------------------------------------------------------
main_dispatch = """        if task_id.startswith("timemachine_"):
            score = run_timemachine_episode(task_id)
        elif task_id.startswith("federated_"):
            score = run_federated_episode(task_id)
        elif task_id.startswith("constitution_"):
            score = run_constitution_episode(task_id)
        elif task_id.startswith("execution_"):
            score = run_execution_episode(task_id)
        elif task_id.startswith("lexmind_"):
            score = run_lexmind_episode(task_id)
        elif task_id.startswith("adversarial_"):
            score = run_adversarial_episode(task_id)
        elif task_id.startswith("curriculum_"):
            score = run_curriculum_episode(task_id)
        else:
            score = run_episode(task_id)"""

code = re.sub(
    r'        if task_id\.startswith\("timemachine_"\):.*?else:\n            score = run_episode\(task_id\)',
    main_dispatch,
    code,
    flags=re.DOTALL
)

# -----------------------------------------------------------------------------
# 2. Add New Runners
# -----------------------------------------------------------------------------
new_runners = """
# ── Execution Environment ────────────────────────────────────────────────────
def run_execution_episode(task_id: str) -> float:
    rewards = []
    steps_taken = 0
    score = 0.001
    success = False
    log_start(task=task_id, env=BENCHMARK, model=MODEL_NAME)
    try:
        reset_resp = requests.post(f"{ENV_BASE_URL}/reset?task_id={task_id}", timeout=30)
        reset_resp.raise_for_status()
        obs = reset_resp.json()
        
        system_prompt = \"\"\"You are a contract execution simulator.
Respond with ONLY a JSON object with key scenario_analyses containing an array. Each element must have exactly these keys: scenario_id, crashes as boolean, crash_pair as array of two clause ID strings, crash_description as string. Use exact scenario_id and clause_id values from the observation. No markdown.\"\"\"
        
        user_message = f"=== OBSERVATION ===\\n{json.dumps(obs, indent=2)}\\nAnalyze execution."
        completion = client.chat.completions.create(
            model=MODEL_NAME,
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": user_message},
            ],
            max_tokens=2000, temperature=0.0,
        )
        raw = (completion.choices[0].message.content or "").strip()
        raw = raw.replace("```json", "").replace("```", "").strip()
        try:
            parsed = json.loads(raw)
            analyses = parsed if isinstance(parsed, list) else parsed.get("scenario_analyses", [])
            normalized = []
            for a in analyses:
                if not isinstance(a, dict): continue
                crashes_val = a.get("crashes", a.get("is_crash", a.get("has_crash", a.get("crash", False))))
                pair_val = a.get("crash_pair", a.get("clause_pair", a.get("conflicting_clauses", a.get("crashed_clauses", []))))
                normalized.append({
                    "scenario_id": str(a.get("scenario_id", "")),
                    "crashes": bool(crashes_val),
                    "crash_pair": pair_val,
                    "crash_description": str(a.get("crash_description", ""))
                })
        except Exception:
            normalized = []
            
        action_payload = {"scenario_analyses": normalized}
        steps_taken = 1
        step_resp = requests.post(f"{ENV_BASE_URL}/execution/step?task_id={task_id}", json=action_payload, timeout=30)
        step_resp.raise_for_status()
        step_data = step_resp.json()
        score = max(0.001, min(0.999, float(step_data.get("score", 0.001))))
        success = score > 0.001
        rewards.append(score)
        log_step(1, "submit_analyses", score, True, None)
    except Exception as e:
        steps_taken = max(1, steps_taken)
        rewards.append(0.001)
        log_step(steps_taken, "error", 0.001, True, str(e))
    finally:
        log_end(success, steps_taken, score, rewards)
    return score

# ── LexMind Environment ──────────────────────────────────────────────────────
def run_lexmind_episode(task_id: str) -> float:
    rewards = []
    steps_taken = 0
    score = 0.001
    success = False
    log_start(task=task_id, env=BENCHMARK, model=MODEL_NAME)
    try:
        reset_resp = requests.post(f"{ENV_BASE_URL}/reset?task_id={task_id}", timeout=30)
        reset_resp.raise_for_status()
        obs = reset_resp.json()
        
        system_prompt = \"\"\"You are analyzing a sequence of contract drafting events.
Respond with ONLY a JSON object with key predictions containing an array. Each element must have exactly: event_id, introduces_contradiction as boolean, contradicts_clause_id as string or null, contradiction_type as string or null. Use exact event_id values from the drafting sequence. No markdown.\"\"\"
        
        user_message = f"=== OBSERVATION ===\\n{json.dumps(obs, indent=2)}\\nAnalyze drafting sequence."
        completion = client.chat.completions.create(
            model=MODEL_NAME,
            messages=[
                {"role": "system", "content": system_prompt},
                {"role": "user", "content": user_message},
            ],
            max_tokens=2000, temperature=0.0,
        )
        raw = (completion.choices[0].message.content or "").strip()
        raw = raw.replace("```json", "").replace("```", "").strip()
        try:
            parsed = json.loads(raw)
            preds = parsed if isinstance(parsed, list) else parsed.get("predictions", [])
            normalized = []
            for p in preds:
                if not isinstance(p, dict): continue
                intro_val = p.get("introduces_contradiction", p.get("has_contradiction", p.get("is_contradiction", p.get("contradicts", False))))
                normalized.append({
                    "event_id": str(p.get("event_id", "")),
                    "introduces_contradiction": bool(intro_val),
                    "contradicts_clause_id": p.get("contradicts_clause_id"),
                    "contradiction_type": p.get("contradiction_type")
                })
        except Exception:
            normalized = []
            
        action_payload = {"predictions": normalized}
        steps_taken = 1
        step_resp = requests.post(f"{ENV_BASE_URL}/lexmind/step?task_id={task_id}", json=action_payload, timeout=30)
        step_resp.raise_for_status()
        step_data = step_resp.json()
        score = max(0.001, min(0.999, float(step_data.get("score", 0.001))))
        success = score > 0.001
        rewards.append(score)
        log_step(1, "submit_predictions", score, True, None)
    except Exception as e:
        steps_taken = max(1, steps_taken)
        rewards.append(0.001)
        log_step(steps_taken, "error", 0.001, True, str(e))
    finally:
        log_end(success, steps_taken, score, rewards)
    return score
"""

# Insert new runners before run_adversarial_episode
code = code.replace("def run_adversarial_episode(task_id: str) -> float:", new_runners + "\ndef run_adversarial_episode(task_id: str) -> float:")

with open("inference.py", "w") as f:
    f.write(code)