From 598e53ca0681a5bfdabd754db3abde96551ef438 Mon Sep 17 00:00:00 2001
From: arsam <me@asabbagh.com>
Date: Fri, 18 Sep 2026 23:14:45 +0330
Subject: [PATCH] Import source: Shayan1/Prod/nash/translate

Import the existing local project snapshot. This commit organizes existing files; it does not represent newly developed functionality.
---
 Shayan1/Prod/nash/translate.py | 57 ++++++++++++++++++++++++++++++++++
 1 file changed, 57 insertions(+)
 create mode 100644 Shayan1/Prod/nash/translate.py

diff --git a/Shayan1/Prod/nash/translate.py b/Shayan1/Prod/nash/translate.py
new file mode 100644
index 0000000..8127b39
--- /dev/null
+++ b/Shayan1/Prod/nash/translate.py
@@ -0,0 +1,57 @@
+"""Optional AI-assisted input: turn a plain-English scenario description into a game
+JSON file matching nash.game.Game's schema. Never called by solver.py or
+simulation.py -- only reachable via the CLI's --describe flag, and its output is
+always shown to the user before anything runs on it.
+"""
+
+import json
+
+from nash.game import Game
+
+SCHEMA_INSTRUCTIONS = """Translate the following plain-English description of a \
+strategic situation into a normal-form game, expressed as a JSON object with \
+EXACTLY this schema:
+
+{
+  "players": ["<player 1 name>", "<player 2 name>", ...],
+  "strategies": [["<player 1 strategy A>", "<player 1 strategy B>", ...], ...],
+  "payoffs": [<player 1's payoff tensor>, <player 2's payoff tensor>, ...]
+}
+
+Each player's payoff tensor is nested lists with one dimension per player, sized \
+to that player's number of strategies. For 2 players with strategies of length m \
+and n, payoffs[i] is an m by n grid where payoffs[i][a][b] is player i's payoff \
+when player 1 picks strategy index a and player 2 picks strategy index b.
+
+Respond with ONLY the JSON object -- no explanation, no markdown code fences.
+"""
+
+
+def describe_to_json(description, model="claude-sonnet-5"):
+    import anthropic
+
+    client = anthropic.Anthropic()
+    prompt = f"{SCHEMA_INSTRUCTIONS}\nDescription: {description}\n"
+    response = client.messages.create(
+        model=model,
+        max_tokens=2000,
+        messages=[{"role": "user", "content": prompt}],
+    )
+    text = response.content[0].text
+    data = _extract_json(text)
+
+    Game(data["players"], data["strategies"], data["payoffs"])
+    return data
+
+
+def _extract_json(text):
+    start = text.find("{")
+    end = text.rfind("}")
+    if start == -1 or end == -1:
+        raise ValueError(f"No JSON object found in model response:\n{text}")
+    return json.loads(text[start : end + 1])
+
+
+def save_json(data, path):
+    with open(path, "w") as f:
+        json.dump(data, f, indent=2)