AWS Bedrock

import json

# ─── محاكاة Bedrock Runtime ────────────────────────────────
class BedrockRuntime:
    """محاكاة boto3 bedrock-runtime client"""

    MODELS = {
        "anthropic.claude-3-haiku-20240307-v1:0": {
            "name": "Claude 3 Haiku",   "provider": "Anthropic",
            "in_price":  0.00025, "out_price": 0.00125,
        },
        "anthropic.claude-3-sonnet-20240229-v1:0": {
            "name": "Claude 3 Sonnet",  "provider": "Anthropic",
            "in_price":  0.003,   "out_price": 0.015,
        },
        "amazon.titan-text-express-v1": {
            "name": "Titan Text Express", "provider": "Amazon",
            "in_price":  0.0002,  "out_price": 0.0006,
        },
    }

    def list_foundation_models(self) -> list:
        return [
            {"modelId": mid, "modelName": m["name"], "providerName": m["provider"]}
            for mid, m in self.MODELS.items()
        ]

    def invoke_model(self, modelId: str, body: dict) -> dict:
        if modelId not in self.MODELS:
            raise ValueError(f"النموذج {modelId} غير متاح")
        m         = self.MODELS[modelId]
        prompt    = (body.get("messages") or [{"content": ""}])[-1].get("content", "")
        in_tok    = max(10, int(len(prompt.split()) * 1.3))
        out_tok   = 80
        cost      = (in_tok / 1000) * m["in_price"] + (out_tok / 1000) * m["out_price"]
        return {
            "content": [{"text": f"[{m['name']}] ردّي على: {prompt[:50]}..."}],
            "usage":   {"input_tokens": in_tok, "output_tokens": out_tok},
            "cost_usd": round(cost, 7),
        }

# ─── Claude Wrapper ────────────────────────────────────────
class ClaudeOnBedrock:
    def __init__(self, model: str = "anthropic.claude-3-haiku-20240307-v1:0"):
        self._rt         = BedrockRuntime()
        self.model       = model
        self.total_cost  = 0.0
        self.total_calls = 0

    def chat(self, message: str, system: str = "") -> str:
        body = {
            "anthropic_version": "bedrock-2023-05-31",
            "max_tokens": 1024,
            "system":     system,
            "messages":   [{"role": "user", "content": message}],
        }
        resp             = self._rt.invoke_model(self.model, body)
        self.total_cost  += resp["cost_usd"]
        self.total_calls += 1
        cost_str = "$" + f"{resp['cost_usd']:.7f}"
        print(f"  tokens: {resp['usage']['input_tokens']}in + {resp['usage']['output_tokens']}out | cost: {cost_str}")
        return resp["content"][0]["text"]

    def summary(self):
        total_str = "$" + f"{self.total_cost:.6f}"
        print(f"\n📊 ملخص الاستخدام:")
        print(f"   المكالمات       : {self.total_calls}")
        print(f"   إجمالي التكلفة : {total_str}")

# ─── عرض النماذج ───────────────────────────────────────────
runtime = BedrockRuntime()
print("🤖 النماذج المتاحة على AWS Bedrock:")
for m in runtime.list_foundation_models():
    print(f"  [{m['providerName']:<12}] {m['modelName']}")
    print(f"   ID: {m['modelId']}")
    print()

# ─── اختبار Claude 3 Haiku ─────────────────────────────────
print("=" * 55)
print("💬 اختبار Claude 3 Haiku عبر Bedrock:")
print("=" * 55)

claude = ClaudeOnBedrock()

questions = [
    ("ما هو AWS Bedrock؟",                   "أجب بجملتين فقط بالعربية"),
    ("متى أستخدم Haiku بدلاً من Sonnet؟",   "جملة واحدة فقط"),
    ("ما هي مزايا Bedrock على Claude API؟",  ""),
]

for q, sys_prompt in questions:
    print(f"\n❓ {q}")
    answer = claude.chat(q, system=sys_prompt)
    print(f"💡 {answer}")

claude.summary()
print("\n✅ تم اختبار AWS Bedrock بنجاح!")