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ai_game/server/app/services/ai.py

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"""
AI服务封装模块
支持多种AI提供商DeepSeek, OpenAI, Claude, 通义千问
"""
from typing import Optional, Dict, Any
import httpx
class AIService:
def __init__(self):
from app.config import get_settings
settings = get_settings()
self.enabled = settings.ai_service_enabled
self.provider = settings.ai_provider
# 根据提供商初始化配置
if self.provider == "deepseek":
self.api_key = settings.deepseek_api_key
self.base_url = settings.deepseek_base_url
self.model = settings.deepseek_model
elif self.provider == "openai":
self.api_key = settings.openai_api_key
self.base_url = settings.openai_base_url
self.model = "gpt-3.5-turbo"
elif self.provider == "claude":
# Claude 需要从环境变量读取
import os
self.api_key = os.getenv("CLAUDE_API_KEY", "")
self.base_url = "https://api.anthropic.com"
self.model = "claude-3-haiku-20240307"
elif self.provider == "qwen":
import os
self.api_key = os.getenv("DASHSCOPE_API_KEY", "")
self.base_url = "https://dashscope.aliyuncs.com/api/v1"
self.model = "qwen-plus"
else:
self.api_key = None
self.base_url = None
self.model = None
async def rewrite_ending(
self,
story_title: str,
story_category: str,
ending_name: str,
ending_content: str,
user_prompt: str
) -> Optional[Dict[str, Any]]:
"""
AI改写结局
:return: {"content": str, "tokens_used": int} None
"""
if not self.enabled or not self.api_key:
return None
# 构建Prompt
system_prompt = """你是一个专业的互动故事创作专家。根据用户的改写指令,重新创作故事结局。
要求
1. 保持原故事的世界观和人物性格
2. 结局要有张力和情感冲击
3. 结局内容字数控制在200-400
4. 为新结局取一个4-8字的新名字体现改写后的剧情走向
5. 输出格式必须是JSON{"ending_name": "新结局名称", "content": "结局内容"}"""
user_prompt_text = f"""故事标题:{story_title}
故事分类{story_category}
原结局名称{ending_name}
原结局内容{ending_content[:500]}
---
用户改写指令{user_prompt}
---
请创作新的结局输出JSON格式"""
try:
if self.provider == "openai":
return await self._call_openai(system_prompt, user_prompt_text)
elif self.provider == "claude":
return await self._call_claude(user_prompt_text)
elif self.provider == "qwen":
return await self._call_qwen(system_prompt, user_prompt_text)
elif self.provider == "deepseek":
return await self._call_deepseek(system_prompt, user_prompt_text)
except Exception as e:
print(f"AI调用失败{e}")
return None
return None
async def _call_openai(self, system_prompt: str, user_prompt: str) -> Optional[Dict]:
"""调用OpenAI API"""
url = f"{self.base_url}/chat/completions"
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
data = {
"model": self.model,
"messages": [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
],
"temperature": 0.8,
"max_tokens": 500
}
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.post(url, headers=headers, json=data)
response.raise_for_status()
result = response.json()
content = result["choices"][0]["message"]["content"]
tokens = result["usage"]["total_tokens"]
return {"content": content.strip(), "tokens_used": tokens}
async def _call_claude(self, prompt: str) -> Optional[Dict]:
"""调用Claude API"""
url = "https://api.anthropic.com/v1/messages"
headers = {
"x-api-key": self.api_key,
"anthropic-version": "2023-06-01",
"content-type": "application/json"
}
data = {
"model": self.model,
"max_tokens": 1024,
"messages": [{"role": "user", "content": prompt}]
}
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.post(url, headers=headers, json=data)
response.raise_for_status()
result = response.json()
content = result["content"][0]["text"]
tokens = result.get("usage", {}).get("output_tokens", 0)
return {"content": content.strip(), "tokens_used": tokens}
async def _call_qwen(self, system_prompt: str, user_prompt: str) -> Optional[Dict]:
"""调用通义千问API"""
url = "https://dashscope.aliyuncs.com/api/v1/services/aigc/text-generation/generation"
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
data = {
"model": self.model,
"input": {
"messages": [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
]
},
"parameters": {
"result_format": "message",
"temperature": 0.8
}
}
async with httpx.AsyncClient(timeout=30.0) as client:
response = await client.post(url, headers=headers, json=data)
response.raise_for_status()
result = response.json()
content = result["output"]["choices"][0]["message"]["content"]
tokens = result.get("usage", {}).get("total_tokens", 0)
return {"content": content.strip(), "tokens_used": tokens}
async def _call_deepseek(self, system_prompt: str, user_prompt: str) -> Optional[Dict]:
"""调用 DeepSeek API"""
url = f"{self.base_url}/chat/completions"
headers = {
"Authorization": f"Bearer {self.api_key}",
"Content-Type": "application/json"
}
data = {
"model": self.model,
"messages": [
{"role": "system", "content": system_prompt},
{"role": "user", "content": user_prompt}
],
"temperature": 0.8,
"max_tokens": 500
}
async with httpx.AsyncClient(timeout=30.0) as client:
try:
response = await client.post(url, headers=headers, json=data)
response.raise_for_status()
result = response.json()
if "choices" in result and len(result["choices"]) > 0:
content = result["choices"][0]["message"]["content"]
tokens = result.get("usage", {}).get("total_tokens", 0)
return {"content": content.strip(), "tokens_used": tokens}
else:
print(f"DeepSeek API 返回异常:{result}")
return None
except httpx.HTTPStatusError as e:
print(f"DeepSeek HTTP 错误:{e.response.status_code} - {e.response.text}")
return None
except Exception as e:
print(f"DeepSeek 调用失败:{e}")
return None
# 单例模式
ai_service = AIService()