Merge 4569b73547 into 96096ea0ff

backend/app/services/oasis_profile_generator.py

@@ -527,16 +527,39 @@ class OasisProfileGenerator:
         
         for attempt in range(max_attempts):
             try:
-                response = self.client.chat.completions.create(
+                kwargs = {
-                    model=self.model_name,
+                    "model": self.model_name,
-                    messages=[
+                    "messages": [
                         {"role": "system", "content": self._get_system_prompt(is_individual)},
                         {"role": "user", "content": prompt}
                     ],
-                    response_format={"type": "json_object"},
+                    "response_format": {"type": "json_object"},
-                    temperature=0.7 - (attempt * 0.1)  # 每次重试降低温度
+                    # 部分模型不支持自定义温度，后续会自动降级重试
-                    # 不设置max_tokens，让LLM自由发挥
+                    "temperature": 0.7 - (attempt * 0.1)
-                )
+                }
+
+                response = None
+                for _ in range(3):
+                    try:
+                        response = self.client.chat.completions.create(**kwargs)
+                        break
+                    except Exception as e:
+                        err_text = str(e).lower()
+
+                        if "unsupported parameter" in err_text and "max_tokens" in err_text and "max_tokens" in kwargs:
+                            kwargs.pop("max_tokens", None)
+                            continue
+
+                        if "temperature" in err_text and (
+                            "unsupported value" in err_text or "default (1) value" in err_text
+                        ) and "temperature" in kwargs:
+                            kwargs.pop("temperature", None)
+                            continue
+
+                        raise
+
+                if response is None:
+                    raise RuntimeError("OpenAI chat completion failed after compatibility retries")
                 
                 content = response.choices[0].message.content
                 

backend/app/services/simulation_config_generator.py

@@ -440,16 +440,39 @@ class SimulationConfigGenerator:
         
         for attempt in range(max_attempts):
             try:
-                response = self.client.chat.completions.create(
+                kwargs = {
-                    model=self.model_name,
+                    "model": self.model_name,
-                    messages=[
+                    "messages": [
                         {"role": "system", "content": system_prompt},
                         {"role": "user", "content": prompt}
                     ],
-                    response_format={"type": "json_object"},
+                    "response_format": {"type": "json_object"},
-                    temperature=0.7 - (attempt * 0.1)  # 每次重试降低温度
+                    # 部分模型不支持自定义温度，后续会自动降级重试
-                    # 不设置max_tokens，让LLM自由发挥
+                    "temperature": 0.7 - (attempt * 0.1)
-                )
+                }
+
+                response = None
+                for _ in range(3):
+                    try:
+                        response = self.client.chat.completions.create(**kwargs)
+                        break
+                    except Exception as e:
+                        err_text = str(e).lower()
+
+                        if "unsupported parameter" in err_text and "max_tokens" in err_text and "max_tokens" in kwargs:
+                            kwargs.pop("max_tokens", None)
+                            continue
+
+                        if "temperature" in err_text and (
+                            "unsupported value" in err_text or "default (1) value" in err_text
+                        ) and "temperature" in kwargs:
+                            kwargs.pop("temperature", None)
+                            continue
+
+                        raise
+
+                if response is None:
+                    raise RuntimeError("OpenAI chat completion failed after compatibility retries")
                 
                 content = response.choices[0].message.content
                 finish_reason = response.choices[0].finish_reason

backend/app/utils/llm_client.py

@@ -1,18 +1,47 @@
 """
 LLM客户端封装
-统一使用OpenAI格式调用
+支持OpenAI和Anthropic格式的API调用
 """
 
 import json
 import re
+from urllib.parse import urlparse
 from typing import Optional, Dict, Any, List
 from openai import OpenAI
 
 from ..config import Config
 
+# 尝试导入Anthropic SDK，如果不可用则设为None
+try:
+    from anthropic import Anthropic
+except ImportError:
+    Anthropic = None
+
+try:
+    from anthropic import AnthropicFoundry
+except ImportError:
+    AnthropicFoundry = None
+
+
+def _foundry_resource_from_endpoint(endpoint: str) -> str:
+    """从 Foundry endpoint 提取 resource 名称。"""
+    if not endpoint:
+        raise ValueError("LLM_BASE_URL is empty")
+    if "://" not in endpoint:
+        return endpoint.strip()
+
+    host = urlparse(endpoint).netloc
+    m = re.match(r"([^.]+)\.services\.ai\.azure\.com$", host)
+    if not m:
+        raise ValueError(
+            f"Could not parse Foundry resource from endpoint: {endpoint!r}. "
+            "Expected https://<resource>.services.ai.azure.com/anthropic/"
+        )
+    return m.group(1)
+
 
 class LLMClient:
-    """LLM客户端"""
+    """LLM客户端 - 支持OpenAI和Anthropic格式"""
     
     def __init__(
         self,
@@ -27,10 +56,60 @@ class LLMClient:
         if not self.api_key:
             raise ValueError("LLM_API_KEY 未配置")
         
-        self.client = OpenAI(
+        # 检测是否是Anthropic格式的端点
-            api_key=self.api_key,
+        self.is_anthropic = "anthropic" in self.base_url.lower()
-            base_url=self.base_url
+        
-        )
+        if self.is_anthropic:
+            # 使用Anthropic SDK
+            if Anthropic is None:
+                raise ImportError("Anthropic SDK未安装。请运行: pip install anthropic")
+            is_foundry_endpoint = "services.ai.azure.com" in self.base_url.lower()
+            if is_foundry_endpoint and AnthropicFoundry is not None:
+                resource = _foundry_resource_from_endpoint(self.base_url)
+                self.client = AnthropicFoundry(
+                    api_key=self.api_key,
+                    resource=resource,
+                )
+            else:
+                self.client = Anthropic(
+                    api_key=self.api_key,
+                    base_url=self.base_url
+                )
+            self.client_type = "anthropic"
+        else:
+            # 使用OpenAI SDK
+            self.client = OpenAI(
+                api_key=self.api_key,
+                base_url=self.base_url
+            )
+            self.client_type = "openai"
+
+    @staticmethod
+    def _convert_messages_for_anthropic(messages: List[Dict[str, str]]) -> Dict[str, Any]:
+        """将 OpenAI 风格消息转换为 Anthropic Messages API 所需格式。"""
+        system_parts: List[str] = []
+        anthropic_messages: List[Dict[str, str]] = []
+
+        for msg in messages:
+            role = msg.get("role", "")
+            content = msg.get("content", "")
+            if role == "system":
+                if content:
+                    system_parts.append(content)
+                continue
+
+            if role not in {"user", "assistant"}:
+                role = "user"
+
+            anthropic_messages.append({"role": role, "content": content})
+
+        if not anthropic_messages:
+            anthropic_messages = [{"role": "user", "content": ""}]
+
+        result: Dict[str, Any] = {"messages": anthropic_messages}
+        if system_parts:
+            result["system"] = "\n\n".join(system_parts)
+        return result
     
     def chat(
         self,
@@ -51,18 +130,65 @@ class LLMClient:
         Returns:
             模型响应文本
         """
-        kwargs = {
+        if self.client_type == "anthropic":
-            "model": self.model,
+            # 使用Anthropic SDK（system 需单独传递，messages 仅支持 user/assistant）
-            "messages": messages,
+            converted = self._convert_messages_for_anthropic(messages)
-            "temperature": temperature,
+            create_kwargs = {
-            "max_tokens": max_tokens,
+                "model": self.model,
-        }
+                "messages": converted["messages"],
+                "system": converted.get("system"),
+                "max_tokens": max_tokens,
+                "temperature": temperature,
+            }
+            try:
+                response = self.client.messages.create(**create_kwargs)
+            except Exception as e:
+                # 某些新模型会拒绝 temperature 参数（报错: temperature is deprecated）
+                if "temperature" in str(e).lower() and "deprecated" in str(e).lower():
+                    create_kwargs.pop("temperature", None)
+                    response = self.client.messages.create(**create_kwargs)
+                else:
+                    raise
+            content = response.content[0].text
+        else:
+            # 使用OpenAI SDK
+            kwargs = {
+                "model": self.model,
+                "messages": messages,
+                "temperature": temperature,
+                "max_tokens": max_tokens,
+            }
+            
+            if response_format:
+                kwargs["response_format"] = response_format
+
+            response = None
+            for _ in range(3):
+                try:
+                    response = self.client.chat.completions.create(**kwargs)
+                    break
+                except Exception as e:
+                    err_text = str(e).lower()
+
+                    # 某些模型（如部分 GPT-5 系列）不支持 max_tokens，仅支持 max_completion_tokens
+                    if "unsupported parameter" in err_text and "max_tokens" in err_text and "max_tokens" in kwargs:
+                        kwargs.pop("max_tokens", None)
+                        kwargs["max_completion_tokens"] = max_tokens
+                        continue
+
+                    # 某些模型仅支持默认 temperature（通常是 1）
+                    if "temperature" in err_text and (
+                        "unsupported value" in err_text or "default (1) value" in err_text
+                    ) and "temperature" in kwargs:
+                        kwargs.pop("temperature", None)
+                        continue
+
+                    raise
+
+            if response is None:
+                raise RuntimeError("OpenAI chat completion failed after compatibility retries")
+            content = response.choices[0].message.content
         
-        if response_format:
-            kwargs["response_format"] = response_format
-        
-        response = self.client.chat.completions.create(**kwargs)
-        content = response.choices[0].message.content
         # 部分模型（如MiniMax M2.5）会在content中包含<think>思考内容，需要移除
         content = re.sub(r'<think>[\s\S]*?</think>', '', content).strip()
         return content
@@ -84,14 +210,34 @@ class LLMClient:
         Returns:
             解析后的JSON对象
         """
-        response = self.chat(
+        if self.client_type == "anthropic":
-            messages=messages,
+            modified_messages = [dict(m) for m in messages]
-            temperature=temperature,
+            json_instruction = "IMPORTANT: You must respond with valid JSON only, no other text."
-            max_tokens=max_tokens,
+            system_index = next((i for i, m in enumerate(modified_messages) if m.get("role") == "system"), None)
-            response_format={"type": "json_object"}
+            if system_index is None:
-        )
+                modified_messages.insert(0, {"role": "system", "content": json_instruction})
+            else:
+                modified_messages[system_index]["content"] = (
+                    f"{modified_messages[system_index].get('content', '')}\n\n{json_instruction}"
+                )
+
+            response_text = self.chat(
+                messages=modified_messages,
+                temperature=temperature,
+                max_tokens=max_tokens,
+            )
+        else:
+            # OpenAI格式：使用response_format
+            response = self.chat(
+                messages=messages,
+                temperature=temperature,
+                max_tokens=max_tokens,
+                response_format={"type": "json_object"}
+            )
+            response_text = response
+        
         # 清理markdown代码块标记
-        cleaned_response = response.strip()
+        cleaned_response = response_text.strip()
         cleaned_response = re.sub(r'^```(?:json)?\s*\n?', '', cleaned_response, flags=re.IGNORECASE)
         cleaned_response = re.sub(r'\n?```\s*$', '', cleaned_response)
         cleaned_response = cleaned_response.strip()

backend/pyproject.toml

@@ -15,6 +15,7 @@ dependencies = [
     
     # LLM 相关
     "openai>=1.0.0",
+    "anthropic>=0.71.0",
     
     # Zep Cloud
     "zep-cloud==3.13.0",

backend/requirements.txt

@@ -12,6 +12,8 @@ flask-cors>=6.0.0
 # ============= LLM 相关 =============
 # OpenAI SDK（统一使用 OpenAI 格式调用 LLM）
 openai>=1.0.0
+# Anthropic SDK（支持 Azure Foundry Anthropic 端点）
+anthropic>=0.71.0
 
 # ============= Zep Cloud =============
 zep-cloud==3.13.0

backend/uv.lock

@@ -24,6 +24,25 @@ wheels = [
     { url = "https://files.pythonhosted.org/packages/78/b6/6307fbef88d9b5ee7421e68d78a9f162e0da4900bc5f5793f6d3d0e34fb8/annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53", size = 13643, upload-time = "2024-05-20T21:33:24.1Z" },
 ]
 
+[[package]]
+name = "anthropic"
+version = "0.109.2"
+source = { registry = "https://pypi.org/simple" }
+dependencies = [
+    { name = "anyio" },
+    { name = "distro" },
+    { name = "docstring-parser" },
+    { name = "httpx" },
+    { name = "jiter" },
+    { name = "pydantic" },
+    { name = "sniffio" },
+    { name = "typing-extensions" },
+]
+sdist = { url = "https://files.pythonhosted.org/packages/1b/b7/9a8e2f79011e89dd6eeb599c27332aed765dac9d6fbee3a55e68e4e3ec25/anthropic-0.109.2.tar.gz", hash = "sha256:d37db299597c7bc124b49b767ff135f1e6456b64af2b2fad4b63b2a1df333cf0", size = 927559, upload-time = "2026-06-15T17:30:25.024Z" }
+wheels = [
+    { url = "https://files.pythonhosted.org/packages/d1/f2/bee5de8a2699fc8a3cce34d61c7a2626a2c310ddde7ea5611327eb0ddbe9/anthropic-0.109.2-py3-none-any.whl", hash = "sha256:e0fb4ca5df0ed983248c9c6c3242adc81d9cfddb8725902da53698554117abac", size = 923800, upload-time = "2026-06-15T17:30:23.124Z" },
+]
+
 [[package]]
 name = "anyio"
 version = "4.12.0"
@@ -988,6 +1007,7 @@ name = "mirofish-backend"
 version = "0.1.0"
 source = { editable = "." }
 dependencies = [
+    { name = "anthropic" },
     { name = "camel-ai" },
     { name = "camel-oasis" },
     { name = "chardet" },
@@ -1016,6 +1036,7 @@ dev = [
 
 [package.metadata]
 requires-dist = [
+    { name = "anthropic", specifier = ">=0.71.0" },
     { name = "camel-ai", specifier = "==0.2.78" },
     { name = "camel-oasis", specifier = "==0.2.5" },
     { name = "chardet", specifier = ">=5.0.0" },

frontend/package-lock.json

@@ -1435,7 +1435,6 @@
       "resolved": "https://registry.npmjs.org/d3-selection/-/d3-selection-3.0.0.tgz",
       "integrity": "sha512-fmTRWbNMmsmWq6xJV8D19U/gw/bwrHfNXxrIN+HfZgnzqTHp9jOmKMhsTUjXOJnZOdZY9Q28y4yebKzqDKlxlQ==",
       "license": "ISC",
-      "peer": true,
       "engines": {
         "node": ">=12"
       }
@@ -1913,7 +1912,6 @@
       "integrity": "sha512-QP88BAKvMam/3NxH6vj2o21R6MjxZUAd6nlwAS/pnGvN9IVLocLHxGYIzFhg6fUQ+5th6P4dv4eW9jX3DSIj7A==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "engines": {
         "node": ">=12"
       },
@@ -2053,7 +2051,6 @@
       "integrity": "sha512-ITcnkFeR3+fI8P1wMgItjGrR10170d8auB4EpMLPqmx6uxElH3a/hHGQabSHKdqd4FXWO1nFIp9rRn7JQ34ACQ==",
       "dev": true,
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "esbuild": "^0.25.0",
         "fdir": "^6.5.0",
@@ -2128,7 +2125,6 @@
       "resolved": "https://registry.npmjs.org/vue/-/vue-3.5.25.tgz",
       "integrity": "sha512-YLVdgv2K13WJ6n+kD5owehKtEXwdwXuj2TTyJMsO7pSeKw2bfRNZGjhB7YzrpbMYj5b5QsUebHpOqR3R3ziy/g==",
       "license": "MIT",
-      "peer": true,
       "dependencies": {
         "@vue/compiler-dom": "3.5.25",
         "@vue/compiler-sfc": "3.5.25",