feat: add AI research chatbot with confirmed business tools

backend/app/ai/provider.py

@@ -0,0 +1,117 @@
+"""Provider creation and synthetic capability checks, with no business access."""
+
+from contextlib import asynccontextmanager
+
+import httpx
+from openai import AsyncOpenAI
+from pydantic_ai import Agent, AgentRunResultEvent
+from pydantic_ai.messages import PartDeltaEvent, PartStartEvent, TextPart, TextPartDelta
+from pydantic_ai.models.openai import OpenAIChatModel, OpenAIResponsesModel
+from pydantic_ai.profiles.openai import OpenAIModelProfile
+from pydantic_ai.providers.openai import OpenAIProvider
+from pydantic_ai.usage import UsageLimits
+
+from ..security import cipher
+
+
+@asynccontextmanager
+async def model_connection(config, settings, transport=None):
+    """Connect only to the administrator's saved endpoint; never follow key-bearing redirects."""
+    key = cipher(settings).decrypt(config.api_key_encrypted.encode()).decode()
+    async with httpx.AsyncClient(
+        transport=transport, follow_redirects=False, trust_env=False, timeout=settings.ai_timeout
+    ) as http:
+        client = AsyncOpenAI(base_url=config.base_url, api_key=key, http_client=http, max_retries=0)
+        provider = OpenAIProvider(openai_client=client)
+        cls = OpenAIChatModel if config.protocol == "chat_completions" else OpenAIResponsesModel
+        # Schema validation belongs to our backend even when a compatible gateway lacks strict mode.
+        model = cls(
+            config.model,
+            provider=provider,
+            profile=OpenAIModelProfile(openai_supports_strict_tool_definition=False),
+        )
+        yield model
+
+
+def public_error(exc):
+    """Never return provider response bodies, URLs, keys, or SDK exception strings."""
+    code = getattr(exc, "status_code", None)
+    if code in (401, 403):
+        return "模型服务拒绝访问，请检查 API Key 和模型权限"
+    if code == 404:
+        return "模型或接口不存在，请检查 Base URL、模型标识及接口协议"
+    if code == 429:
+        return "模型服务限流或额度不足，请稍后重试"
+    if isinstance(exc, (TimeoutError, httpx.TimeoutException)):
+        return "模型服务响应超时，请重试或检查服务状态"
+    return "模型服务调用失败，请检查连接和接口兼容性"
+
+
+def ensure_complete(model, result):
+    """A closed socket without a provider terminal frame is an interrupted stream."""
+    from pydantic_ai.messages import ModelResponse
+
+    if isinstance(model, (OpenAIChatModel, OpenAIResponsesModel)):
+        responses = [m for m in result.new_messages() if isinstance(m, ModelResponse)]
+        if not responses or any(m.finish_reason is None for m in responses):
+            raise ValueError("Provider stream did not include a completion marker")
+
+
+async def test_capabilities(model):
+    """Require actual stream text plus a test tool call followed by its exact output."""
+    from uuid import uuid4
+
+    result = {}
+    try:
+        streamed = False
+        text = ""
+        async with Agent(model, tool_retries=0, output_retries=0).run_stream_events(
+            "Reply with READY.", model_settings={"max_tokens": 256}, usage_limits=UsageLimits(request_limit=1)
+        ) as stream:
+            async for event in stream:
+                if isinstance(event, AgentRunResultEvent):
+                    ensure_complete(model, event.result)
+                if isinstance(event, PartStartEvent) and isinstance(event.part, TextPart):
+                    streamed = True
+                    text += event.part.content
+                elif isinstance(event, PartDeltaEvent) and isinstance(event.delta, TextPartDelta):
+                    streamed = True
+                    text += event.delta.content_delta
+        result["answer"] = {
+            "ok": bool(text.strip()),
+            "message": "收到回答" if text.strip() else "没有收到文本回答",
+        }
+        result["stream"] = {
+            "ok": streamed and bool(text.strip()),
+            "message": "收到流式文本" if streamed else "没有收到流式文本",
+        }
+    except Exception as exc:
+        result["answer"] = result["stream"] = {"ok": False, "message": public_error(exc)}
+    secret = uuid4().hex
+    called = False
+
+    async def capability_probe() -> str:
+        """Read a random test marker. Call this tool and repeat its returned marker exactly."""
+        nonlocal called
+        called = True
+        return secret
+
+    try:
+        final = None
+        async with Agent(model, tools=[capability_probe], tool_retries=0, output_retries=0).run_stream_events(
+            "Call capability_probe, then reply with the exact marker it returned. Do not guess.",
+            model_settings={"max_tokens": 256},
+            usage_limits=UsageLimits(request_limit=2, tool_calls_limit=1),
+        ) as stream:
+            async for event in stream:
+                if isinstance(event, AgentRunResultEvent):
+                    ensure_complete(model, event.result)
+                    final = event.result.output
+        ok = called and isinstance(final, str) and secret in final
+        result["tools"] = {
+            "ok": ok,
+            "message": "工具调用与结果回传成功" if ok else "工具调用或结果回传未通过",
+        }
+    except Exception as exc:
+        result["tools"] = {"ok": False, "message": public_error(exc)}
+    return result