refactor: centralize llm provider transport

app/ARCHITECTURE.md

@@ -38,8 +38,9 @@ background scheduler
   adapters. Root `database.py` remains the legacy schema/composition anchor and combines the
   feature repository mixins; do not add feature queries to it.
 - `backend/jobs/` owns job definitions, locks, retries, idempotency, and persisted run state.
-- `backend/llm/` owns model selection, membership/quota checks, fallback, streaming rules,
+- `backend/llm/` owns model selection, membership/quota checks, fallback, provider transport,
-  and call audit. Feature agents only prepare context and provider payloads.
+  streaming rules, and call audit. Feature agents only prepare messages and interpret
+  feature-specific results.
 - `frontend/shared/` is the only browser API/state/Shell/component boundary.
 - `frontend/pages/` owns page-local behavior. The original runtime was split mechanically;
   source markers and preservation tests prove that the pieces reassemble to the audited

app/backend/features/heaven/agent.py

@@ -1,11 +1,10 @@
 from __future__ import annotations
 
 import json
-import time
-import urllib.error
-import urllib.request
 from typing import Any
 
+from backend.llm import transport as llm_transport
+
 
 class HeavenAgentError(RuntimeError):
     pass
@@ -24,45 +23,33 @@ def interpret_heaven(
     if not api_key or not model:
         raise HeavenAgentError("LLM API Key 或模型尚未配置。")
     system_prompt = _system_prompt(mode)
-    payload = json.dumps(
+    messages = [
+        {"role": "system", "content": system_prompt},
         {
-            "model": model,
+            "role": "user",
-            "messages": [
+            "content": json.dumps(context, ensure_ascii=False, separators=(",", ":")),
-                {"role": "system", "content": system_prompt},
-                {
-                    "role": "user",
-                    "content": json.dumps(context, ensure_ascii=False, separators=(",", ":")),
-                },
-            ],
-            "stream": False,
         },
-        ensure_ascii=False,
+    ]
-    ).encode("utf-8")
-    request = urllib.request.Request(
-        f"{base_url.rstrip('/')}/chat/completions",
-        data=payload,
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "User-Agent": "XiaobaiReviewWeb/0.7",
-        },
-        method="POST",
-    )
-    started = time.perf_counter()
     try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:
+        result = llm_transport.chat_completion(
-            result = json.loads(response.read().decode("utf-8"))
+            api_key=api_key,
-        answer = str(result["choices"][0]["message"]["content"]).strip()
+            base_url=base_url,
+            model=model,
+            messages=messages,
+            timeout=timeout,
+            user_agent="XiaobaiReviewWeb/0.7",
+        )
+        answer = str(result.content).strip()
         if not answer:
             raise KeyError("empty response")
-    except urllib.error.HTTPError as exc:
+    except llm_transport.OpenAIHTTPError as exc:
-        raise HeavenAgentError(_http_error_message(exc)) from exc
+        raise HeavenAgentError(exc.describe("问天模型调用失败")) from exc
-    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+    except (llm_transport.OpenAITransportError, KeyError) as exc:
         raise HeavenAgentError(f"问天模型调用失败：{exc}") from exc
     return {
         "answer": answer,
         "model": model,
-        "latency_ms": round((time.perf_counter() - started) * 1000),
+        "latency_ms": result.latency_ms,
     }
 
 
@@ -99,20 +86,3 @@ def _system_prompt(mode: str) -> str:
 全文控制在180至350个中文字符。只写一句卦意；一小段动爻与之卦；最后三句极短的问心句。
 不要重述六条爻辞，不猜用户未说出口的问题，不以吉凶二字替代思考，不给出股票涨跌预测。语气安静、克制，越短越有余味。
 """.strip()
-
-
-def _http_error_message(exc: urllib.error.HTTPError) -> str:
-    detail = ""
-    try:
-        payload = json.loads(exc.read().decode("utf-8", errors="replace"))
-        error = payload.get("error")
-        if isinstance(error, dict):
-            detail = str(error.get("message") or error.get("code") or "")
-        elif error:
-            detail = str(error)
-        elif payload.get("message"):
-            detail = str(payload["message"])
-    except (json.JSONDecodeError, OSError):
-        detail = ""
-    suffix = f"：{detail[:300]}" if detail else ""
-    return f"问天模型调用失败（HTTP {exc.code}）{suffix}"

app/backend/features/mentor/agent.py

@@ -3,14 +3,12 @@ from __future__ import annotations
 import json
 import re
 import time
-import urllib.error
-import urllib.request
 from collections.abc import Iterator
 from dataclasses import dataclass
 from pathlib import Path
 from typing import Any
 
-from llm_stream import OpenAIStreamAccumulator
+from backend.llm import transport as llm_transport
 
 
 class MentorAgentError(RuntimeError):
@@ -195,50 +193,20 @@ def stream_with_mentor(
     messages = [{"role": "system", "content": system_prompt}]
     messages.extend(history[-10:])
     messages.append({"role": "user", "content": question})
-    payload = json.dumps(
-        {"model": model, "messages": messages, "stream": True},
-        ensure_ascii=False,
-    ).encode("utf-8")
-    request = urllib.request.Request(
-        f"{base_url.rstrip('/')}/chat/completions",
-        data=payload,
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "User-Agent": "XiaobaiReviewWeb/0.6",
-            "Accept": "text/event-stream",
-        },
-        method="POST",
-    )
     try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:
+        yield from llm_transport.stream_chat_completion(
-            yielded = False
+            api_key=api_key,
-            accumulator = OpenAIStreamAccumulator()
+            base_url=base_url,
-            for raw_line in response:
+            model=model,
-                line = raw_line.decode("utf-8", errors="replace").strip()
+            messages=messages,
-                if not line or line.startswith(":"):
+            timeout=timeout,
-                    continue
+            user_agent="XiaobaiReviewWeb/0.6",
-                if line.startswith("data:"):
+        )
-                    line = line[5:].strip()
+    except llm_transport.OpenAIEmptyResponseError as exc:
-                if line == "[DONE]":
+        raise MentorAgentError("问师模型未返回有效内容。") from exc
-                    break
+    except llm_transport.OpenAIHTTPError as exc:
-                try:
+        raise MentorAgentError(exc.describe("问师模型调用失败")) from exc
-                    result = json.loads(line)
+    except llm_transport.OpenAITransportError as exc:
-                except json.JSONDecodeError:
-                    continue
-                choices = result.get("choices") or []
-                if not choices:
-                    continue
-                choice = choices[0] or {}
-                content = accumulator.feed(choice)
-                if content:
-                    yielded = True
-                    yield str(content)
-            if not yielded:
-                raise MentorAgentError("问师模型未返回有效内容。")
-    except urllib.error.HTTPError as exc:
-        raise MentorAgentError(_http_error_message(exc)) from exc
-    except (urllib.error.URLError, TimeoutError, OSError) as exc:
         raise MentorAgentError(f"问师模型调用失败：{exc}") from exc
 
 
@@ -298,20 +266,3 @@ def _parse_frontmatter(content: str) -> dict[str, str]:
 def _first_sentence(text: str) -> str:
     compact = " ".join(line.strip() for line in text.splitlines() if line.strip())
     return re.split(r"[。；]", compact, maxsplit=1)[0].strip()
-
-
-def _http_error_message(exc: urllib.error.HTTPError) -> str:
-    detail = ""
-    try:
-        payload = json.loads(exc.read().decode("utf-8", errors="replace"))
-        error = payload.get("error")
-        if isinstance(error, dict):
-            detail = str(error.get("message") or error.get("code") or "")
-        elif error:
-            detail = str(error)
-        elif payload.get("message"):
-            detail = str(payload["message"])
-    except (json.JSONDecodeError, OSError):
-        detail = ""
-    suffix = f"：{detail[:300]}" if detail else ""
-    return f"问师模型调用失败（HTTP {exc.code}）{suffix}"

app/backend/features/review/agent.py

@@ -1,12 +1,10 @@
 from __future__ import annotations
 
 import json
-import urllib.error
-import urllib.request
 from collections.abc import Iterator
 from typing import Any
 
-from llm_stream import OpenAIStreamAccumulator
+from backend.llm import transport as llm_transport
 
 
 class ReviewAssistantError(RuntimeError):
@@ -27,48 +25,20 @@ def stream_review_assistant(
     messages = [{"role": "system", "content": _system_prompt(context)}]
     messages.extend(history[-12:])
     messages.append({"role": "user", "content": question})
-    request = urllib.request.Request(
-        f"{base_url.rstrip('/')}/chat/completions",
-        data=json.dumps(
-            {"model": model, "messages": messages, "stream": True}, ensure_ascii=False
-        ).encode("utf-8"),
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "User-Agent": "XiaobaiReviewWeb/1.0",
-            "Accept": "text/event-stream",
-        },
-        method="POST",
-    )
     try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:
+        yield from llm_transport.stream_chat_completion(
-            yielded = False
+            api_key=api_key,
-            accumulator = OpenAIStreamAccumulator()
+            base_url=base_url,
-            for raw_line in response:
+            model=model,
-                line = raw_line.decode("utf-8", errors="replace").strip()
+            messages=messages,
-                if not line or line.startswith(":"):
+            timeout=timeout,
-                    continue
+            user_agent="XiaobaiReviewWeb/1.0",
-                if line.startswith("data:"):
+        )
-                    line = line[5:].strip()
+    except llm_transport.OpenAIEmptyResponseError as exc:
-                if line == "[DONE]":
+        raise ReviewAssistantError("智能解读未返回有效内容。") from exc
-                    break
+    except llm_transport.OpenAIHTTPError as exc:
-                try:
-                    payload = json.loads(line)
-                except json.JSONDecodeError:
-                    continue
-                choices = payload.get("choices") or []
-                if not choices:
-                    continue
-                choice = choices[0] or {}
-                content = accumulator.feed(choice)
-                if content:
-                    yielded = True
-                    yield str(content)
-            if not yielded:
-                raise ReviewAssistantError("智能解读未返回有效内容。")
-    except urllib.error.HTTPError as exc:
         raise ReviewAssistantError(f"智能解读服务暂不可用（{exc.code}）。") from exc
-    except (urllib.error.URLError, TimeoutError, OSError) as exc:
+    except llm_transport.OpenAITransportError as exc:
         raise ReviewAssistantError("智能解读连接中断，请稍后重试。") from exc
 
 

app/backend/features/screener/compiler.py

@@ -1,11 +1,9 @@
 from __future__ import annotations
 
 import json
-import time
-import urllib.error
-import urllib.request
 from typing import Any
 
+from backend.llm import transport as llm_transport
 from screener import FACTOR_FIELDS, REGIMES
 
 
@@ -21,39 +19,25 @@ def test_llm_connection(
 ) -> dict[str, Any]:
     if not api_key or not model:
         raise LLMCompilerError("API Key 或模型未配置。")
-    endpoint = f"{base_url.rstrip('/')}/chat/completions"
-    payload = json.dumps(
-        {
-            "model": model,
-            "messages": [{"role": "user", "content": "只回复 OK"}],
-            "stream": False,
-        },
-        ensure_ascii=False,
-    ).encode("utf-8")
-    request = urllib.request.Request(
-        endpoint,
-        data=payload,
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "User-Agent": "XiaobaiReviewWeb/0.5",
-        },
-        method="POST",
-    )
-    started = time.perf_counter()
     try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:
+        result = llm_transport.chat_completion(
-            result = json.loads(response.read().decode("utf-8"))
+            api_key=api_key,
-        reply = str(result["choices"][0]["message"]["content"]).strip()
+            base_url=base_url,
-    except urllib.error.HTTPError as exc:
+            model=model,
-        raise LLMCompilerError(_http_error_message(exc)) from exc
+            messages=[{"role": "user", "content": "只回复 OK"}],
-    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+            timeout=timeout,
+            user_agent="XiaobaiReviewWeb/0.5",
+        )
+        reply = str(result.content).strip()
+    except llm_transport.OpenAIHTTPError as exc:
+        raise LLMCompilerError(exc.describe("模型连接测试失败")) from exc
+    except llm_transport.OpenAITransportError as exc:
         raise LLMCompilerError(f"模型连接测试失败：{exc}") from exc
     return {
         "ok": True,
         "model": model,
         "reply": reply[:100],
-        "latency_ms": round((time.perf_counter() - started) * 1000),
+        "latency_ms": result.latency_ms,
     }
 
 
@@ -67,7 +51,6 @@ def compile_strategy_with_llm(
 ) -> dict[str, Any]:
     if not api_key or not model:
         raise LLMCompilerError("尚未配置 LLM API Key 或模型。")
-    endpoint = f"{base_url.rstrip('/')}/chat/completions"
     schema = {
         "name": "策略名称",
         "description": "策略说明",
@@ -90,57 +73,28 @@ def compile_strategy_with_llm(
         "退潮和冰点策略必须提高门槛并允许结果为空。"
         f"严格遵循以下结构：{json.dumps(schema, ensure_ascii=False)}"
     )
-    payload = json.dumps(
+    try:
-        {
+        result = llm_transport.chat_completion(
-            "model": model,
+            api_key=api_key,
-            "messages": [
+            base_url=base_url,
+            model=model,
+            messages=[
                 {"role": "system", "content": system_prompt},
                 {"role": "user", "content": prompt[:3000]},
             ],
-            "stream": False,
+            timeout=timeout,
-        },
+            user_agent="XiaobaiReviewWeb/0.4",
-        ensure_ascii=False,
+        )
-    ).encode("utf-8")
+        content = result.content.strip()
-    request = urllib.request.Request(
-        endpoint,
-        data=payload,
-        headers={
-            "Content-Type": "application/json",
-            "Authorization": f"Bearer {api_key}",
-            "User-Agent": "XiaobaiReviewWeb/0.4",
-        },
-        method="POST",
-    )
-    try:
-        with urllib.request.urlopen(request, timeout=timeout) as response:
-            result = json.loads(response.read().decode("utf-8"))
-        content = result["choices"][0]["message"]["content"].strip()
         if content.startswith("```"):
             content = content.strip("`")
             if content.startswith("json"):
                 content = content[4:].strip()
         compiled = json.loads(content)
-    except urllib.error.HTTPError as exc:
+    except llm_transport.OpenAIHTTPError as exc:
-        raise LLMCompilerError(_http_error_message(exc).replace("模型连接测试", "LLM 策略编译")) from exc
+        raise LLMCompilerError(exc.describe("LLM 策略编译失败")) from exc
-    except (urllib.error.URLError, TimeoutError, json.JSONDecodeError, KeyError, IndexError) as exc:
+    except (llm_transport.OpenAITransportError, json.JSONDecodeError) as exc:
         raise LLMCompilerError(f"LLM 策略编译失败：{exc}") from exc
     compiled["compiler"] = "llm"
     compiled["model"] = model
     return compiled
-
-
-def _http_error_message(exc: urllib.error.HTTPError) -> str:
-    detail = ""
-    try:
-        payload = json.loads(exc.read().decode("utf-8", errors="replace"))
-        error = payload.get("error")
-        if isinstance(error, dict):
-            detail = str(error.get("message") or error.get("code") or "")
-        elif error:
-            detail = str(error)
-        elif payload.get("message"):
-            detail = str(payload["message"])
-    except (json.JSONDecodeError, OSError):
-        detail = ""
-    suffix = f"：{detail[:300]}" if detail else ""
-    return f"模型连接测试失败（HTTP {exc.code}）{suffix}"

app/backend/llm/transport.py

@@ -0,0 +1,148 @@
+from __future__ import annotations
+
+import json
+import time
+import urllib.error
+import urllib.request
+from collections.abc import Iterator
+from dataclasses import dataclass
+from typing import Any
+
+from .stream import OpenAIStreamAccumulator
+
+
+class OpenAITransportError(RuntimeError):
+    pass
+
+
+class OpenAIHTTPError(OpenAITransportError):
+    def __init__(self, code: int, detail: str = "") -> None:
+        super().__init__(f"HTTP {code}")
+        self.code = code
+        self.detail = detail
+
+    def describe(self, label: str) -> str:
+        suffix = f"：{self.detail[:300]}" if self.detail else ""
+        return f"{label}（HTTP {self.code}）{suffix}"
+
+
+class OpenAIEmptyResponseError(OpenAITransportError):
+    pass
+
+
+@dataclass(frozen=True)
+class OpenAIChatCompletion:
+    content: Any
+    latency_ms: int
+
+
+def chat_completion(
+    *,
+    api_key: str,
+    base_url: str,
+    model: str,
+    messages: list[dict[str, Any]],
+    timeout: int,
+    user_agent: str,
+) -> OpenAIChatCompletion:
+    request = _request(api_key, base_url, model, messages, user_agent, stream=False)
+    started = time.perf_counter()
+    try:
+        with urllib.request.urlopen(request, timeout=timeout) as response:
+            result = json.loads(response.read().decode("utf-8"))
+        content = result["choices"][0]["message"]["content"]
+    except urllib.error.HTTPError as exc:
+        raise OpenAIHTTPError(exc.code, _http_error_detail(exc)) from exc
+    except (
+        urllib.error.URLError,
+        TimeoutError,
+        json.JSONDecodeError,
+        KeyError,
+        IndexError,
+    ) as exc:
+        raise OpenAITransportError(str(exc)) from exc
+    return OpenAIChatCompletion(
+        content=content,
+        latency_ms=round((time.perf_counter() - started) * 1000),
+    )
+
+
+def stream_chat_completion(
+    *,
+    api_key: str,
+    base_url: str,
+    model: str,
+    messages: list[dict[str, Any]],
+    timeout: int,
+    user_agent: str,
+) -> Iterator[str]:
+    request = _request(api_key, base_url, model, messages, user_agent, stream=True)
+    yielded = False
+    try:
+        with urllib.request.urlopen(request, timeout=timeout) as response:
+            accumulator = OpenAIStreamAccumulator()
+            for raw_line in response:
+                line = raw_line.decode("utf-8", errors="replace").strip()
+                if not line or line.startswith(":"):
+                    continue
+                if line.startswith("data:"):
+                    line = line[5:].strip()
+                if line == "[DONE]":
+                    break
+                try:
+                    result = json.loads(line)
+                except json.JSONDecodeError:
+                    continue
+                choices = result.get("choices") or []
+                if not choices:
+                    continue
+                content = accumulator.feed(choices[0] or {})
+                if content:
+                    yielded = True
+                    yield str(content)
+    except urllib.error.HTTPError as exc:
+        raise OpenAIHTTPError(exc.code, _http_error_detail(exc)) from exc
+    except (urllib.error.URLError, TimeoutError, OSError) as exc:
+        raise OpenAITransportError(str(exc)) from exc
+    if not yielded:
+        raise OpenAIEmptyResponseError("empty response")
+
+
+def _request(
+    api_key: str,
+    base_url: str,
+    model: str,
+    messages: list[dict[str, Any]],
+    user_agent: str,
+    *,
+    stream: bool,
+) -> urllib.request.Request:
+    headers = {
+        "Content-Type": "application/json",
+        "Authorization": f"Bearer {api_key}",
+        "User-Agent": user_agent,
+    }
+    if stream:
+        headers["Accept"] = "text/event-stream"
+    return urllib.request.Request(
+        f"{base_url.rstrip('/')}/chat/completions",
+        data=json.dumps(
+            {"model": model, "messages": messages, "stream": stream},
+            ensure_ascii=False,
+        ).encode("utf-8"),
+        headers=headers,
+        method="POST",
+    )
+
+
+def _http_error_detail(exc: urllib.error.HTTPError) -> str:
+    try:
+        payload = json.loads(exc.read().decode("utf-8", errors="replace"))
+        error = payload.get("error")
+        if isinstance(error, dict):
+            return str(error.get("message") or error.get("code") or "")
+        if error:
+            return str(error)
+        return str(payload.get("message") or "")
+    except (json.JSONDecodeError, OSError):
+        return ""

app/config/architecture-inventory.json

@@ -1,6 +1,6 @@
 {
   "schema_version": 1,
-  "captured_from": "app modular preservation candidate",
+  "captured_from": "app accepted modular runtime",
   "runtime": {
     "http_server": "http.server.ThreadingHTTPServer",
     "application_processes": 1,
@@ -242,6 +242,16 @@
       "path": "backend/features/screener/compiler.py"
     }
   ],
+  "llm_transport": [
+    {
+      "function": "chat_completion",
+      "path": "backend/llm/transport.py"
+    },
+    {
+      "function": "stream_chat_completion",
+      "path": "backend/llm/transport.py"
+    }
+  ],
   "css_layers": [
     "/shared/tokens.css?v=20260729-1",
     "/styles/styles.css",

app/tests/test_llm_transport.py

@@ -0,0 +1,187 @@
+from __future__ import annotations
+
+import io
+import json
+import unittest
+import urllib.error
+from pathlib import Path
+from unittest.mock import patch
+
+from assistant_agent import ReviewAssistantError, stream_review_assistant
+from backend.llm import transport
+from heaven_agent import HeavenAgentError, interpret_heaven
+from llm_strategy import LLMCompilerError, test_llm_connection
+from mentor_agent import MentorAgentError, MentorSkill, stream_with_mentor
+
+
+ROOT = Path(__file__).resolve().parents[1]
+
+
+class FakeResponse:
+    def __init__(self, *, payload: bytes = b"", lines: list[bytes] | None = None) -> None:
+        self.payload = payload
+        self.lines = lines or []
+
+    def __enter__(self):
+        return self
+
+    def __exit__(self, exc_type, exc_value, traceback):
+        return False
+
+    def read(self) -> bytes:
+        return self.payload
+
+    def __iter__(self):
+        return iter(self.lines)
+
+
+class OpenAITransportTests(unittest.TestCase):
+    def test_chat_completion_builds_one_openai_compatible_request(self) -> None:
+        captured = {}
+        response = FakeResponse(
+            payload=json.dumps(
+                {"choices": [{"message": {"content": "OK"}}]}
+            ).encode("utf-8")
+        )
+
+        def open_request(request, timeout):
+            captured["url"] = request.full_url
+            captured["headers"] = request.headers
+            captured["payload"] = json.loads(request.data.decode("utf-8"))
+            captured["timeout"] = timeout
+            return response
+
+        with patch("backend.llm.transport.urllib.request.urlopen", side_effect=open_request):
+            result = transport.chat_completion(
+                api_key="secret",
+                base_url="https://example.test/v1/",
+                model="model",
+                messages=[{"role": "user", "content": "ping"}],
+                timeout=17,
+                user_agent="XiaobaiReviewWeb/test",
+            )
+
+        self.assertEqual(result.content, "OK")
+        self.assertGreaterEqual(result.latency_ms, 0)
+        self.assertEqual(captured["url"], "https://example.test/v1/chat/completions")
+        self.assertEqual(captured["payload"]["stream"], False)
+        self.assertEqual(captured["headers"]["Authorization"], "Bearer secret")
+        self.assertEqual(captured["timeout"], 17)
+
+    def test_stream_completion_parses_deltas_and_ignores_final_snapshot(self) -> None:
+        response = FakeResponse(
+            lines=[
+                b'data: {"choices":[{"delta":{"content":"first"}}]}\n',
+                b'data: {"choices":[{"delta":{"content":" second"}}]}\n',
+                b'data: {"choices":[{"message":{"content":"first second"}}]}\n',
+                b"data: [DONE]\n",
+            ]
+        )
+        with patch("backend.llm.transport.urllib.request.urlopen", return_value=response):
+            chunks = list(
+                transport.stream_chat_completion(
+                    api_key="secret",
+                    base_url="https://example.test/v1",
+                    model="model",
+                    messages=[],
+                    timeout=17,
+                    user_agent="XiaobaiReviewWeb/test",
+                )
+            )
+        self.assertEqual(chunks, ["first", " second"])
+
+    def test_empty_stream_has_a_stable_transport_error(self) -> None:
+        response = FakeResponse(lines=[b"data: [DONE]\n"])
+        with patch("backend.llm.transport.urllib.request.urlopen", return_value=response):
+            with self.assertRaises(transport.OpenAIEmptyResponseError):
+                list(
+                    transport.stream_chat_completion(
+                        api_key="secret",
+                        base_url="https://example.test/v1",
+                        model="model",
+                        messages=[],
+                        timeout=17,
+                        user_agent="XiaobaiReviewWeb/test",
+                    )
+                )
+
+    def test_http_error_keeps_code_and_sanitized_provider_detail(self) -> None:
+        error = urllib.error.HTTPError(
+            "https://example.test/v1/chat/completions",
+            429,
+            "rate limited",
+            {},
+            io.BytesIO(b'{"error":{"message":"capacity"}}'),
+        )
+        self.addCleanup(error.close)
+        with patch("backend.llm.transport.urllib.request.urlopen", side_effect=error):
+            with self.assertRaises(transport.OpenAIHTTPError) as caught:
+                transport.chat_completion(
+                    api_key="secret",
+                    base_url="https://example.test/v1",
+                    model="model",
+                    messages=[],
+                    timeout=17,
+                    user_agent="XiaobaiReviewWeb/test",
+                )
+        self.assertEqual(caught.exception.code, 429)
+        self.assertEqual(
+            caught.exception.describe("模型调用失败"),
+            "模型调用失败（HTTP 429）：capacity",
+        )
+
+    def test_feature_agents_have_no_direct_provider_transport(self) -> None:
+        paths = (
+            "backend/features/mentor/agent.py",
+            "backend/features/heaven/agent.py",
+            "backend/features/review/agent.py",
+            "backend/features/screener/compiler.py",
+        )
+        for relative in paths:
+            source = (ROOT / relative).read_text(encoding="utf-8")
+            with self.subTest(path=relative):
+                self.assertNotIn("urllib.request", source)
+                self.assertNotIn("/chat/completions", source)
+                self.assertIn("llm_transport.", source)
+
+
+class FeatureErrorMappingTests(unittest.TestCase):
+    def test_feature_specific_http_messages_are_preserved(self) -> None:
+        error = transport.OpenAIHTTPError(429, "capacity")
+        skill = MentorSkill(
+            skill_id="test",
+            name="测试老师",
+            description="",
+            tagline="",
+            focus=(),
+            content="",
+            path=Path("SKILL.md"),
+        )
+        with patch(
+            "mentor_agent.llm_transport.stream_chat_completion", side_effect=error
+        ):
+            with self.assertRaisesRegex(
+                MentorAgentError, "问师模型调用失败（HTTP 429）：capacity"
+            ):
+                list(stream_with_mentor(skill, {}, "问题", [], "key", "https://x", "m"))
+        with patch("heaven_agent.llm_transport.chat_completion", side_effect=error):
+            with self.assertRaisesRegex(
+                HeavenAgentError, "问天模型调用失败（HTTP 429）：capacity"
+            ):
+                interpret_heaven("heart", {}, "key", "https://x", "m")
+        with patch(
+            "assistant_agent.llm_transport.stream_chat_completion", side_effect=error
+        ):
+            with self.assertRaisesRegex(
+                ReviewAssistantError, "智能解读服务暂不可用（429）"
+            ):
+                list(stream_review_assistant({}, "问题", [], "key", "https://x", "m"))
+        with patch("llm_strategy.llm_transport.chat_completion", side_effect=error):
+            with self.assertRaisesRegex(
+                LLMCompilerError, "模型连接测试失败（HTTP 429）：capacity"
+            ):
+                test_llm_connection("key", "https://x", "m")
+
+
+if __name__ == "__main__":
+    unittest.main()

app/tests/test_mentor_stream.py

@@ -44,7 +44,7 @@ class MentorStreamTests(unittest.TestCase):
             captured["accept"] = request.headers.get("Accept")
             return FakeStreamResponse(self.lines)
 
-        with patch("mentor_agent.urllib.request.urlopen", side_effect=open_request):
+        with patch("backend.llm.transport.urllib.request.urlopen", side_effect=open_request):
             chunks = list(
                 stream_with_mentor(
                     self.skill, {"data_trade_date": "20260723"}, "怎么看？", [],
@@ -58,7 +58,7 @@ class MentorStreamTests(unittest.TestCase):
 
     def test_non_streaming_compatibility_wrapper_collects_chunks(self):
         with patch(
-            "mentor_agent.urllib.request.urlopen",
+            "backend.llm.transport.urllib.request.urlopen",
             return_value=FakeStreamResponse(self.lines),
         ):
             result = chat_with_mentor(
@@ -74,7 +74,7 @@ class MentorStreamTests(unittest.TestCase):
             b"data: [DONE]\n",
         ]
         with patch(
-            "mentor_agent.urllib.request.urlopen",
+            "backend.llm.transport.urllib.request.urlopen",
             return_value=FakeStreamResponse(lines),
         ):
             chunks = list(
@@ -92,7 +92,7 @@ class MentorStreamTests(unittest.TestCase):
             b"data: [DONE]\n",
         ]
         with patch(
-            "mentor_agent.urllib.request.urlopen",
+            "backend.llm.transport.urllib.request.urlopen",
             return_value=FakeStreamResponse(lines),
         ):
             chunks = list(

app/tests/test_preservation_slice_heaven.py

@@ -91,11 +91,12 @@ class HeavenSliceSourceEquivalenceTests(unittest.TestCase):
         for name in sorted(expected - (adapted or set())):
             self.assertEqual(migrated[name], original[name], name)
 
-    def test_heaven_agent_is_an_exact_file(self) -> None:
+    def test_heaven_agent_uses_shared_transport(self) -> None:
-        self.assertEqual(
+        source = (
-            sha256(ORIGINAL_ROOT / "heaven_agent.py"),
+            APP_ROOT / "backend" / "features" / "heaven" / "agent.py"
-            sha256(APP_ROOT / "backend" / "features" / "heaven" / "agent.py"),
+        ).read_text(encoding="utf-8")
-        )
+        self.assertIn("llm_transport.chat_completion", source)
+        self.assertNotIn("urllib.request", source)
 
     def test_heaven_engine_definitions_are_exact_original_ast(self) -> None:
         self.assertEqual(

app/tests/test_preservation_slice_mentor_llm.py

@@ -105,11 +105,12 @@ class MentorLLMSliceSourceEquivalenceTests(unittest.TestCase):
         for name in sorted(expected):
             self.assertEqual(migrated[name], original[name], name)
 
-    def test_mentor_agent_and_stream_accumulator_are_exact_files(self) -> None:
+    def test_mentor_agent_uses_shared_transport_and_stream_accumulator_is_exact(self) -> None:
-        self.assertEqual(
+        mentor_source = (APP_ROOT / "backend" / "features" / "mentor" / "agent.py").read_text(
-            sha256(ORIGINAL_ROOT / "mentor_agent.py"),
+            encoding="utf-8"
-            sha256(APP_ROOT / "backend" / "features" / "mentor" / "agent.py"),
         )
+        self.assertIn("llm_transport.stream_chat_completion", mentor_source)
+        self.assertNotIn("urllib.request", mentor_source)
         self.assertEqual(
             sha256(ORIGINAL_ROOT / "llm_stream.py"),
             sha256(APP_ROOT / "backend" / "llm" / "stream.py"),

app/tests/test_preservation_slice_review_alerts.py

@@ -109,11 +109,12 @@ class ReviewAlertsSliceSourceEquivalenceTests(unittest.TestCase):
         for name in sorted(expected):
             self.assertEqual(migrated[name], original[name], name)
 
-    def test_review_assistant_agent_is_an_exact_file(self) -> None:
+    def test_review_assistant_agent_uses_shared_transport(self) -> None:
-        self.assertEqual(
+        source = (
-            sha256(ORIGINAL_ROOT / "assistant_agent.py"),
+            APP_ROOT / "backend" / "features" / "review" / "agent.py"
-            sha256(APP_ROOT / "backend" / "features" / "review" / "agent.py"),
+        ).read_text(encoding="utf-8")
-        )
+        self.assertIn("llm_transport.stream_chat_completion", source)
+        self.assertNotIn("urllib.request", source)
 
     def test_review_assistant_compatibility_module_is_canonical(self) -> None:
         self.assertIs(assistant_agent, canonical_agent)

app/tests/test_preservation_slice_screener.py

@@ -170,12 +170,16 @@ class ScreenerSliceSourceEquivalenceTests(unittest.TestCase):
             ),
         )
 
-    def test_library_and_compiler_files_are_exact_copies(self) -> None:
+    def test_library_is_exact_and_compiler_uses_shared_transport(self) -> None:
-        for original, migrated in (
+        self.assertEqual(
-            ("advanced_strategies.py", "backend/features/screener/strategies.py"),
+            sha256(ORIGINAL_ROOT / "advanced_strategies.py"),
-            ("llm_strategy.py", "backend/features/screener/compiler.py"),
+            sha256(APP_ROOT / "backend/features/screener/strategies.py"),
-        ):
+        )
-            self.assertEqual(sha256(ORIGINAL_ROOT / original), sha256(APP_ROOT / migrated))
+        compiler_source = (
+            APP_ROOT / "backend/features/screener/compiler.py"
+        ).read_text(encoding="utf-8")
+        self.assertEqual(compiler_source.count("llm_transport.chat_completion"), 2)
+        self.assertNotIn("urllib.request", compiler_source)
 
     def test_compatibility_modules_export_the_canonical_objects(self) -> None:
         self.assertIs(screener, engine)

app/tests/test_review_assistant.py

@@ -31,7 +31,7 @@ class ReviewAssistantStreamingTests(unittest.TestCase):
                 b'data: [DONE]\n',
             ]
         )
-        with patch("assistant_agent.urllib.request.urlopen", return_value=response):
+        with patch("backend.llm.transport.urllib.request.urlopen", return_value=response):
             chunks = list(
                 stream_review_assistant({}, "question", [], "key", "https://example.test/v1", "model")
             )
@@ -39,7 +39,7 @@ class ReviewAssistantStreamingTests(unittest.TestCase):
 
     def test_empty_stream_is_rejected(self):
         response = StreamingResponse([b"data: [DONE]\n"])
-        with patch("assistant_agent.urllib.request.urlopen", return_value=response):
+        with patch("backend.llm.transport.urllib.request.urlopen", return_value=response):
             with self.assertRaises(ReviewAssistantError):
                 list(
                     stream_review_assistant({}, "question", [], "key", "https://example.test/v1", "model")
@@ -54,7 +54,7 @@ class ReviewAssistantStreamingTests(unittest.TestCase):
                 b"data: [DONE]\n",
             ]
         )
-        with patch("assistant_agent.urllib.request.urlopen", return_value=response):
+        with patch("backend.llm.transport.urllib.request.urlopen", return_value=response):
             chunks = list(
                 stream_review_assistant(
                     {}, "question", [], "key", "https://example.test/v1", "model"

app/tools/build_architecture_inventory.py

@@ -127,7 +127,7 @@ def build() -> dict[str, Any]:
     tables = database_inventory(database_sources)
     return {
         "schema_version": 1,
-        "captured_from": "app modular preservation candidate",
+        "captured_from": "app accepted modular runtime",
         "runtime": {
             "http_server": "http.server.ThreadingHTTPServer",
             "application_processes": 1,
@@ -163,6 +163,10 @@ def build() -> dict[str, Any]:
             {"function": "compile_strategy_with_llm", "path": "backend/features/screener/compiler.py"},
             {"function": "test_llm_connection", "path": "backend/features/screener/compiler.py"},
         ],
+        "llm_transport": [
+            {"function": "chat_completion", "path": "backend/llm/transport.py"},
+            {"function": "stream_chat_completion", "path": "backend/llm/transport.py"},
+        ],
         "css_layers": css_layers(html),
         "code_hotspots": code_hotspots(),
     }

docs/governance/code-reduction.md

@@ -0,0 +1,45 @@
+# `app/`代码减法账本
+
+> 基线：`xiaobai-preservation-complete-20260801`  
+> 工作目录：只允许修改`webapp/app/`；原版根目录和冻结的`next/`只读  
+> 目标：删除重复实现和历史补丁，不改变功能、视觉、交互、动画、计算、权限、API或数据行为
+
+## 固定规则
+
+1. 每批只处理一个明确边界，先证明重复或无消费者，再修改。
+2. 新共享实现必须在同一提交删除全部被替代实现；禁止只加一层包装。
+3. 运行代码总量原则上不得增加；测试和证据代码单独统计。
+4. 迁移期源码相等测试不得简单删除。发生已批准的结构重构时，必须替换成行为、错误语义和
+   唯一所有权契约。
+5. 每批通过领域测试、全量候选测试、独立导出测试和受影响的浏览器流程后才建立Git检查点。
+6. CSS最后处理；没有逐页日间、夜间和多视口截图证据，不删除视觉规则。
+
+## 批次记录
+
+| 批次 | 边界 | 基线问题 | 目标 | 状态 |
+|---|---|---|---|---|
+| CR-01 | LLM供应商传输 | 问师、问天、复盘助手和策略编译各自构造HTTP请求、解析响应和读取错误 | 只保留`backend/llm/transport.py`一个网络出口 | 已完成 |
+
+## CR-01验收口径
+
+- 四个功能模块不得包含`urllib.request`或`/chat/completions`。
+- 非流式与流式请求的URL、鉴权、User-Agent、SSE累积和空响应行为保持不变。
+- 各功能原有错误类型和用户可见错误文案保持不变。
+- `LLMGateway`的会员、额度、主辅回退、首字后不中途换模型和审计规则保持不变。
+- 架构清单必须登记唯一传输入口；完整测试和真实主模型最小调用通过。
+
+## CR-01结果
+
+- 四个功能模块的运行代码由572行降至422行；新增唯一传输实现129行，生产代码净减少21行、
+  约1.4 KB。行数不是主要收益，关键是5处`/chat/completions`请求只剩1处。
+- 三套重复HTTP错误正文解析合并为一套；各功能原有错误类型和用户可见文案由专项测试固定。
+- 迁移期4个“Agent文件逐字相等”断言没有直接删除，而是替换为共享传输唯一所有权、提示词模块
+  归属、SSE行为和兼容模块对象契约。
+- 候选311项、纯`app/`导出248项、45项Playwright通过；24个JavaScript文件、架构/API注册表和
+  SQLite完整性检查通过。
+- 使用候选数据库中加密保存的主模型完成真实非流式与流式最小调用，分别成功返回完整响应和
+  4个流式分片。调用未输出密钥或模型正文。
+- 本批不修改页面、CSS、提示词、业务计算、会员额度、模型回退、数据库或部署。
+
+回档基线为`xiaobai-preservation-complete-20260801`；本批检查点为
+`xiaobai-reduction-01-llm-transport-20260801`。