{"repo": "cangyeone/sage", "files": {"web_app/routes/llm.py": {"5ef458cab746280eb97d2dfb27bd545c578d5400": {"t": 1785746376.4386458, "n": 24876, "h": "5fc0a19131931741", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _mask_key(value):\n    if not value:\n        return ''\n    value = str(value)\n    return '****' + value[-4:] if len(value) > 4 else '****'\n\n\ndef _public_search_config(raw_search):\n    from config_manager import SEARCH_PROVIDER_DEFAULTS\n    raw_search = raw_search or {}\n    providers = raw_search.get('providers') or {}\n    out = {}\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        cfg = providers.get(key) or {}\n        out[key] = {\n            'display': meta.get('display', key),\n            'description': meta.get('description', ''),\n            'requires_key': bool(meta.get('requires_key')),\n            'enabled': bool(cfg.get('enabled', meta.get('enabled', False))),\n            'api_key_masked': _mask_key(cfg.get('api_key', '')),\n            'api_base': cfg.get('api_base', ''),\n        }\n    return {\n        'providers': out,\n        'default_sources': raw_search.get('default_sources') or ['openalex', 'semantic_scholar'],\n    }\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'search': _public_search_config(cfg_mgr.get_search_config()),\n        'app_paths': cfg_mgr.get_app_paths(),\n        'coding_agent': cfg_mgr.get_coding_agent_config(),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/config/search', methods=['GET', 'POST'])\ndef search_config():\n    \"\"\"Get/update web/literature search provider configuration.\"\"\"\n    from config_manager import get_config_manager, SEARCH_PROVIDER_DEFAULTS\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    search = project_cfg.setdefault('search', {})\n    providers = search.setdefault('providers', {})\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        providers.setdefault(key, {'enabled': meta['enabled'], 'api_key': '', 'api_base': ''})\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n    data = request.get_json(silent=True) or {}\n    incoming = data.get('providers') or {}\n    for key, item in incoming.items():\n        if key not in SEARCH_PROVIDER_DEFAULTS or not isinstance(item, dict):\n            continue\n        cur = providers.setdefault(key, {'enabled': False, 'api_key': '', 'api_base': ''})\n        if 'enabled' in item:\n            cur['enabled'] = bool(item.get('enabled'))\n        if item.get('api_key'):\n            cur['api_key'] = str(item.get('api_key')).strip()\n        if 'api_base' in item:\n            cur['api_base'] = str(item.get('api_base') or '').strip().rstrip('/')\n    if isinstance(data.get('default_sources'), list):\n        search['default_sources'] = [\n            s for s in data['default_sources']\n            if s in SEARCH_PROVIDER_DEFAULTS\n        ] or ['openalex', 'semantic_scholar']\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n\n@bp.route('/api/config/app_paths', methods=['GET', 'POST'])\ndef app_paths_config():\n    \"\"\"Get/update shared Chat and Parameter Optimizer path defaults.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    paths = project_cfg.setdefault('app_paths', mgr.get_app_paths())\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'app_paths': paths})\n\n    data = request.get_json(silent=True) or {}\n    if 'chat_workspace_enabled' in data:\n        paths['chat_workspace_enabled'] = bool(data.get('chat_workspace_enabled'))\n    if 'chat_workspace_paths' in data:\n        raw = data.get('chat_workspace_paths')\n        if isinstance(raw, str):\n            vals = [x.strip() for x in raw.replace(';', '\\n').replace(',', '\\n').splitlines() if x.strip()]\n        elif isinstance(raw, list):\n            vals = [str(x).strip() for x in raw if str(x).strip()]\n        else:\n            vals = []\n        paths['chat_workspace_paths'] = vals\n    for key in ('geo_workspace_root', 'geo_literature_root', 'geo_output_dir'):\n        if key in data:\n            paths[key] = str(data.get(key) or '').strip()\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'app_paths': paths})\n\n\n@bp.route('/api/config/coding_agent', methods=['GET', 'POST'])\ndef coding_agent_config():\n    \"\"\"Get/update the project-scoped coding backend configuration.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    cfg = project_cfg.setdefault('coding_agent', mgr.get_coding_agent_config())\n\n    if request.method == 'GET':\n        status = {}\n        try:\n            from seismo_code.external_coding_agent import external_agent_status\n            status = external_agent_status(cfg)\n        except Exception as exc:\n            status = {'available': False, 'error': str(exc)}\n        return jsonify({'ok': True, 'coding_agent': cfg, 'status': status})\n\n    data = request.get_json(silent=True) or {}\n    backend = str(data.get('backend') or cfg.get('backend') or 'builtin').strip()\n    if backend not in {'builtin', 'aider', 'openhands'}:\n        return jsonify({'ok': False, 'error': f'Invalid coding agent backend: {backend}'}), 400\n    cfg['backend'] = backend\n    # Backend selection is the source of truth. Keep `enabled` only for older clients.\n    cfg['enabled'] = backend != 'builtin'\n    for key in ('command', 'model', 'extra_args'):\n        if key in data:\n            cfg[key] = str(data.get(key) or '').strip()\n    if 'timeout_s' in data:\n        try:\n            cfg['timeout_s'] = max(30, min(7200, int(data.get('timeout_s') or 900)))\n        except Exception:\n            cfg['timeout_s'] = 900\n    if 'auto_approve' in data:\n        cfg['auto_approve'] = bool(data.get('auto_approve'))\n    if 'use_current_llm_env' in data:\n        cfg['use_current_llm_env'] = bool(data.get('use_current_llm_env'))\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'coding_agent': cfg})\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models with a single short HTTP request.\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    recommended = config.get_recommended_models().get('ollama', [])\n    ollama_cfg = config.config.get('ollama', {}) if isinstance(config.config.get('ollama', {}), dict) else {}\n    llm_cfg = config.config.get('llm', {}) if isinstance(config.config.get('llm', {}), dict) else {}\n    saved_llm_base = llm_cfg.get('api_base') if llm_cfg.get('provider') == 'ollama' else ''\n    api_base = (\n        request.args.get('api_base')\n        or ollama_cfg.get('api_base')\n        or saved_llm_base\n        or 'http://localhost:11434'\n    ).strip().rstrip('/')\n    if not api_base.startswith(('http://localhost', 'http://127.0.0.1', 'http://0.0.0.0', 'http://[::1]')):\n        api_base = 'http://localhost:11434'\n\n    models = []\n    available = False\n    error = ''\n    try:\n        req = _ur.Request(f'{api_base}/api/tags')\n        with _ur.urlopen(req, timeout=2.5) as resp:\n            available = resp.status == 200\n            if available:\n                data = json.loads(resp.read().decode('utf-8'))\n                models = _parse_model_list(data)\n    except Exception as exc:\n        error = str(exc)\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': available,\n        'api_base': api_base,\n        'error': error,\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "3dda843da5bdf26f88e70417b3041523a2477544": {"t": 1785763088.8084035, "n": 24876, "h": "5fc0a19131931741", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _mask_key(value):\n    if not value:\n        return ''\n    value = str(value)\n    return '****' + value[-4:] if len(value) > 4 else '****'\n\n\ndef _public_search_config(raw_search):\n    from config_manager import SEARCH_PROVIDER_DEFAULTS\n    raw_search = raw_search or {}\n    providers = raw_search.get('providers') or {}\n    out = {}\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        cfg = providers.get(key) or {}\n        out[key] = {\n            'display': meta.get('display', key),\n            'description': meta.get('description', ''),\n            'requires_key': bool(meta.get('requires_key')),\n            'enabled': bool(cfg.get('enabled', meta.get('enabled', False))),\n            'api_key_masked': _mask_key(cfg.get('api_key', '')),\n            'api_base': cfg.get('api_base', ''),\n        }\n    return {\n        'providers': out,\n        'default_sources': raw_search.get('default_sources') or ['openalex', 'semantic_scholar'],\n    }\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'search': _public_search_config(cfg_mgr.get_search_config()),\n        'app_paths': cfg_mgr.get_app_paths(),\n        'coding_agent': cfg_mgr.get_coding_agent_config(),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/config/search', methods=['GET', 'POST'])\ndef search_config():\n    \"\"\"Get/update web/literature search provider configuration.\"\"\"\n    from config_manager import get_config_manager, SEARCH_PROVIDER_DEFAULTS\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    search = project_cfg.setdefault('search', {})\n    providers = search.setdefault('providers', {})\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        providers.setdefault(key, {'enabled': meta['enabled'], 'api_key': '', 'api_base': ''})\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n    data = request.get_json(silent=True) or {}\n    incoming = data.get('providers') or {}\n    for key, item in incoming.items():\n        if key not in SEARCH_PROVIDER_DEFAULTS or not isinstance(item, dict):\n            continue\n        cur = providers.setdefault(key, {'enabled': False, 'api_key': '', 'api_base': ''})\n        if 'enabled' in item:\n            cur['enabled'] = bool(item.get('enabled'))\n        if item.get('api_key'):\n            cur['api_key'] = str(item.get('api_key')).strip()\n        if 'api_base' in item:\n            cur['api_base'] = str(item.get('api_base') or '').strip().rstrip('/')\n    if isinstance(data.get('default_sources'), list):\n        search['default_sources'] = [\n            s for s in data['default_sources']\n            if s in SEARCH_PROVIDER_DEFAULTS\n        ] or ['openalex', 'semantic_scholar']\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n\n@bp.route('/api/config/app_paths', methods=['GET', 'POST'])\ndef app_paths_config():\n    \"\"\"Get/update shared Chat and Parameter Optimizer path defaults.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    paths = project_cfg.setdefault('app_paths', mgr.get_app_paths())\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'app_paths': paths})\n\n    data = request.get_json(silent=True) or {}\n    if 'chat_workspace_enabled' in data:\n        paths['chat_workspace_enabled'] = bool(data.get('chat_workspace_enabled'))\n    if 'chat_workspace_paths' in data:\n        raw = data.get('chat_workspace_paths')\n        if isinstance(raw, str):\n            vals = [x.strip() for x in raw.replace(';', '\\n').replace(',', '\\n').splitlines() if x.strip()]\n        elif isinstance(raw, list):\n            vals = [str(x).strip() for x in raw if str(x).strip()]\n        else:\n            vals = []\n        paths['chat_workspace_paths'] = vals\n    for key in ('geo_workspace_root', 'geo_literature_root', 'geo_output_dir'):\n        if key in data:\n            paths[key] = str(data.get(key) or '').strip()\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'app_paths': paths})\n\n\n@bp.route('/api/config/coding_agent', methods=['GET', 'POST'])\ndef coding_agent_config():\n    \"\"\"Get/update the project-scoped coding backend configuration.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    cfg = project_cfg.setdefault('coding_agent', mgr.get_coding_agent_config())\n\n    if request.method == 'GET':\n        status = {}\n        try:\n            from seismo_code.external_coding_agent import external_agent_status\n            status = external_agent_status(cfg)\n        except Exception as exc:\n            status = {'available': False, 'error': str(exc)}\n        return jsonify({'ok': True, 'coding_agent': cfg, 'status': status})\n\n    data = request.get_json(silent=True) or {}\n    backend = str(data.get('backend') or cfg.get('backend') or 'builtin').strip()\n    if backend not in {'builtin', 'aider', 'openhands'}:\n        return jsonify({'ok': False, 'error': f'Invalid coding agent backend: {backend}'}), 400\n    cfg['backend'] = backend\n    # Backend selection is the source of truth. Keep `enabled` only for older clients.\n    cfg['enabled'] = backend != 'builtin'\n    for key in ('command', 'model', 'extra_args'):\n        if key in data:\n            cfg[key] = str(data.get(key) or '').strip()\n    if 'timeout_s' in data:\n        try:\n            cfg['timeout_s'] = max(30, min(7200, int(data.get('timeout_s') or 900)))\n        except Exception:\n            cfg['timeout_s'] = 900\n    if 'auto_approve' in data:\n        cfg['auto_approve'] = bool(data.get('auto_approve'))\n    if 'use_current_llm_env' in data:\n        cfg['use_current_llm_env'] = bool(data.get('use_current_llm_env'))\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'coding_agent': cfg})\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models with a single short HTTP request.\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    recommended = config.get_recommended_models().get('ollama', [])\n    ollama_cfg = config.config.get('ollama', {}) if isinstance(config.config.get('ollama', {}), dict) else {}\n    llm_cfg = config.config.get('llm', {}) if isinstance(config.config.get('llm', {}), dict) else {}\n    saved_llm_base = llm_cfg.get('api_base') if llm_cfg.get('provider') == 'ollama' else ''\n    api_base = (\n        request.args.get('api_base')\n        or ollama_cfg.get('api_base')\n        or saved_llm_base\n        or 'http://localhost:11434'\n    ).strip().rstrip('/')\n    if not api_base.startswith(('http://localhost', 'http://127.0.0.1', 'http://0.0.0.0', 'http://[::1]')):\n        api_base = 'http://localhost:11434'\n\n    models = []\n    available = False\n    error = ''\n    try:\n        req = _ur.Request(f'{api_base}/api/tags')\n        with _ur.urlopen(req, timeout=2.5) as resp:\n            available = resp.status == 200\n            if available:\n                data = json.loads(resp.read().decode('utf-8'))\n                models = _parse_model_list(data)\n    except Exception as exc:\n        error = str(exc)\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': available,\n        'api_base': api_base,\n        'error': error,\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "6de3bc7d641e6f1823ee83d5ebb94ea714480e89": {"t": 1785763090.6604872, "n": 24866, "h": "7811fc0e3d9371ed", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _mask_key(value):\n    if not value:\n        return ''\n    value = str(value)\n    return '****' + value[-4:] if len(value) > 4 else '****'\n\n\ndef _public_search_config(raw_search):\n    from config_manager import SEARCH_PROVIDER_DEFAULTS\n    raw_search = raw_search or {}\n    providers = raw_search.get('providers') or {}\n    out = {}\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        cfg = providers.get(key) or {}\n        out[key] = {\n            'display': meta.get('display', key),\n            'description': meta.get('description', ''),\n            'requires_key': bool(meta.get('requires_key')),\n            'enabled': bool(cfg.get('enabled', meta.get('enabled', False))),\n            'api_key_masked': _mask_key(cfg.get('api_key', '')),\n            'api_base': cfg.get('api_base', ''),\n        }\n    return {\n        'providers': out,\n        'default_sources': raw_search.get('default_sources') or ['openalex', 'semantic_scholar'],\n    }\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'search': _public_search_config(cfg_mgr.get_search_config()),\n        'app_paths': cfg_mgr.get_app_paths(),\n        'coding_agent': cfg_mgr.get_coding_agent_config(),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/config/search', methods=['GET', 'POST'])\ndef search_config():\n    \"\"\"Get/update web/literature search provider configuration.\"\"\"\n    from config_manager import get_config_manager, SEARCH_PROVIDER_DEFAULTS\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    search = project_cfg.setdefault('search', {})\n    providers = search.setdefault('providers', {})\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        providers.setdefault(key, {'enabled': meta['enabled'], 'api_key': '', 'api_base': ''})\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n    data = request.get_json(silent=True) or {}\n    incoming = data.get('providers') or {}\n    for key, item in incoming.items():\n        if key not in SEARCH_PROVIDER_DEFAULTS or not isinstance(item, dict):\n            continue\n        cur = providers.setdefault(key, {'enabled': False, 'api_key': '', 'api_base': ''})\n        if 'enabled' in item:\n            cur['enabled'] = bool(item.get('enabled'))\n        if item.get('api_key'):\n            cur['api_key'] = str(item.get('api_key')).strip()\n        if 'api_base' in item:\n            cur['api_base'] = str(item.get('api_base') or '').strip().rstrip('/')\n    if isinstance(data.get('default_sources'), list):\n        search['default_sources'] = [\n            s for s in data['default_sources']\n            if s in SEARCH_PROVIDER_DEFAULTS\n        ] or ['openalex', 'semantic_scholar']\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n\n@bp.route('/api/config/app_paths', methods=['GET', 'POST'])\ndef app_paths_config():\n    \"\"\"Get/update shared Chat and Geo Agent path defaults.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    paths = project_cfg.setdefault('app_paths', mgr.get_app_paths())\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'app_paths': paths})\n\n    data = request.get_json(silent=True) or {}\n    if 'chat_workspace_enabled' in data:\n        paths['chat_workspace_enabled'] = bool(data.get('chat_workspace_enabled'))\n    if 'chat_workspace_paths' in data:\n        raw = data.get('chat_workspace_paths')\n        if isinstance(raw, str):\n            vals = [x.strip() for x in raw.replace(';', '\\n').replace(',', '\\n').splitlines() if x.strip()]\n        elif isinstance(raw, list):\n            vals = [str(x).strip() for x in raw if str(x).strip()]\n        else:\n            vals = []\n        paths['chat_workspace_paths'] = vals\n    for key in ('geo_workspace_root', 'geo_literature_root', 'geo_output_dir'):\n        if key in data:\n            paths[key] = str(data.get(key) or '').strip()\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'app_paths': paths})\n\n\n@bp.route('/api/config/coding_agent', methods=['GET', 'POST'])\ndef coding_agent_config():\n    \"\"\"Get/update the project-scoped coding backend configuration.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    cfg = project_cfg.setdefault('coding_agent', mgr.get_coding_agent_config())\n\n    if request.method == 'GET':\n        status = {}\n        try:\n            from seismo_code.external_coding_agent import external_agent_status\n            status = external_agent_status(cfg)\n        except Exception as exc:\n            status = {'available': False, 'error': str(exc)}\n        return jsonify({'ok': True, 'coding_agent': cfg, 'status': status})\n\n    data = request.get_json(silent=True) or {}\n    backend = str(data.get('backend') or cfg.get('backend') or 'builtin').strip()\n    if backend not in {'builtin', 'aider', 'openhands'}:\n        return jsonify({'ok': False, 'error': f'Invalid coding agent backend: {backend}'}), 400\n    cfg['backend'] = backend\n    # Backend selection is the source of truth. Keep `enabled` only for older clients.\n    cfg['enabled'] = backend != 'builtin'\n    for key in ('command', 'model', 'extra_args'):\n        if key in data:\n            cfg[key] = str(data.get(key) or '').strip()\n    if 'timeout_s' in data:\n        try:\n            cfg['timeout_s'] = max(30, min(7200, int(data.get('timeout_s') or 900)))\n        except Exception:\n            cfg['timeout_s'] = 900\n    if 'auto_approve' in data:\n        cfg['auto_approve'] = bool(data.get('auto_approve'))\n    if 'use_current_llm_env' in data:\n        cfg['use_current_llm_env'] = bool(data.get('use_current_llm_env'))\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'coding_agent': cfg})\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models with a single short HTTP request.\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    recommended = config.get_recommended_models().get('ollama', [])\n    ollama_cfg = config.config.get('ollama', {}) if isinstance(config.config.get('ollama', {}), dict) else {}\n    llm_cfg = config.config.get('llm', {}) if isinstance(config.config.get('llm', {}), dict) else {}\n    saved_llm_base = llm_cfg.get('api_base') if llm_cfg.get('provider') == 'ollama' else ''\n    api_base = (\n        request.args.get('api_base')\n        or ollama_cfg.get('api_base')\n        or saved_llm_base\n        or 'http://localhost:11434'\n    ).strip().rstrip('/')\n    if not api_base.startswith(('http://localhost', 'http://127.0.0.1', 'http://0.0.0.0', 'http://[::1]')):\n        api_base = 'http://localhost:11434'\n\n    models = []\n    available = False\n    error = ''\n    try:\n        req = _ur.Request(f'{api_base}/api/tags')\n        with _ur.urlopen(req, timeout=2.5) as resp:\n            available = resp.status == 200\n            if available:\n                data = json.loads(resp.read().decode('utf-8'))\n                models = _parse_model_list(data)\n    except Exception as exc:\n        error = str(exc)\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': available,\n        'api_base': api_base,\n        'error': error,\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "bfecc1f48452eb4f1ea84a99369c06dae9f312a9": {"t": 1785763092.1301532, "n": 23018, "h": "f01fb127bc89d078", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _mask_key(value):\n    if not value:\n        return ''\n    value = str(value)\n    return '****' + value[-4:] if len(value) > 4 else '****'\n\n\ndef _public_search_config(raw_search):\n    from config_manager import SEARCH_PROVIDER_DEFAULTS\n    raw_search = raw_search or {}\n    providers = raw_search.get('providers') or {}\n    out = {}\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        cfg = providers.get(key) or {}\n        out[key] = {\n            'display': meta.get('display', key),\n            'description': meta.get('description', ''),\n            'requires_key': bool(meta.get('requires_key')),\n            'enabled': bool(cfg.get('enabled', meta.get('enabled', False))),\n            'api_key_masked': _mask_key(cfg.get('api_key', '')),\n            'api_base': cfg.get('api_base', ''),\n        }\n    return {\n        'providers': out,\n        'default_sources': raw_search.get('default_sources') or ['openalex', 'semantic_scholar'],\n    }\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'search': _public_search_config(cfg_mgr.get_search_config()),\n        'app_paths': cfg_mgr.get_app_paths(),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/config/search', methods=['GET', 'POST'])\ndef search_config():\n    \"\"\"Get/update web/literature search provider configuration.\"\"\"\n    from config_manager import get_config_manager, SEARCH_PROVIDER_DEFAULTS\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    search = project_cfg.setdefault('search', {})\n    providers = search.setdefault('providers', {})\n    for key, meta in SEARCH_PROVIDER_DEFAULTS.items():\n        providers.setdefault(key, {'enabled': meta['enabled'], 'api_key': '', 'api_base': ''})\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n    data = request.get_json(silent=True) or {}\n    incoming = data.get('providers') or {}\n    for key, item in incoming.items():\n        if key not in SEARCH_PROVIDER_DEFAULTS or not isinstance(item, dict):\n            continue\n        cur = providers.setdefault(key, {'enabled': False, 'api_key': '', 'api_base': ''})\n        if 'enabled' in item:\n            cur['enabled'] = bool(item.get('enabled'))\n        if item.get('api_key'):\n            cur['api_key'] = str(item.get('api_key')).strip()\n        if 'api_base' in item:\n            cur['api_base'] = str(item.get('api_base') or '').strip().rstrip('/')\n    if isinstance(data.get('default_sources'), list):\n        search['default_sources'] = [\n            s for s in data['default_sources']\n            if s in SEARCH_PROVIDER_DEFAULTS\n        ] or ['openalex', 'semantic_scholar']\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'search': _public_search_config(search)})\n\n\n@bp.route('/api/config/app_paths', methods=['GET', 'POST'])\ndef app_paths_config():\n    \"\"\"Get/update shared Chat and Geo Agent path defaults.\"\"\"\n    from config_manager import get_config_manager\n    mgr = get_config_manager()\n    project_cfg = mgr.get_project_config()\n    paths = project_cfg.setdefault('app_paths', mgr.get_app_paths())\n\n    if request.method == 'GET':\n        return jsonify({'ok': True, 'app_paths': paths})\n\n    data = request.get_json(silent=True) or {}\n    if 'chat_workspace_enabled' in data:\n        paths['chat_workspace_enabled'] = bool(data.get('chat_workspace_enabled'))\n    if 'chat_workspace_paths' in data:\n        raw = data.get('chat_workspace_paths')\n        if isinstance(raw, str):\n            vals = [x.strip() for x in raw.replace(';', '\\n').replace(',', '\\n').splitlines() if x.strip()]\n        elif isinstance(raw, list):\n            vals = [str(x).strip() for x in raw if str(x).strip()]\n        else:\n            vals = []\n        paths['chat_workspace_paths'] = vals\n    for key in ('geo_workspace_root', 'geo_literature_root', 'geo_output_dir'):\n        if key in data:\n            paths[key] = str(data.get(key) or '').strip()\n    mgr.save_project_config(project_cfg)\n    return jsonify({'ok': True, 'app_paths': paths})\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models with a single short HTTP request.\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    recommended = config.get_recommended_models().get('ollama', [])\n    ollama_cfg = config.config.get('ollama', {}) if isinstance(config.config.get('ollama', {}), dict) else {}\n    llm_cfg = config.config.get('llm', {}) if isinstance(config.config.get('llm', {}), dict) else {}\n    saved_llm_base = llm_cfg.get('api_base') if llm_cfg.get('provider') == 'ollama' else ''\n    api_base = (\n        request.args.get('api_base')\n        or ollama_cfg.get('api_base')\n        or saved_llm_base\n        or 'http://localhost:11434'\n    ).strip().rstrip('/')\n    if not api_base.startswith(('http://localhost', 'http://127.0.0.1', 'http://0.0.0.0', 'http://[::1]')):\n        api_base = 'http://localhost:11434'\n\n    models = []\n    available = False\n    error = ''\n    try:\n        req = _ur.Request(f'{api_base}/api/tags')\n        with _ur.urlopen(req, timeout=2.5) as resp:\n            available = resp.status == 200\n            if available:\n                data = json.loads(resp.read().decode('utf-8'))\n                models = _parse_model_list(data)\n    except Exception as exc:\n        error = str(exc)\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': available,\n        'api_base': api_base,\n        'error': error,\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "82a35cf579f18dd06b563a9e2eb347e021da2138": {"t": 1785763095.4462836, "n": 19054, "h": "a233b5ad837d40ea", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models with a single short HTTP request.\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    recommended = config.get_recommended_models().get('ollama', [])\n    ollama_cfg = config.config.get('ollama', {}) if isinstance(config.config.get('ollama', {}), dict) else {}\n    llm_cfg = config.config.get('llm', {}) if isinstance(config.config.get('llm', {}), dict) else {}\n    saved_llm_base = llm_cfg.get('api_base') if llm_cfg.get('provider') == 'ollama' else ''\n    api_base = (\n        request.args.get('api_base')\n        or ollama_cfg.get('api_base')\n        or saved_llm_base\n        or 'http://localhost:11434'\n    ).strip().rstrip('/')\n    if not api_base.startswith(('http://localhost', 'http://127.0.0.1', 'http://0.0.0.0', 'http://[::1]')):\n        api_base = 'http://localhost:11434'\n\n    models = []\n    available = False\n    error = ''\n    try:\n        req = _ur.Request(f'{api_base}/api/tags')\n        with _ur.urlopen(req, timeout=2.5) as resp:\n            available = resp.status == 200\n            if available:\n                data = json.loads(resp.read().decode('utf-8'))\n                models = _parse_model_list(data)\n    except Exception as exc:\n        error = str(exc)\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': available,\n        'api_base': api_base,\n        'error': error,\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "056f8ca68adc0b24d483aabf77c8ec70f28f37ab": {"t": 1785763096.9841034, "n": 17992, "h": "bcefe2c07a8c841f", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                **({\n                    'notice': (\n                        f'已验证当前模型可用；该平台的 /models 列表接口返回 HTTP {e.code}。'\n                    )\n                } if verified else {\n                    'warning': (\n                        f'/models 接口不可用或返回 HTTP {e.code}，'\n                        '但聊天接口可能仍可使用；已使用当前/预设模型。'\n                    )\n                }),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "232f6d443b92ded1e6d11315df2a99a5b18e9bc5": {"t": 1785763098.3570983, "n": 17773, "h": "23318db50c6a642f", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\ndef _parse_model_list(data):\n    models = []\n    if isinstance(data, dict) and isinstance(data.get('data'), list):\n        models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n    elif isinstance(data, dict) and isinstance(data.get('models'), list):\n        models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n    elif isinstance(data, list):\n        models = [\n            m.get('id') or m.get('name', '')\n            for m in data\n            if isinstance(m, dict)\n        ]\n    return sorted({m for m in models if m})\n\n\ndef _fallback_model_candidates(provider, api_base, current_model):\n    candidates = []\n    if current_model:\n        candidates.append(current_model)\n    preset = ONLINE_PROVIDERS.get(provider, {})\n    if preset.get('default_model'):\n        candidates.append(preset['default_model'])\n    base_l = (api_base or '').lower()\n    if 'aliyuncs.com' in base_l or 'dashscope' in base_l:\n        candidates.extend(['qwen3.6-plus', 'qwen-plus', 'qwen-turbo'])\n    return list(dict.fromkeys(candidates))\n\n\ndef _chat_model_available(api_base, api_key, model):\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 1,\n        'temperature': 0,\n    }).encode('utf-8')\n    req = _ur.Request(\n        f'{api_base.rstrip(\"/\")}/chat/completions',\n        data=payload,\n        headers={\n            'Content-Type': 'application/json',\n            'Authorization': f'Bearer {api_key}',\n        },\n        method='POST',\n    )\n    with _ur.urlopen(req, timeout=20) as resp:\n        data = json.loads(resp.read().decode('utf-8'))\n    return bool(data.get('choices'))\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key, model。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n    current_model = request.args.get('model', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        if not current_model:\n            current_model = (\n                cfg.config.get('online', {}).get('model')\n                or cfg.config.get('llm', {}).get('model', '')\n            )\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = _parse_model_list(data)\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models, 'source': 'models_endpoint'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try:\n            body = e.read().decode('utf-8', errors='ignore')[:240]\n        except Exception:\n            pass\n        msgs = {\n            401: 'API Key 无效或已过期 (401)',\n            403: '访问被拒绝，请检查权限 (403)',\n            404: '该平台不支持模型列表接口 (404)',\n        }\n        candidates = _fallback_model_candidates(provider, api_base, current_model)\n        if e.code in {400, 404, 405, 501} and candidates:\n            verified = []\n            for model in candidates[:4]:\n                try:\n                    if _chat_model_available(api_base, api_key, model):\n                        verified.append(model)\n                        break\n                except Exception:\n                    continue\n            models = verified or candidates\n            return jsonify({\n                'models': models,\n                'source': 'chat_probe' if verified else 'fallback',\n                'warning': (\n                    f'/models 接口不可用或返回 HTTP {e.code}，'\n                    '但聊天接口可以继续使用；已使用当前/预设模型。'\n                ),\n            })\n\n        detail = msgs.get(e.code, f'HTTP {e.code}: {e.reason}')\n        if body:\n            detail += f' — {body}'\n        return jsonify({'error': detail, 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "2cff0b2b6a61da229ee41f5b73819021f38e3470": {"t": 1785763099.7802978, "n": 15255, "h": "d31e04154907957d", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.get_json(silent=True) or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.get_json(silent=True) or {}\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = []\n        if isinstance(data.get('data'), list):\n            models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n        elif isinstance(data.get('models'), list):\n            models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n        elif isinstance(data, list):\n            models = [\n                m.get('id') or m.get('name', '')\n                for m in data\n                if isinstance(m, dict)\n            ]\n\n        models = sorted([m for m in models if m])\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models})\n\n    except _ure.HTTPError as e:\n        msgs = {401: 'API Key 无效或已过期 (401)', 403: '访问被拒绝，请检查权限 (403)',\n                404: '该平台不支持模型列表接口 (404)'}\n        return jsonify({'error': msgs.get(e.code, f'HTTP {e.code}: {e.reason}'), 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "43aa9e4e69b71bb056bce2af01ec97a1243c332f": {"t": 1785763101.163703, "n": 15215, "h": "c07f261d97126ef1", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\ntry:\n    from backend_manager import ONLINE_PROVIDERS\nexcept Exception:\n    ONLINE_PROVIDERS = {\n        \"openai\": {\"display\": \"OpenAI\", \"api_base\": \"https://api.openai.com/v1\", \"default_model\": \"gpt-4o-mini\", \"need_key\": True},\n        \"deepseek\": {\"display\": \"DeepSeek\", \"api_base\": \"https://api.deepseek.com/v1\", \"default_model\": \"deepseek-v4-flash\", \"need_key\": True},\n        \"siliconflow\": {\"display\": \"SiliconFlow\", \"api_base\": \"https://api.siliconflow.cn/v1\", \"default_model\": \"Qwen/Qwen2.5-7B-Instruct\", \"need_key\": True},\n        \"moonshot\": {\"display\": \"Moonshot / Kimi\", \"api_base\": \"https://api.moonshot.cn/v1\", \"default_model\": \"moonshot-v1-8k\", \"need_key\": True},\n        \"dashscope\": {\"display\": \"DashScope\", \"api_base\": \"https://dashscope.aliyuncs.com/compatible-mode/v1\", \"default_model\": \"qwen-turbo\", \"need_key\": True},\n        \"zhipu\": {\"display\": \"Zhipu AI\", \"api_base\": \"https://open.bigmodel.cn/api/paas/v4\", \"default_model\": \"glm-4-flash\", \"need_key\": True},\n        \"custom\": {\"display\": \"Custom OpenAI-compatible\", \"api_base\": \"\", \"default_model\": \"\", \"need_key\": True},\n    }\n\n\ndef _public_online_providers():\n    \"\"\"Provider metadata safe to send to the browser.\"\"\"\n    return {\n        key: {\n            'display': value.get('display', key),\n            'api_base': value.get('api_base', ''),\n            'default_model': value.get('default_model', ''),\n            'need_key': value.get('need_key', True),\n        }\n        for key, value in ONLINE_PROVIDERS.items()\n        if key != 'anthropic'\n    }\n\n\ndef _mask_api_key(config):\n    config = dict(config or {})\n    if config.get('api_key'):\n        key = config['api_key']\n        config['api_key_masked'] = '****' + key[-4:] if len(key) > 4 else '****'\n        config['api_key'] = ''\n    return config\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    raw_config = cfg_mgr.config\n    llm_config = dict(raw_config.get('llm', {}))\n\n    if raw_config.get('active_backend') == 'online' and raw_config.get('online'):\n        online = raw_config.get('online', {})\n        llm_config.update({\n            'provider': online.get('provider', llm_config.get('provider', 'custom')),\n            'model': online.get('model', llm_config.get('model', '')),\n            'api_base': online.get('api_base', llm_config.get('api_base', '')),\n            'api_key': online.get('api_key', llm_config.get('api_key', '')),\n        })\n    elif raw_config.get('active_backend') == 'ollama' and raw_config.get('ollama'):\n        ollama = raw_config.get('ollama', {})\n        llm_config.update({\n            'provider': 'ollama',\n            'model': ollama.get('model', llm_config.get('model', '')),\n            'api_base': ollama.get('api_base', llm_config.get('api_base', 'http://localhost:11434')),\n            'api_key': '',\n        })\n\n    return jsonify({\n        'config': _mask_api_key(llm_config),\n        'online_providers': _public_online_providers(),\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.json or {}\n    config = get_config_manager()\n\n    try:\n        cfg = config.config\n        llm = cfg.setdefault('llm', {})\n        provider = (data.get('provider') or llm.get('provider') or 'ollama').strip()\n        if provider not in ['ollama', 'openai', 'deepseek', 'siliconflow', 'moonshot', 'dashscope', 'zhipu', 'custom']:\n            raise ValueError(f'Invalid provider: {provider}')\n\n        if provider == 'ollama':\n            api_base = (data.get('api_base') or 'http://localhost:11434').strip().rstrip('/')\n            model = (data.get('model') or llm.get('model') or '').strip()\n            llm.update({\n                'provider': 'ollama',\n                'model': model,\n                'api_base': api_base,\n                'api_key': '',\n            })\n            cfg['active_backend'] = 'ollama'\n            cfg.setdefault('ollama', {}).update({\n                'model': model,\n                'api_base': api_base,\n            })\n        else:\n            preset = ONLINE_PROVIDERS.get(provider, {})\n            online = cfg.setdefault('online', {})\n            api_base = (data.get('api_base') or preset.get('api_base') or online.get('api_base') or llm.get('api_base') or '').strip().rstrip('/')\n            model = (data.get('model') or preset.get('default_model') or online.get('model') or llm.get('model') or '').strip()\n            api_key = data.get('api_key')\n            if api_key is None or api_key == '':\n                api_key = online.get('api_key') or llm.get('api_key', '')\n            else:\n                api_key = api_key.strip()\n\n            llm.update({\n                'provider': provider,\n                'model': model,\n                'api_base': api_base,\n                'api_key': api_key,\n            })\n            cfg['active_backend'] = 'online'\n            online.update({\n                'provider': provider,\n                'api_base': api_base,\n                'api_key': api_key,\n                'model': model,\n            })\n\n        if 'temperature' in data:\n            llm['temperature'] = data['temperature']\n        if 'max_tokens' in data:\n            llm['max_tokens'] = data['max_tokens']\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            cfg['first_run'] = False\n\n        config.save_config()\n        return jsonify({'message': 'Configuration updated successfully', 'config': _mask_api_key(llm)})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.json\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: provider, api_base, api_key。\"\"\"\n    from config_manager import get_config_manager\n\n    provider = request.args.get('provider', '').strip()\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n\n    if not api_base and provider in ONLINE_PROVIDERS:\n        api_base = ONLINE_PROVIDERS[provider].get('api_base', '')\n\n    # 如果请求没带 api_key，使用已保存的 online/llm key\n    if not api_key:\n        cfg = get_config_manager()\n        api_key = (\n            cfg.config.get('online', {}).get('api_key')\n            or cfg.config.get('llm', {}).get('api_key', '')\n        )\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = []\n        if isinstance(data.get('data'), list):\n            models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n        elif isinstance(data.get('models'), list):\n            models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n        elif isinstance(data, list):\n            models = [\n                m.get('id') or m.get('name', '')\n                for m in data\n                if isinstance(m, dict)\n            ]\n\n        models = sorted([m for m in models if m])\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models})\n\n    except _ure.HTTPError as e:\n        msgs = {401: 'API Key 无效或已过期 (401)', 403: '访问被拒绝，请检查权限 (403)',\n                404: '该平台不支持模型列表接口 (404)'}\n        return jsonify({'error': msgs.get(e.code, f'HTTP {e.code}: {e.reason}'), 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    manager = get_config_manager()\n    cfg = dict(manager.get_llm_config())\n    body = request.get_json(silent=True) or {}\n    if body:\n        saved_online = manager.config.get('online', {})\n        saved_llm = manager.config.get('llm', {})\n        cfg.update({\n            'provider': body.get('provider', cfg.get('provider', 'ollama')),\n            'model': body.get('model', cfg.get('model', '')),\n            'api_base': body.get('api_base', cfg.get('api_base', '')),\n        })\n        if body.get('api_key'):\n            cfg['api_key'] = body.get('api_key')\n        else:\n            cfg['api_key'] = saved_online.get('api_key') or saved_llm.get('api_key') or cfg.get('api_key', '')\n\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "4e0caf42daab295ef7c847f9fbd2c98b89993812": {"t": 1785763103.125807, "n": 10043, "h": "99df870b54b2d93d", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    llm_config = dict(cfg_mgr.config.get('llm', {}))\n\n    # Hide API key for security\n    if llm_config.get('api_key'):\n        k = llm_config['api_key']\n        llm_config['api_key_masked'] = '****' + k[-4:] if len(k) > 4 else '****'\n        llm_config['api_key'] = ''   # don't send raw key to browser\n\n    return jsonify({\n        'config': llm_config,\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.json\n    config = get_config_manager()\n\n    try:\n        if 'provider' in data:\n            config.set_llm_provider(data['provider'])\n\n        if 'model' in data:\n            config.set_llm_model(data['model'])\n\n        if 'api_key' in data and data['api_key']:\n            config.set_api_key(data['api_key'])\n\n        if 'api_base' in data:\n            config.set_api_base(data['api_base'])\n\n        if 'temperature' in data:\n            config.config['llm']['temperature'] = data['temperature']\n            config.save_config()\n\n        if 'max_tokens' in data:\n            config.config['llm']['max_tokens'] = data['max_tokens']\n            config.save_config()\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            config.mark_first_run_complete()\n\n        return jsonify({'message': 'Configuration updated successfully'})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.json\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/online/models', methods=['GET'])\ndef get_online_api_models():\n    \"\"\"从在线 API 获取可用模型列表。支持 GET 参数: api_base, api_key (可选，优先用已保存的 key)\"\"\"\n    from config_manager import get_config_manager\n\n    api_base = request.args.get('api_base', '').strip()\n    api_key  = request.args.get('api_key', '').strip()\n\n    # 如果请求没带 api_key，使用已保存的\n    if not api_key:\n        cfg = get_config_manager()\n        api_key = cfg.config.get('llm', {}).get('api_key', '')\n\n    if not api_base:\n        return jsonify({'error': '请提供 api_base 参数', 'models': []}), 400\n    if not api_key:\n        return jsonify({'error': '请先填写并保存 API Key，或在参数中提供 api_key', 'models': []}), 400\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    url = api_base.rstrip('/') + '/models'\n    try:\n        req = _urq.Request(\n            url,\n            headers={\n                'Authorization': f'Bearer {api_key}',\n                'Content-Type': 'application/json',\n            }\n        )\n        with _urq.urlopen(req, timeout=12) as resp:\n            data = json.loads(resp.read().decode('utf-8'))\n\n        models = []\n        if isinstance(data.get('data'), list):\n            models = [m['id'] for m in data['data'] if isinstance(m, dict) and m.get('id')]\n        elif isinstance(data.get('models'), list):\n            models = [m.get('id') or m.get('name', '') for m in data['models'] if isinstance(m, dict)]\n\n        models = sorted([m for m in models if m])\n        if not models:\n            return jsonify({'error': '接口返回了空模型列表', 'models': []}), 502\n\n        return jsonify({'models': models})\n\n    except _ure.HTTPError as e:\n        msgs = {401: 'API Key 无效或已过期 (401)', 403: '访问被拒绝，请检查权限 (403)',\n                404: '该平台不支持模型列表接口 (404)'}\n        return jsonify({'error': msgs.get(e.code, f'HTTP {e.code}: {e.reason}'), 'models': []}), 502\n    except (_ure.URLError, OSError) as e:\n        return jsonify({'error': f'网络连接失败: {e.reason if hasattr(e, \"reason\") else str(e)}', 'models': []}), 502\n    except Exception as e:\n        return jsonify({'error': f'获取模型列表失败: {str(e)}', 'models': []}), 502\n\n\n@bp.route('/api/llm/test', methods=['POST'])\ndef test_llm_connection():\n    \"\"\"轻量测试 LLM 连接：发送一条最短的 chat 消息，返回详细错误信息。\"\"\"\n    from config_manager import get_config_manager\n\n    cfg = get_config_manager().get_llm_config()\n    provider = cfg.get('provider', 'ollama')\n    model    = cfg.get('model', '')\n    api_base = cfg.get('api_base', 'http://localhost:11434')\n    api_key  = cfg.get('api_key', '')\n\n    if not model:\n        return jsonify({'ok': False, 'error': '未配置模型，请先保存配置'})\n\n    import urllib.request as _urq\n    import urllib.error as _ure\n\n    # ── Ollama 分支 ─────────────────────────────────────────────────\n    if provider == 'ollama':\n        try:\n            req = _urq.Request(f'{api_base.rstrip(\"/\")}/api/tags')\n            with _urq.urlopen(req, timeout=5) as resp:\n                ok = resp.status == 200\n            if ok:\n                return jsonify({'ok': True, 'message': f'Ollama 连接正常，当前模型: {model}'})\n            return jsonify({'ok': False, 'error': 'Ollama 服务未响应，请运行 ollama serve'})\n        except Exception as e:\n            return jsonify({'ok': False, 'error': f'Ollama 连接失败: {str(e)}'})\n\n    # ── 在线 API 分支 ────────────────────────────────────────────────\n    if not api_key:\n        return jsonify({'ok': False, 'error': '未配置 API Key，请填写后保存'})\n\n    payload = json.dumps({\n        'model': model,\n        'messages': [{'role': 'user', 'content': 'hi'}],\n        'max_tokens': 5,\n        'temperature': 0,\n    }).encode('utf-8')\n\n    try:\n        req = _urq.Request(\n            f'{api_base.rstrip(\"/\")}/chat/completions',\n            data=payload,\n            headers={\n                'Content-Type': 'application/json',\n                'Authorization': f'Bearer {api_key}',\n            },\n            method='POST',\n        )\n        with _urq.urlopen(req, timeout=30) as resp:\n            result = json.loads(resp.read().decode('utf-8'))\n\n        if result.get('choices'):\n            return jsonify({'ok': True, 'message': f'✓ {model} 响应正常'})\n        return jsonify({'ok': False, 'error': '模型返回了空结果，请检查模型名称'})\n\n    except _ure.HTTPError as e:\n        body = ''\n        try: body = e.read().decode('utf-8', errors='ignore')[:200]\n        except Exception: pass\n        msgs = {\n            401: f'API Key 无效或已过期 (401)',\n            403: f'访问被拒绝，请检查权限 (403)',\n            404: f'模型 \"{model}\" 不存在，请确认模型名称 (404)',\n            429: '请求频率超限，稍后再试 (429)',\n        }\n        err = msgs.get(e.code, f'HTTP {e.code}')\n        if body: err += f' — {body}'\n        return jsonify({'ok': False, 'error': err})\n    except (_ure.URLError, OSError) as e:\n        reason = e.reason if hasattr(e, 'reason') else str(e)\n        if 'timed out' in str(reason).lower():\n            return jsonify({'ok': False, 'error': '连接超时，请检查网络或 API 地址是否正确'})\n        return jsonify({'ok': False, 'error': f'网络连接失败: {reason}'})\n    except Exception as e:\n        return jsonify({'ok': False, 'error': f'测试失败: {str(e)}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}, "55f2c6c1786312cbce126a819d884e7942ebce74": {"t": 1785763104.3573942, "n": 5016, "h": "2c18e189462468b8", "c": "\"\"\"LLM 配置路由\"\"\"\nfrom flask import Blueprint, request, jsonify\nimport sys\nimport json\nimport threading\nimport time as _time\nimport urllib.request as _ur\nfrom pathlib import Path\nfrom state import _pull_status\n\nbp = Blueprint('llm', __name__)\n\n\n@bp.route('/api/llm/config', methods=['GET'])\ndef llm_config_get():\n    \"\"\"Get current LLM configuration (reads directly from config.json)\"\"\"\n    from config_manager import LLMConfigManager\n    cfg_mgr = LLMConfigManager()\n    llm_config = dict(cfg_mgr.config.get('llm', {}))\n\n    # Hide API key for security\n    if llm_config.get('api_key'):\n        k = llm_config['api_key']\n        llm_config['api_key_masked'] = '****' + k[-4:] if len(k) > 4 else '****'\n        llm_config['api_key'] = ''   # don't send raw key to browser\n\n    return jsonify({\n        'config': llm_config,\n        'first_run': cfg_mgr.is_first_run(),\n        'ollama_available': cfg_mgr.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/config', methods=['POST'])\ndef update_llm_config():\n    \"\"\"Update LLM configuration\"\"\"\n    from config_manager import get_config_manager\n    data = request.json\n    config = get_config_manager()\n\n    try:\n        if 'provider' in data:\n            config.set_llm_provider(data['provider'])\n\n        if 'model' in data:\n            config.set_llm_model(data['model'])\n\n        if 'api_key' in data and data['api_key']:\n            config.set_api_key(data['api_key'])\n\n        if 'api_base' in data:\n            config.set_api_base(data['api_base'])\n\n        if 'temperature' in data:\n            config.config['llm']['temperature'] = data['temperature']\n            config.save_config()\n\n        if 'max_tokens' in data:\n            config.config['llm']['max_tokens'] = data['max_tokens']\n            config.save_config()\n\n        # Mark first run complete if this is the first setup\n        if config.is_first_run():\n            config.mark_first_run_complete()\n\n        return jsonify({'message': 'Configuration updated successfully'})\n    except Exception as e:\n        return jsonify({'error': str(e)}), 400\n\n\n@bp.route('/api/llm/ollama/models', methods=['GET'])\ndef get_ollama_models():\n    \"\"\"Get available Ollama models\"\"\"\n    from config_manager import get_config_manager\n    config = get_config_manager()\n    models = config.get_ollama_models()\n    recommended = config.get_recommended_models().get('ollama', [])\n\n    return jsonify({\n        'installed': models,\n        'recommended': recommended,\n        'ollama_available': config.check_ollama_available()\n    })\n\n\n@bp.route('/api/llm/ollama/pull', methods=['POST'])\ndef pull_ollama_model():\n    \"\"\"Pull an Ollama model and track progress.\"\"\"\n    data = request.json\n    model_name = data.get('model')\n\n    if not model_name:\n        return jsonify({'error': 'Model name required'}), 400\n\n    _pull_status[model_name] = {'status': 'pulling', 'progress': 0, 'detail': '', 'error': ''}\n\n    def pull_in_background():\n        try:\n            # Use Ollama streaming pull API to track progress\n            url     = 'http://localhost:11434/api/pull'\n            payload = json.dumps({'name': model_name, 'stream': True}).encode()\n            req     = _ur.Request(url, data=payload, method='POST',\n                                  headers={'Content-Type': 'application/json'})\n            with _ur.urlopen(req, timeout=1800) as resp:\n                for raw_line in resp:\n                    line = raw_line.decode().strip()\n                    if not line:\n                        continue\n                    try:\n                        obj = json.loads(line)\n                    except Exception:\n                        continue\n                    status_msg = obj.get('status', '')\n                    total      = obj.get('total', 0)\n                    completed  = obj.get('completed', 0)\n                    pct = int(completed * 100 / total) if total else 0\n                    detail = f\"{completed/1e9:.1f} GB / {total/1e9:.1f} GB\" if total else status_msg\n                    _pull_status[model_name] = {\n                        'status': 'pulling', 'progress': pct,\n                        'detail': detail, 'error': ''\n                    }\n            _pull_status[model_name] = {'status': 'done', 'progress': 100, 'detail': '', 'error': ''}\n        except Exception as ex:\n            _pull_status[model_name] = {'status': 'error', 'progress': 0,\n                                        'detail': '', 'error': str(ex)}\n\n    thread = threading.Thread(target=pull_in_background, daemon=True)\n    thread.start()\n    return jsonify({'message': f'Started pulling model: {model_name}'})\n\n\n@bp.route('/api/llm/ollama/pull/status', methods=['GET'])\ndef pull_ollama_status():\n    \"\"\"Return current pull progress for a model.\"\"\"\n    model_name = request.args.get('model', '')\n    if not model_name:\n        return jsonify({'error': 'model param required'}), 400\n    info = _pull_status.get(model_name, {'status': 'unknown', 'progress': 0, 'detail': '', 'error': ''})\n    return jsonify(info)\n"}}, "ONLINE_API_SETUP.md": {"5ef458cab746280eb97d2dfb27bd545c578d5400": {"t": 1785747354.8156664, "n": 5621, "h": "2cd419e3d01ee55c", "c": "# 在线 API 模型配置指南\n\n## 问题诊断\n\n你的大模型接入在线 API 不工作的原因已找到并已修复！\n\n### 原始问题\n- **旧代码**只支持 Ollama 本地模型\n- 当设置 Qwen/DeepSeek 的在线 API 时，系统会自动降级到规则引擎\n- 没有自动检测在线 API 的模型列表功能\n\n### 已修复项目\n✅ 扩展了 `llm_agent.py`，添加 `OpenAICompatibleClient` 支持  \n✅ 修改了 `build_agent_from_config()` 以支持在线 API  \n✅ 添加了在线 API 模型列表自动检测功能  \n✅ 更新了 `IntentClassifier` 以正确调用在线 API  \n✅ 提供了模型列表获取工具\n\n---\n\n## 配置方法\n\n### 方法 1：使用 Python API（推荐）\n\n```python\nfrom config_manager import LLMConfigManager\n\ncfg = LLMConfigManager()\n\n# 设置 DeepSeek\ncfg.set_llm_provider('deepseek')\ncfg.set_api_base('https://api.deepseek.com/v1')\ncfg.set_api_key('your-deepseek-api-key-here')\n\n# 自动检测可用模型\nmodels = cfg.get_online_api_models()\nif models:\n    print(f\"可用模型: {models}\")\n    # 选择第一个模型\n    cfg.set_llm_model(models[0])\n```\n\n### 方法 2：直接编辑配置文件\n\n配置文件位置：`~/.seismicx/config.json`\n\n```json\n{\n  \"llm\": {\n    \"provider\": \"deepseek\",\n    \"model\": \"deepseek-v4-flash\",\n    \"api_base\": \"https://api.deepseek.com/v1\",\n    \"api_key\": \"your-api-key-here\",\n    \"temperature\": 0.3,\n    \"max_tokens\": 2000\n  }\n}\n```\n\n---\n\n## 支持的在线 API 服务商\n\n### 🔷 DeepSeek\n- **官网**: https://www.deepseek.com/\n- **API 文档**: https://platform.deepseek.com/api-docs/\n- **API Base**: `https://api.deepseek.com/v1`\n- **推荐模型**:\n  - `deepseek-v4-flash` (快速，适合实时应用)\n  - `deepseek-v4-pro` (强大的推理)\n\n### 🟢 OpenAI\n- **官网**: https://openai.com/\n- **API 文档**: https://platform.openai.com/docs/\n- **API Base**: `https://api.openai.com/v1`\n- **推荐模型**:\n  - `gpt-4o-mini` (经济，性价比高)\n  - `gpt-4o` (最强)\n\n### 🔶 通义千问（SiliconFlow 代理）\n- **官网**: https://www.siliconflow.cn/\n- **API 文档**: https://docs.siliconflow.cn/\n- **API Base**: `https://api.siliconflow.cn/v1`\n- **推荐模型**:\n  - `Qwen/Qwen2.5-7B-Instruct` (中文优化)\n  - `Qwen/Qwen2.5-14B-Instruct` (更强)\n\n### 🌙 Moonshot / Kimi\n- **官网**: https://www.moonshot.cn/\n- **API 文档**: https://platform.moonshot.cn/docs/\n- **API Base**: `https://api.moonshot.cn/v1`\n- **推荐模型**:\n  - `moonshot-v1-8k`\n\n### 🌩️ 阿里云 DashScope\n- **官网**: https://dashscope.aliyun.com/\n- **API Base**: `https://dashscope.aliyuncs.com/compatible-mode/v1`\n- **推荐模型**:\n  - `qwen-turbo` (快速)\n  - `qwen-plus` (均衡)\n\n### 💠 智谱 AI\n- **官网**: https://www.zhipuai.cn/\n- **API Base**: `https://open.bigmodel.cn/api/paas/v4`\n- **推荐模型**:\n  - `glm-4-flash` (免费)\n  - `glm-4` (强大)\n\n---\n\n## 快速开始\n\n### 1️⃣ 获取 API Key\n\n以 DeepSeek 为例：\n1. 访问 https://platform.deepseek.com/\n2. 创建账户并充值\n3. 在 API Keys 页面创建新的 API Key\n4. 复制 API Key\n\n### 2️⃣ 检测可用模型\n\n运行工具脚本：\n\n```bash\n# 检测当前配置\npython test_online_api_models.py\n\n# 检测特定 API\npython test_online_api_models.py deepseek sk-xxxxxxxxxxxxxxxx\npython test_online_api_models.py qwen sk-xxxxxxxxxxxxxxxx\n```\n\n### 3️⃣ 配置系统\n\n```python\nfrom config_manager import LLMConfigManager\n\ncfg = LLMConfigManager()\ncfg.set_llm_provider('deepseek')\ncfg.set_api_key('sk-your-key-here')\n\n# 自动获取并设置第一个可用模型\nmodels = cfg.get_online_api_models()\nif models:\n    cfg.set_llm_model(models[0])\n    print(f\"✓ 已配置为: {models[0]}\")\n```\n\n### 4️⃣ 测试连接\n\n```python\nfrom conversational_agent import ConversationalAgent\n\nagent = ConversationalAgent()\nif agent.llm_agent:\n    print(\"✓ 在线 API 已连接，支持 AI 驱动的对话\")\n    result = agent.process_message(\"你好，我想检测地震数据\")\n    print(result['response'])\nelse:\n    print(\"✗ 在线 API 连接失败，使用规则引擎模式\")\n```\n\n---\n\n## 常见问题\n\n### Q: 为什么设置完 API 后还是不工作？\n\n**A**: 请检查：\n1. **API Key 是否正确**：在代码中测试 API Key\n2. **网络连接**：确保能访问 API 端点\n3. **模型名称**：确保模型名称与 API 返回的完全一致\n4. **API Base URL**：检查是否包含 `/v1` 后缀（某些 API 需要）\n\n### Q: 如何查看当前是否使用了在线 API？\n\n**A**: \n```python\nfrom conversational_agent import ConversationalAgent\nagent = ConversationalAgent()\nprint(f\"使用 LLM 路径: {agent.llm_agent is not None}\")\nprint(f\"错误信息: {agent.llm_error}\")\n```\n\n### Q: 为什么 API 调用很慢？\n\n**A**: \n- 在线 API 响应时间取决于网络和服务器\n- 建议使用 `temperature=0.3` 以下的低温值以加快响应\n- 某些模型比其他模型更快（如 `-flash` / `-mini` 版本）\n\n### Q: 可以同时使用多个 API 吗？\n\n**A**: 当前配置支持一个活跃 API。如果需要多个，可以：\n1. 在不同的配置文件中切换\n2. 在代码中动态创建多个 `OpenAICompatibleClient` 实例\n\n---\n\n## 深度集成\n\n### 在自定义脚本中使用\n\n```python\nfrom llm_agent import OpenAICompatibleClient, OllamaToolAgent\nfrom conversational_agent import SkillExecutor, ConversationContext\nfrom config_manager import LLMConfigManager\n\n# 获取配置\ncfg = LLMConfigManager()\nllm_cfg = cfg.get_llm_config()\n\n# 创建 OpenAI-compatible 客户端\nclient = OpenAICompatibleClient(\n    api_base=llm_cfg['api_base'],\n    model=llm_cfg['model'],\n    api_key=llm_cfg['api_key'],\n)\n\n# 创建 Agent\nexecutor = SkillExecutor()\ncontext = ConversationContext()\nagent = OllamaToolAgent(\n    skill_executor=executor,\n    context=context,\n    client=client,\n)\n\n# 使用 Agent\nresponse = agent.process_message(\"检测数据目录下的所有地震波形\")\nprint(response['response'])\n```\n\n### 获取在线 API 的模型列表\n\n```python\nfrom llm_agent import OpenAICompatibleClient\n\n# 获取 DeepSeek 的所有模型\nmodels = OpenAICompatibleClient.list_models(\n    api_base='https://api.deepseek.com/v1',\n    api_key='your-api-key'\n)\nprint(f\"可用模型: {models}\")\n```\n\n---\n\n## 技术细节\n\n### 支持的 API 格式\n系统支持 **OpenAI-compatible** API 格式，包括：\n- `/v1/chat/completions` 端点\n- `/v1/models` 或 `/models` 端点\n- `Bearer {api_key}` 认证方式\n\n### 响应格式兼容\n自动处理的响应格式：\n```json\n{\n  \"data\": [\n    {\"id\": \"model-name\"},\n    ...\n  ]\n}\n```\n\n或\n\n```json\n{\n  \"models\": [\n    {\"name\": \"model-name\"},\n    ...\n  ]\n}\n```\n\n### 工具调用支持\n在线 API 支持与 Ollama 相同的 tool-calling 格式，自动转换为 OpenAI 格式。\n\n---\n\n## 性能建议\n\n| 场景 | 推荐模型 | API |\n|------|---------|-----|\n| **快速响应** | deepseek-v4-flash / gpt-4o-mini | DeepSeek / OpenAI |\n| **中文优化** | Qwen2.5-7B-Instruct | SiliconFlow |\n| **最高质量** | deepseek-v4-pro / gpt-4o | DeepSeek / OpenAI |\n| **成本最低** | glm-4-flash | 智谱 AI |\n\n---\n\n## 更新日志\n\n### v2025.04.28\n✅ 添加 OpenAI-compatible API 支持  \n✅ 自动模型列表检测  \n✅ 多 provider 支持（DeepSeek、OpenAI、通义千问等）  \n✅ 工具调用兼容性  \n\n---\n\n**需要帮助？** 查看 `pnsn/LLM_SETUP_GUIDE.md` 了解更多详情。\n"}, "4e0caf42daab295ef7c847f9fbd2c98b89993812": {"t": 1785763087.5777206, "n": 5621, "h": "2cd419e3d01ee55c", "c": "# 在线 API 模型配置指南\n\n## 问题诊断\n\n你的大模型接入在线 API 不工作的原因已找到并已修复！\n\n### 原始问题\n- **旧代码**只支持 Ollama 本地模型\n- 当设置 Qwen/DeepSeek 的在线 API 时，系统会自动降级到规则引擎\n- 没有自动检测在线 API 的模型列表功能\n\n### 已修复项目\n✅ 扩展了 `llm_agent.py`，添加 `OpenAICompatibleClient` 支持  \n✅ 修改了 `build_agent_from_config()` 以支持在线 API  \n✅ 添加了在线 API 模型列表自动检测功能  \n✅ 更新了 `IntentClassifier` 以正确调用在线 API  \n✅ 提供了模型列表获取工具\n\n---\n\n## 配置方法\n\n### 方法 1：使用 Python API（推荐）\n\n```python\nfrom config_manager import LLMConfigManager\n\ncfg = LLMConfigManager()\n\n# 设置 DeepSeek\ncfg.set_llm_provider('deepseek')\ncfg.set_api_base('https://api.deepseek.com/v1')\ncfg.set_api_key('your-deepseek-api-key-here')\n\n# 自动检测可用模型\nmodels = cfg.get_online_api_models()\nif models:\n    print(f\"可用模型: {models}\")\n    # 选择第一个模型\n    cfg.set_llm_model(models[0])\n```\n\n### 方法 2：直接编辑配置文件\n\n配置文件位置：`~/.seismicx/config.json`\n\n```json\n{\n  \"llm\": {\n    \"provider\": \"deepseek\",\n    \"model\": \"deepseek-v4-flash\",\n    \"api_base\": \"https://api.deepseek.com/v1\",\n    \"api_key\": \"your-api-key-here\",\n    \"temperature\": 0.3,\n    \"max_tokens\": 2000\n  }\n}\n```\n\n---\n\n## 支持的在线 API 服务商\n\n### 🔷 DeepSeek\n- **官网**: https://www.deepseek.com/\n- **API 文档**: https://platform.deepseek.com/api-docs/\n- **API Base**: `https://api.deepseek.com/v1`\n- **推荐模型**:\n  - `deepseek-v4-flash` (快速，适合实时应用)\n  - `deepseek-v4-pro` (强大的推理)\n\n### 🟢 OpenAI\n- **官网**: https://openai.com/\n- **API 文档**: https://platform.openai.com/docs/\n- **API Base**: `https://api.openai.com/v1`\n- **推荐模型**:\n  - `gpt-4o-mini` (经济，性价比高)\n  - `gpt-4o` (最强)\n\n### 🔶 通义千问（SiliconFlow 代理）\n- **官网**: https://www.siliconflow.cn/\n- **API 文档**: https://docs.siliconflow.cn/\n- **API Base**: `https://api.siliconflow.cn/v1`\n- **推荐模型**:\n  - `Qwen/Qwen2.5-7B-Instruct` (中文优化)\n  - `Qwen/Qwen2.5-14B-Instruct` (更强)\n\n### 🌙 Moonshot / Kimi\n- **官网**: https://www.moonshot.cn/\n- **API 文档**: https://platform.moonshot.cn/docs/\n- **API Base**: `https://api.moonshot.cn/v1`\n- **推荐模型**:\n  - `moonshot-v1-8k`\n\n### 🌩️ 阿里云 DashScope\n- **官网**: https://dashscope.aliyun.com/\n- **API Base**: `https://dashscope.aliyuncs.com/compatible-mode/v1`\n- **推荐模型**:\n  - `qwen-turbo` (快速)\n  - `qwen-plus` (均衡)\n\n### 💠 智谱 AI\n- **官网**: https://www.zhipuai.cn/\n- **API Base**: `https://open.bigmodel.cn/api/paas/v4`\n- **推荐模型**:\n  - `glm-4-flash` (免费)\n  - `glm-4` (强大)\n\n---\n\n## 快速开始\n\n### 1️⃣ 获取 API Key\n\n以 DeepSeek 为例：\n1. 访问 https://platform.deepseek.com/\n2. 创建账户并充值\n3. 在 API Keys 页面创建新的 API Key\n4. 复制 API Key\n\n### 2️⃣ 检测可用模型\n\n运行工具脚本：\n\n```bash\n# 检测当前配置\npython test_online_api_models.py\n\n# 检测特定 API\npython test_online_api_models.py deepseek sk-xxxxxxxxxxxxxxxx\npython test_online_api_models.py qwen sk-xxxxxxxxxxxxxxxx\n```\n\n### 3️⃣ 配置系统\n\n```python\nfrom config_manager import LLMConfigManager\n\ncfg = LLMConfigManager()\ncfg.set_llm_provider('deepseek')\ncfg.set_api_key('sk-your-key-here')\n\n# 自动获取并设置第一个可用模型\nmodels = cfg.get_online_api_models()\nif models:\n    cfg.set_llm_model(models[0])\n    print(f\"✓ 已配置为: {models[0]}\")\n```\n\n### 4️⃣ 测试连接\n\n```python\nfrom conversational_agent import ConversationalAgent\n\nagent = ConversationalAgent()\nif agent.llm_agent:\n    print(\"✓ 在线 API 已连接，支持 AI 驱动的对话\")\n    result = agent.process_message(\"你好，我想检测地震数据\")\n    print(result['response'])\nelse:\n    print(\"✗ 在线 API 连接失败，使用规则引擎模式\")\n```\n\n---\n\n## 常见问题\n\n### Q: 为什么设置完 API 后还是不工作？\n\n**A**: 请检查：\n1. **API Key 是否正确**：在代码中测试 API Key\n2. **网络连接**：确保能访问 API 端点\n3. **模型名称**：确保模型名称与 API 返回的完全一致\n4. **API Base URL**：检查是否包含 `/v1` 后缀（某些 API 需要）\n\n### Q: 如何查看当前是否使用了在线 API？\n\n**A**: \n```python\nfrom conversational_agent import ConversationalAgent\nagent = ConversationalAgent()\nprint(f\"使用 LLM 路径: {agent.llm_agent is not None}\")\nprint(f\"错误信息: {agent.llm_error}\")\n```\n\n### Q: 为什么 API 调用很慢？\n\n**A**: \n- 在线 API 响应时间取决于网络和服务器\n- 建议使用 `temperature=0.3` 以下的低温值以加快响应\n- 某些模型比其他模型更快（如 `-flash` / `-mini` 版本）\n\n### Q: 可以同时使用多个 API 吗？\n\n**A**: 当前配置支持一个活跃 API。如果需要多个，可以：\n1. 在不同的配置文件中切换\n2. 在代码中动态创建多个 `OpenAICompatibleClient` 实例\n\n---\n\n## 深度集成\n\n### 在自定义脚本中使用\n\n```python\nfrom llm_agent import OpenAICompatibleClient, OllamaToolAgent\nfrom conversational_agent import SkillExecutor, ConversationContext\nfrom config_manager import LLMConfigManager\n\n# 获取配置\ncfg = LLMConfigManager()\nllm_cfg = cfg.get_llm_config()\n\n# 创建 OpenAI-compatible 客户端\nclient = OpenAICompatibleClient(\n    api_base=llm_cfg['api_base'],\n    model=llm_cfg['model'],\n    api_key=llm_cfg['api_key'],\n)\n\n# 创建 Agent\nexecutor = SkillExecutor()\ncontext = ConversationContext()\nagent = OllamaToolAgent(\n    skill_executor=executor,\n    context=context,\n    client=client,\n)\n\n# 使用 Agent\nresponse = agent.process_message(\"检测数据目录下的所有地震波形\")\nprint(response['response'])\n```\n\n### 获取在线 API 的模型列表\n\n```python\nfrom llm_agent import OpenAICompatibleClient\n\n# 获取 DeepSeek 的所有模型\nmodels = OpenAICompatibleClient.list_models(\n    api_base='https://api.deepseek.com/v1',\n    api_key='your-api-key'\n)\nprint(f\"可用模型: {models}\")\n```\n\n---\n\n## 技术细节\n\n### 支持的 API 格式\n系统支持 **OpenAI-compatible** API 格式，包括：\n- `/v1/chat/completions` 端点\n- `/v1/models` 或 `/models` 端点\n- `Bearer {api_key}` 认证方式\n\n### 响应格式兼容\n自动处理的响应格式：\n```json\n{\n  \"data\": [\n    {\"id\": \"model-name\"},\n    ...\n  ]\n}\n```\n\n或\n\n```json\n{\n  \"models\": [\n    {\"name\": \"model-name\"},\n    ...\n  ]\n}\n```\n\n### 工具调用支持\n在线 API 支持与 Ollama 相同的 tool-calling 格式，自动转换为 OpenAI 格式。\n\n---\n\n## 性能建议\n\n| 场景 | 推荐模型 | API |\n|------|---------|-----|\n| **快速响应** | deepseek-v4-flash / gpt-4o-mini | DeepSeek / OpenAI |\n| **中文优化** | Qwen2.5-7B-Instruct | SiliconFlow |\n| **最高质量** | deepseek-v4-pro / gpt-4o | DeepSeek / OpenAI |\n| **成本最低** | glm-4-flash | 智谱 AI |\n\n---\n\n## 更新日志\n\n### v2025.04.28\n✅ 添加 OpenAI-compatible API 支持  \n✅ 自动模型列表检测  \n✅ 多 provider 支持（DeepSeek、OpenAI、通义千问等）  \n✅ 工具调用兼容性  \n\n---\n\n**需要帮助？** 查看 `pnsn/LLM_SETUP_GUIDE.md` 了解更多详情。\n"}}}}