上传 .msg 文件后，解析结果将在此展示
{data["intent_analysis"]}
') if data.get("suggested_action"): parts.append(f'{data["suggested_action"]}
') if data.get("tone_assessment"): _tm = {"professional": "专业正式", "friendly": "友好亲切", "cold": "冷淡敷衍", "encouraging": "鼓励积极", "standard": "标准常规"} _t = _tm.get(data["tone_assessment"], data["tone_assessment"]) parts.append(f'{_t}
') if data.get("key_phrases"): _ph = "".join(f"{data["follow_up_template"]}'
)
new_a[i] = "\n".join(parts) if parts else "（无内容）"
except Exception as e:
logger.error(f"AI 解析失败: {e}")
new_a[i] = f"[warn] 解析失败：{str(e)[:100]}"
progress(1.0, desc="[ok] AI 解析完成")
return _render_results_html(parsed_list, results, None, new_a), new_a
# ─────────────────────────────────────────────
# 连接测试
# ─────────────────────────────────────────────
def test_llm_connection(provider: str, api_key: str, model: str) -> str:
if not api_key.strip():
return "[x] 请先填写 API Key"
cfg.apply_runtime_config(provider.lower(), api_key.strip(), model.strip())
try:
import openai
burl = cfg.get_llm_base_url()
ck = {"api_key": api_key.strip()}
if burl:
ck["base_url"] = burl
client = openai.OpenAI(**ck)
resp = client.chat.completions.create(
model=cfg.get_llm_model(),
messages=[{"role": "user", "content": "Reply with just: OK"}],
max_tokens=10,
temperature=0,
)
reply = resp.choices[0].message.content.strip()
return f'[ok] 连接成功！模型回复：{reply}'
except Exception as e:
return f'[x] 连接失败：{str(e)[:120]}'
# ─────────────────────────────────────────────
# Gradio 界面构建
# ─────────────────────────────────────────────
def build_app() -> gr.Blocks:
curr = cfg.get_current_config()
with gr.Blocks(
title="邮件分析查看器",
css=CUSTOM_CSS,
theme=gr.themes.Soft(
primary_hue=gr.themes.colors.violet,
neutral_hue=gr.themes.colors.slate,
),
) as demo:
parsed_st = gr.State([])
results_st = gr.State([])
trans_st = gr.State([])
analyses_st = gr.State([])
gr.HTML(
''
)
with gr.Accordion("⚙️ API 配置（展开设置 LLM 密钥）",
open=not bool(curr["api_key"]),
elem_classes="config-panel"):
with gr.Row():
prov_dd = gr.Dropdown(
choices=["deepseek", "openai"],
value=curr["provider"],
label="LLM 提供商",
scale=1,
)
key_box = gr.Textbox(
value=curr["api_key"],
label="API Key",
type="password",
scale=3,
)
mdl_box = gr.Textbox(
value=curr["model"],
label="模型名称",
scale=2,
)
with gr.Row():
tst_btn = gr.Button("🔌 测试连接", variant="secondary", size="sm")
tst_res = gr.HTML(label="")
tst_btn.click(test_llm_connection, [prov_dd, key_box, mdl_box], tst_res)
gr.HTML("上传 .msg 文件并点击「开始解析」后，结果将在此展示
' '