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优化: AI Chat全栈多批审查修复与架构清理(risk_level清理/路由解耦/工具渲染/测试补测/死代码)

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绝尘
2026-06-18 22:57:19 +08:00
parent 0ca5d9805f
commit a2871a66e0
87 changed files with 5720 additions and 3012 deletions
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26
crates/df-ai-core/src/provider.rs
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@@ -121,29 +121,41 @@ pub struct ChatMessage {
/// DeepSeek thinking 模式的推理内容（多轮需回传）
#[serde(default, skip_serializing_if = "Option::is_none")]
pub reasoning_content: Option<String>,
/// 消息创建时间(Unix 毫秒)。仅前端时间戳展示用,序列化进 messages JSON 持久化;
/// provider 请求映射不读此字段(构造器打戳→映射忽略,不进 LLM 请求),老数据反序列化为 None。
#[serde(default, skip_serializing_if = "Option::is_none")]
pub timestamp: Option<i64>,
}
/// 当前 Unix 毫秒(ChatMessage 打戳用;df-ai-core 不依赖 df-types,内联避免新增依赖)。
fn now_millis_i64() -> i64 {
std::time::SystemTime::now()
.duration_since(std::time::UNIX_EPOCH)
.map(|d| d.as_millis() as i64)
.unwrap_or(0)
}
impl ChatMessage {
pub fn system(content: impl Into<String>) -> Self {
Self { role: MessageRole::System, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None }
Self { role: MessageRole::System, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
pub fn user(content: impl Into<String>) -> Self {
Self { role: MessageRole::User, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None }
Self { role: MessageRole::User, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
pub fn assistant(content: impl Into<String>) -> Self {
Self { role: MessageRole::Assistant, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None }
Self { role: MessageRole::Assistant, content: content.into(), parts: None, tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
pub fn assistant_with_tools(content: impl Into<String>, tool_calls: Vec<ToolCall>) -> Self {
Self { role: MessageRole::Assistant, content: content.into(), parts: None, tool_call_id: None, tool_calls: Some(tool_calls), model: None, status: None, reasoning_content: None }
Self { role: MessageRole::Assistant, content: content.into(), parts: None, tool_call_id: None, tool_calls: Some(tool_calls), model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
pub fn tool_result(call_id: impl Into<String>, content: impl Into<String>) -> Self {
Self { role: MessageRole::Tool, content: content.into(), parts: None, tool_call_id: Some(call_id.into()), tool_calls: None, model: None, status: None, reasoning_content: None }
Self { role: MessageRole::Tool, content: content.into(), parts: None, tool_call_id: Some(call_id.into()), tool_calls: None, model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
/// 多模态 user 消息：content 文本 + parts（含 Image 片）。
/// content 作为人类可读文本（也作非 vision 端点降级载荷）；parts 透传给 vision 端点。
pub fn user_parts(content: impl Into<String>, parts: Vec<ContentPart>) -> Self {
Self { role: MessageRole::User, content: content.into(), parts: Some(parts), tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None }
Self { role: MessageRole::User, content: content.into(), parts: Some(parts), tool_call_id: None, tool_calls: None, model: None, status: None, reasoning_content: None, timestamp: Some(now_millis_i64()) }
}
/// 是否含图片片（供 provider 判定走多模态分支）。
@@ -462,6 +474,7 @@ mod tests {
model: None,
status: None,
reasoning_content: None,
timestamp: None,
};
assert_eq!(m.content, "字面量构造");
assert!(m.parts.is_none());
@@ -512,6 +525,7 @@ mod tests {
model: None,
status: None,
reasoning_content: Some("thinking process".to_string()),
timestamp: None,
};
let json = serde_json::to_string(&m).unwrap();
assert!(json.contains("reasoning_content"));