206 lines
6.9 KiB
Rust
206 lines
6.9 KiB
Rust
use platform_llm::{LlmClient, LlmMessage, LlmStreamDelta, LlmTextRequest};
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use serde_json::Value as JsonValue;
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use crate::llm_model_routing::CREATION_TEMPLATE_LLM_MODEL;
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#[derive(Clone, Copy, Debug)]
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pub(crate) struct CreationAgentLlmTurnErrorMessages<'a> {
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pub model_unavailable: &'a str,
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pub generation_failed: &'a str,
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pub parse_failed: &'a str,
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}
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#[derive(Clone, Debug)]
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pub(crate) struct CreationAgentJsonTurnOutput {
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pub parsed: JsonValue,
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}
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/**
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* 创作 Agent 的通用流式 JSON turn 调用。
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* 这里只处理跨玩法一致的 LLM 调用骨架，prompt 内容和领域 JSON 解析仍由调用方负责。
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*/
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pub(crate) async fn stream_creation_agent_json_turn<F, E>(
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llm_client: Option<&LlmClient>,
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system_prompt: String,
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user_prompt: impl Into<String>,
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enable_web_search: bool,
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messages: CreationAgentLlmTurnErrorMessages<'_>,
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mut on_reply_update: F,
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build_error: impl Fn(String) -> E,
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) -> Result<CreationAgentJsonTurnOutput, E>
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where
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F: FnMut(&str),
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{
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let llm_client =
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llm_client.ok_or_else(|| build_error(messages.model_unavailable.to_string()))?;
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let mut latest_reply_text = String::new();
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let response = llm_client
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.stream_text(
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build_creation_agent_llm_request(system_prompt, user_prompt.into(), enable_web_search),
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|delta: &LlmStreamDelta| {
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if let Some(reply_progress) =
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extract_reply_text_from_partial_json(delta.accumulated_text.as_str())
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&& reply_progress != latest_reply_text
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{
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latest_reply_text = reply_progress.clone();
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on_reply_update(reply_progress.as_str());
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}
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},
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)
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.await
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.map_err(|_| build_error(messages.generation_failed.to_string()))?;
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let parsed = parse_json_response_text(response.content.as_str())
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.map_err(|_| build_error(messages.parse_failed.to_string()))?;
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let reply_text = read_reply_text(&parsed);
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if let Some(reply_text) = reply_text.as_deref()
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&& reply_text != latest_reply_text
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{
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on_reply_update(reply_text);
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}
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Ok(CreationAgentJsonTurnOutput { parsed })
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}
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fn build_creation_agent_llm_request(
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system_prompt: String,
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user_prompt: String,
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enable_web_search: bool,
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) -> LlmTextRequest {
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// 创作 Agent 是否联网由 api-server 配置集中传入，避免各玩法各自散落默认值。
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LlmTextRequest::new(vec![
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LlmMessage::system(system_prompt),
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LlmMessage::user(user_prompt),
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])
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.with_model(CREATION_TEMPLATE_LLM_MODEL)
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.with_responses_api()
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.with_web_search(enable_web_search)
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}
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pub(crate) async fn request_creation_agent_json_turn<E>(
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llm_client: &LlmClient,
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system_prompt: String,
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user_prompt: String,
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build_error: impl Fn(String) -> E,
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) -> Result<JsonValue, E> {
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let response = llm_client
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.request_text(
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LlmTextRequest::new(vec![
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LlmMessage::system(system_prompt),
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LlmMessage::user(user_prompt),
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])
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.with_model(CREATION_TEMPLATE_LLM_MODEL)
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.with_responses_api(),
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)
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.await
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.map_err(|error| build_error(error.to_string()))?;
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parse_json_response_text(response.content.as_str())
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.map_err(|error| build_error(error.to_string()))
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}
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pub(crate) fn parse_json_response_text(text: &str) -> Result<JsonValue, serde_json::Error> {
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let trimmed = text.trim();
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if let Some(start) = trimmed.find('{')
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&& let Some(end) = trimmed.rfind('}')
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&& end > start
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{
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return serde_json::from_str::<JsonValue>(&trimmed[start..=end]);
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}
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serde_json::from_str::<JsonValue>(trimmed)
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}
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pub(crate) fn extract_reply_text_from_partial_json(text: &str) -> Option<String> {
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let key_index = text.find("\"replyText\"")?;
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let colon_index = text[key_index..].find(':')? + key_index;
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let mut cursor = colon_index + 1;
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while cursor < text.len() && text.as_bytes()[cursor].is_ascii_whitespace() {
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cursor += 1;
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}
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if text.as_bytes().get(cursor).copied() != Some(b'"') {
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return None;
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}
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cursor += 1;
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let mut decoded = String::new();
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let remainder = text.get(cursor..)?;
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let mut characters = remainder.chars().peekable();
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while let Some(current) = characters.next() {
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if current == '"' {
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return Some(decoded);
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}
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if current == '\\' {
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let escaped = characters.next()?;
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match escaped {
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'"' => decoded.push('"'),
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'\\' => decoded.push('\\'),
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'/' => decoded.push('/'),
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'b' => decoded.push('\u{0008}'),
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'f' => decoded.push('\u{000C}'),
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'n' => decoded.push('\n'),
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'r' => decoded.push('\r'),
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't' => decoded.push('\t'),
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'u' => {
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let mut hex = String::new();
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for _ in 0..4 {
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hex.push(characters.next()?);
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}
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if let Ok(code) = u16::from_str_radix(hex.as_str(), 16)
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&& let Some(character) = char::from_u32(code as u32)
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{
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decoded.push(character);
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}
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}
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other => decoded.push(other),
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}
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continue;
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}
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decoded.push(current);
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}
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Some(decoded)
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}
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fn read_reply_text(parsed: &JsonValue) -> Option<String> {
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parsed
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.get("replyText")
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.and_then(JsonValue::as_str)
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.map(str::trim)
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.filter(|value| !value.is_empty())
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.map(str::to_string)
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}
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#[cfg(test)]
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mod tests {
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use crate::llm_model_routing::CREATION_TEMPLATE_LLM_MODEL;
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use super::{
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build_creation_agent_llm_request, extract_reply_text_from_partial_json,
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parse_json_response_text,
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};
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#[test]
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fn extracts_reply_text_from_partial_json_with_chinese_text() {
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let partial_json = r#"{"replyText":"你好，潮雾列岛","progressPercent":32"#;
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let extracted = extract_reply_text_from_partial_json(partial_json);
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assert_eq!(extracted.as_deref(), Some("你好，潮雾列岛"));
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}
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#[test]
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fn parses_json_inside_model_markdown_noise() {
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let parsed = parse_json_response_text("```json\n{\"replyText\":\"好\"}\n```")
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.expect("应能截取模型返回中的 JSON 对象");
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assert_eq!(parsed["replyText"].as_str(), Some("好"));
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}
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#[test]
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fn builds_stream_request_with_web_search_when_enabled() {
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let request =
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build_creation_agent_llm_request("系统提示".to_string(), "用户提示".to_string(), true);
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assert!(request.enable_web_search);
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assert_eq!(request.model.as_deref(), Some(CREATION_TEMPLATE_LLM_MODEL));
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assert_eq!(request.protocol, platform_llm::LlmTextProtocol::Responses);
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assert_eq!(request.messages.len(), 2);
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}
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}
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