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update:1.优化 AI 流式生成和进度显示系统 2.新增写作风格系统提示词支持 3.灵感模式功能增强,支持灵感重写 4.设置页面功能扩展，新增Gemini适配器 5.提示词模板系统优化，调整灵感模式提示词

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xiamuceer
2025-12-28 19:35:23 +08:00
parent f32e51b594
commit 89848e2258
40 changed files with 2752 additions and 1824 deletions
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backend/app/api/inspiration.py
+204 -28
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@@ -105,23 +105,27 @@ async def generate_options(
user_id = getattr(http_request.state, 'user_id', None)
# 获取对应的提示词模板（根据step确定模板key）
# 新结构：每个步骤有独立的 SYSTEM 和 USER 模板
template_key_map = {
"title": "INSPIRATION_TITLE",
"description": "INSPIRATION_DESCRIPTION",
"theme": "INSPIRATION_THEME",
"genre": "INSPIRATION_GENRE"
"title": ("INSPIRATION_TITLE_SYSTEM", "INSPIRATION_TITLE_USER"),
"description": ("INSPIRATION_DESCRIPTION_SYSTEM", "INSPIRATION_DESCRIPTION_USER"),
"theme": ("INSPIRATION_THEME_SYSTEM", "INSPIRATION_THEME_USER"),
"genre": ("INSPIRATION_GENRE_SYSTEM", "INSPIRATION_GENRE_USER")
}
template_key = template_key_map.get(step)
template_keys = template_key_map.get(step)
if not template_key:
if not template_keys:
return {
"error": f"不支持的步骤: {step}",
"prompt": "",
"options": []
}
# 获取自定义提示词模板
prompt_template_str = await PromptService.get_template(template_key, user_id, db)
system_key, user_key = template_keys
# 获取自定义提示词模板（分别获取 system 和 user）
system_template = await PromptService.get_template(system_key, user_id, db)
user_template = await PromptService.get_template(user_key, user_id, db)
# 准备格式化参数
format_params = {
@@ -131,19 +135,9 @@ async def generate_options(
"theme": context.get("theme", "")
}
# 格式化提示词（灵感模式的模板是特殊格式，包含system和user两部分）
# 尝试解析为JSON格式的字典
try:
prompt_template = json.loads(prompt_template_str)
system_prompt = prompt_template["system"].format(**format_params)
user_prompt = prompt_template["user"].format(**format_params)
except (json.JSONDecodeError, KeyError):
# 如果不是JSON格式，降级使用原有方法
prompt_template = prompt_service.get_inspiration_prompt(step)
if not prompt_template:
return {"error": f"无法获取提示词模板: {step}", "prompt": "", "options": []}
system_prompt = prompt_template["system"].format(**format_params)
user_prompt = prompt_template["user"].format(**format_params)
# 格式化提示词
system_prompt = system_template.format(**format_params)
user_prompt = user_template.format(**format_params)
# 如果是重试，在提示词中强调格式要求
if attempt > 0:
@@ -153,13 +147,18 @@ async def generate_options(
# 关键改进：使用递减的temperature以保持后续阶段与前文的一致性
temperature = TEMPERATURE_SETTINGS.get(step, 0.7)
logger.info(f"调用AI生成{step}选项... (temperature={temperature})")
response = await ai_service.generate_text(
# 流式生成并累积文本
accumulated_text = ""
async for chunk in ai_service.generate_text_stream(
prompt=user_prompt,
system_prompt=system_prompt,
temperature=temperature
)
):
accumulated_text += chunk
content = response.get("content", "")
response = {"content": accumulated_text}
content = accumulated_text
logger.info(f"AI返回内容长度: {len(content)}")
# 解析JSON（使用统一的JSON清洗方法）
@@ -222,6 +221,180 @@ async def generate_options(
}
@router.post("/refine-options")
async def refine_options(
data: Dict[str, Any],
http_request: Request,
db: AsyncSession = Depends(get_db),
ai_service: AIService = Depends(get_user_ai_service)
) -> Dict[str, Any]:
"""
基于用户反馈重新生成选项（支持多轮对话）
Request:
{
"step": "title", // 当前步骤
"context": {
"initial_idea": "...",
"title": "...",
"description": "...",
"theme": "..."
},
"feedback": "我想要更悲剧一些的主题", // 用户反馈
"previous_options": ["选项1", "选项2", ...] // 之前的选项（可选）
}
Response:
{
"prompt": "引导语",
"options": ["新选项1", "新选项2", ...]
}
"""
max_retries = 3
for attempt in range(max_retries):
try:
step = data.get("step", "title")
context = data.get("context", {})
feedback = data.get("feedback", "")
previous_options = data.get("previous_options", [])
logger.info(f"灵感模式：根据反馈重新生成{step}阶段的选项（第{attempt + 1}次尝试）")
logger.info(f"用户反馈: {feedback}")
# 获取用户ID
user_id = getattr(http_request.state, 'user_id', None)
# 获取对应的提示词模板
template_key_map = {
"title": ("INSPIRATION_TITLE_SYSTEM", "INSPIRATION_TITLE_USER"),
"description": ("INSPIRATION_DESCRIPTION_SYSTEM", "INSPIRATION_DESCRIPTION_USER"),
"theme": ("INSPIRATION_THEME_SYSTEM", "INSPIRATION_THEME_USER"),
"genre": ("INSPIRATION_GENRE_SYSTEM", "INSPIRATION_GENRE_USER")
}
template_keys = template_key_map.get(step)
if not template_keys:
return {
"error": f"不支持的步骤: {step}",
"prompt": "",
"options": []
}
system_key, user_key = template_keys
# 获取自定义提示词模板
system_template = await PromptService.get_template(system_key, user_id, db)
user_template = await PromptService.get_template(user_key, user_id, db)
# 准备格式化参数
format_params = {
"initial_idea": context.get("initial_idea", context.get("description", "")),
"title": context.get("title", ""),
"description": context.get("description", ""),
"theme": context.get("theme", "")
}
# 格式化提示词
system_prompt = system_template.format(**format_params)
user_prompt = user_template.format(**format_params)
# 添加反馈信息到提示词
feedback_instruction = f"""
⚠️ 用户对之前的选项不太满意，提供了以下反馈：
「{feedback}」
之前生成的选项：
{chr(10).join([f"- {opt}" for opt in previous_options]) if previous_options else "（无）"}
请根据用户的反馈调整生成策略，提供更符合用户期望的新选项。
注意：
1. 仔细理解用户的反馈意图
2. 生成的新选项要明显体现用户要求的调整方向
3. 保持与已有上下文的一致性
4. 确保返回6个有效选项
"""
system_prompt += feedback_instruction
# 如果是重试，强调格式要求
if attempt > 0:
system_prompt += f"\n\n⚠️ 这是第{attempt + 1}次生成，请务必严格按照JSON格式返回！"
# 调用AI生成选项
temperature = TEMPERATURE_SETTINGS.get(step, 0.7)
# 反馈生成时使用稍高的temperature以获得更多样化的结果
temperature = min(temperature + 0.1, 0.9)
logger.info(f"调用AI根据反馈生成{step}选项... (temperature={temperature})")
# 流式生成并累积文本
accumulated_text = ""
async for chunk in ai_service.generate_text_stream(
prompt=user_prompt,
system_prompt=system_prompt,
temperature=temperature
):
accumulated_text += chunk
content = accumulated_text
logger.info(f"AI返回内容长度: {len(content)}")
# 解析JSON
try:
cleaned_content = ai_service._clean_json_response(content)
result = json.loads(cleaned_content)
# 校验返回格式
is_valid, error_msg = validate_options_response(result, step)
if not is_valid:
logger.warning(f"⚠️ 第{attempt + 1}次生成格式校验失败: {error_msg}")
if attempt < max_retries - 1:
logger.info("准备重试...")
continue
else:
return {
"prompt": f"请为【{step}】提供内容：",
"options": ["让AI重新生成", "我自己输入"],
"error": f"AI生成格式错误（{error_msg}），已自动重试{max_retries}次"
}
logger.info(f"✅ 第{attempt + 1}次根据反馈成功生成{len(result.get('options', []))}个有效选项")
return result
except json.JSONDecodeError as e:
logger.error(f"第{attempt + 1}次JSON解析失败: {e}")
if attempt < max_retries - 1:
logger.info("JSON解析失败，准备重试...")
continue
else:
return {
"prompt": f"请为【{step}】提供内容：",
"options": ["让AI重新生成", "我自己输入"],
"error": f"AI返回格式错误，已自动重试{max_retries}次"
}
except Exception as e:
logger.error(f"第{attempt + 1}次根据反馈生成失败: {e}", exc_info=True)
if attempt < max_retries - 1:
logger.info("发生异常，准备重试...")
continue
else:
return {
"error": str(e),
"prompt": "生成失败，请重试",
"options": ["重新生成", "我自己输入"]
}
return {
"error": "生成失败",
"prompt": "请重试",
"options": []
}
@router.post("/quick-generate")
async def quick_generate(
data: Dict[str, Any],
@@ -280,14 +453,17 @@ async def quick_generate(
# 降级使用原有方法
prompts = prompt_service.get_inspiration_quick_complete_prompt(existing=existing_text)
# 调用AI
response = await ai_service.generate_text(
# 调用AI - 流式生成并累积文本
accumulated_text = ""
async for chunk in ai_service.generate_text_stream(
prompt=prompts["user"],
system_prompt=prompts["system"],
temperature=0.7
)
):
accumulated_text += chunk
content = response.get("content", "")
response = {"content": accumulated_text}
content = accumulated_text
# 解析JSON（使用统一的JSON清洗方法）
try: