main
HuangHai 4 weeks ago
parent 1fc0d454d7
commit fe86c88161

@ -41,8 +41,6 @@ async def lifespan(app: FastAPI):
# 初始化阿里云大模型工具
app.state.aliyun_util = ALiYunUtil()
yield
# 清理资源
await app.state.aliyun_util.close()
app = FastAPI(lifespan=lifespan)
# 挂载静态文件目录
@ -124,7 +122,17 @@ async def rag_stream(request: Request):
es_conn = es_search_util.es_pool.get_connection()
try:
# 向量搜索
logger.info(f"\n=== 开始执行查询 ===")
logger.info(f"原始查询文本: {query}")
logger.info(f"查询标签: {query_tags}")
logger.info("\n=== 向量搜索阶段 ===")
logger.info("1. 文本分词和向量化处理中...")
query_embedding = es_search_util.text_to_embedding(query)
logger.info(f"2. 生成的查询向量维度: {len(query_embedding)}")
logger.info(f"3. 前3维向量值: {query_embedding[:3]}")
logger.info("4. 正在执行Elasticsearch向量搜索...")
vector_results = es_conn.search(
index=ES_CONFIG['index_name'],
body={
@ -151,8 +159,11 @@ async def rag_stream(request: Request):
"size": 3
}
)
logger.info(f"5. 向量搜索结果数量: {len(vector_results['hits']['hits'])}")
# 文本精确搜索
logger.info("\n=== 文本精确搜索阶段 ===")
logger.info("1. 正在执行Elasticsearch文本精确搜索...")
text_results = es_conn.search(
index=ES_CONFIG['index_name'],
body={
@ -175,15 +186,66 @@ async def rag_stream(request: Request):
"size": 3
}
)
logger.info(f"2. 文本搜索结果数量: {len(text_results['hits']['hits'])}")
# 合并结果
results = {
logger.info("\n=== 最终搜索结果 ===")
logger.info(f"向量搜索结果: {len(vector_results['hits']['hits'])}")
for i, hit in enumerate(vector_results['hits']['hits'], 1):
logger.info(f" {i}. 文档ID: {hit['_id']}, 相似度分数: {hit['_score']:.2f}")
logger.info(f" 内容: {hit['_source']['user_input']}")
logger.info("文本精确搜索结果:")
for i, hit in enumerate(text_results['hits']['hits']):
logger.info(f" {i+1}. 文档ID: {hit['_id']}, 匹配分数: {hit['_score']:.2f}")
logger.info(f" 内容: {hit['_source']['user_input']}")
search_results = {
"vector_results": [hit['_source'] for hit in vector_results['hits']['hits']],
"text_results": [hit['_source'] for hit in text_results['hits']['hits']]
}
return results
# 调用阿里云大模型整合结果
aliyun_util = request.app.state.aliyun_util
# 构建提示词
context = "\n".join([
f"结果{i+1}: {res['tags']['full_content']}"
for i, res in enumerate(search_results['vector_results'] + search_results['text_results'])
])
prompt = f"""
信息检索与回答助手
根据以下关于'{query}'的相关信息
基本信息
- 语言: 中文
- 描述: 根据提供的材料检索信息并回答问题
- 特点: 快速准确提取关键信息清晰简洁地回答
相关信息
{context}
回答要求
1. 依托给定的资料快速准确地回答问题可以添加一些额外的信息但请勿重复内容
2. 如果未提供相关信息请不要回答
3. 如果发现相关信息与原来的问题契合度低也不要回答
4. 使用HTML格式返回包含适当的段落列表和标题标签
5. 确保内容结构清晰便于前端展示
"""
# 调用阿里云大模型
if len(context) > 0:
# 调用大模型生成回答
html_content = aliyun_util.chat(prompt)
return {"data": html_content}
else:
logger.warning(f"未找到查询'{query}'的相关数据tags: {query_tags}")
return {"data": "没有在知识库中找到相关的信息,无法回答此问题。", "debug": {"query": query, "tags": query_tags}}
except Exception as e:
return {"data": f"生成报告时出错: {str(e)}"}
finally:
es_search_util.es_pool.release_connection(es_conn)

@ -219,15 +219,15 @@
<h3>知识库范围</h3>
<div class="doc-checkboxes">
<label>
<input type="checkbox" name="documents" value="MATH_1">
<input type="checkbox" name="tags" value="MATH_1">
小学数学教学中的若干问题
</label>
<label>
<input type="checkbox" name="documents" value="MATH_2">
<input type="checkbox" name="tags" value="MATH_2">
小学数学知识点
</label>
<label>
<input type="checkbox" name="documents" value="CHINESE_1">
<input type="checkbox" name="tags" value="CHINESE_1">
高中语文文言文
</label>
</div>
@ -254,7 +254,7 @@
function submitQuestion() {
const question = document.getElementById('questionInput').value.trim();
const checkboxes = document.querySelectorAll('input[name="documents"]:checked');
const checkboxes = document.querySelectorAll('input[name="tags"]:checked');
if (!question) {
alert('请输入问题!');
@ -278,7 +278,7 @@
},
body: JSON.stringify({
query: question,
documents: selectedDocs
tags: selectedDocs // 使用selectedDocs作为tags参数
})
})
.then(response => response.json()) // 改回使用json()
@ -300,12 +300,12 @@
function clearAll() {
document.getElementById('questionInput').value = '';
document.getElementById('answerArea').innerHTML = '';
document.querySelectorAll('input[name="documents"]').forEach(cb => cb.checked = false);
document.querySelectorAll('input[name="tags"]').forEach(cb => cb.checked = false);
}
function saveToWord() {
const htmlContent = document.getElementById('answerArea').innerHTML;
const checkboxes = document.querySelectorAll('input[name="documents"]:checked');
const checkboxes = document.querySelectorAll('input[name="tags"]:checked');
if (!htmlContent) {
alert('没有内容可保存!');
@ -317,7 +317,7 @@
return;
}
const selectedDocs = Array.from(checkboxes).map(cb => cb.value);
const selectTags = Array.from(checkboxes).map(cb => cb.value);
const loader = document.getElementById('loader');
loader.style.display = 'block';
@ -329,7 +329,7 @@
},
body: JSON.stringify({
html_content: htmlContent,
documents: selectedDocs
tags: selectTags
})
})
.then(response => response.blob())

@ -0,0 +1,68 @@
D:\anaconda3\envs\rag\python.exe D:\dsWork\dsProject\dsRag\StartEs.py
INFO: Started server process [28828]
INFO: Waiting for application startup.
INFO: Application startup complete.
INFO: Uvicorn running on http://0.0.0.0:8000 (Press CTRL+C to quit)
INFO: 10.10.21.22:50333 - "GET /static/ai.html HTTP/1.1" 304 Not Modified
INFO: 10.10.21.22:50333 - "POST /api/rag HTTP/1.1" 500 Internal Server Error
ERROR: Exception in ASGI application
Traceback (most recent call last):
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\encoders.py", line 324, in jsonable_encoder
data = dict(obj)
TypeError: 'async_generator' object is not iterable
During handling of the above exception, another exception occurred:
Traceback (most recent call last):
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\encoders.py", line 329, in jsonable_encoder
data = vars(obj)
TypeError: vars() argument must have __dict__ attribute
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "D:\anaconda3\envs\rag\lib\site-packages\uvicorn\protocols\http\h11_impl.py", line 403, in run_asgi
result = await app( # type: ignore[func-returns-value]
File "D:\anaconda3\envs\rag\lib\site-packages\uvicorn\middleware\proxy_headers.py", line 60, in __call__
return await self.app(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\applications.py", line 1054, in __call__
await super().__call__(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\applications.py", line 112, in __call__
await self.middleware_stack(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\middleware\errors.py", line 187, in __call__
raise exc
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\middleware\errors.py", line 165, in __call__
await self.app(scope, receive, _send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\middleware\exceptions.py", line 62, in __call__
await wrap_app_handling_exceptions(self.app, conn)(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\_exception_handler.py", line 53, in wrapped_app
raise exc
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\routing.py", line 714, in __call__
await self.middleware_stack(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\routing.py", line 734, in app
await route.handle(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\routing.py", line 288, in handle
await self.app(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\routing.py", line 76, in app
await wrap_app_handling_exceptions(app, request)(scope, receive, send)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\_exception_handler.py", line 53, in wrapped_app
raise exc
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\_exception_handler.py", line 42, in wrapped_app
await app(scope, receive, sender)
File "D:\anaconda3\envs\rag\lib\site-packages\starlette\routing.py", line 73, in app
response = await f(request)
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\routing.py", line 327, in app
content = await serialize_response(
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\routing.py", line 201, in serialize_response
return jsonable_encoder(response_content)
File "D:\anaconda3\envs\rag\lib\site-packages\fastapi\encoders.py", line 332, in jsonable_encoder
raise ValueError(errors) from e
ValueError: [TypeError("'async_generator' object is not iterable"), TypeError('vars() argument must have __dict__ attribute')]
INFO: Shutting down
INFO: Waiting for application shutdown.
INFO: Application shutdown complete.
INFO: Finished server process [28828]
进程已结束,退出代码为 0
Loading…
Cancel
Save