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HuangHai 2 weeks ago
parent 3c655d4ca1
commit 0f184f08a6
8 changed files with 107 additions and 107 deletions
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40
dsLightRag/StartPG.py → dsLightRag/Backup/Start.py
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@ -43,14 +43,16 @@ async def print_stream(stream):
app = FastAPI(lifespan=lifespan)
# 挂载静态文件目录
app.mount("/static", StaticFiles(directory="Static"), name="static")
app.mount("../static", StaticFiles(directory="Static"), name="static")
@app.post("/api/rag")
async def rag(request: fastapi.Request):
data = await request.json()
workspace = data.get("topic") # Chinese, Math
topic = data.get("topic") # Chinese, Math
mode = data.get("mode", "hybrid") # 默认为hybrid模式
# 拼接路径
WORKING_PATH = "./Topic/" + topic
# 查询的问题
query = data.get("query")
# 关闭参考资料
@ -60,12 +62,17 @@ async def rag(request: fastapi.Request):
user_prompt = user_prompt + "\n 4、资料中提到的知识内容，需要判断是否与本次问题相关，不相关的绝对不要输出！"
user_prompt = user_prompt + "\n 5、如果问题与提供的知识库内容不符，则明确告诉未在知识库范围内提到！"
user_prompt = user_prompt + "\n 6、发现输出内容中包含Latex公式的，一定要检查是不是包含了$$或$的包含符号,不能让Latex无包含符号出现！"
# 使用PG库后，这个是没有用的,但目前的项目代码要求必传，就写一个吧。
WORKING_DIR = f"./output"
async def generate_response_stream(query: str):
try:
rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace=workspace)
rag = LightRAG(
working_dir=WORKING_PATH,
llm_model_func=create_llm_model_func(),
embedding_func=create_embedding_func()
)
await rag.initialize_storages()
await initialize_pipeline_status()
resp = await rag.aquery(
query=query,
param=QueryParam(mode=mode, stream=True, user_prompt=user_prompt))
@ -140,7 +147,7 @@ async def get_tree_data():
try:
pg_pool = await init_postgres_pool()
async with pg_pool.acquire() as conn:
# 执行查询
# 执行查询
rows = await conn.fetch("""
SELECT id,
title,
@ -211,22 +218,23 @@ async def update_knowledge(request: fastapi.Request):
SET prerequisite = $1
WHERE id = $2
""",
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
else: # related knowledge
await conn.execute("""
UPDATE knowledge_points
SET related = $1
WHERE id = $2
""",
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
return {"code": 0, "msg": "更新成功"}
except Exception as e:

0
dsLightRag/T1_Train.py → dsLightRag/Backup/T1_Train.py
Unescape View File

46
dsLightRag/Backup/T2_Query.py
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@ -0,0 +1,46 @@
import asyncio
import inspect
from Util.LightRagUtil import configure_logging, initialize_rag, print_stream
from lightrag import QueryParam
# 化学
data = [
# {"NAME": "Chemistry", "Q": "硝酸光照分解的化学反应方程式是什么", "ChineseName": "化学"},
{"NAME": "Chemistry", "Q": "氢气与氧气燃烧的现象", "ChineseName": "化学"},
{"NAME": "Math", "Q": "氧化铁与硝酸的化学反应方程式是什么", "ChineseName": "数学"},
{"NAME": "Chinese", "Q": "氧化铁与硝酸的化学反应方程式是什么", "ChineseName": "语文"},
{"NAME": "JiHe", "Q": "三角形两边之和大于第三边的证明", "ChineseName": "几何"}
]
# 准备查询的科目
KEMU = "JiHe" # Chemistry JiHe
# 查找索引号
idx = [i for i, d in enumerate(data) if d["NAME"] == KEMU][0]
async def main():
try:
user_prompt = "\n 1、资料中提供化学反应方程式的，一定要严格按提供的Latex公式输出，绝对不允许对Latex公式进行修改 ！"
user_prompt = user_prompt + "\n 2、如果资料中提供了图片的，一定要严格按照原文提供图片输出，不允许省略或不输出！"
user_prompt = user_prompt + "\n 3、资料中提到的知识内容，需要判断是否与本次问题相关，不相关的绝对不要输出！"
rag = await initialize_rag('Topic/' + data[idx]["NAME"])
resp = await rag.aquery(
data[idx]["Q"],
param=QueryParam(mode="hybrid", stream=True, user_prompt=user_prompt),
# hybrid naive
)
if inspect.isasyncgen(resp):
await print_stream(resp)
else:
print(resp)
except Exception as e:
print(f"An error occurred: {e}")
finally:
if rag:
await rag.finalize_storages()
if __name__ == "__main__":
configure_logging()
asyncio.run(main())

0
dsLightRag/Backup/__init__.py
Unescape View File

38
dsLightRag/Start.py
Unescape View File

@ -49,10 +49,8 @@ app.mount("/static", StaticFiles(directory="Static"), name="static")
@app.post("/api/rag")
async def rag(request: fastapi.Request):
data = await request.json()
topic = data.get("topic") # Chinese, Math
workspace = data.get("topic") # Chinese, Math
mode = data.get("mode", "hybrid") # 默认为hybrid模式
# 拼接路径
WORKING_PATH = "./Topic/" + topic
# 查询的问题
query = data.get("query")
# 关闭参考资料
@ -62,17 +60,12 @@ async def rag(request: fastapi.Request):
user_prompt = user_prompt + "\n 4、资料中提到的知识内容，需要判断是否与本次问题相关，不相关的绝对不要输出！"
user_prompt = user_prompt + "\n 5、如果问题与提供的知识库内容不符，则明确告诉未在知识库范围内提到！"
user_prompt = user_prompt + "\n 6、发现输出内容中包含Latex公式的，一定要检查是不是包含了$$或$的包含符号,不能让Latex无包含符号出现！"
# 使用PG库后，这个是没有用的,但目前的项目代码要求必传，就写一个吧。
WORKING_DIR = f"./output"
async def generate_response_stream(query: str):
try:
rag = LightRAG(
working_dir=WORKING_PATH,
llm_model_func=create_llm_model_func(),
embedding_func=create_embedding_func()
)
await rag.initialize_storages()
await initialize_pipeline_status()
rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace=workspace)
resp = await rag.aquery(
query=query,
param=QueryParam(mode=mode, stream=True, user_prompt=user_prompt))
@ -147,7 +140,7 @@ async def get_tree_data():
try:
pg_pool = await init_postgres_pool()
async with pg_pool.acquire() as conn:
# 执行查询
# 执行查询
rows = await conn.fetch("""
SELECT id,
title,
@ -218,23 +211,22 @@ async def update_knowledge(request: fastapi.Request):
SET prerequisite = $1
WHERE id = $2
""",
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
else: # related knowledge
await conn.execute("""
UPDATE knowledge_points
SET related = $1
WHERE id = $2
""",
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
json.dumps(
[{"id": p["id"], "title": p["title"]} for p in knowledge],
ensure_ascii=False
),
node_id)
return {"code": 0, "msg": "更新成功"}
except Exception as e:

42
dsLightRag/T2_Query.py
Unescape View File

@ -1,34 +1,36 @@
import asyncio
import inspect
from Util.LightRagUtil import configure_logging, initialize_rag, print_stream
import logging
from lightrag import QueryParam
# 化学
data = [
# {"NAME": "Chemistry", "Q": "硝酸光照分解的化学反应方程式是什么", "ChineseName": "化学"},
{"NAME": "Chemistry", "Q": "氢气与氧气燃烧的现象", "ChineseName": "化学"},
{"NAME": "Math", "Q": "氧化铁与硝酸的化学反应方程式是什么", "ChineseName": "数学"},
{"NAME": "Chinese", "Q": "氧化铁与硝酸的化学反应方程式是什么", "ChineseName": "语文"},
{"NAME": "JiHe", "Q": "三角形两边之和大于第三边的证明", "ChineseName": "几何"}
]
from Util.LightRagUtil import configure_logging, print_stream, initialize_pg_rag
# 在程序开始时添加以下配置
logging.basicConfig(
level=logging.INFO, # 设置日志级别为INFO
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# 或者如果你想更详细地控制日志输出
logger = logging.getLogger('lightrag')
logger.setLevel(logging.INFO)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
logger.addHandler(handler)
# 准备查询的科目
KEMU = "JiHe" # Chemistry JiHe
WORKING_DIR = f"./dsWorking"
# 查找索引号
idx = [i for i, d in enumerate(data) if d["NAME"] == KEMU][0]
logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO)
async def main():
try:
user_prompt = "\n 1、资料中提供化学反应方程式的，一定要严格按提供的Latex公式输出，绝对不允许对Latex公式进行修改 ！"
user_prompt = user_prompt + "\n 2、如果资料中提供了图片的，一定要严格按照原文提供图片输出，不允许省略或不输出！"
user_prompt = user_prompt + "\n 3、资料中提到的知识内容，需要判断是否与本次问题相关，不相关的绝对不要输出！"
rag = await initialize_rag('Topic/' + data[idx]["NAME"])
rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace='SuShi')
resp = await rag.aquery(
data[idx]["Q"],
param=QueryParam(mode="hybrid", stream=True, user_prompt=user_prompt),
# hybrid naive
# "苏轼的家人都有谁？",
"苏轼与美食",
param=QueryParam(mode="hybrid", stream=True),
)
if inspect.isasyncgen(resp):
await print_stream(resp)

48
dsLightRag/T5_QueryPg.py
Unescape View File

@ -1,48 +0,0 @@
import asyncio
import inspect
import logging
from lightrag import QueryParam
from Util.LightRagUtil import configure_logging, print_stream, initialize_pg_rag
# 在程序开始时添加以下配置
logging.basicConfig(
level=logging.INFO, # 设置日志级别为INFO
format='%(asctime)s - %(name)s - %(levelname)s - %(message)s'
)
# 或者如果你想更详细地控制日志输出
logger = logging.getLogger('lightrag')
logger.setLevel(logging.INFO)
handler = logging.StreamHandler()
handler.setFormatter(logging.Formatter('%(asctime)s - %(name)s - %(levelname)s - %(message)s'))
logger.addHandler(handler)
WORKING_DIR = f"./dsWorking"
logging.basicConfig(format="%(levelname)s:%(message)s", level=logging.INFO)
async def main():
try:
rag = await initialize_pg_rag(WORKING_DIR=WORKING_DIR, workspace='SuShi')
resp = await rag.aquery(
# "苏轼的家人都有谁？",
"苏轼与美食",
param=QueryParam(mode="hybrid", stream=True),
)
if inspect.isasyncgen(resp):
await print_stream(resp)
else:
print(resp)
except Exception as e:
print(f"An error occurred: {e}")
finally:
if rag:
await rag.finalize_storages()
if __name__ == "__main__":
configure_logging()
asyncio.run(main())

0
dsLightRag/T4_TrainPg.py → dsLightRag/T_Train.py
Unescape View File

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