Spaces:
Running
on
Zero
Running
on
Zero
test
Browse files- babyagi/classesa/diamond.py +53 -0
- chat_history.db +0 -0
- controllers/gpt_enginner20240623055745 +1 -0
- controllers/gpt_enginner20240623060021 +1 -0
- controllers/gpt_enginner20240623060323 +1 -0
- controllers/gpt_enginner20240623062247 +1 -0
- controllers/gra_02_openInterpreter/OpenInterpreter.py +1 -1
- mysite/routers/diamond.py +138 -0
- workspace/product_info.json +12 -0
babyagi/classesa/diamond.py
CHANGED
@@ -80,6 +80,59 @@ class ProductDatabase:
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results = cursor.fetchall()
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return results
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def main():
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# データベース接続情報
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DATABASE_URL = "postgresql://miyataken999:yz1wPf4KrWTm@ep-odd-mode-93794521.us-east-2.aws.neon.tech/neondb?sslmode=require"
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results = cursor.fetchall()
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return results
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def calculate(x,y,z,c):
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# データベース接続情報
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DATABASE_URL = "postgresql://miyataken999:yz1wPf4KrWTm@ep-odd-mode-93794521.us-east-2.aws.neon.tech/neondb?sslmode=require"
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# ProductDatabaseクラスのインスタンスを作成
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db = ProductDatabase(DATABASE_URL)
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# データベースに接続
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db.connect()
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try:
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# pgvector拡張機能のインストールとカラムの追加
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db.setup_vector_extension_and_column()
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print("Vector extension installed and column added successfully.")
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query_text="1"
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results = db.search_similar_all(query_text)
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print("Search results:")
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DEBUG=0
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if DEBUG==1:
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for result in results:
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print(result)
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id = result[0]
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sample_text = str(result[1])+str(result[2])+str(result[3])+str(result[4])+str(result[5])+str(result[6])+str(result[7])+str(result[8])+str(result[9])
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print(sample_text)
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db.insert_vector(id, sample_text)
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#return
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# サンプルデータの挿入
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#sample_text = """"""
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#sample_product_id = 1 # 実際の製品IDを使用
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#db.insert_vector(sample_product_id, sample_text)
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#db.insert_vector(2, sample_text)
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#print(f"Vector inserted for product ID {sample_product_id}.")
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# ベクトル検索
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query_text = "2.03Very GoodJSI262.058.08.068.125.05"
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query_text = "2.03Very GoodJSI2"
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#query_text = "2.03-Very Good-J-SI2-62.2-58.0-7.27-7.33-4.55"
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results = db.search_similar_vectors(query_text)
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res_all = ""
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print("Search results:")
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for result in results:
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print(result)
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res_all += result+""
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finally:
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# 接続を閉じる
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db.close()
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def main():
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# データベース接続情報
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DATABASE_URL = "postgresql://miyataken999:yz1wPf4KrWTm@ep-odd-mode-93794521.us-east-2.aws.neon.tech/neondb?sslmode=require"
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chat_history.db
CHANGED
Binary files a/chat_history.db and b/chat_history.db differ
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controllers/gpt_enginner20240623055745
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Subproject commit 35fa17068f94587089db2c188dfebe760e97c074
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controllers/gpt_enginner20240623060021
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Subproject commit 33283e43c1fb61111147c97ecf3587ade44b4c4e
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controllers/gpt_enginner20240623060323
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Subproject commit e48e80a8f35468c3d3965d84ddc03745878db6f3
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controllers/gpt_enginner20240623062247
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Subproject commit b14eca59be89da0baf0648650a8a86c6e155572a
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controllers/gra_02_openInterpreter/OpenInterpreter.py
CHANGED
@@ -3,7 +3,7 @@ from mysite.libs.utilities import chat_with_interpreter, completion, process_fil
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from interpreter import interpreter
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import mysite.interpreter.interpreter_config # インポートするだけで設定が適用されます
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import duckdb
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-
from logger import logger
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def format_response(chunk, full_response):
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# Message
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from interpreter import interpreter
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import mysite.interpreter.interpreter_config # インポートするだけで設定が適用されます
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import duckdb
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#from logger import logger
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def format_response(chunk, full_response):
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# Message
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mysite/routers/diamond.py
ADDED
@@ -0,0 +1,138 @@
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# prompt: fastapi route 処理作成 引数は calat wehth state x
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from fastapi import APIRouter, HTTPException
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from babyagi.classesa import da
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import psycopg2
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from sentence_transformers import SentenceTransformer
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from fastapi import APIRouter, HTTPException
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router = APIRouter(prefix="/leaning", tags=["leaning"])
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@router.get("/route/{calat}/{wehth}/{state}/{x}")
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async def route(calat: float, wehth: float, state: str, x: int):
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# Validate input parameters
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if not (0.0 <= calat <= 90.0):
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raise HTTPException(status_code=400, detail="Invalid calat value.")
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if not (0.0 <= wehth <= 180.0):
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raise HTTPException(status_code=400, detail="Invalid wehth value.")
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if state not in ["AC", "AL", "AP", ..., "TO"]:
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raise HTTPException(status_code=400, detail="Invalid state value.")
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if not (0 <= x <= 100):
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raise HTTPException(status_code=400, detail="Invalid x value.")
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# Process the request and return a response
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# ...
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return {"result": "OK"}
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class ProductDatabase:
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def __init__(self, database_url):
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self.database_url = database_url
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self.conn = None
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self.model = SentenceTransformer('sentence-transformers/all-MiniLM-L6-v2')
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def connect(self):
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self.conn = psycopg2.connect(self.database_url)
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def close(self):
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if self.conn:
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self.conn.close()
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def setup_vector_extension_and_column(self):
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with self.conn.cursor() as cursor:
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# pgvector拡張機能のインストール
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cursor.execute("CREATE EXTENSION IF NOT EXISTS vector;")
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# ベクトルカラムの追加
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cursor.execute("ALTER TABLE products ADD COLUMN IF NOT EXISTS vector_col vector(384);")
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self.conn.commit()
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def get_embedding(self, text):
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embedding = self.model.encode(text)
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return embedding
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def insert_vector(self, product_id, text):
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vector = self.get_embedding(text).tolist() # ndarray をリストに変換
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with self.conn.cursor() as cursor:
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cursor.execute("UPDATE diamondprice SET vector_col = %s WHERE id = %s", (vector, product_id))
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self.conn.commit()
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def search_similar_vectors(self, query_text, top_k=50):
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query_vector = self.get_embedding(query_text).tolist() # ndarray をリストに変換
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with self.conn.cursor() as cursor:
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cursor.execute("""
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SELECT id,price,carat, cut, color, clarity, depth, diamondprice.table, x, y, z, vector_col <=> %s::vector AS distance
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FROM diamondprice
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WHERE vector_col IS NOT NULL
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ORDER BY distance asc
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LIMIT %s;
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""", (query_vector, top_k))
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results = cursor.fetchall()
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return results
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def search_similar_all(self, query_text, top_k=5):
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query_vector = self.get_embedding(query_text).tolist() # ndarray をリストに変換
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with self.conn.cursor() as cursor:
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cursor.execute("""
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SELECT id,carat, cut, color, clarity, depth, diamondprice.table, x, y, z
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FROM diamondprice
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order by id asc
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limit 10000000
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""", (query_vector, top_k))
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results = cursor.fetchall()
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return results
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def calculate(x,y,z,c):
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# データベース接続情報
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DATABASE_URL = "postgresql://miyataken999:yz1wPf4KrWTm@ep-odd-mode-93794521.us-east-2.aws.neon.tech/neondb?sslmode=require"
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# ProductDatabaseクラスのインスタンスを作成
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db = ProductDatabase(DATABASE_URL)
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# データベースに接続
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db.connect()
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try:
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# pgvector拡張機能のインストールとカラムの追加
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db.setup_vector_extension_and_column()
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print("Vector extension installed and column added successfully.")
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query_text="1"
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results = db.search_similar_all(query_text)
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print("Search results:")
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DEBUG=0
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if DEBUG==1:
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for result in results:
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print(result)
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id = result[0]
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sample_text = str(result[1])+str(result[2])+str(result[3])+str(result[4])+str(result[5])+str(result[6])+str(result[7])+str(result[8])+str(result[9])
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print(sample_text)
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db.insert_vector(id, sample_text)
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#return
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# サンプルデータの挿入
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#sample_text = """"""
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#sample_product_id = 1 # 実際の製品IDを使用
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#db.insert_vector(sample_product_id, sample_text)
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#db.insert_vector(2, sample_text)
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#print(f"Vector inserted for product ID {sample_product_id}.")
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# ベクトル検索
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query_text = "2.03Very GoodJSI262.058.08.068.125.05"
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query_text = "2.03Very GoodJSI2"
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#query_text = "2.03-Very Good-J-SI2-62.2-58.0-7.27-7.33-4.55"
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results = db.search_similar_vectors(query_text)
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res_all = ""
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print("Search results:")
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for result in results:
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print(result)
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res_all += result+""
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finally:
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# 接続を閉じる
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db.close()
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#router = APIRouter()
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workspace/product_info.json
ADDED
@@ -0,0 +1,12 @@
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{
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"ブランド名": "",
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"モデル名": "",
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"型番や品番": "",
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"購入店": "",
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"購入時期": "",
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"購入金額": "",
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"付属品": "",
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"コンディション": "",
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"貴金属品位": "",
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"貴金属重量": ""
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}
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