Create app.py

app.py

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+import gradio as gr
+import cohere
+import os
+from dotenv import load_dotenv
+from email.mime.text import MIMEText
+import json
+
+from qdrant_client.models import Distance, VectorParams
+from qdrant_client import QdrantClient, models
+import uuid
+import base64
+import requests
+
+load_dotenv(verbose=True)
+
+#sessuid = ""
+state = gr.State({"loginuser": ""})
+
+# Initialize Qdrant and Cohere clients
+#client = QdrantClient(url=os.environ.get("QDRANT_URL"))
+client = QdrantClient(url="os.environ.get("QDRANT_URL")", api_key="os.environ.get("QDRANT_API_KEY")")
+cohere_client = cohere.Client(api_key=os.environ.get("COHERE_API_KEY"))  # Add your Cohere API key here
+co = cohere.ClientV2(api_key=os.environ.get("COHERE_API_KEY"))
+
+def user_info(state):
+    #print("state:",state)
+    gr.Info("USER INFO: "+state["loginuser"])
+    #username = state["loginuser"]
+    #return username
+
+def auth(user_name, password):
+    encoded = base64.b64encode(password.encode("utf-8"))
+
+    # APIエンドポイントのURL
+    url = "https://www.ryhintl.com/dbjson/getjson?sqlcmd=select userid from ku_credential where password = '" + encoded.decode("utf-8") + "'"
+
+    # GETリクエストの例
+    response = requests.get(url)
+    if response.status_code == 200:
+        credential_id = response.content.decode('utf-8')
+        parsed_data = json.loads(credential_id)
+
+        # useridを取得
+        taken_userid = parsed_data[0]["userid"]
+        if (taken_userid == user_name):
+            state.value["loginuser"] = user_name
+            return True # 認証成功
+        else:
+            return False
+
+def process_invitees(state,input_json):
+    try:
+        # Parse the JSON input
+        invitees = json.loads(input_json)
+
+        # Generate embeddings using Cohere
+        response = cohere_client.embed(
+            texts=[
+                f"{note.get('kx_subject', '')}, {note.get('kx_creator', '')}, {note.get('kx_content', '')}, {note.get('kx_industry', '')}, {note.get('kx_kind', '')}, {note.get('kx_category', '')}, {note.get('kx_date', '')}"
+                for note in invitees
+            ],
+            model="embed-multilingual-v3.0",
+            input_type="search_document",
+        )
+
+        # Upload points to Qdrant
+        client.upload_points(
+            collection_name="knowledge_utility",
+            points=[
+                models.PointStruct(
+                    id=uuid.uuid4().hex,
+                    vector=embedding,
+                    payload=note,
+                )
+                for note, embedding in zip(invitees, response.embeddings)
+            ]
+        )
+
+        return "Data uploaded successfully!"
+
+    except Exception as e:
+        return f"Error: {str(e)}"
+
+# Function to send Gmail
+def send_gmail(mail_from, mail_to, mail_subject, mail_body):
+    try:
+        sent_mails = f"From: {mail_from}\nTo: {mail_to}\nSubject: {mail_subject}\nBody:\n{mail_body}\n"
+    except Exception as e:
+        sent_mails = f"Error sending mail: {str(e)}"
+    return sent_mails
+
+# Function to handle search query
+def search(state,query: str):
+    state["userid"] = state["loginuser"]
+    
+    global sent_mails
+    # Embed query using Cohere
+    response = cohere_client.embed(
+        texts=[query],
+        model="embed-multilingual-v3.0",
+        input_type="search_query",
+    )
+    
+    # Query Qdrant collection for relevant points
+    results = client.query_points(
+        collection_name="knowledge_utility",
+        query=response.embeddings[0],
+        limit=1,
+    ).points
+
+    for result in results:
+        state["score"] = result.score
+        
+    # Filter points based on similarity threshold
+    similarity_threshold = 0.1  # Example threshold for filtering
+    filtered_points = [point for point in results if point.score >= similarity_threshold]
+
+    #print("filtered_points:",filtered_points)
+
+    # Apply limit to the filtered points
+    final_limit = len(filtered_points)  # Example limit
+    limited_points = filtered_points[:final_limit]
+    #print("finals:",final_limit,limited_points)
+
+    # Assuming `results` is a list of ScoredPoint objects
+    payload_list = []
+
+    # Iterate through the limited results and extract payloads
+    for point in limited_points:
+        # Access the payload attribute and append it to the list
+        print("point:",point)
+        payload_list.append(point.payload)
+    
+    #print("payload_list:",payload_list)
+
+    # Template for the invitation letter
+    template = ""
+
+    '''print("kx_subject:",payload_list[0]["kx_subject"])
+    # Generate invitation letters
+    letters = []
+    for invitee in payload_list:
+        # Replace placeholders in the template with actual invitee information
+        letter = template.format(
+            表題=payload_list[0]["kx_subject"],
+            コンテンツ=payload_list[0]["kx_content"],
+            業種=payload_list[0]["kx_industry"],
+            業界=payload_list[0]["kx_kind"],
+            作成者=payload_list[0]["kx_creator"]
+        )
+
+        letters.append(letter)
+
+        print("letters:",letters)
+
+    # Print generated letters
+    invitations = ""
+    for idx, letter in enumerate(letters, start=1):
+        invitations += f"Invitation Letter {idx}:\n{letter}\n"'''
+
+    # Prepare results in a user-friendly format
+    formatted_results = [
+        f"kx_subject: {point.payload['kx_subject']}\nkx_content: {point.payload['kx_content']}\nkx_creator: {point.payload['kx_creator']}\nkx_industry: {point.payload['kx_industry']}\nkx_kind: {point.payload['kx_kind']}\nkx_category: {point.payload['kx_category']}\nkx_date: {point.payload['kx_date']}"
+        for point in results
+    ]
+
+    #print("formatted_results",formatted_results)
+    final_result = "\n\n".join(formatted_results)
+
+    res = co.chat(
+    model="command-a-03-2025",
+    messages=[
+        {
+            "role": "user",
+            "content": final_result+"を要約してください。 必ず、日本語で答えてください。",
+        }
+    ],
+    )
+    final = res.message.content[0].text
+
+    # Extract content between "---"
+    start_marker = "---"
+    end_marker = "---"
+    start_index = final.find(start_marker) + len(start_marker)
+    end_index = final.rfind(end_marker)
+
+    return final,state["score"]
+
+# Gradio Blocks Interface
+with gr.Blocks(css="footer {visibility: hidden;} .custom-btn {width: 150px; height: 30px; background-color: lightblue; border-radius: 10px; font-size: 12px; color: #3C82F6;} #header {display: flex; justify-content: space-between; align-items: center; font-size: 24px; font-weight: bold;} #logo {width: 50px; height: 50px;}",title="Knowledge Utility",theme=gr.themes.Glass()) as ku:
+    state = gr.State({
+        "userid": "",
+        "score": 0
+    })
+
+    with gr.Column():
+        gr.HTML('<div id="header"><span>🛡️ Knowledge Utility</span><img id="logo" src="https://www.ryhintl.com/images/ryhlogo/ryhlogo.png" width="64" height="64" alt="Logo"></div>')
+        gr.Markdown("# ナレッジ・エージェント")
+        gr.Markdown("📧 ベクターDBに保存されている知識ベースのインベントリを使用して知識共有します。")
+        user_btn = gr.Button("ユーザー情報", elem_classes=["custom-btn"])
+
+    user_btn.click(fn=user_info, inputs=[state], outputs=None)
+
+
+    with gr.Sidebar(open=False):
+        gr.HTML("""
+        <!DOCTYPE html>
+        <html lang="ja">
+        <head>
+        <meta charset="UTF-8">
+        <meta name="viewport" content="width=device-width, initial-scale=1.0">
+        <title>Knowledge Utility</title>
+        <style>
+        body {
+            font-family: Arial, sans-serif;
+            line-height: 1.6;
+            background-color: #f4f4f9;
+            color: #333;
+            margin: 0;
+            padding: 0;
+        }
+        header {
+            background: #0078d7;
+            color: #fff;
+            padding: 1rem 0;
+            text-align: center;
+        }
+        section {
+            max-width: 800px;
+            margin: 2rem auto;
+            padding: 1rem;
+            background: #fff;
+            border-radius: 5px;
+            box-shadow: 0 2px 4px rgba(0, 0, 0, 0.1);
+        }
+        h1, h2, h3 {
+            color: #0078d7;
+        }
+        ul {
+            padding-left: 1.5rem;
+        }
+        footer {
+            text-align: center;
+            padding: 1rem 0;
+            margin-top: 2rem;
+            background: #0078d7;
+            color: white;
+        }
+        </style>
+        </head>
+        <body>
+        <header>
+            <h1 style="color: white;">Knowledge Utility</h1>
+            <p style="color: white;">知識をシェアし、成長を加速させる。</p>
+        </header>
+        <section>
+            <h2>Knowledge Utilityとは？</h2>
+            <p>
+                Knowledge Utilityは、企業や個人が知識を効果的に共有し、成長を促進するためのプラットフォームです。
+                データ、アイデア、専門知識をシームレスに交換し、新たな価値を生み出します。
+            </p>
+        <h2>主な機能</h2>
+        <ul>
+            <li><strong>情報の検索:</strong> 高速かつ正確なクエリによる知識の取得。</li>
+            <li><strong>データの登録:</strong> 個人または企業の資産をデータベースに統合。</li>
+            <li><strong>コラボレーション:</strong> チームやコミュニティ間の知識交換を促進。</li>
+        </ul>
+        <h2>メリット</h2>
+        <p>
+            Knowledge Utilityを活用することで、効率の向上、意思決定のスピードアップ、そして
+            組織の成長が期待できます。
+        </p>
+        </section>
+        <footer>
+            <p>&copy; 2025 Knowledge Utility Platform. All rights reserved.</p>
+        </footer>
+        </body>
+        </html>
+    """)
+
+    with gr.Tab("KU 検索"):
+        with gr.Row():
+            query_input = gr.Textbox(
+                label="クエリ",
+                placeholder="例）物流・流通業界向けの提案書を内容を教えてください。",
+                info="例）物流・流通業界向けの提案書を内容を教えてください。", 
+                value="経営デジタル・トランスフォーメーション関連のプロジェクトの提案書を書こうと思っています。参考できる事例を教えてください。",
+                lines=2,
+            )
+            with gr.Column():
+                search_button = gr.Button("実行", elem_classes=["custom-btn"])
+                clear_button = gr.Button("クリア", elem_classes=["custom-btn"])
+    
+        result_output = [gr.Textbox(label="結果", show_copy_button=True),gr.Textbox(label="スコア")]
+
+        # Button click events
+        search_button.click(fn=search, inputs=[state,query_input], outputs=result_output)
+        clear_button.click(lambda: "", None, result_output)
+
+    with gr.Tab("KU インベントリ登録"):
+        with gr.Row():
+            input_text = gr.Textbox(label="KU JSON Payroll", lines=10, placeholder="Paste your JSON Payroll here...", info="""[{"kx_subject": "中古車販売における現状と問題点", "kx_creator": "richardhuh0629@gmail.com", "kx_content": "事前情報の収集: 顧客動向、問題・課題の想定、3C分析を通じて仮説を策定する。企業動向、顧客動向、競合動向を分析し、仮説を立案する。仮説提案営業の商談フロー: あいさつ、自社紹介、詳細ヒアリング、仮説検証、解決策の提案、ディスカッション、宿題の出し合い、あいさつのステップを踏む。効果的な商談の進め方: 訪問の趣旨を伝え、基本的な質問をし、相手に話させる。仮説をぶつけ、次回の日付と宿題を決める。ヒアリングの技術: 荷主担当者と営業担当者の知識の差を理解し、必要に応じて役割を分担する。ロジスティクスフローを描き、詳細な設問項目を作成する。", "kx_industry": "物流・流通", "kx_kind": "小売", "kx_category": "提案書", "kx_date": "2025/06/02"}]""")
+            output_text = gr.Textbox(label="Result")
+        with gr.Row():
+            submit_button = gr.Button("実行", elem_classes=["custom-btn"])
+
+        submit_button.click(process_invitees, inputs=[state,input_text], outputs=output_text)
+
+# Launch the app
+ku.launch(auth=auth,favicon_path="favicon.ico")