Initial implementation of the chat application with MariaDB and ArangoDB integration, including Docker setup and web interface.

api/app.py

@@ -0,0 +1,70 @@
+from flask import Flask, request, jsonify
+import mysql.connector
+import requests
+import os
+from arango import ArangoClient
+
+app = Flask(__name__)
+
+# MariaDB Verbindung
+def get_db():
+    return mysql.connector.connect(
+        host=os.environ['DB_HOST'],
+        user=os.environ['DB_USER'],
+        password=os.environ['DB_PASSWORD'],
+        database=os.environ['DB_NAME']
+    )
+
+# ArangoDB Verbindung
+def get_arango():
+    client = ArangoClient(hosts=os.environ['ARANGO_URL'])
+    sys_db = client.db('_system', username=os.environ['ARANGO_USER'], password=os.environ['ARANGO_PASSWORD'])
+    if not sys_db.has_database('llm_facts'):
+        sys_db.create_database('llm_facts')
+    db = client.db('llm_facts', username=os.environ['ARANGO_USER'], password=os.environ['ARANGO_PASSWORD'])
+    if not db.has_collection('facts'):
+        db.create_collection('facts')
+    return db.collection('facts')
+
+# Skill-Trigger
+def extract_fact(text):
+    triggers = ["merke dir", "notiere", "speichere"]
+    for t in triggers:
+        if text.lower().startswith(t):
+            fact = text[len(t):].strip()
+            return fact
+    return None
+
+@app.route("/chat", methods=["POST"])
+def chat():
+    data = request.json
+    project = data.get("project")
+    message = data.get("message")
+
+    # Lernbefehl
+    fact = extract_fact(message)
+    if fact:
+        arango = get_arango()
+        arango.insert({
+            "_raw": message,
+            "_source": project,
+            "content": fact,
+            "tags": ["skill:merke"],
+            "relations": []
+        })
+        return jsonify({"reply": f"Fakt gespeichert: {fact}"})
+
+    # Chat speichern in MariaDB
+    db = get_db()
+    cursor = db.cursor()
+    cursor.execute("INSERT INTO chats (project, user_input) VALUES (%s,%s)", (project, message))
+    db.commit()
+    cursor.close()
+    db.close()
+
+    # Anfrage an LLM
+    resp = requests.post(f"{os.environ['LM_API_URL']}/generate", json={"prompt": message})
+    return jsonify({"reply": resp.json()})
+
+if __name__ == "__main__":
+    app.run(host="0.0.0.0", port=5000)