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Conversational AI

Oracle provides a RESTful API to handle user conversations seamlessly. The /chat endpoint interacts with AI agents, maintains chat history, and gracefully handles errors.

        
@app.route("/chat", methods=["POST"])
def chat():
    data = request.json
    agent_index = data.get("agentIndex", 0)
    user_message = data.get("message", "").strip()

    if not user_message:
        return jsonify({"error": "Empty message"}), 400

    agent = get_agent(agent_index)
    persist_chat(agent_index, "user", user_message)

    bot_reply = fetch_openai_response(f"You are a {agent['traits']} assistant.", user_message)
    persist_chat(agent_index, "bot", bot_reply)

    return jsonify({"reply": bot_reply, "history": chat_history[agent_index]})
        
    

API Endpoints for Agent Management

Oracle offers APIs for managing AI agents, enabling seamless customization and management.

        
@app.route('/agents', methods=['POST'])
def create_agent():
    data = request.json
    required_fields = ['name', 'traits']
    for field in required_fields:
        if field not in data:
            return handle_error(f"Missing required field: {field}")

    try:
        new_agent = Agent(
            name=data['name'],
            description=data.get('description', ''),
            traits=data['traits'],
            image=data.get('image'),
            skill=data.get('skill'),
            communication_style=data.get('communication_style'),
            learning_style=data.get('learning_style'),
            response_length=data.get('response_length')
        )
        db.session.add(new_agent)
        db.session.commit()
        return jsonify(new_agent.to_dict()), 201
    except Exception as e:
        db.session.rollback()
        return handle_error(f"Error creating agent: {str(e)}")
        
    

Agent Management

The Agent model defines the structure and attributes of AI agents stored in the PostgreSQL database.

        
class Agent(db.Model):
    __tablename__ = 'agents'

    id = db.Column(db.Integer, primary_key=True)
    name = db.Column(db.String(255), nullable=False)
    description = db.Column(db.Text, nullable=True)
    traits = db.Column(ARRAY(db.String), nullable=False, default=[])
    image = db.Column(db.String(500), nullable=True)
    skill = db.Column(db.String(255), nullable=True)
    communication_style = db.Column(db.String(255), nullable=True)
    learning_style = db.Column(db.String(255), nullable=True)
    response_length = db.Column(db.String(50), nullable=True)
    created_at = db.Column(db.DateTime, default=datetime.utcnow)
    updated_at = db.Column(db.DateTime, default=datetime.utcnow, onupdate=datetime.utcnow)

    def to_dict(self):
        return {
            "id": self.id,
            "name": self.name,
            "description": self.description,
            "traits": self.traits,
            "image": self.image,
            "skill": self.skill,
            "communication_style": self.communication_style,
            "learning_style": self.learning_style,
            "response_length": self.response_length,
            "created_at": self.created_at,
            "updated_at": self.updated_at
        }
        
    

Smart CLI for Initialization

Oracle includes a CLI tool to initialize the database effortlessly.

        
@app.cli.command("init-db")
def init_db():
    """Initialize the database."""
    db.create_all()
    print("Database initialized successfully!")