Customer Support Bot

# Clone the template
git clone https://github.com/xenoISA/quickstart-customer-support
cd quickstart-customer-support
 
# Install
pip install -r requirements.txt
 
# Configure
cp .env.example .env
# Add your ISA_API_KEY to .env
 
# Run
python main.py

quickstart-customer-support/
├── main.py              # FastAPI application
├── agent.py             # Support agent definition
├── knowledge/           # Knowledge base documents
│   ├── faq.md
│   └── product-guide.md
├── routes/
│   ├── chat.py          # Chat endpoints
│   └── webhooks.py      # Ticket webhooks
├── .env.example
└── requirements.txt

# agent.py
from isa_agent_sdk import Agent
from isa_agent_sdk.rag import DocumentStore
 
# Initialize knowledge base
knowledge_base = DocumentStore(
    collection="support-kb",
    embedding_model="text-embedding-3-small"
)
 
# Create the support agent
support_agent = Agent(
    name="support-bot",
    model="claude-sonnet-4-20250514",
    tools=[
        knowledge_base.as_tool(),
        "create_ticket",
        "escalate_to_human"
    ],
    memory={
        "type": "persistent",
        "store": "redis",
        "ttl": 86400  # 24 hours
    },
    system_prompt="""You are a helpful customer support agent for [Company Name].
 
    Guidelines:
    1. Always search the knowledge base first
    2. Be friendly, empathetic, and professional
    3. If you can't resolve an issue, offer to create a ticket
    4. For urgent issues, escalate to human support
 
    Available actions:
    - Search knowledge base for answers
    - Create support ticket
    - Escalate to human agent
    """
)

# main.py
from fastapi import FastAPI
from fastapi.responses import StreamingResponse
from agent import support_agent
from pydantic import BaseModel
 
app = FastAPI(title="Support Bot API")
 
class ChatRequest(BaseModel):
    message: str
    conversation_id: str
    user_id: str
 
@app.post("/chat")
async def chat(request: ChatRequest):
    """Send a message and get a response."""
    response = await support_agent.run(
        request.message,
        context={"user_id": request.user_id},
        conversation_id=request.conversation_id
    )
    return {"response": response.content}
 
@app.post("/chat/stream")
async def chat_stream(request: ChatRequest):
    """Stream the response for real-time display."""
    async def generate():
        async for chunk in support_agent.stream(
            request.message,
            context={"user_id": request.user_id},
            conversation_id=request.conversation_id
        ):
            yield f"data: {chunk.content}\n\n"
        yield "data: [DONE]\n\n"
 
    return StreamingResponse(
        generate(),
        media_type="text/event-stream"
    )

# tools.py
from isa_agent_sdk import tool
import httpx
 
@tool
async def create_ticket(
    title: str,
    description: str,
    priority: str = "medium",
    user_email: str = None
) -> dict:
    """Create a support ticket in the ticketing system.
 
    Args:
        title: Ticket title
        description: Detailed description
        priority: low, medium, high, urgent
        user_email: Customer email
 
    Returns:
        Ticket information with ID
    """
    # Integration with your ticketing system (Zendesk, Freshdesk, etc.)
    async with httpx.AsyncClient() as client:
        response = await client.post(
            "https://api.your-ticketing-system.com/tickets",
            json={
                "title": title,
                "description": description,
                "priority": priority,
                "requester_email": user_email
            },
            headers={"Authorization": f"Bearer {TICKET_API_KEY}"}
        )
        return response.json()
 
@tool
async def escalate_to_human(
    reason: str,
    conversation_id: str,
    urgency: str = "normal"
) -> str:
    """Escalate conversation to human support.
 
    Args:
        reason: Why escalation is needed
        conversation_id: Current conversation ID
        urgency: normal or urgent
 
    Returns:
        Confirmation message
    """
    # Notify human support team
    await notify_support_team(conversation_id, reason, urgency)
    return f"Escalated to human support. A team member will join shortly."

# .env
ISA_API_KEY=your-api-key
REDIS_URL=redis://localhost:6379
TICKET_API_KEY=your-ticketing-api-key

<!-- knowledge/faq.md -->
# Frequently Asked Questions
 
## How do I reset my password?
1. Go to Settings > Security
2. Click "Reset Password"
3. Check your email for the reset link
 
## What payment methods do you accept?
We accept Visa, Mastercard, American Express, and PayPal.

# scripts/ingest_kb.py
from agent import knowledge_base
import asyncio
 
async def main():
    await knowledge_base.ingest("./knowledge/")
    print("Knowledge base updated!")
 
asyncio.run(main())

FROM python:3.11-slim
WORKDIR /app
COPY requirements.txt .
RUN pip install -r requirements.txt
COPY . .
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]

isa deploy --env production