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import gradio as gr |
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import requests |
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from fastapi import FastAPI |
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from fastapi.testclient import TestClient |
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from routes import query_handler, purchase, order_management, account_management, customer_support, search_products |
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app = FastAPI() |
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app.include_router(purchase.router, prefix="/purchase", tags=["purchase"]) |
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app.include_router(order_management.router, |
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prefix="/order-management", tags=["order-management"]) |
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app.include_router(account_management.router, |
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prefix="/account-management", tags=["account-management"]) |
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app.include_router(customer_support.router, |
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prefix="/customer-support", tags=["customer-support"]) |
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app.include_router(search_products.router, |
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prefix="/search-products", tags=["search-products"]) |
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app.include_router(query_handler.router, |
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prefix="/query-handler", tags=["query-handler"]) |
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client = TestClient(app) |
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def fastlane_agent(message, history): |
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history_openai_format = [ |
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{"role": "system", "content": "You are an assistant for an eCommerce store."}] |
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for human, assistant in history: |
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history_openai_format.append({"role": "user", "content": human}) |
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history_openai_format.append( |
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{"role": "assistant", "content": assistant}) |
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history_openai_format.append({"role": "user", "content": message}) |
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response = client.post("/query-handler/", json={"text": message, "history": history_openai_format}) |
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if response.status_code == 200: |
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return response.json().get("generative response") |
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else: |
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return "Error: Could not fetch response." |
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iface = gr.ChatInterface( |
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fn=fastlane_agent, |
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chatbot=gr.Chatbot(height=400), |
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textbox=gr.Textbox( |
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placeholder="How can I help you?", container=False, scale=7 |
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), |
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title="Fastlane Chat GPT", |
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description="AI sales assistance for e-commmerce", |
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theme="soft", |
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examples=["Hello", "What is the status of my order?", |
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"Recommend me products"], |
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cache_examples=True, |
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retry_btn=None, |
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undo_btn="Delete Previous", |
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clear_btn="Clear" |
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).launch() |
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app = gr.mount_gradio_app(app, iface, path="./") |
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