app.py

import gradio as gr
import cohere
import difflib

# Replace with your actual Cohere API Key
co = cohere.Client("YOUR_COHERE_API_KEY")

# Hardcoded FAQ knowledge base
faq_data = {
    "What does the eligibility verification agent (EVA) do?":
        "EVA automates the process of verifying a patient’s eligibility and benefits information in real-time, eliminating manual data entry errors and reducing claim rejections.",
    "What does the claims processing agent (CAM) do?":
        "CAM streamlines the submission and management of claims, improving accuracy, reducing manual intervention, and accelerating reimbursements.",
    "How does the payment posting agent (PHIL) work?":
        "PHIL automates the posting of payments to patient accounts, ensuring fast, accurate reconciliation of payments and reducing administrative burden.",
    "Tell me about Thoughtful AI's Agents.":
        "Thoughtful AI provides a suite of AI-powered automation agents designed to streamline healthcare processes. These include Eligibility Verification (EVA), Claims Processing (CAM), and Payment Posting (PHIL), among others.",
    "What are the benefits of using Thoughtful AI's agents?":
        "Using Thoughtful AI's Agents can significantly reduce administrative costs, improve operational efficiency, and reduce errors in critical processes like claims management and payment posting."
}

SIMILARITY_THRESHOLD = 0.7

def get_faq_answer(user_input):
    questions = list(faq_data.keys())
    match = difflib.get_close_matches(user_input, questions, n=1, cutoff=SIMILARITY_THRESHOLD)
    return faq_data[match[0]] if match else None

def thoughtful_response(user_input, chat_history):
    # Append user message
    chat_history.append({"role": "user", "content": user_input})

    # Check hardcoded knowledge base first
    faq_answer = get_faq_answer(user_input)
    if faq_answer:
        response = f"🧠 Thoughtful AI Agent:\n\n{faq_answer}"
    else:
        try:
            result = co.chat(
                message=user_input,
                model="command-r-plus",
                temperature=0.7,
                chat_history=[]  # You can optionally build chat history here
            )
            response = f"🤖 Cohere:\n\n{result.text}"
        except Exception as e:
            response = f"⚠️ Error from Cohere: {e}"

    # Append assistant response
    chat_history.append({"role": "assistant", "content": response})
    return chat_history, chat_history

# Build Gradio UI
with gr.Blocks(title="Thoughtful AI Support Agent") as demo:
    gr.Markdown("## 💬 Thoughtful AI Support Agent\nAsk me about our automation agents. If I don’t know, I’ll ask my smart friend (Cohere)!")

    chatbot = gr.Chatbot(label="Support Chat", type="messages")
    user_input = gr.Textbox(placeholder="Ask a question about Thoughtful AI...", lines=1)
    send_button = gr.Button("Send")

    state = gr.State([])

    send_button.click(fn=thoughtful_response, inputs=[user_input, state], outputs=[chatbot, state])
    user_input.submit(fn=thoughtful_response, inputs=[user_input, state], outputs=[chatbot, state])

# Launch with shareable link
demo.launch(ssr_mode=False, share=True)