app.py

import gradio as gr
import requests
import json

# Function to interact with Vectara API
def query_vectara(question, chat_history):
    api_endpoint = "https://api.vectara.io/v1/query"
    customer_id = "<YOUR-CUSTOMER-ID>"
    corpus_id = "<YOUR-CORPUS-ID>"
    api_key = "<YOUR-API-KEY>"

    # Get the user's message from the chat history
    user_message = chat_history[-1][0]

    query_body = {
        "query": [
            {
                "query": user_message,  # Use the user's message as the query
                "start": 0,
                "numResults": 10,
                "corpusKey": [
                    {
                        "customerId": customer_id,
                        "corpusId": corpus_id,
                        "lexicalInterpolationConfig": {"lambda": 0.025}
                    }
                ],
                "contextConfig": {
                    "sentencesBefore": 3,
                    "sentencesAfter": 3,
                    "startTag": "%START_TAG%",
                    "endTag": "%END_TAG%"
                },
                "summary": [
                    {
                        "responseLang": "eng",
                        "maxSummarizedResults": 7,
                        "summarizerPromptName": "vectara-summarizer-ext-v1.3.0"
                    }
                ]
            }
        ]
    }

    post_headers = {
        "Content-type": "application/json",
        "Accept": "application/json",
        "customer-id": customer_id,
        "x-api-key": api_key
    }

    response = requests.post(api_endpoint, json=query_body, headers=post_headers)

    if response.status_code == 200:
        return response.json()
    else:
        return {"error": "Failed to query Vectara API"}

# Create a Gradio ChatInterface
iface = gr.ChatInterface(
    fn=query_vectara,
    examples=["Hello", "What is the weather today?", "Tell me a joke"],
    title="Vectara Chatbot",
    description="Ask me anything using the Vectara API!",
)

# Run the Gradio interface
iface.launch()