Create app.py

app.py

@@ -0,0 +1,66 @@
+import gradio as gr
+import requests
+import json
+
+# Function to interact with Vectara API
+def query_vectara(query_str):
+    api_endpoint = "https://api.vectara.io/v1/query"
+    customer_id = "<YOUR-CUSTOMER-ID>"
+    corpus_id = "<YOUR-CORPUS-ID>"
+    api_key = "<YOUR-API-KEY>"
+
+    query_body = {
+        "query": [
+            {
+                "query": query_str,
+                "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 interface
+iface = gr.Interface(
+    fn=query_vectara,
+    inputs=gr.inputs.Textbox(text="Ask a question:"),
+    outputs=gr.outputs.JSON(),
+    live=True,
+    capture_session=True
+)
+
+# Run the Gradio interface
+iface.launch()