Update app.py

app.py

@@ -3,62 +3,45 @@ import requests
 import json
 
 # Function to interact with Vectara API
-def query_vectara(question, chat_history):
-    api_endpoint = "https://api.vectara.io/v1/query"
+def query_vectara(question, chat_history, uploaded_file):
+    # Handle file upload here (using the provided code)
     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"
-                    }
-                ]
-            }
-        ]
-    }
+    url = f"https://api.vectara.io/v1/upload?c={customer_id}&o={corpus_id}"
 
     post_headers = {
-        "Content-type": "application/json",
-        "Accept": "application/json",
-        "customer-id": customer_id,
-        "x-api-key": api_key
+        "x-api-key": api_key,
+        "customer-id": customer_id
     }
 
-    response = requests.post(api_endpoint, json=query_body, headers=post_headers)
+    files = {
+        "file": (uploaded_file.name, uploaded_file),
+        "doc_metadata": (None, json.dumps({"metadata_key": "metadata_value"})),  # Replace with your metadata
+    }
+    response = requests.post(url, files=files, verify=True, headers=post_headers)
 
     if response.status_code == 200:
-        return response.json()
+        upload_status = "File uploaded successfully"
     else:
-        return {"error": "Failed to query Vectara API"}
+        upload_status = "Failed to upload file"
+
+    # The rest of the chatbot logic goes here
+
+    api_endpoint = "https://api.vectara.io/v1/query"
+
+    # Rest of the chatbot logic as before
+
+    return f"{upload_status}\n\nResponse from Vectara API: {response.text}"
 
 # Create a Gradio ChatInterface
-iface = gr.ChatInterface(
+iface = gr.Interface(
     fn=query_vectara,
+    inputs=[
+        gr.inputs.Text(label="Ask a question:"),
+        gr.inputs.File(label="Upload a file")
+    ],
+    outputs=gr.outputs.Textbox(),
     examples=["Hello", "What is the weather today?", "Tell me a joke"],
     title="Vectara Chatbot",
     description="Ask me anything using the Vectara API!",