Tonic commited on
Commit
176b9ce
1 Parent(s): d3b7d83

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +45 -17
app.py CHANGED
@@ -13,35 +13,63 @@ def query_vectara(question):
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  CORPUS_ID = config('CORPUS_ID')
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  API_KEY = config('API_KEY')
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- # Define the data dictionary
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- data_dict = {
 
 
 
 
 
 
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  "query": [
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  {
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  "query": user_message,
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- "num_results": 10,
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- "corpus_key": [
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  {
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- "customer_id": CUSTOMER_ID,
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- "corpus_id": CORPUS_ID
 
 
 
 
 
 
 
 
 
 
 
 
 
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  }
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  ]
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  }
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  ]
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  }
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- # Define the headers
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- api_key_header = {
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- "customer-id": CUSTOMER_ID,
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- "x-api-key": API_KEY,
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- "Content-Type": "application/json" # Set Content-Type header
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- }
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-
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- # Make the API request
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  response = requests.post(
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  "https://api.vectara.io/v1/query",
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- data=json.dumps(data_dict),
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  verify=True,
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- headers=api_key_header # Use the updated headers dictionary
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  )
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  if response.status_code == 200:
@@ -55,7 +83,7 @@ def query_vectara(question):
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  iface = gr.Interface(
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  fn=query_vectara,
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  inputs=[gr.Textbox(label="Input Text")],
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- outputs=[gr.Textbox(label="Output Text")],
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  title="Vectara Chatbot",
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  description="Ask me anything using the Vectara API!"
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  )
 
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  CORPUS_ID = config('CORPUS_ID')
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  API_KEY = config('API_KEY')
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+ # Define the headers
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+ api_key_header = {
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+ "customer-id": CUSTOMER_ID,
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+ "x-api-key": API_KEY
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+ }
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+
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+ # Define the request body in the structure provided in the example
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+ request_body = {
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  "query": [
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  {
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  "query": user_message,
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+ "queryContext": "",
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+ "start": 0,
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+ "numResults": 25,
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+ "contextConfig": {
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+ "charsBefore": 0,
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+ "charsAfter": 0,
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+ "sentencesBefore": 2,
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+ "sentencesAfter": 2,
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+ "startTag": "%START_SNIPPET%",
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+ "endTag": "%END_SNIPPET%",
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+ },
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+ "rerankingConfig": {
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+ "rerankerId": 272725718,
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+ "mmrConfig": {
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+ "diversityBias": 0.3
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+ }
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+ },
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+ "corpusKey": [
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  {
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+ "customerId": CUSTOMER_ID,
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+ "corpusId": CORPUS_ID,
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+ "semantics": 0,
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+ "metadataFilter": "",
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+ "lexicalInterpolationConfig": {
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+ "lambda": 0
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+ },
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+ "dim": []
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+ }
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+ ],
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+ "summary": [
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+ {
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+ "maxSummarizedResults": 1,
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+ "responseLang": "eng",
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+ "summarizerPromptName": "vectara-summary-ext-v1.2.0"
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  }
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  ]
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  }
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  ]
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  }
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+ # Make the API request using Gradio
 
 
 
 
 
 
 
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  response = requests.post(
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  "https://api.vectara.io/v1/query",
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+ json=request_body, # Use json to automatically serialize the request body
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  verify=True,
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+ headers=api_key_header
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  )
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  if response.status_code == 200:
 
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  iface = gr.Interface(
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  fn=query_vectara,
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  inputs=[gr.Textbox(label="Input Text")],
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+ outputs=gr.Textbox(label="Output Text"),
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  title="Vectara Chatbot",
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  description="Ask me anything using the Vectara API!"
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  )