Upload 2 files

utils.py

@@ -492,23 +492,23 @@ def generate_alpaca_ner_prompt(query):
 
 ### Input:
 
-What was discussed regarding Wearables revenue performance in Apple's Q3 2023 earnings call?
-Company - Apple, Quarter - Q3, Year - 2023
+What was discussed regarding Services revenue performance in Apple's Q3 2020 earnings call?
+Company - Apple, Quarter - Q3, Year - 2020
 
-How has the growth in Q1 been for the PC market as seen by AMD?
+How has the growth in Q1 been for the consumer market as seen by AMD?
 Company - AMD, Quarter - Q1, Year - none
 
 What was the long term view on GOOGL's cloud business growth as discussed in their earnings call?
 Company - Google, Quarter - none, Year - none
 
-What is Nvidia's visibility in the data center business in 2020?
-Company - Nvidia, Quarter - none, Year - 2020
+What is Nvidia's outlook in the data center business in Q3 2020?
+Company - Nvidia, Quarter - Q3, Year - 2020
 
-What are the opportunities and challenges in the Indian market that Amazon is facing?
+What are the expansion plans of Amazon in the Asia Pacific region as discussed in their earnings call?
 Company - Amazon, Quarter - none, Year - none
 
-What did the Analysts ask about CSCO's cybersecurity business in the earnings call?
-Company - Cisco, Quarter - none, Year - none
+What did the Analysts ask about CSCO's cybersecurity business in the earnings call in 2016?
+Company - Cisco, Quarter - none, Year - 2016
 
 
 {query}
@@ -517,14 +517,20 @@ Company - Cisco, Quarter - none, Year - none
 
 def generate_entities_flan_alpaca_inference_api(prompt):
     API_URL = "https://api-inference.huggingface.co/models/declare-lab/flan-alpaca-xl"
+    API_TOKEN = st.secrets["hg_key"]
+    headers = {"Authorization": f"Bearer {API_TOKEN}"}
     payload = {
         "inputs": prompt,
         "parameters": {"do_sample": True, "temperature":0.1, "max_length":80},
-        "options": {"use_cache": True, "wait_for_model": True}
+        "options": {"use_cache": False, "wait_for_model": True}
     }
-    data = json.dumps(payload)
-    response = requests.request("POST", API_URL, data=data)
-    output = json.loads(response.content.decode("utf-8"))[0]["generated_text"]
+    try:
+        data = json.dumps(payload)
+        response = requests.request("POST", API_URL, data=data)
+        output = json.loads(response.content.decode("utf-8"))[0]["generated_text"]
+    except:
+        output = ""
+    print(output)
     return output
 
 
@@ -569,6 +575,8 @@ def format_entities_flan_alpaca(model_output):
 
     except:
         year = None
+    
+    print((company, quarter, year))
     return company, quarter, year