eagle0504 commited on
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91d0ca7
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1 Parent(s): 1a1bd77

Update app.py

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Files changed (1) hide show
  1. app.py +14 -2
app.py CHANGED
@@ -54,7 +54,12 @@ if st.session_state.logged_in:
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  data = {
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  "🏒 Company": ["AWS", "AWS", "AWS", "Azure"],
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  "πŸ“ Task": ["πŸ’» Code assist", "🧠 Protein Compound", "πŸ’» Code assist", "πŸ’» Code assist"],
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- "πŸ–₯️ Instance Type": ["t2.micro (1 vcpu, 1.0 GiB memory)", "t2.micro (1 vcpu, 1.0 GiB memory)", "t2.micro (1 vcpu, 1.0 GiB memory)", "Standard DS1 v2 (1 vcpu, 3.5 GiB memory)"],
 
 
 
 
 
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  "πŸš€ GPU Accelerator": ["A40, 9 vCPU 50 GB RAM", "A40, 9 vCPU 50 GB RAM", "A100, 24 vCPU 125 GB RAM", "A100, 24 vCPU 125 GB RAM"],
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  "πŸ’° Price": ["$0.67 / hour", "$0.78 / hour", "$1.89 / hour", "$0.78 / hour"],
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  "🌐 IPv4": [
@@ -62,7 +67,10 @@ if st.session_state.logged_in:
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  f"[Link]({BASE_CONTENT_PROTEIN_T2_MICRO})",
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  f"[Link]({BASE_CONTENT_CODE_ASSIST_T2_MICRO})",
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  f"[Link]({BASE_CONTENT_CODE_ASSIST_DS1})"
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- ]
 
 
 
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  }
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  # Convert the data to a DataFrame
@@ -115,6 +123,10 @@ if st.session_state.logged_in:
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  When you make a suggestion, also make sure to mention, for first time user, use sample login info:
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  username={JUPYTER_USERNAME}, and password={JUPYTER_PASSWORD} when click on the link recommended.
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  """})
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  st.session_state.messages.append({"role": "user", "content": prompt})
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  data = {
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  "🏒 Company": ["AWS", "AWS", "AWS", "Azure"],
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  "πŸ“ Task": ["πŸ’» Code assist", "🧠 Protein Compound", "πŸ’» Code assist", "πŸ’» Code assist"],
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+ "πŸ–₯️ Instance Type": [
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+ "t2.micro (1 vcpu, 1.0 GiB memory)",
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+ "t2.micro (1 vcpu, 1.0 GiB memory)",
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+ "t2.micro (1 vcpu, 1.0 GiB memory)",
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+ "Standard DS1 v2 (1 vcpu, 3.5 GiB memory)"
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+ ],
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  "πŸš€ GPU Accelerator": ["A40, 9 vCPU 50 GB RAM", "A40, 9 vCPU 50 GB RAM", "A100, 24 vCPU 125 GB RAM", "A100, 24 vCPU 125 GB RAM"],
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  "πŸ’° Price": ["$0.67 / hour", "$0.78 / hour", "$1.89 / hour", "$0.78 / hour"],
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  "🌐 IPv4": [
 
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  f"[Link]({BASE_CONTENT_PROTEIN_T2_MICRO})",
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  f"[Link]({BASE_CONTENT_CODE_ASSIST_T2_MICRO})",
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  f"[Link]({BASE_CONTENT_CODE_ASSIST_DS1})"
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+ ],
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+ "πŸ›‘οΈ HIPAA": ["βœ…", "βœ…", "βœ…", "βœ…"], # All rows have HIPAA compliance
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+ "πŸ“Š SOC1-3": ["βœ…", "βœ…", "βœ…", "βœ…"], # All rows have SOC1-3 compliance
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+ "πŸ’³ PCI DSS": ["βœ…", "βœ…", "βœ…", "βœ…"] # All rows have PCI DSS compliance
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  }
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  # Convert the data to a DataFrame
 
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  When you make a suggestion, also make sure to mention, for first time user, use sample login info:
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  username={JUPYTER_USERNAME}, and password={JUPYTER_PASSWORD} when click on the link recommended.
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+ User can also ask you certification eligibility. Currently, the data provided above has check marks.
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+ The check marks indicate which certification and data protection eligibility each instance has.
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+ You can recommend each instance according to user question if user asks about this part.
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+
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  """})
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  st.session_state.messages.append({"role": "user", "content": prompt})
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