matanninio commited on
Commit
cec3465
·
1 Parent(s): 32cc43e

query -> promps

Browse files
Files changed (1) hide show
  1. app.py +10 -10
app.py CHANGED
@@ -23,14 +23,14 @@ protein_calmodulin = "MADQLTEEQIAEFKEAFSLFDKDGDGTITTKELGTVMRSLGQNPTEAELQDMISELDQ
23
  protein_calcineurin = "MSSKLLLAGLDIERVLAEKNFYKEWDTWIIEAMNVGDEEVDRIKEFKEDEIFEEAKTLGTAEMQEYKKQKLEEAIEGAFDIFDKDGNGYISAAELRHVMTNLGEKLTDEEVDEMIRQMWDQNGDWDRIKELKFGEIKKLSAKDTRGTIFIKVFENLGTGVDSEYEDVSKYMLKHQ"
24
 
25
 
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- def format_query(prot1,prot2):
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  # Formatting prompt to match pre-training syntax
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  return f"<@TOKENIZER-TYPE=AA><BINDING_AFFINITY_CLASS><SENTINEL_ID_0><MOLECULAR_ENTITY><MOLECULAR_ENTITY_GENERAL_PROTEIN><SEQUENCE_NATURAL_START>{prot1}<SEQUENCE_NATURAL_END><MOLECULAR_ENTITY><MOLECULAR_ENTITY_GENERAL_PROTEIN><SEQUENCE_NATURAL_START>{prot2}<SEQUENCE_NATURAL_END><EOS>"
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- def run_query(query):
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  # Create and load sample
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  sample_dict = dict()
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- sample_dict[ENCODER_INPUTS_STR] = query
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  # Tokenize
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  sample_dict=tokenizer_op(
@@ -58,9 +58,9 @@ def run_query(query):
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59
  return generated_output,score
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- def create_and_run_query(prot1, prot2):
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- query = format_query(prot1, prot2)
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- res=query, *run_query(query=query)
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  return res
65
 
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  def create_application():
@@ -92,16 +92,16 @@ Given two protein sequences, estimate if the proteins interact or not.
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  value=protein_calcineurin,
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  )
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  with gr.Row():
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- run_mammal = gr.Button("Run Mammal query for Protein-Protein Interaction",variant='primary')
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  with gr.Row():
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- query_box = gr.Textbox(label="Mammal query",lines=5)
98
 
99
  with gr.Row():
100
  decoded = gr.Textbox(label="Mammal output")
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  run_mammal.click(
102
- fn=create_and_run_query,
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  inputs=[prot1,prot2],
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- outputs=[query_box,decoded,gr.Number(label='PPI score')]
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  )
106
  with gr.Row():
107
  gr.Markdown("```<SENTINEL_ID_0>``` contains the binding affinity class, which is ```<1>``` for interating and ```<0>``` for non-interating")
 
23
  protein_calcineurin = "MSSKLLLAGLDIERVLAEKNFYKEWDTWIIEAMNVGDEEVDRIKEFKEDEIFEEAKTLGTAEMQEYKKQKLEEAIEGAFDIFDKDGNGYISAAELRHVMTNLGEKLTDEEVDEMIRQMWDQNGDWDRIKELKFGEIKKLSAKDTRGTIFIKVFENLGTGVDSEYEDVSKYMLKHQ"
24
 
25
 
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+ def format_prompt(prot1,prot2):
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  # Formatting prompt to match pre-training syntax
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  return f"<@TOKENIZER-TYPE=AA><BINDING_AFFINITY_CLASS><SENTINEL_ID_0><MOLECULAR_ENTITY><MOLECULAR_ENTITY_GENERAL_PROTEIN><SEQUENCE_NATURAL_START>{prot1}<SEQUENCE_NATURAL_END><MOLECULAR_ENTITY><MOLECULAR_ENTITY_GENERAL_PROTEIN><SEQUENCE_NATURAL_START>{prot2}<SEQUENCE_NATURAL_END><EOS>"
29
 
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+ def run_prompt(prompt):
31
  # Create and load sample
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  sample_dict = dict()
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+ sample_dict[ENCODER_INPUTS_STR] = prompt
34
 
35
  # Tokenize
36
  sample_dict=tokenizer_op(
 
58
 
59
  return generated_output,score
60
 
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+ def create_and_run_prompt(prot1, prot2):
62
+ prompt = format_prompt(prot1, prot2)
63
+ res=prompt, *run_prompt(prompt=prompt)
64
  return res
65
 
66
  def create_application():
 
92
  value=protein_calcineurin,
93
  )
94
  with gr.Row():
95
+ run_mammal = gr.Button("Run Mammal prompt for Protein-Protein Interaction",variant='primary')
96
  with gr.Row():
97
+ prompt_box = gr.Textbox(label="Mammal prompt",lines=5)
98
 
99
  with gr.Row():
100
  decoded = gr.Textbox(label="Mammal output")
101
  run_mammal.click(
102
+ fn=create_and_run_prompt,
103
  inputs=[prot1,prot2],
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+ outputs=[prompt_box,decoded,gr.Number(label='PPI score')]
105
  )
106
  with gr.Row():
107
  gr.Markdown("```<SENTINEL_ID_0>``` contains the binding affinity class, which is ```<1>``` for interating and ```<0>``` for non-interating")