SantanuBanerjee commited on
Commit
e40f174
·
verified ·
1 Parent(s): 3f53103

Update app.py

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Files changed (1) hide show
  1. app.py +30 -11
app.py CHANGED
@@ -361,6 +361,10 @@ def create_cluster_dataframes(processed_df):
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  from transformers import GPTNeoForCausalLM, GPT2Tokenizer
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  def generate_project_proposal(problem_descriptions, location, problem_domain):
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  print("Trying to access gpt-neo-1.3B")
 
 
 
 
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  model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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  tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
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@@ -371,17 +375,32 @@ def generate_project_proposal(problem_descriptions, location, problem_domain):
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  prompt = f"Generate a solution oriented project proposal for the following:\n\nLocation: {location}\nProblem Domain: {problem_domain}\nProblems: {problems_summary}\n\nProject Proposal:"
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  # Generate the proposal
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- input_ids = tokenizer.encode(prompt, return_tensors="pt")
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- output = model.generate(
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- input_ids,
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- max_length=300,
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- num_return_sequences=1,
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- no_repeat_ngram_size=2,
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- temperature=0.75)
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-
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- proposal = tokenizer.decode(output[0], skip_special_tokens=True)
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- print("Successfully accessed gpt-neo-1.3B and returning")
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- return proposal
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  def create_project_proposals(budget_cluster_df, problem_cluster_df, location_clusters, problem_clusters):
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  print("\n Starting function: create_project_proposals")
 
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  from transformers import GPTNeoForCausalLM, GPT2Tokenizer
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  def generate_project_proposal(problem_descriptions, location, problem_domain):
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  print("Trying to access gpt-neo-1.3B")
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+ print("problem_descriptions: ", problem_descriptions)
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+ print("location: ", location)
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+ print("problem_domain: ", problem_domain)
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+
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  model = GPTNeoForCausalLM.from_pretrained("EleutherAI/gpt-neo-1.3B")
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  tokenizer = GPT2Tokenizer.from_pretrained("EleutherAI/gpt-neo-1.3B")
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  prompt = f"Generate a solution oriented project proposal for the following:\n\nLocation: {location}\nProblem Domain: {problem_domain}\nProblems: {problems_summary}\n\nProject Proposal:"
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  # Generate the proposal
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+ try:
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+ input_ids = tokenizer.encode(prompt, return_tensors="pt")
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+ print("Input IDs shape:", input_ids.shape)
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+ output = model.generate(
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+ input_ids,
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+ max_length=300,
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+ num_return_sequences=1,
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+ no_repeat_ngram_size=2,
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+ temperature=0.75)
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+ print("Output shape:", output.shape)
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+ proposal = tokenizer.decode(output[0], skip_special_tokens=True)
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+ print("Successfully accessed gpt-neo-1.3B and returning")
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+ return proposal
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+ except Exception as e:
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+ print("Error generating proposal:", str(e))
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+ return prompt
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+
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+
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+
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+
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+
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+
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+
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+
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+
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+
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  def create_project_proposals(budget_cluster_df, problem_cluster_df, location_clusters, problem_clusters):
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  print("\n Starting function: create_project_proposals")