ashishanand commited on
Commit
f3f65fe
·
1 Parent(s): 85eda94

param changed

Browse files
Files changed (1) hide show
  1. app.py +15 -5
app.py CHANGED
@@ -53,8 +53,8 @@ def call_Llama_api(query, context):
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  "content": "User Question: " + query + "\n\nRelevant Excerpt(s):\n\n" + context,
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  }
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  ],
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- temperature=0.7,
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- max_tokens=50,
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  top_p=1,
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  stream=False,
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  stop=None,
@@ -128,12 +128,15 @@ def colbert_rerank(query=None, chunks=None):
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  # ... (same as your original function)
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  d = ranker.rank(query=query, docs=chunks)
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  reranked_chunks = [d[i].text for i in range(len(chunks))]
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- return reranked_chunks[:10]
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  def process_query(query):
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  # Use global variables
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  global available_car_models, collection
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  car_model = is_car_model_available(query, available_car_models)
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  if not car_model:
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  return "The manual for the specified car model is not present."
@@ -158,12 +161,19 @@ def process_query(query):
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  answer = call_Llama_api(query, final_context)
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  # Prepare citations
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  citations = [
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  f"Page {meta.get('page_number', 'N/A')}" for meta in metadatas[:5]
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  ]
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- citations_text = "Citations:\n" + "\n".join(citations)
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  return f"{answer}\n\n{citations_text}"
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@@ -192,7 +202,7 @@ def initialize():
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  # name=collection_name,
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  # embedding_function=embedding_function
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  # )
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- available_car_models = ['Tiago', 'Astor']
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  # else:
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  collection = client.get_collection(
 
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  "content": "User Question: " + query + "\n\nRelevant Excerpt(s):\n\n" + context,
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  }
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  ],
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+ temperature=0.6,
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+ max_tokens=200,
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  top_p=1,
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  stream=False,
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  stop=None,
 
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  # ... (same as your original function)
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  d = ranker.rank(query=query, docs=chunks)
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  reranked_chunks = [d[i].text for i in range(len(chunks))]
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+ return reranked_chunks
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  def process_query(query):
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  # Use global variables
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  global available_car_models, collection
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+ print("Input Query:",query)
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+ print(type(query))
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+
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  car_model = is_car_model_available(query, available_car_models)
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  if not car_model:
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  return "The manual for the specified car model is not present."
 
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  answer = call_Llama_api(query, final_context)
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+ last_complete = answer.rfind('.')
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+ # last_newline = answer.rfind('\n')
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+ # last_complete = max(last_period, last_newline)
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+
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+ if last_complete != -1:
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+ answer = answer[:last_complete + 1].strip()
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+
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  # Prepare citations
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  citations = [
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  f"Page {meta.get('page_number', 'N/A')}" for meta in metadatas[:5]
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  ]
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+ citations_text = "Pages cited from:\n" + "\n".join(citations)
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  return f"{answer}\n\n{citations_text}"
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  # name=collection_name,
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  # embedding_function=embedding_function
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  # )
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+ available_car_models = ['TIAGO', 'Astor']
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  # else:
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  collection = client.get_collection(