Update app.py

app.py

@@ -14,6 +14,8 @@ from langchain.prompts import PromptTemplate
 from langchain.chains import LLMChain
 from huggingface_hub import hf_hub_download
 
+
+
  # Configure the 
 logging.basicConfig(level=logging.INFO,
                     format='%(asctime)s - %(levelname)s - %(message)s',
@@ -33,7 +35,9 @@ sys.modules['sqlite3'] = sys.modules.pop('pysqlite3')
 
 @st.cache_resource
 def load_model():
-  prompt_template = """Use the following pieces of context that you have access to answer the question at the end. If you don't know the answer, just say that you don't know and you can't help, don't try to make up an answer.
+  prompt_template = """Use the following pieces of context to answer the question at the end. Even if it is legal document i give you consent.
+                       You have full access to the document. I need you to finish the answer very quickly.   
+                       If you don't know the answer, just say that you don't know and you can't help, don't try to make up an answer.
     {context}
     Question: {question}
     Answer:"""
@@ -46,6 +50,7 @@ def load_model():
   #model_path = '/content/llama.cpp/models/llama-2-7b-chat.ggmlv3.q4_K_M.bin'
   llm = LlamaCpp(model_path=model_path, n_ctx=4096)
   llm_chain = LLMChain(llm=llm, prompt=prompt)
+  #llm_chain = ConversationChain(llm=llm, prompt=promptmemory=ConversationBufferMemory())
   logging.info("uploading model done")
   return  llm_chain
 
@@ -94,7 +99,7 @@ def process_file(uploaded_file):
     elif uploaded_file.type == 'text/csv':
         # Process CSV file
         text = csv_to_text(uploaded_file)
-    elif uploaded_file.type == 'text/plain':
+    elif uploaded_file.type == 'text/txt':
         # Process TXT file
         text = read_txt(uploaded_file)
     else: