Update app.py

app.py

@@ -149,15 +149,27 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, pr
     retriever=vector_db.as_retriever()
     progress(0.8, desc="Defining retrieval chain...")
 
-    prompt_template_string = f'''Your task is as follows: 1. Determine if the input is compliant with the provided context. 2. If the requirement is compliant, report "This requirement is compliant." 3. If the requirement is not compliant report "This requirement is not compliant." 4. If the requirement is not compliant, give the reason for non compliance and return the specific rule or guideline the requirement violates. 5. If the requirement is not compliant, report a refined version of the requirement delimited in quotes that is compliant with the provided context.'''
+    #prompt_template_string = f'''Your task is as follows: 1. Determine if the input is compliant with the provided context. 2. If the requirement is compliant, report "This requirement is compliant." 3. If the requirement is not compliant report "This requirement is not compliant." 4. If the requirement is not compliant, give the reason for non compliance and return the specific rule or guideline the requirement violates. 5. If the requirement is not compliant, report a refined version of the requirement delimited in quotes that is compliant with the provided context.'''
 
     # Create a PromptTemplate object
-    prompt_template = PromptTemplate(
-        template=prompt_template_string,
-        input_variables=["user_question","context"]
-    )
+    #prompt_template = PromptTemplate(
+    #    template=prompt_template_string,
+    #    input_variables=["user_question","context"]
+    #)
+
+
 
+    template = """Your task is as follows: 1. Determine if the input requirement is compliant with the provided context. 2. If the requirement is compliant, report "This requirement is compliant." 3. If the requirement is not compliant report "This requirement is not compliant." 4. If the requirement is not compliant, give the reason for non compliance and return the specific rule or guideline the requirement violates. 5. If the requirement is not compliant, report a refined version of the requirement delimited in quotes that is compliant with the provided context.
+    Context: {context}
+    Chat History: {chat_history}
+    Follow Up Input: {question}
+    Standalone question:"""
     
+    PROMPT = PromptTemplate(
+        input_variables=["context", "chat_history", "question"], 
+        template=template
+    )
+
     qa_chain = ConversationalRetrievalChain.from_llm(
         llm,
         retriever=retriever,
@@ -165,6 +177,7 @@ def initialize_llmchain(llm_model, temperature, max_tokens, top_k, vector_db, pr
         memory=memory,
         #prompt = prompt_template,
         #combine_docs_chain_kwargs={"prompt": prompt_template},
+        combine_docs_chain_kwargs={"prompt": PROMPT}
         return_source_documents=True,
         #return_generated_question=False,
         verbose=False,