reverted to original order

app.py

@@ -280,7 +280,7 @@ def text_to_text_generation(verbose, prompt):
 
                     )
                     retrieved_results = semantic_search(prompt)
-                    prompt = f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: {retrieved_results} </s>\n<s> [INST] Answer the following question: {prompt} [/INST]\nAnswer: "
+                    prompt = f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: {retrieved_results} </s>\n<s> [INST] Answer the following question: {prompt} [/INST]\nAnswer:\n\n"
 
                     md = (
                         f"### Step 1: Preparing prompt for additional documentation\n"
@@ -288,7 +288,7 @@ def text_to_text_generation(verbose, prompt):
                         f"### Step 2: Retrieving documentation from a book.\n"
                         f"{retrieved_results}\n"
                         f"### Step 3: Creating full prompt given to model\n"
-                        f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_BOOK] [INST] Answer the following question: {question} [/INST]\nAnswer:  \n"
+                        f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_BOOK] [INST] Answer the following question: {question} [/INST]\nAnswer:"
                     )
                 elif retriever == "google_search":
                     retrieved_results = google_search(prompt)
@@ -298,7 +298,7 @@ def text_to_text_generation(verbose, prompt):
                     print('Google search prompt:')
                     print(
                         (
-                            f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_GOOGLE] [INST] Answer the following question: {question} [/INST]\nAnswer:  \n" 
+                            f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_GOOGLE] [INST] Answer the following question: {question} [/INST]\nAnswer:\n\n" 
                         )
                     )
 
@@ -308,7 +308,7 @@ def text_to_text_generation(verbose, prompt):
                         f"### Step 2: Retrieving documentation from Google.\n"
                         f"{retrieved_results}\n"
                         f"### Step 3: Creating full prompt given to model\n"
-                        f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_GOOGLE] [INST] Answer the following question: {question} [/INST]\nAnswer:  \n"
+                        f"You are a helpful kubernetes professional. [INST] Use the following documentation, if it is relevant to answer the question below. [/INST]\nDocumentation: [RETRIEVED_RESULTS_FROM_GOOGLE] [INST] Answer the following question: {question} [/INST]\nAnswer:"
                     )
                 else:
                     prompt = f"[INST] Answer the following question: {prompt} [/INST]\nAnswer: "
@@ -445,12 +445,12 @@ def text_to_text_generation(verbose, prompt):
             f"{str_to_md(res_normal)}\n\n"
             f"--------------------------------------------\n"
             f"# Answer with RAG\n"
-            f"## Section 1: Preparing for generation\n\n {res_semantic_search_md}\n"
-            f"## Section 2: Generating answer\n\n ##### {str_to_md(res_semantic_search)}\n"
+            f"## Section 1: Preparing for generation  \n\n{res_semantic_search_md}  \n\n"
+            f"## Section 2: Generating answer  \n\n{str_to_md(res_semantic_search.strip())}  \n\n"
             f"--------------------------------------------\n"
             f"# Answer with Google search\n"
-            f"## Section 1: Preparing for generation\n\n {res_google_search_md}\n"
-            f"## Section 2: Generating answer\n\n {str_to_md(res_google_search)}\n"
+            f"## Section 1: Preparing for generation  \n\n{res_google_search_md}  \n\n"
+            f"## Section 2: Generating answer  \n\n{str_to_md(res_google_search.strip())}  \n\n"
         )
     else:
         return (
@@ -459,9 +459,9 @@ def text_to_text_generation(verbose, prompt):
             f"--------------------------------------------\n"
             f"# Classified your prompt as:\n"
             f"{modes}\n\n"
-            f"# Answer with finetuned model\n\n {str_to_md(res_normal)}\n"
-            f"# Answer with RAG\n\n ##### {str_to_md(res_semantic_search)}\n"
-            f"# Answer with Google search\n\n {str_to_md(res_google_search)}"
+            f"# Answer with finetuned model  \n\n{str_to_md(res_normal)}  \n\n"
+            f"# Answer with RAG  \n\n{str_to_md(res_semantic_search.strip())}  \n\n"
+            f"# Answer with Google search  \n\n{str_to_md(res_google_search)}  \n\n"
         )