Update app.py

app.py

@@ -54,8 +54,6 @@ st.set_page_config(
 
 # My Inference API Copy
 API_URL = 'https://qe55p8afio98s0u3.us-east-1.aws.endpoints.huggingface.cloud'  # Dr Llama
-# Meta's Original - Chat HF Free Version:
-#API_URL = "https://api-inference.huggingface.co/models/meta-llama/Llama-2-7b-chat-hf"
 API_KEY = os.getenv('API_KEY')
 MODEL1="meta-llama/Llama-2-7b-chat-hf"
 MODEL1URL="https://huggingface.co/meta-llama/Llama-2-7b-chat-hf"
@@ -111,10 +109,6 @@ def SpeechSynthesis(result):
 
 
 
-
-
-
-
 # GPT4o documentation
 # 1. Cookbook:  https://cookbook.openai.com/examples/gpt4o/introduction_to_gpt4o
 # 2. Configure your Project and Orgs to limit/allow Models:  https://platform.openai.com/settings/organization/general
@@ -685,42 +679,6 @@ def generate_html(local_files):
 
 
 
-
-
-#from gradio_client import Client
-#client = Client("awacke1/Arxiv-Paper-Search-And-QA-RAG-Pattern")
-#result = client.predict(
-#		message="Hello!!",
-#		llm_results_use=5,
-#		database_choice="Semantic Search",
-#		llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
-#		api_name="/update_with_rag_md"
-#)
-#print(result)
-#Accepts 4 parameters:
-#message str Required
-##The input value that is provided in the "Search" Textbox component.
-#llm_results_use float Default: 5
-#The input value that is provided in the "Top n results as context" Slider component.
-#database_choice Literal['Semantic Search', 'Arxiv Search - Latest - (EXPERIMENTAL)'] Default: "Semantic Search"
-#The input value that is provided in the "Search Source" Dropdown component.
-#llm_model_picked Literal['mistralai/Mixtral-8x7B-Instruct-v0.1', 'mistralai/Mistral-7B-Instruct-v0.2', 'google/gemma-7b-it', 'None'] Default: "mistralai/Mistral-7B-Instruct-v0.2"
-#The input value that is provided in the "LLM Model" Dropdown component.
-#Returns tuple of 2 elements
-#[0] str
-#The output value that appears in the "value_14" Markdown component.
-#[1] str
-#The output value that appears in the "value_13" Textbox component.
-
-
-
-
-
-
-
-
-
-
 #@st.cache_resource
 def search_arxiv(query):
     start_time = time.strftime("%Y-%m-%d %H:%M:%S")
@@ -732,14 +690,7 @@ def search_arxiv(query):
 		llm_model_picked="mistralai/Mistral-7B-Instruct-v0.2",
 		api_name="/update_with_rag_md"
     )
-    
-    #response1 = client.predict(
-    #    query,
-    #    20,
-    #    "Semantic Search - up to 10 Mar 2024",
-    #    "mistralai/Mixtral-8x7B-Instruct-v0.1",
-    #    api_name="/update_with_rag_md"
-    #)
+
     Question = '### 🔎 ' + query + '\r\n'  # Format for markdown display with links
     References =  response1[0]  
     References2 =  response1[1]  
@@ -778,9 +729,6 @@ def search_arxiv(query):
     st.write(f"Start time: {start_time}")
     st.write(f"Finish time: {end_time}")
     st.write(f"Elapsed time: {elapsed_seconds:.2f} seconds")
-
-    #filename = generate_filename(query, "md")
-    #create_file(filename, query, results, should_save)
     
     return results
 
@@ -1215,16 +1163,11 @@ def FileSidebar():
         if next_action=='search':
             file_content_area = st.text_area("File Contents:", file_contents, height=500)
             user_prompt = file_contents
-        #try:
-            #search_glossary(file_contents)
             filesearch = PromptPrefix2 + file_content_area
             st.markdown(filesearch)
             if st.button(key='rerun', label='🔍Re-Code' ):
-                #search_glossary(filesearch)
                 search_arxiv(filesearch)
                     
-        #except:
-            #st.markdown('GPT is sleeping.  Restart ETA 30 seconds.')
     # ----------------------------------------------------- File Sidebar for Jump Gates ------------------------------------------
 
 # Randomly select a title
@@ -1558,22 +1501,10 @@ def create_file(filename, prompt, response, should_save=True):
     if ext in ['.txt', '.htm', '.md']:
 
 
-
-        # ******    line 344 is read    utf-8 encoding was needed when running locally to save utf-8 encoding and not fail on write
-
-        #with open(f"{base_filename}.md", 'w') as file:
-        #with open(f"{base_filename}.md", 'w', encoding="ascii", errors="surrogateescape") as file:
         with open(f"{base_filename}.md", 'w', encoding='utf-8') as file:
-            #try:
-            #content = (prompt.strip() + '\r\n' + decode(response, ))
             file.write(response)
-            #except:
-            #    st.write('.')
-        # ******        utf-8 encoding was needed when running locally to save utf-8 encoding and not fail on write
-
-
-
 
+    # Code Interpreter
     #has_python_code = re.search(r"```python([\s\S]*?)```", prompt.strip() + '\r\n' + response)
     #has_python_code = bool(re.search(r"```python([\s\S]*?)```", prompt.strip() + '\r\n' + response))
         #if has_python_code:
@@ -1961,29 +1892,8 @@ if filename is not None: # whisper1
             st.session_state.messages.append({"role": "assistant", "content": result})
     except:
         st.write(' ')
-    #st.sidebar.markdown(get_table_download_link(filename), unsafe_allow_html=True)
     filename = None
 
-    #MODEL = "gpt-4o-2024-05-13"
-    #openai.api_key = os.getenv('OPENAI_API_KEY')
-    #openai.organization = os.getenv('OPENAI_ORG_ID')
-    #client = OpenAI(api_key= os.getenv('OPENAI_API_KEY'), organization=os.getenv('OPENAI_ORG_ID'))
-    #st.session_state.messages.append({"role": "user", "content": transcript})
-    
-    #with st.chat_message("user"):
-    #    st.markdown(transcript)
-                   
-    #with st.chat_message("assistant"):
-    #    completion = client.chat.completions.create(
-    #        model=MODEL,
-    #        messages = st.session_state.messages,
-    #        stream=True
-    #    )
-        
-    #    response = process_text2(text_input=prompt)
-        
-    #st.session_state.messages.append({"role": "assistant", "content": response})
-
 
 # Scholary ArXiV Search  -------------------------  !!
 session_state = {}
@@ -2088,15 +1998,7 @@ def main():
         if audio_input is not None:
             # To read file as bytes:
             bytes_data = uploaded_file.getvalue()
-            #st.write(bytes_data)
-            
-            # To convert to a string based IO:
-            #stringio = StringIO(uploaded_file.getvalue().decode("utf-8"))
-            #st.write(stringio)
-            
-            # To read file as string:
-            #string_data = stringio.read()
-            #st.write(string_data)
+
 
         process_audio(audio_input, text_input)