update file func

app.py

@@ -483,7 +483,7 @@ async def start_playwright(question: str):
 langchain.debug = True
 
 global memory3
-memory3 = ConversationBufferWindowMemory(memory_key="chat_history", return_messages=True)
+memory3 = ConversationBufferWindowMemory(memory_key="chat_history", input_key="input", output_key='output', return_messages=True)
 
 global memory2
 memory2 = ConversationBufferWindowMemory(memory_key="chat_history")
@@ -536,11 +536,12 @@ LOADER_MAPPING = {
 
 source_directory = 'Upload Files'
 global file_list_loaded
-file_list_loaded = ''
+file_list_loaded = []
 chunk_size = 500
 chunk_overlap = 300
 
-
+global file_list_by_user
+file_list_by_user = []
 
 global Filename_Chatbot
 Filename_Chatbot = ""
@@ -785,7 +786,7 @@ def text_to_speech_2(text):
         response.raise_for_status()
         timestr = time.strftime("%Y%m%d-%H%M%S")
         with open('sample-' + timestr + '.wav', 'wb') as audio:
-                audio.write(response.content)
+            audio.write(response.content)
         print ("File Name  ", audio.name)
         # print (audio)
         Audio_output.append(audio.name)
@@ -1002,10 +1003,11 @@ When you are clear about the request, you can start to answer the request by **w
 When you need information, you can use tools as below and merge all gathered information from different tools.
 When you need to use "Code Runner" for code running, **Always recap the plan between each code block** (you have extreme short-term memory loss, so you need to recap the plan between each message block to retain it).
 When you send a message containing code to "Code Runner", it will be executed **on the user's machine**. The user has given you **full and complete permission** to execute any code necessary to complete the task. You have full access to control their computer to help them. Code entered into "Code Runner" will be executed **in the users local environment**.
-If you want to send data between programming languages, save the data to a txt or json.
+If you want to send data between programming languages, save the data to a txt or json. You should finish each step and output the result with the text content.
 You can access the internet. Run **any code** to achieve the goal, and if at first you don't succeed, try again and again.
 You can install new packages with pip. Try to install all necessary packages in one command at the beginning.
 When a user refers to a filename, they're likely referring to an existing file in the directory you're currently in ("Code Runner" executes on the user's machine).
+When a user refers to a uploaded file, they're likely referring to an existing file in {file_list_by_user}
 In general, choose packages that have the most universal chance to be already installed and to work across multiple applications. Packages like ffmpeg and pandoc that are well-supported and powerful.
 Write messages to the user in Markdown. When the final answer has output files, you must output the **name** of the file.
 You are capable of **any** task.
@@ -1141,7 +1143,7 @@ prompt_openai = OpenAIMultiFunctionsAgent.create_prompt(
 )
 
 input_variables=["input", "chat_history", "agent_scratchpad"]
-
+input_variables_2=["input", "chat_history", "agent_scratchpad", "file_list_by_user"]
 
 agent_ZEROSHOT_REACT = initialize_agent(tools2, llm, 
                         #  agent=AgentType.ZERO_SHOT_REACT_DESCRIPTION,
@@ -1198,7 +1200,7 @@ agent_STRUCTURED_ZEROSHOT_REACT = initialize_agent(tools_remote, GPTfake,
                             'format_instructions': FORMAT_INSTRUCTIONS_STRUC,
                             # 'suffix': SUFFIX2,
                             "memory_prompts": [MessagesPlaceholder(variable_name="chat_history")],
-                            'input_variables': input_variables,
+                            'input_variables': input_variables_2,
                          
                          },
                         #  input_variables = input_variables,
@@ -1473,6 +1475,23 @@ def Summary_upload_file(files, chat_history2):
     yield chat_history2
 
 
+def User_Upload_file(files, chat_history2):
+    global file_list_by_user
+    file_list_by_user = []
+    for unit in files:
+        file_list_by_user.append(unit.name)
+    # file_list_loaded = files
+    print(file_list_by_user)
+    # print(chat_history)
+    # test_msg = ["Request Upload File into DB", "Operation Ongoing...."]
+    
+    chat_history2 = chat_history2 + [("Updated Files:\n", None)]
+    yield chat_history2
+    # chat_history.append(test_msg)
+    for file in files:
+        chat_history2 = chat_history2 + [((file.name,), None)]
+    yield chat_history2
+
 class Logger:
     def __init__(self, filename):
         self.terminal = sys.stdout
@@ -1528,7 +1547,9 @@ def chathmi3(message, history2):
     yield ["", history2]
     try:
         if agent is not None:
-            response = agent.run(message)
+            # response = agent.run(message)
+            temp = agent({'file_list_by_user':file_list_by_user, 'input': message})
+            response = temp['output']
         elif agent is None:
             response = asyncio.run(start_playwright(message))
         time.sleep(0.1)
@@ -1615,7 +1636,10 @@ def chathmi4(message, history2):
     try:
         if agent is not None:
 
-            response = agent.run(message)
+            # response = agent.run(message)
+            temp = agent({'file_list_by_user':file_list_by_user, 'input': message})
+            response = temp['output']
+            # print("chathmi4 response:", response)
             # test callback
             
             # temp = []
@@ -1941,14 +1965,12 @@ def UpdateChatbot(Running_history):
     # # Running_history = Running_history + [(None, 'Timestamp: '+timestr)]
     # # yield Running_history
         WelcomeStr = """
-        This is AI Assistant powered by MECH Core Team.
-        It is connected remotely with GPT4. The following function is available for you.
+        This is AI Assistant powered by MECH Core Team and it is connected remotely with GPT4. The following function is available for you.
         1. Free Chat with AI assistant
         2. Search Information and Engineering Data: Vector Database + Internet
-        3. Make specific task with tools:
-            - Text to Sound | Sound to Text | Doc summary
-            - Code interpret (Beta version)
-            - Text to Image (forecast)
+        3. Make specific task with tools: Text to Sound | Sound to Text | Doc summary
+        4. Code interpret: very powerful to modify/create/analyze documents (90%)
+        5. Text to Image | Image to Text: (forecast)
         """
         Running_history = Running_history + [(None, timestr+'\n'+WelcomeStr)]
     # ChatbotHistory = ChatbotHistory + [(None, timestr+'\n'+WelcomeStr)]
@@ -2066,12 +2088,13 @@ with gr.Blocks() as demo:
     # UserRecord.append((None, timestr+'\n'+WelcomeStr))
     with gr.Column() as main2:
         title = gr.Markdown("""# <center> STLA BABY - YOUR FRIENDLY GUIDE
-                            <center> v0.7.11: Powered by MECH Core Team - GPT4 REMOTE MODE"""),
+                            <center> v0.7.12: Powered by MECH Core Team - GPT4 REMOTE MODE"""),
         chatbot = gr.Chatbot(
             # avatar_images=((os.path.join(os.path.dirname(__file__),"User.png")), (os.path.join(os.path.dirname(__file__),"AI.png"))),
         )
         
         with gr.Row():
+            AddFile_button = gr.UploadButton("⤴️ File", file_count="multiple", scale= 0, variant="secondary",size='sm')
             inputtext = gr.Textbox(
                 scale= 4, 
                 label="",
@@ -2124,7 +2147,7 @@ with gr.Blocks() as demo:
     """
     GUI Func
     """
-
+    AddFile_button.upload(User_Upload_file, [AddFile_button, chatbot], chatbot)
     # upload_button.upload(func_upload_file, [upload_button, main.chatbot], main.chatbot)
     chatbot.like(vote, None, None)
     retry_button.click(retry, chatbot, chatbot).success(playsound1, None, voice_output).\