updated function calling code

app.py

@@ -22,10 +22,11 @@ from langchain.schema import (
     HumanMessage,
     SystemMessage
 )
+# import all defined functions, their definitions and a dictionary
+from gpt_function_definitions import generate_image, generate_caption, get_news
 
 
 # Get the value of the openai_api_key from environment variable
-#openai_api_key = os.getenv("OPENAI_API_KEY")
 openai.api_key = os.getenv("OPENAI_API_KEY")
 
 chat = ChatOpenAI(
@@ -35,16 +36,12 @@ chat = ChatOpenAI(
     model='gpt-3.5-turbo-0613'
     )
 
-# import all defined functions, their definitions and a dictionary
-from gpt_function_definitions import generate_image, generate_caption, get_news
-
-
 #Streaming endpoint
 API_URL = "https://api.openai.com/v1/chat/completions" #os.getenv("API_URL") + "/generate_stream"
 
 
 
-# TOOLS , FUNCTION CALLING, AND AGENTS
+# TOOLS and FUNCTION CALLING
 # Load the tool configs that are needed.
 # 'Tool' dataclass wraps functions that accept a single string input and returns a string output.
 tools = [
@@ -75,32 +72,49 @@ tools = [
 
 # Creating OpenAI functions
 # use LangChain tools as OpenAI functions.
-functions = [format_tool_to_openai_function(t) for t in tools]
-functions
+#functions = [format_tool_to_openai_function(t) for t in tools]
+#functions
 
 # defining agents using tools and openai functions
-agent = initialize_agent(tools, chat, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)
+#agent = initialize_agent(tools, chat, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)
 
 
 # function calling
-def run_conversation(user_input):
-    # calling the agent
-    function_response = agent.run(user_input)
-    print(f"function_response is - {function_response}")
-
-    image_file_extns = ['png', 'jpg', 'gif', 'tiff', 'tif', 'svg', 'bmp']
-    literal_terms = ['caption', 'captions']
-    if any(extn in function_response for extn in image_file_extns) and not any(term in function_response for term in literal_terms) :
-        image_file = function_response.replace('sandbox:',"").split('(')[-1].split(')')[0]
-        print(f"image_file is -{image_file}")
-        return function_response, image_file
-
-    return function_response, None
-
-
-system = SystemMessage(content = "You are a helpful AI assistant") # that translates English to Pirate English.")
-
-def predict(user_input, temperature, stable_diff, image_cap, top_news, file_output, chatbot):
+def run_conversation(user_input, plugins, tools):
+    
+    print(f"Plugins are - {plugins}")
+    print(f"Total available PLUGINS/Tools are - {tools}")
+    
+    # Load the tool configs that are needed.
+    # 'Tool' dataclass wraps functions that accept a single string input and returns a string output.
+    tools = [val for val, flag in zip(tools, plugins) if flag]
+    print(f"PLUGINS/Tools enabled in this run are - {tools}")
+
+    try:
+        # defining agents using tools and openai functions
+        agent = initialize_agent(tools, chat, agent=AgentType.OPENAI_FUNCTIONS, verbose=True)
+
+        # calling the agent
+        function_response = agent.run(user_input)
+        print(f"function_response is - {function_response}")
+            
+        image_file_extns = ['png', 'jpg', 'gif', 'tiff', 'tif', 'svg', 'bmp']
+        literal_terms = ['caption', 'captions']
+        if any(extn in function_response for extn in image_file_extns) and not any(term in function_response for term in literal_terms) :
+            image_file = function_response.replace('sandbox:',"").split('(')[-1].split(')')[0]
+            print(f"image_file is -{image_file}")
+            return function_response, image_file
+
+        return function_response, None
+    
+    except Exception as e:
+        print(f"An error occured while calling agents using 'Function Calling': {e}")
+        return None, None
+
+
+system = SystemMessage(content = "You are a helpful AI assistant") 
+
+def predict(user_input, temperature, stable_diff, image_cap, top_news, google_search, file_output, chatbot):
 
     print(f"chatbot - {chatbot}")
     print(f"user_input - {user_input}")
@@ -115,13 +129,14 @@ def predict(user_input, temperature, stable_diff, image_cap, top_news, file_outp
 
 
     chat = ChatOpenAI(
-    #openai_api_key=openai_api_key,
+    openai_api_key=openai_api_key,
     temperature=temperature, #1.0
     streaming=True,
     model='gpt-3.5-turbo-0613')
     messages = [system]
-    plugins = [stable_diff, image_cap, top_news, ] #music_gen
-    function_call_decision = True if any(plugins) else False #"auto" if any(plugins) else "none"
+    # image, caption, news, serach
+    plugins = [stable_diff, image_cap, top_news, google_search] 
+    function_call_decision = True if any(plugins) else False 
 
     if len(chatbot) != 0:
         for conv in chatbot:
@@ -130,28 +145,30 @@ def predict(user_input, temperature, stable_diff, image_cap, top_news, file_outp
             messages.append(human)
             messages.append(ai)
         messages.append(HumanMessage(content=user_input))
+        print(f"messages list is - {messages}")
+
         if function_call_decision:
             # getting openAI function agent reponse
-            function_response, image_file = run_conversation(user_input)
-            gpt_response = AIMessage(content= function_response)
-            bot_message = gpt_response.content
-            print(f"bot_message - {bot_message}")
-            chatbot.append((user_input, bot_message))
-            return "", chatbot, image_file
+            function_response, image_file = run_conversation(user_input, plugins, tools)
+            if function_response is not None:
+                gpt_response = AIMessage(content= function_response)
+                bot_message = gpt_response.content
+                print(f"bot_message - {bot_message}")
+                chatbot.append((user_input, bot_message))
+                return "", chatbot, image_file
     else: # for first user message
-        #human = HumanMessage(content=user_input)
-        #messages.append(human)
         messages.append(HumanMessage(content=user_input))
+        print(f"messages list is - {messages}")
+
         if function_call_decision:
             # getting openAI function agent reponse
-            function_response, image_file = run_conversation(user_input)
-            gpt_response = AIMessage(content= function_response)
-            bot_message = gpt_response.content
-            print(f"bot_message - {bot_message}")
-            chatbot.append((user_input, bot_message))
-            return "", chatbot, image_file
-
-    print(f"messages - {messages}")
+            function_response, image_file = run_conversation(user_input, plugins, tools)
+            if function_response is not None:
+                gpt_response = AIMessage(content= function_response)
+                bot_message = gpt_response.content
+                print(f"bot_message - {bot_message}")
+                chatbot.append((user_input, bot_message))
+                return "", chatbot, image_file
 
     # getting gpt3.5's response
     gpt_response = chat(messages)
@@ -161,8 +178,7 @@ def predict(user_input, temperature, stable_diff, image_cap, top_news, file_outp
 
     chatbot.append((user_input, bot_message))
 
-    return "", chatbot, None
-
+    return "", chatbot, None #"", chatbot
 
 
 def add_image(file_to_save, file_output):
@@ -177,6 +193,7 @@ def add_image(file_to_save, file_output):
     print(f"Logging: Updated file directory - {file_output}")
     return file_output #gr.update(value="dog1.jpg")
 
+
 def add_audio(file_to_save, file_output):
     print(f"audio file_to_save is - {file_to_save}")
     print(f"files available in directory are -{file_output}")
@@ -189,6 +206,7 @@ def add_audio(file_to_save, file_output):
     print(f"Logging: Updated file directory - {file_output}")
     return file_output #gr.update(value="dog1.jpg")
 
+
 def upload_file(file, file_output):
     print(f"Logging: all files available - {file_output}")
     print(f"Logging: file uploaded is - {file}")
@@ -279,54 +297,54 @@ Thats it! you are have added your own brand new CHATGPT Plugin for yourself. Go
 """
 
 
-
 # GRADIO BLOCK
 with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
                 #chatbot {height: 520px; overflow: auto;}""") as demo:   # #width: 1000px;
-    gr.HTML('<h1 align="center">🚀ChatGPT🧩Plugin-UI using Langchain & Gradio</h1>')
+    gr.HTML('<h1 align="center">🚀ChatGPT🧩Plugin WebUI using Langchain & Gradio</h1>')
     with gr.Accordion("What is happening?", open=False):
       gr.HTML(messaging)
     gr.HTML('''<center><a href="https://huggingface.co/spaces/ysharma/ChatGPT-Plugins-UI-with-Langchain?duplicate=true"><img src="https://bit.ly/3gLdBN6" alt="Duplicate Space"></a>Duplicate the Space and run securely with your OpenAI API Key</center>''')
     with gr.Row():
       with gr.Column():
         openai_api_key_tb = gr.Textbox(label="Enter your OpenAI API key here",
-                                         value="🎁Keys are provided by HuggingFace for Free🥳 Don't need to enter yours!😉🙌",
+                                         value="🎁ChatGPT Keys are provided by HuggingFace for Free🥳 You don't need to enter yours!😉🙌",
                                          container=False)
           #plugin_message = gr.HTML()
-        with gr.Accordion("Plug-ins🛠️",open=True):
+        with gr.Accordion("Plugins🛠️ Available",open=True):
           with gr.Row():
             #music_gen = gr.Checkbox(label="🎵MusicGen", value=False)
             stable_diff = gr.Checkbox(label="🖼️Diffusers", value=False)
             image_cap = gr.Checkbox(label="🎨Describe Image", value=False)
             top_news = gr.Checkbox(label="📰News", value=False)
+            google_search = gr.Checkbox(label="🌐Google Search", value=False)
             #texttospeech = gr.Checkbox(label="📝🗣️Text-To-Speech", value=False)
             #gr.CheckboxGroup(["🎵MusicGen", "🖼️Diffusers", "🎨Describe Image", "📰News", "📝🗣️Text-To-Speech" ], label="Plug-ins", info="enhance your ChatGPT experience using Plugins : Powered by Gradio!")
       with gr.Column():
-        gen_image = gr.Image(label="generated image", type="filepath")
+        gen_image = gr.Image(label="generated image", type="filepath", interactive=False)
 
     with gr.Row():
         chatbot = gr.Chatbot(elem_id='chatbot')
 
     with gr.Row():
-      with gr.Column(scale=0.85):
+      with gr.Column(scale=0.70):
         inputs = gr.Textbox(placeholder= "Hi there!", label= "Type an input and press Enter")
+      with gr.Column(scale=0.15, min_width=0):
+          b1 = gr.Button("🏃Run")
       with gr.Column(scale=0.15, min_width=0):
           btn = gr.UploadButton("📁Upload", file_types=["image", "audio"],  file_count="single")
 
-    b1 = gr.Button("🏃Run")
-
     with gr.Row():
       with gr.Accordion("Parameters", open=False):
         top_p = gr.Slider( minimum=-0, maximum=1.0, value=1.0, step=0.05, interactive=True, label="Top-p (nucleus sampling)",)
         temperature = gr.Slider( minimum=-0, maximum=5.0, value=1.0, step=0.1, interactive=True, label="Temperature",)
       with gr.Accordion("Available Files", open=False):
-        file_output = gr.File(file_count="multiple", file_types=["image", "audio"])
+        file_output = gr.File(file_count="multiple", file_types=["image", "audio"], label="Files Available")
 
     inputs.submit( predict,
-                  [inputs, temperature, stable_diff, image_cap, top_news, file_output, chatbot],
+                  [inputs, temperature, stable_diff, image_cap, top_news, google_search, file_output, chatbot],
                    [inputs, chatbot, gen_image ])
     b1.click( predict,
-            [inputs, temperature, stable_diff, image_cap, top_news, file_output, chatbot],
+            [inputs, temperature, stable_diff, image_cap, top_news, google_search, file_output, chatbot],
              [inputs, chatbot, gen_image ])
 
 
@@ -337,8 +355,16 @@ with gr.Blocks(css = """#col_container { margin-left: auto; margin-right: auto;}
     with gr.Accordion("How to add more Plugins to ChatGPT", open=False ):
       gr.Markdown(add_plugin_steps)
 
-    #gr.Examples(
-    #    inputs, top_p, temperature, openai_api_key, chat_counter, music_gen, stable_diff, image_cap, top_news, texttospeech, file_output, plugin_message, chatbot, state
-    #)
+    gr.Examples(
+        examples = [["generate an image of a puppy", 1.0, True, False, False, False, None],
+                    ["generate a caption for the image cat2.jpg", 1.0, False, True, False, False, "cat2.jpg"],
+                    ["What is the latest top news on Inflation in Europe", 1.0, False, False, True, False, None],
+                    ["What is Europe's stand on the ongoing generative AI revolution?", 1.0, False, False, False, True, None],
+                    ["Write a very short poem on 'sparkling water'", 1.0, False, False, False, False, None],
+                    ["What is the weather in LA and SF?", 1.0, False, False, False, True, None],
+                    ["Who is the owner of Twitter? Are there any competitors of Twitter yet?", 1.0, True, True, True, True, None],
+                    ],
+        inputs = [inputs, temperature, stable_diff, image_cap, top_news, google_search, file_output, chatbot]
+    )
 
 demo.queue().launch(debug=True, height = '1000')