Create app.py

app.py

@@ -0,0 +1,142 @@
+from openai import AsyncAssistantEventHandler
+from openai import AsyncOpenAI
+import gradio as gr
+import asyncio
+import os
+
+# set the keys
+client = AsyncOpenAI(
+  api_key=os.getenv("OPENAI_API_KEY")
+)
+
+assistantID = os.getenv("OPENAI_ASSISTANT_ID")
+mypassword = os.getenv("RTL_PASSWORD")
+
+class EventHandler(AsyncAssistantEventHandler):
+    def __init__(self) -> None:
+        super().__init__()
+        self.response_text = ""
+
+    async def on_text_created(self, text) -> None:
+        self.response_text += str(text)
+
+    async def on_text_delta(self, delta, snapshot):
+        self.response_text += str(delta.value)
+
+    async def on_text_done(self, text):
+        pass
+
+    async def on_tool_call_created(self, tool_call):
+        self.response_text += f"\n[Tool Call]: {str(tool_call.type)}\n"
+
+    async def on_tool_call_delta(self, delta, snapshot):
+        if snapshot.id != getattr(self, "current_tool_call", None):
+            self.current_tool_call = snapshot.id
+            self.response_text += f"\n[Tool Call Delta]: {str(delta.type)}\n"
+
+        if delta.type == 'code_interpreter':
+            if delta.code_interpreter.input:
+                self.response_text += str(delta.code_interpreter.input)
+            if delta.code_interpreter.outputs:
+                self.response_text += "\n\n[Output]:\n"
+                for output in delta.code_interpreter.outputs:
+                    if output.type == "logs":
+                        self.response_text += f"\n{str(output.logs)}"
+
+    async def on_tool_call_done(self, text):
+        pass
+
+# Initialize session variables
+session_data = {"assistant_id": assistantID, "thread_id": None}
+
+async def initialize_thread():
+    # Create a Thread
+    thread = await client.beta.threads.create()
+    # Store thread ID in session_data for later use
+    session_data["thread_id"] = thread.id
+
+async def generate_response(user_input):
+    if user_input == "":
+        yield "Submit your question as input !"
+    else:
+        assistant_id = session_data["assistant_id"]
+        thread_id = session_data["thread_id"]
+
+        # Add a Message to the Thread
+        oai_message = await client.beta.threads.messages.create(
+            thread_id=thread_id,
+            role="user",
+            content=user_input
+    )
+
+    # Create and Stream a Run
+    event_handler = EventHandler()
+
+    async with client.beta.threads.runs.stream(
+        thread_id=thread_id,
+        assistant_id=assistant_id,
+        instructions="Please assist the user with their query.",
+        event_handler=event_handler,
+    ) as stream:
+        # Yield incremental updates
+        async for _ in stream:
+            await asyncio.sleep(0.1)  # Small delay to mimic streaming
+            yield event_handler.response_text
+
+# Gradio interface function (generator)
+async def gradio_chat_interface(mode, password, user_input, example):
+    if mode == "Examples":
+        filename = example[-6:-2] + ".md"
+        file = open("examples/" + filename, "r")
+        output = file.read()
+        yield output
+    else:
+        # check the password
+        if password == "":
+            yield "To search you need to enter an RTL password !"
+        elif password != mypassword:
+            yield "Please enter the correct RTL password !"
+        else:
+
+            # Create a new event loop if none exists (or if we are in a new thread)
+            try:
+                loop = asyncio.get_running_loop()
+            except RuntimeError:
+                loop = asyncio.new_event_loop()
+                asyncio.set_event_loop(loop)
+
+            # Initialize the thread if not already done
+            if session_data["thread_id"] is None:
+                await initialize_thread()
+
+            # Generate and yield responses
+            async for response in generate_response(user_input):
+                yield response
+
+with gr.Blocks() as demo:
+    with gr.Row():
+        myTitle = gr.HTML("<h2 align=center>RTL Multilingual AI News Reader : What happened in the country 🇱🇺 or in the world 🌎 ?</h2>")   
+    with gr.Row():
+        myDescription = gr.HTML("""
+            <h3 align='center'>What topic interests you ?</h3>
+            <p align='center'>🐶 🏃🏻‍♂️ 🌗 🍇 🌈 🍽️ 🏆 🚘 ✈️ 🩺 </p>
+            <p align='center' bgcolor="Moccasin">Submit your question in english or in another language !</p>
+            """            
+        )
+    with gr.Row():
+        mode = gr.Radio(choices=["Search", "Examples"], label = "You can run the examples without password !", value = "Examples")
+        pw = gr.Textbox(lines=1, label="Enter the RTL password : ")
+    with gr.Row():
+            question = gr.Textbox(lines=3, label="Please submit your question ?")
+    with gr.Row():    
+            examples = gr.Radio(["What happened in May 2009 in Luxembourg ?", "What were the highlights in 2017 ?"], value="What happened in May 2009 in Luxembourg ?", label="Examples")
+    with gr.Row():
+        clear = gr.Button("Clear")
+        submit = gr.Button("Submit")
+    with gr.Row():
+        mySubtitle = gr.HTML("<p align='center' bgcolor='Khaki'>English RTL News :</p>")
+    with gr.Row():
+        myOutput = gr.Markdown(label="Answer from the OpenAI File-Search Assistent :")
+
+    submit.click(fn = gradio_chat_interface, inputs=[mode, pw, question, examples], outputs = myOutput)
+demo.launch()