Add app and requirements files

app.py

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+# %% [markdown]
+# # ChatBot app with Gradio
+
+# %%
+import os
+from dotenv import load_dotenv, find_dotenv
+import gradio as gr
+import openai
+
+_ = load_dotenv(find_dotenv(filename="secrets.env", raise_error_if_not_found=True))
+
+# Global variable
+ROOT_DIR = os.environ["ROOT_DIR"]
+AUTH_USERNAME = os.environ["AUTH_USERNAME"]
+AUTH_PASSWORD = os.environ["AUTH_PASSWORD"]
+
+# Load credentials
+openai.api_key = os.environ["OPENAI_API_KEY"]
+
+SYSTEM_PROMPT = "You are a helpful assistant and do your best to answer the user's questions.\
+	You do not make up answers."
+
+# %% [markdown]
+# ## Define and test the API calls
+
+# %%
+# define the function that will make the API calls 
+def APIcall(prompt:str, temperature = 0.7, max_tokens = 1024, model="GPT-3.5", stream=True):
+	if model == "GPT-3.5":
+		model = "gpt-3.5-turbo"
+	else:
+		model = "gpt-4"
+	# make the API call with the given parameter
+	response = openai.chat.completions.create(
+		model=model,
+		messages=prompt,
+		max_tokens = max_tokens,
+		temperature=temperature,
+		stream=stream,
+	)
+
+	# return the completed text
+	if stream:
+		for chunk in response:
+			output = chunk.choices[0].delta.content # when Stream is set to True
+			yield output
+	else:
+		output = response.choices[0].message.content # when Stream is set to False
+
+
+# %% [markdown]
+# ## Building the ChatBot with Gradio
+
+# %%
+# Helper function: format the prompt to include history
+def formatPrompt(newMsg:str, chatHistory, instruction):
+	
+	# start with the system prompt
+	messages = []
+	messages.append({
+		"role": "system",
+		"content": instruction
+	})
+
+	# add the history
+	for turn in chatHistory:
+		# retrieve the user and assistant messages from history
+		userMsg, AssistantMsg = turn
+		
+		# add the user message
+		messages.append({
+			"role": "user",
+			"content": userMsg
+		})
+
+		# add the assistant message
+		messages.append({
+			"role": "assistant",
+			"content": AssistantMsg
+		})
+	
+	# add the last message that needs to be answer
+	messages.append({
+		"role": "user",
+		"content": newMsg
+	})
+
+	# return the formated messages
+	return messages
+
+# def the response function (to get the answer as one block after generation)
+def response(newMsg:str, chatHistory, instruction, temperature, max_tokens, model, stream=False):
+	prompt = formatPrompt(newMsg=newMsg, chatHistory=chatHistory, instruction=instruction)
+	response = APIcall(prompt=prompt, temperature=temperature, max_tokens=max_tokens, model=model)
+	chatHistory.append([newMsg, response])
+	return "", chatHistory
+
+# def the streamResponse function, to stream the results as they are generated
+def streamResponse(newMsg:str, chatHistory, instruction, temperature, max_tokens, model, stream = True):
+	chatHistory.append([newMsg, ""])
+	prompt = formatPrompt(newMsg=newMsg, chatHistory=chatHistory, instruction=instruction)
+	stream = APIcall(prompt=prompt, temperature=temperature, max_tokens=max_tokens, model=model)
+	for chunk in stream:
+		if chunk != None:
+			chatHistory[-1][1] += chunk
+			yield "", chatHistory
+		else:
+			return "", chatHistory
+
+# Build the app
+with gr.Blocks(theme='Insuz/Mocha') as app:
+	gr.Markdown("# Private GPT")
+	gr.Markdown("This chatbot is powered by the openAI GPT series.\
+			 \nThe default model is `GPT-3.5`, but `GPT-4` can be selected in the advanced options.\
+			 \nAs it uses the openAI API, user data is not used to train openAI models.")
+	chatbot = gr.Chatbot() # Associated variable: chatHistory
+	msg = gr.Textbox(label="Message")
+	with gr.Accordion(label="Advanced options", open=False):
+		model = gr.Dropdown(
+			choices=["GPT-3.5", "GPT-4"],
+			value="GPT-3.5",
+			multiselect=False,
+			label="Model",
+			info="Choose the model you want to chat with"
+		)
+		instruction = gr.Textbox(
+			value=SYSTEM_PROMPT,
+			label="System instructions",
+			lines=2,)
+		temperature = gr.Slider(
+			minimum=0,
+			maximum=2,
+			step=0.1,
+			value=0.7,
+			label="Temperature",
+			info="The higher, the more random the results will be"
+		)
+		max_token = gr.Slider(
+			minimum=64,
+			maximum=2048,
+			step=64,
+			value=1024,
+			label="Max Token",
+			info="Maximum number of token the model will take into consideration"
+		)
+	Button = gr.Button(value="Submit")
+	msg.submit(
+		fn=streamResponse,
+		inputs=[msg, chatbot, instruction, temperature, max_token, model],
+		outputs=[msg, chatbot]
+	)
+	Button.click(
+		fn=streamResponse,
+		inputs=[msg, chatbot, instruction, temperature, max_token, model],
+		outputs=[msg, chatbot]
+	)
+
+gr.close_all()
+app.queue().launch(auth=(AUTH_USERNAME, AUTH_PASSWORD))
+
+# %%
+
+
+

requirements.txt

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+gradio == 4.14.1
+openai == 1.3.6
+dotenv