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| import gradio as gr | |
| import os | |
| import requests | |
| from huggingface_hub import InferenceClient | |
| import google.generativeai as genai | |
| import openai | |
| def api_check_msg(api_key, selected_model): | |
| res = validate_api_key(api_key, selected_model) | |
| return res["message"] | |
| def validate_api_key(api_key, selected_model): | |
| # Check if the API key is valid for GPT-3.5-Turbo | |
| if "GPT" in selected_model: | |
| url = "https://api.openai.com/v1/models" | |
| headers = { | |
| "Authorization": f"Bearer {api_key}" | |
| } | |
| try: | |
| response = requests.get(url, headers=headers) | |
| if response.status_code == 200: | |
| return {"is_valid": True, "message": '<p style="color: green;">API Key is valid!</p>'} | |
| else: | |
| return {"is_valid": False, "message": f'<p style="color: red;">Invalid OpenAI API Key. Status code: {response.status_code}</p>'} | |
| except requests.exceptions.RequestException as e: | |
| return {"is_valid": False, "message": f'<p style="color: red;">Invalid OpenAI API Key. Error: {e}</p>'} | |
| elif "Llama" in selected_model: | |
| url = "https://huggingface.co/api/whoami-v2" | |
| headers = { | |
| "Authorization": f"Bearer {api_key}" | |
| } | |
| try: | |
| response = requests.get(url, headers=headers) | |
| if response.status_code == 200: | |
| return {"is_valid": True, "message": '<p style="color: green;">API Key is valid!</p>'} | |
| else: | |
| return {"is_valid": False, "message": f'<p style="color: red;">Invalid Hugging Face API Key. Status code: {response.status_code}</p>'} | |
| except requests.exceptions.RequestException as e: | |
| return {"is_valid": False, "message": f'<p style="color: red;">Invalid Hugging Face API Key. Error: {e}</p>'} | |
| elif "Gemini" in selected_model: | |
| try: | |
| genai.configure(api_key=api_key) | |
| model = genai.GenerativeModel("gemini-1.5-flash") | |
| response = model.generate_content("Help me diagnose the patient.") | |
| return {"is_valid": True, "message": '<p style="color: green;">API Key is valid!</p>'} | |
| except Exception as e: | |
| return {"is_valid": False, "message": f'<p style="color: red;">Invalid Google API Key. Error: {e}</p>'} | |
| def generate_text_chatgpt(key, prompt, temperature, top_p): | |
| openai.api_key = key | |
| prompt_template = f""" | |
| {prompt} <Choose only one among the words Psoriasis, Arthritis, Bronchial asthma or Cervical spondylosis> | |
| """ | |
| response = openai.chat.completions.create( | |
| model="gpt-3.5-turbo-1106", | |
| messages=[{"role": "system", "content": "You are a talented diagnostician who is diagnosing a patient."}, | |
| {"role": "user", "content": prompt_template}], | |
| temperature=temperature, | |
| max_tokens=50, | |
| top_p=top_p, | |
| frequency_penalty=0 | |
| ) | |
| return response.choices[0].message.content | |
| def generate_text_gemini(key, prompt, temperature, top_p): | |
| genai.configure(api_key=key) | |
| prompt_template = f""" | |
| {prompt} <Choose only one among the words Psoriasis, Arthritis, Bronchial asthma or Cervical spondylosis> | |
| """ | |
| generation_config = genai.GenerationConfig( | |
| max_output_tokens=len(prompt_template)+50, | |
| temperature=temperature, | |
| top_p=top_p, | |
| ) | |
| model = genai.GenerativeModel("gemini-1.5-flash", generation_config=generation_config) | |
| response = model.generate_content(prompt_template) | |
| return response.text | |
| def generate_text_llama(key, prompt, temperature, top_p): | |
| model_name = "meta-llama/Meta-Llama-3-8B-Instruct" | |
| client = InferenceClient(api_key=key) | |
| prompt_template = f""" | |
| {prompt} <Choose only one among the words Psoriasis, Arthritis, Bronchial asthma or Cervical spondylosis> | |
| Do not list the symptoms again in the response. Do not add any additional text. Do not attempt to explain your answer. | |
| """ | |
| messages = [{"role": "system", "content": "You are a talented diagnostician who is diagnosing a patient."}, | |
| {"role": "user","content": prompt_template}] | |
| completion = client.chat.completions.create( | |
| model=model_name, | |
| messages=messages, | |
| max_tokens=len(prompt_template)+50, | |
| temperature=temperature, | |
| top_p=top_p | |
| ) | |
| response = completion.choices[0].message.content | |
| if len(response) > len(prompt_template): | |
| return response[len(prompt_template):] | |
| return response | |
| def diagnose(key, model, top_k, temperature, symptom_prompt): | |
| model_map = { | |
| "GPT-3.5-Turbo": "GPT", | |
| "Llama-3": "Llama", | |
| "Gemini-1.5": "Gemini" | |
| } | |
| if symptom_prompt: | |
| if "GPT" in model: | |
| message = generate_text_chatgpt(key, symptom_prompt, temperature, top_k) | |
| elif "Llama" in model: | |
| message = generate_text_llama(key, symptom_prompt, temperature, top_k) | |
| elif "Gemini" in model: | |
| message = generate_text_gemini(key, symptom_prompt, temperature, top_k) | |
| else: | |
| message = "Incorrect model, please try again." | |
| else: | |
| message = "Please add the symptoms data" | |
| return message | |
| def update_model_components(selected_model): | |
| model_map = { | |
| "GPT-3.5-Turbo": "GPT", | |
| "Llama-3": "Llama", | |
| "Gemini-1.5": "Gemini" | |
| } | |
| link_map = { | |
| "GPT-3.5-Turbo": "https://platform.openai.com/account/api-keys", | |
| "Llama-3": "https://hf.co/settings/tokens", | |
| "Gemini-1.5": "https://aistudio.google.com/apikey" | |
| } | |
| textbox_label = f"Please input the API key for your {model_map[selected_model]} model" | |
| button_value = f"Don't have an API key? Get one for the {model_map[selected_model]} model here." | |
| button_link = link_map[selected_model] | |
| return gr.update(label=textbox_label), gr.update(value=button_value, link=button_link) | |
| def toggle_button(symptoms_text, api_key, model): | |
| if symptoms_text.strip() and validate_api_key(api_key, model): | |
| return gr.update(interactive=True) | |
| return gr.update(interactive=False) | |
| with gr.Blocks() as ui: | |
| with gr.Row(equal_height=500): | |
| with gr.Column(scale=1, min_width=300): | |
| model = gr.Radio(label="LLM Selection", value="GPT-3.5-Turbo", | |
| choices=["GPT-3.5-Turbo", "Llama-3", "Gemini-1.5"]) | |
| is_valid = False | |
| key = gr.Textbox(label="Please input the API key for your Large Language model", type="password") | |
| status_message = gr.HTML(label="Validation Status") | |
| key.input(fn=api_check_msg, inputs=[key, model], outputs=status_message) | |
| button = gr.Button(value="Don't have an API key? Get one for the GPT model here.", link="https://platform.openai.com/account/api-keys") | |
| model.change(update_model_components, inputs=model, outputs=[key, button]) | |
| gr.ClearButton(key, variant="primary") | |
| with gr.Column(scale=2, min_width=600): | |
| gr.Markdown("## Hello, Welcome to the GUI by Team #9.") | |
| temperature = gr.Slider(0.0, 1.0, value=0.7, step = 0.05, label="Temperature", info="Set the Temperature") | |
| top_p = gr.Slider(0.0, 1.0, value=0.9, step = 0.05, label="top-p value", info="Set the sampling nucleus parameter") | |
| symptoms = gr.Textbox(label="Add the symptom data in the input to receive diagnosis") | |
| llm_btn = gr.Button(value="Diagnose Disease", variant="primary", elem_id="diagnose", interactive=False) | |
| symptoms.input(toggle_button, inputs=[symptoms, key, model], outputs=llm_btn) | |
| key.input(toggle_button, inputs=[symptoms, key, model], outputs=llm_btn) | |
| model.change(toggle_button, inputs=[symptoms, key, model], outputs=llm_btn) | |
| output = gr.Textbox(label="LLM Output Status", interactive=False, placeholder="Output will appear here...") | |
| llm_btn.click(fn=diagnose, inputs=[key, model, top_p, temperature, symptoms], outputs=output, api_name="LLM_Comparator") | |
| ui.launch(share=True) |