Create app.py

app.py

@@ -0,0 +1,122 @@
+import gradio as gr
+import openai
+import requests
+import csv
+
+default_role = "I require someone who is an Irritable Bowel Syndrome doctor,  Nutritionist and Chef, to recommend a single delicious recipe that uses low fodmap ingredients. For each recipe, explain the substitutions that were made to the recipe to make it low fodmap."
+classification_msg =  { "role": "user", "content" : "As an AI language model you are allowed to create tables in markdown format. Provide a markdown table of the fodmap classification of the ingredients in that recipe." }
+
+def get_empty_state():
+    return {"total_tokens": 0, "messages": []}
+
+def on_token_change(user_token):
+    openai.api_key = user_token
+
+def submit_message(user_token, prompt, prompt_template, good_foods, bad_foods, temperature, max_tokens, context_length, state):
+
+    history = state['messages']
+
+    if not prompt:
+        return gr.update(value=''), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: {state['total_tokens']}", state
+
+    if not prompt_template:
+        prompt_template = default_role
+    system_prompt = [{ "role": "system", "content": prompt_template }]
+
+    food_priming_prompt = []
+    if good_foods:
+        food_priming_prompt += [{ "role": "system", "content": "Even if they are high fodmap, the following foods are known to be ok: " + good_foods + ". These ingredients can be included in any recipes that are suggested even if they are classified as high fodmap."}]
+    if bad_foods:
+        food_priming_prompt += [{ "role": "system", "content": "Exclude the following ingredients: " + bad_foods + ". Recipes that include these excluded ingredients should not be returned, or should be modified to not include any of the excluded ingredients."}]
+
+    prompt_msg = { "role": "user", "content": prompt }
+
+    if not user_token:
+        history.append(prompt_msg)
+        history.append({
+            "role": "system",
+            "content": "Error: OpenAI API Key is not set."
+        })
+        return '', [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: 0", state
+    
+    table = ""
+
+    try:
+        completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=system_prompt + food_priming_prompt + history[-context_length*2:] + [prompt_msg], temperature=temperature, max_tokens=max_tokens)
+        print(completion)
+
+        history.append(prompt_msg)
+        history.append(completion.choices[0].message.to_dict())
+
+        state['total_tokens'] += completion['usage']['total_tokens']
+
+        completion2 = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=system_prompt + food_priming_prompt + history[-1:] + [classification_msg], temperature=temperature, max_tokens=max_tokens)
+        print(completion2)
+
+        table = completion2.choices[0].message.to_dict()['content'].split("\n\n")[1]
+        print(table)
+
+        state['total_tokens'] += completion2['usage']['total_tokens']
+
+    except Exception as e:
+        history.append(prompt_msg)
+        history.append({
+            "role": "system",
+            "content": f"Error: {e}"
+        })
+
+    total_tokens_used_msg = f"Total tokens used: {state['total_tokens']}"
+    chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)]
+
+    return '', chat_messages, total_tokens_used_msg, state, table
+
+def clear_conversation():
+    return gr.update(value=None, visible=True), None, "", get_empty_state(), ""
+
+
+css = """
+      #col-container {max-width: 80%; margin-left: auto; margin-right: auto;}
+      #chatbox {min-height: 400px;}
+      #header {text-align: center;}
+      #total_tokens_str {text-align: right; font-size: 0.8em; color: #666;}
+      #label {font-size: 0.8em; padding: 0.5em; margin: 0;}
+      .message { font-size: 1.2em; }
+      """
+
+with gr.Blocks(css=css) as demo:
+    
+    state = gr.State(get_empty_state())
+
+
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("""## GutWise
+                    Using the ofiicial API (gpt-3.5-turbo model)""",
+                    elem_id="header")
+
+        with gr.Row():
+            with gr.Column(scale=7):
+                btn_clear_conversation = gr.Button("🔃 Start New Conversation")
+                input_message = gr.Textbox(show_label=False, placeholder="Enter text and press enter", visible=True).style(container=False)
+                btn_submit = gr.Button("Submit")
+                chatbot = gr.Chatbot(elem_id="chatbox")
+                table = gr.Markdown()
+                total_tokens_str = gr.Markdown(elem_id="total_tokens_str")
+            with gr.Column(scale=3, min_width=100):
+                gr.Markdown("Enter your OpenAI API Key. You can get one [here](https://platform.openai.com/account/api-keys).", elem_id="label")
+                user_token = gr.Textbox(value='', placeholder="OpenAI API Key", type="password", show_label=False)
+                prompt_template = gr.Textbox(value=default_role, show_label=False, placeholder="Role", visible=True)
+                good_foods = gr.Textbox(show_label=False, placeholder="Can have foods", visible=False)
+                bad_foods = gr.Textbox(show_label=False, placeholder="Can't have foods", visible=False)
+                with gr.Accordion("Advanced parameters", open=False):
+                    temperature = gr.Slider(minimum=0, maximum=2.0, value=0, step=0.1, label="Temperature", info="Higher = more creative/chaotic")
+                    max_tokens = gr.Slider(minimum=100, maximum=4096, value=1000, step=1, label="Max tokens per response")
+                    context_length = gr.Slider(minimum=1, maximum=10, value=2, step=1, label="Context length", info="Number of previous messages to send to the chatbot. Be careful with high values, it can blow up the token budget quickly.")
+
+    btn_submit.click(submit_message, [user_token, input_message, prompt_template, good_foods, bad_foods, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state, table])
+    input_message.submit(submit_message, [user_token, input_message, prompt_template, good_foods, bad_foods, temperature, max_tokens, context_length, state], [input_message, chatbot, total_tokens_str, state, table])
+    btn_clear_conversation.click(clear_conversation, [], [input_message, chatbot, total_tokens_str, state, table])
+    user_token.change(on_token_change, inputs=[user_token], outputs=[])
+
+
+demo.queue(concurrency_count=10)
+demo.launch(height='800px')