Create app.py

app.py

@@ -0,0 +1,141 @@
+import gradio as gr
+import os
+import openai
+import json
+import tiktoken
+import pandas as pd
+
+openai.api_key = os.environ["OPENAI_API_KEY"]
+prompt_templates = {"Default ChatGPT": ""}
+
+def num_tokens_from_messages(messages, model="gpt-3.5-turbo"):
+    """Returns the number of tokens used by a list of messages."""
+    try:
+        encoding = tiktoken.encoding_for_model(model)
+    except KeyError:
+        encoding = tiktoken.get_encoding("cl100k_base")
+    if model == "gpt-3.5-turbo": 
+        num_tokens = 0
+        for message in messages:
+            num_tokens += 4  # every message follows <im_start>{role/name}\n{content}<im_end>\n
+            for key, value in message.items():
+                num_tokens += len(encoding.encode(value))
+                if key == "name":  # if there's a name, the role is omitted
+                    num_tokens += -1  # role is always required and always 1 token
+        num_tokens += 2  # every reply is primed with <im_start>assistant
+        return num_tokens
+    else:
+        raise NotImplementedError(f"""num_tokens_from_messages() is not presently implemented for model {model}. 
+        See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens.""")
+
+
+def get_empty_state():
+    return {"total_tokens": 0, "messages": [], "threshold": 0}
+
+def download_prompt_templates():
+    df = pd.read_csv('prompts.csv', encoding='unicode_escape')
+    prompt_templates.update(dict(zip(df['act'], df['prompt'])))
+    choices = list(prompt_templates.keys())
+    return gr.update(value=choices[0], choices=choices)
+
+def on_token_change(user_token):
+    openai.api_key = user_token or os.environ.get("OPENAI_API_KEY")
+
+def on_prompt_template_change(prompt_template):
+    if not isinstance(prompt_template, str): return
+    return prompt_templates[prompt_template]
+
+def submit_message(prompt, prompt_template, temperature, max_tokens, state):
+
+    history = state['messages']
+
+    if not prompt:
+        return gr.update(value='', visible=state['total_tokens'] < 1_000), [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)], f"Total tokens used: {state['total_tokens']} / 4090", state
+    
+    prompt_template = prompt_templates[prompt_template]
+    print(prompt_template)
+    system_prompt = []
+    if prompt_template:
+        system_prompt = [{ "role": "system", "content": prompt_template}]
+
+    prompt_msg = {"role": "user", "content": prompt }
+    
+    # check length token message
+    messages = system_prompt + history + [prompt_msg]
+    history_id = 2
+    while num_tokens_from_messages(messages) >= 4090:
+        messages = system_prompt + history[history_id:] + [prompt_msg]
+        history_id +=2
+        state['threshold'] +=1
+        if history_id > len(history):
+            break
+    try:
+        completion = openai.ChatCompletion.create(model="gpt-3.5-turbo", messages=messages, temperature=temperature, max_tokens=max_tokens)
+        history.append(prompt_msg)
+        history.append(completion.choices[0].message.to_dict())
+
+        state['total_tokens'] += completion['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']} / 4090. "
+    chat_messages = [(history[i]['content'], history[i+1]['content']) for i in range(0, len(history)-1, 2)]
+
+    if state['threshold'] >= 3:
+        input_visibility = False
+        total_tokens_used_msg += "Reach the limit of this conversation. Start the new one"
+    else:
+        input_visibility = True
+
+    return gr.update(value='', visible=input_visibility), chat_messages, total_tokens_used_msg, state
+
+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;}
+      #prompt_template_preview {padding: 1em; border-width: 1px; border-style: solid; border-color: #e0e0e0; border-radius: 4px;}
+      #total_tokens_str {text-align: right; font-size: 0.8em; color: #666; height: 1em;}
+      #label {font-size: 0.8em; padding: 0.5em; margin: 0;}
+      """
+
+with gr.Blocks(css=css) as demo:
+    
+    state = gr.State(get_empty_state())
+
+
+    with gr.Column(elem_id="col-container"):
+        gr.Markdown("""## OpenAI ChatGPT with awesome prompts
+                    Current limit is 4090 tokens per conversation<br>
+                    Input your text with a custom insruction (If need).""",
+                    elem_id="header")
+
+        with gr.Row():
+            with gr.Column():
+                chatbot = gr.Chatbot(elem_id="chatbox")
+                input_message = gr.Textbox(show_label=False, placeholder="Enter text and press enter", visible=True).style(container=False)
+                total_tokens_str = gr.Markdown(elem_id="total_tokens_str")
+                btn_clear_conversation = gr.Button("🔃 Start New Conversation")
+            with gr.Column():
+                prompt_template = gr.Dropdown(label="Set a custom insruction for the chatbot:", choices=list(prompt_templates.keys()))
+                prompt_template_preview = gr.Markdown(elem_id="prompt_template_preview")
+
+                with gr.Accordion("Advanced parameters", open=False):
+                    temperature = gr.Slider(minimum=0, maximum=2.0, value=0.7, step=0.1, interactive=True, label="Temperature (higher = more creative/chaotic)")
+                    max_tokens = gr.Slider(minimum=100, maximum=4096, value=1000, step=1, interactive=True, label="Max tokens per response")
+
+    input_message.submit(submit_message, [input_message, prompt_template, temperature, max_tokens, state], [input_message, chatbot, total_tokens_str, state])
+    btn_clear_conversation.click(clear_conversation, [], [input_message, chatbot, total_tokens_str, state])
+    prompt_template.change(on_prompt_template_change, inputs=[prompt_template], outputs=[prompt_template_preview])
+
+    demo.load(download_prompt_templates, inputs=None, outputs=[prompt_template])
+
+
+demo.launch(debug=True, height='800px', share=True, auth=("admin", "dtm1234"))