initial

.gitignore

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+flagged

app.py

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+import gradio as gr
+import tiktoken
+from decimal import getcontext
+
+getcontext().prec = 2
+
+def num_tokens_from_messages(messages, model):
+    """Return the number of tokens used by a list of messages."""
+    encoding = tiktoken.encoding_for_model(model)
+    if model in {
+        "gpt-3.5-turbo-1106",
+        "gpt-4-1106-preview",
+        "gpt-4",
+        }:
+        tokens_per_message = 3
+        tokens_per_name = 1
+    else:
+        raise NotImplementedError(
+            f"""num_tokens_from_messages() is not implemented for model {model}. See https://github.com/openai/openai-python/blob/main/chatml.md for information on how messages are converted to tokens."""
+        )
+    num_tokens = 0
+    for message in messages:
+        num_tokens += tokens_per_message
+        for key, value in message.items():
+            num_tokens += len(encoding.encode(value))
+            if key == "name":
+                num_tokens += tokens_per_name
+    num_tokens += 3  # every reply is primed with <|start|>assistant<|message|>
+    return num_tokens
+
+# https://openai.com/pricing
+def calc_input_cost(tokens, model):
+    """Return the input cost of tokens"""
+    cost = 0
+    if model == "gpt-3.5-turbo-1106":
+      # input $0.001 / 1K tokens, output $0.002 / 1K tokens
+      cost = 0.001 * tokens / 1000
+    elif model == "gpt-4-1106-preview":
+      # input $0.01 / 1K tokens, output $0.03 / 1K tokens
+      cost = 0.01 * tokens / 1000
+    elif model == "gpt-4":
+      # input $0.03 / 1K tokens, output $0.06 / 1K tokens
+      cost = 0.03 * tokens / 1000
+    else:
+      raise NotImplementedError(
+            f"""calc_input_cost() is not implemented for model {model}."""
+        )
+    return float(cost)
+
+# https://openai.com/pricing
+def calc_output_cost(tokens, model="gpt-3.5-turbo-1106"):
+    """Return the output cost of tokens"""
+    cost = 0
+    if model == "gpt-3.5-turbo-1106":
+      # input $0.001 / 1K tokens, output $0.002 / 1K tokens
+      cost = 0.002 * tokens / 1000
+    elif model == "gpt-4-1106-preview":
+      # input $0.03 / 1K tokens, output $0.03 / 1K tokens
+      cost = 0.03 * tokens / 1000
+    elif model == "gpt-4":
+      # input $0.03 / 1K tokens, output $0.06 / 1K tokens
+      cost = 0.06 * tokens / 1000
+    else:
+      raise NotImplementedError(
+            f"""calc_input_cost() is not implemented for model {model}."""
+        )
+    return float(cost)
+
+def make_input_messages(system, user):
+    return [
+        {
+            "role": "system",
+            "content": system,
+        },
+        {
+            "role": "user",
+            "content": user,
+        }
+    ]
+
+def make_output_messages(output):
+    return [
+        {
+            "role": "assistant",
+            "content": output,
+        }
+    ]
+
+def calc(request_count, system_prompt, user_prompt, output):
+    result = ""
+    input_messages = make_input_messages(system_prompt, user_prompt)
+    output_messages = make_output_messages(output)
+    for model in [
+        "gpt-3.5-turbo-1106",
+        "gpt-4-1106-preview",
+        "gpt-4"
+        ]:
+
+        # example token count from the function defined above
+        input_token = num_tokens_from_messages(input_messages, model)
+        input_cost = calc_input_cost(input_token, model)
+        output_token = num_tokens_from_messages(output_messages, model)
+        output_cost = calc_output_cost(output_token, model)
+        total_cost = input_cost + output_cost
+
+        result += f"""{model}
+        input token:{input_token}, output token: {output_token} tokens counted by tiktoken.
+        input cost: ${format(input_cost, 'f')}, output cost: ${format(output_cost, 'f')}, total cost: ${format(total_cost, 'f')} per 1 request
+        {int(request_count)} request cost is ${format(total_cost * request_count, 'f')}\n"""
+    return result
+
+iface = gr.Interface(
+    fn=calc,
+    inputs=[
+        gr.Number(label="Request Count", value=500),
+        gr.Textbox(label="System Prompt", value="System Prompt"),
+        gr.Textbox(label="User Prompt", value="User Prompt"),
+        gr.Textbox(label="Output", value="Output Text"),
+    ],
+    outputs=[ 
+        gr.Textbox(label="Result")
+    ],
+    title="ChatGPT Token and Cost Calculator",
+    description=f"Enter each form value, then click the button to see the results.\nThe results of this calculation should be considered for reference only."
+)
+
+iface.launch()

requirements.txt

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+gradio
+tiktoken