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add messages example to readme
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36
README.md
36
README.md
@@ -48,15 +48,41 @@ import tokencost
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2. Calculate tokens and cost (using `from tokencost import *`):
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```python
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prompt = "Your sample text here"
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string_prompt = "Your sample text here"
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response = "Sample response text"
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model= "gpt-3.5-turbo"
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prompt_token_count = count_string_tokens(prompt, model)
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completion_token_count = count_string_tokens(response, model)
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cost = calculate_cost(prompt, response, model)
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string_cost = calculate_cost(string_prompt, response, model)
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print(f"Prompt Token Count: {prompt_token_count}, Completion Token Count: {completion_token_count}, Cost: ${cost/USD_PER_TPU} ({cost/CENTS_PER_TPU} cents)")
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prompt_string_token_count = count_string_tokens(string_prompt, model)
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print(f"Prompt Token Count: {prompt_string_token_count}, Completion Token Count:{completion_string_token_count}, Cost: ${string_cost/USD_PER_TPU} ({string_cost/CENTS_PER_TPU} cents)")
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messages =[
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{
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"role": "user",
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"content": "Hey how is your day",
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},
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{
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"role": 'assistant',
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"content": "As an LLM model I do not have days"
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},
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{
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"role": "user",
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"content": "Err sure okay fine"
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}
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]
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response = "Sample response text"
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model= "gpt-3.5-turbo"
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message_cost = calculate_cost(messages, response, model)
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prompt_message_token_count = count_message_tokens(messages, model)
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completion_string_token_count = count_string_tokens(response, model)
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print(f"Prompt Token Count: {prompt_message_token_count}, Completion Token Count: {completion_string_token_count}, Cost: ${message_cost/USD_PER_TPU} ({message_cost/CENTS_PER_TPU} cents)")
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```
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This is what it should look like when you use iPython:
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