Live programming @ University of Washington
prompt1 = `Consider the task of annotation updating. Look at the following old annotated file, then copy the annotations to the updated version of the file below it. In this case, annotations are represented by numbered opening and closing tags, like <1> </1>. Your response should be only the updated file with annotations transferred to analogous positions.
OLD ANNOTATED FILE:
${old_annotated_file}
END OLD ANNOTATED FILE
UPDATED FILE:
${updated_file}
END UPDATED FILE
Write your answer below. Again, your response should be only the updated file with annotations transferred to analogous positions.
`
output = askChatGPT(prompt1)
fpcore = askChatGPT(fpcore_prompt(output))
import {secret} from "@tmcw/secret"
openai = new OpenAI({
apiKey: OPENAI_API_KEY,
dangerouslyAllowBrowser: true
})
OpenAI = (await import("https://esm.sh/openai@4.19.0")).OpenAI
test = {
//return 42 // comment to run test on completion endpoint
let completion = await openai.chat.completions.create({
model: "gpt-3.5-turbo",
messages: [
//{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: fpcore_prompt },
// {
// role: "assistant",
// content: "4"
// },
// { role: "user", content: "What is 3 times 3?" }
]
});
console.log(completion.choices[0]);
return completion;
}
test.choices[0].message.content
messages = [
//{ role: "system", content: "You are a helpful assistant." },
{ role: "user", content: prompt },
// {
// role: "assistant",
// content: "4"
// },
// { role: "user", content: "What is 3 times 3?" }
]
function getFirstChoice(completion) {
return completion.choices[0].message.content
}
async function getChatCompletion(model, messages) {
let completion = await openai.chat.completions.create({
model, //: "gpt-3.5-turbo",
messages
})
return completion;
}
getChatCompletion([{role: 'user', content: prompt1}])
async function askChatGPT(prompt, model='gpt-3.5-turbo') {
return getFirstChoice(await getChatCompletion(model, [{role: 'user', content: prompt}]))
}
output1 = `static Py_complex
cmath_asinh_impl(PyObject *module, Py_complex z)
/*[clinic end generated code: output=733d8107841a7599 input=5c09448fcfc89a79]*/
/*last modified Jan 2024*/
{
Py_complex s1, s2, r;
SPECIAL_VALUE(z, asinh_special_values);
if (fabs(z.real) > CM_LARGE_DOUBLE || fabs(z.imag) > CM_LARGE_DOUBLE) {
if (z.imag >= 0.) {
r.real = copysign(<1>log(hypot(z.real/2., z.imag/2.)) +
M_LN2*2.</1>, z.real);
} else {
r.real = -copysign(log(hypot(z.real/2., z.imag/2.)) +
M_LN2*2., -z.real);
}
r.imag = atan2(z.imag, fabs(z.real));
} else {
s1.real = 1.+z.imag;
s1.imag = -z.real;
s1 = cmath_sqrt_impl(module, s1);
s2.real = 1.-z.imag;
s2.imag = z.real;
s2 = cmath_sqrt_impl(module, s2);
r.real = asinh(s1.real*s2.imag-s2.real*s1.imag);
r.imag = atan2(z.imag, s1.real*s2.real-s1.imag*s2.imag);
}
errno = 0;
return r;
}
END UPDATED FILE`
function extractFirstMatch(str) {
const regex = /<1>(.*?)<\/1>/s;
const match = str.match(regex);
return match ? match[1] : null;
}
fpcore_prompt = output => `Consider the following Python code.
\`\`\`python
import math
def compute_expression(N):
if N > 1 and N < 1e+40:
if N >= 1e+3:
return 1/N - 1/(2*N**2) + 1/(3*N**3) - 1/(4*N**4)
else:
return math.log(1 + 1/N)
else:
return "N is out of the valid range"
\`\`\`
We can represent this expression in FPCore, a format for floating-point analysis, as follows:
\`\`\`fpcore
(FPCore (N)
:pre (and (> N 1) (< N 1e+40))
(if (>= N 1e+3)
(+ (/ 1 N) (/ -1 (* 2 (pow N 2))) (/ 1 (* 3 (pow N 3))) (/ -1 (* 4 (pow N 4))))
(log (+ 1 (/ 1 N)))))
\`\`\`
Now, represent the following expression (which may or may not be Python!) as an FPCore expression:
${extractFirstMatch(output)}
Write the FPCore expression only below.
`
/*
TODO
Model may need fine-tune or introductory examples of how this process works, especially for covering corner cases.
* Test effect of structure of language on success
* Maybe in some places error is tolerated?
* Could it learn through examples?
* Probably should let the user help the model fit the domain
Things to do with the snippet
* Translate into English
* Execute
* Visualize
* Structured editing/Livelits
* Using AST/types would let you attach visualizations to particular branches
* Test different models
* would want to know what users "mean" by section
* what about one-to-many mappings (code duplication)
* Git 3-way-merge as baseline -- good as anecdote
*
*/
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