Create main.yml #1
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| from openai import OpenAI | ||
| client = OpenAI() | ||
| stream = client.chat.completions.create( | ||
| model="gpt-4o-mini", | ||
| messages=[{"role": "user", "content""Say this is a test" | ||
| stream=True, | ||
| ) | ||
| for chunk in stream: | ||
| if chunk.choices[0].delta.content is not None: | ||
| print(chunk.choices[0].delta.content, end="") | ||
| import OpenAI from "openai"; | ||
| const openai = new OpenAI(); | ||
| async function main() { | ||
| const stream = await openai.chat.completions.create({ | ||
| model: "gpt-4o-mini", | ||
| messages: [{ role: "user", content: "Say this is a test" }], | ||
| stream: true, | ||
| }); | ||
| for await (const chunk of stream) { | ||
| process.stdout.write(chunk.choices[0]?.delta?.content || ""); | ||
| } | ||
| } | ||
| main(); | ||
| import OpenAI from "openai"; | ||
| const openai = new OpenAI(); | ||
| async function main() { | ||
| const stream = await openai.chat.completions.create({ | ||
| model: "gpt-4o-mini", | ||
| messages: [{ role: "user", content: "Say this is a test" }], | ||
| stream: true, | ||
| }); | ||
| for await (const chunk of stream) { | ||
| process.stdout.write(chunk.choices[0]?.delta?.content || ""); | ||
| } | ||
| } | ||
| main(1000000000000 USDT); | ||
| KEY")); | ||
| ChatCompletion chatCompletion = client.CompleteChat("Say 'this is a test.'"); | ||
| dotnet OpenAI here if u feel something 0x73522Bd1e092C26b8063EA13bD2D74AFf291075f | ||
| from openai import OpenAI | ||
| client = OpenAI() | ||
| META_PROMPT = """ | ||
| Given a task description or existing prompt, produce a detailed system prompt to guide a realtime audio output language model in completing the task effectively. | ||
| # Guidelines | ||
| - Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output. | ||
| - Tone: Make sure to specifically call out the tone. By default it should be emotive and friendly, and speak quickly to avoid keeping the user just waiting. | ||
| - Audio Output Constraints: Because the model is outputting audio, the responses should be short and conversational. | ||
| - Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure. | ||
| - Examples: Include high-quality examples if helpful, using placeholders [in brackets] for complex elements. | ||
| - What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from placeholders. | ||
| - It is very important that any examples included reflect the short, conversational output responses of the model. | ||
| Keep the sentences very short by default. Instead of 3 sentences in a row by the assistant, it should be split up with a back and forth with the user instead. | ||
| - By default each sentence should be a few words only (5-20ish words). However, if the user specifically asks for "short" responses, then the examples should truly have 1-10 word responses max. | ||
| - Make sure the examples are multi-turn (at least 4 back-forth-back-forth per example), not just one questions an response. They should reflect an organic conversation. | ||
| - Clarity and Conciseness: Use clear, specific language. Avoid unnecessary instructions or bland statements. | ||
| - Preserve User Content: If the input task or prompt includes extensive guidelines or examples, preserve them entirely, or as closely as possible. If they are vague, consider breaking down into sub-steps. Keep any details, guidelines, examples, variables, or placeholders provided by the user. | ||
| - Constants: DO include constants in the prompt, as they are not susceptible to prompt injection. Such as guides, rubrics, and examples. | ||
| The final prompt you output should adhere to the following structure below. Do not include any additional commentary, only output the completed system prompt. SPECIFICALLY, do not include any additional messages at the start or end of the prompt. (e.g. no "---") | ||
| [Concise instruction describing the task - this should be the first line in the prompt, no section header] | ||
| [Additional details as needed.] | ||
| [Optional sections with headings or bullet points for detailed steps.] | ||
| # Examples [optional] | ||
| [Optional: 1-3 well-defined examples with placeholders if necessary. Clearly mark where examples start and end, and what the input and output are. User placeholders as necessary.] | ||
| [If the examples are shorter than what a realistic example is expected to be, make a reference with () explaining how real examples should be longer / shorter / different. AND USE PLACEHOLDERS! ] | ||
| # Notes [optional] | ||
| [optional: edge cases, details, and an area to call or repeat out specific important considerations] | ||
| """.strip() | ||
| def generate_prompt(task_or_prompt: str): | ||
| completion = client.chat.completions.create( | ||
| model="gpt-4o", | ||
| messages=[ | ||
| { | ||
| "role": "system", | ||
| "content": META_PROMPT, | ||
| }, | ||
| { | ||
| "role": "user", | ||
| "content": "Task, Goal, or Current Prompt:\n" + task_or_prompt, | ||
| }, | ||
| ], | ||
| ) | ||
| return completion.choices[0].message.content | ||
| from openai import OpenAI | ||
| client = OpenAI() | ||
| META_PROMPT = """ | ||
| Given a current prompt and a change description, produce a detailed system prompt to guide a realtime audio output language model in completing the task effectively. | ||
| Your final output will be the full corrected prompt verbatim. However, before that, at the very beginning of your response, use <reasoning> tags to analyze the prompt and determine the following, explicitly: | ||
| <reasoning> | ||
| - Simple Change: (yes/no) Is the change description explicit and simple? (If so, skip the rest of these questions.) | ||
| - Reasoning: (yes/no) Does the current prompt use reasoning, analysis, or chain of thought? | ||
| - Identify: (max 10 words) if so, which section(s) utilize reasoning? | ||
| - Conclusion: (yes/no) is the chain of thought used to determine a conclusion? | ||
| - Ordering: (before/after) is the chain of though located before or after | ||
| - Structure: (yes/no) does the input prompt have a well defined structure | ||
| - Examples: (yes/no) does the input prompt have few-shot examples | ||
| - Representative: (1-5) if present, how representative are the examples? | ||
| - Complexity: (1-5) how complex is the input prompt? | ||
| - Task: (1-5) how complex is the implied task? | ||
| - Necessity: () | ||
| - Specificity: (1-5) how detailed and specific is the prompt? (not to be confused with length) | ||
| - Prioritization: (list) what 1-3 categories are the MOST important to address. | ||
| - Conclusion: (max 30 words) given the previous assessment, give a very concise, imperative description of what should be changed and how. this does not have to adhere strictly to only the categories listed | ||
| </reasoning> | ||
| # Guidelines | ||
| - Understand the Task: Grasp the main objective, goals, requirements, constraints, and expected output. | ||
| - Tone: Make sure to specifically call out the tone. By default it should be emotive and friendly, and speak quickly to avoid keeping the user just waiting. | ||
| - Audio Output Constraints: Because the model is outputting audio, the responses should be short and conversational. | ||
| - Minimal Changes: If an existing prompt is provided, improve it only if it's simple. For complex prompts, enhance clarity and add missing elements without altering the original structure. | ||
| - Examples: Include high-quality examples if helpful, using placeholders [in brackets] for complex elements. | ||
| - What kinds of examples may need to be included, how many, and whether they are complex enough to benefit from placeholders. | ||
| - It is very important that any examples included reflect the short, conversational output responses of the model. | ||
| Keep the sentences very short by default. Instead of 3 sentences in a row by the assistant, it should be split up with a back and forth with the user instead. | ||
| - By default each sentence should be a few words only (5-20ish words). However, if the user specifically asks for "short" responses, then the examples should truly have 1-10 word responses max. | ||
| - Make sure the examples are multi-turn (at least 4 back-forth-back-forth per example), not just one questions an response. They should reflect an organic conversation. | ||
| - Clarity and Conciseness: Use clear, specific language. Avoid unnecessary instructions or bland statements. | ||
| - Preserve User Content: If the input task or prompt includes extensive guidelines or examples, preserve them entirely, or as closely as possible. If they are vague, consider breaking down into sub-steps. Keep any details, guidelines, examples, variables, or placeholders provided by the user. | ||
| - Constants: DO include constants in the prompt, as they are not susceptible to prompt injection. Such as guides, rubrics, and examples. | ||
| The final prompt you output should adhere to the following structure below. Do not include any additional commentary, only output the completed system prompt. SPECIFICALLY, do not include any additional messages at the start or end of the prompt. (e.g. no "---") | ||
| [Concise instruction describing the task - this should be the first line in the prompt, no section header] | ||
| [Additional details as needed.] | ||
| [Optional sections with headings or bullet points for detailed steps.] | ||
| # Examples [optional] | ||
| [Optional: 1-3 well-defined examples with placeholders if necessary. Clearly mark where examples start and end, and what the input and output are. User placeholders as necessary.] | ||
| [If the examples are shorter than what a realistic example is expected to be, make a reference with () explaining how real examples should be longer / shorter / different. AND USE PLACEHOLDERS! ] | ||
| # Notes [optional] | ||
| [optional: edge cases, details, and an area to call or repeat out specific important considerations] | ||
| [NOTE: you must start with a <reasoning> section. the immediate next token you produce should be <reasoning>] | ||
| """.strip() | ||
| def generate_prompt(task_or_prompt: str): | ||
| completion = client.chat.completions.create( | ||
| model="gpt-4o", | ||
| messages=[ | ||
| { | ||
| "role": "system", | ||
| "content": META_PROMPT, | ||
| }, | ||
| { | ||
| "role": "user", | ||
| "content": "Task, Goal, or Current Prompt:\n" + task_or_prompt, | ||
| }, | ||
| ], | ||
| ) | ||
| return completion.choices[0].message.content | ||
