ChainForge/chainforge/oaievals/heart-disease.cforge

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TypeScript backend, HuggingFace models, JavaScript evaluators, Comment Nodes, and more (#81) * Beginning to convert Python backend to Typescript * Change all fetch() calls to fetch_from_backend switcher * wip converting query.py to query.ts * wip started utils.js conversion. Tested that OpenAI API call works * more progress on converting utils.py to Typescript * jest tests for query, utils, template.ts. Confirmed PromptPipeline works. * wip converting queryLLM in flask_app to TS * Tested queryLLM and StorageCache compressed saving/loading * wip execute() in backend.ts * Added execute() and tested w concrete func. Need to test eval() * Added craco for optional webpack config. Config'd for TypeScript with Node.js packages browserify'd * Execute JS code on iframe sandbox * Tested and working JS Evaluator execution. * wip swapping backends * Tested TypeScript backendgit status! :) woot * Added fetchEnvironAPIKeys to Flask server to fetch os.environ keys when running locally * Route Anthropic calls through Flask when running locally * Added info button to Eval nodes. Rebuilt react * Edits to info modal on Eval node * Remove/error out on Python eval nodes when not running locally. * Check browser compat and display error if not supported * Changed all example flows to use JS. Bug fix in query.ts * Refactored to LLMProvider to streamline model additions * Added HuggingFace models API * Added back Dalai call support, routing through Flask * Remove flask app calls and socketio server that are no longer used * Added Comment Nodes. Rebuilt react. * Fix PaLM temp=0 build, update package vers and rebuild react
2023-06-30 15:11:20 -04:00
{"flow": {"nodes": [{"width": 312, "height": 311, "id": "prompt-heart-disease", "type": "prompt", "data": {"prompt": "{prompt}", "n": 1, "llms": [{"key": "aa3c0f03-22bd-416e-af4d-4bf5c4278c99", "settings": {"system_msg": "You are an AI tasked with predicting whether patients are likely to have heart disease. You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have heart disease, or a 0 if the patient is not likely to have heart disease. Do not respond with any text or disclaimers, only respond with either 1 or 0.", "temperature": 1, "functions": [], "function_call": "", "top_p": 1, "stop": [], "presence_penalty": 0, "frequency_penalty": 0}, "name": "GPT3.5", "emoji": "\ud83d\ude42", "model": "gpt-3.5-turbo", "base_model": "gpt-3.5-turbo", "temp": 1, "formData": {"shortname": "GPT3.5", "model": "gpt-3.5-turbo", "system_msg": "You are an AI tasked with predicting whether patients are likely to have heart disease. You will be given a description of the patient with relevant medical signals. Respond with only a 1 to signify if the patient is likely to have heart disease, or a 0 if the patient is not likely to have heart disease. Do not respond with any text or disclaimers, only respond with either 1 or 0.", "temperature": 1, "functions": "", "function_call": "", "top_p": 1, "stop": "", "presence_penalty": 0, "frequency_penalty": 0}}]}, "position": {"x": 448, "y": 224}, "selected": false, "positionAbsolute": {"x": 448, "y": 224}, "dragging": false}, {"width": 333, "height": 182, "id": "eval-heart-disease", "type": "evaluator", "data": {"code": "function evaluate(response) {\n\tlet ideal = response.meta['Ideal'];\n\treturn response.text.startsWith(ideal);\n}", "language": "javascript"}, "position": {"x": 820, "y": 150}, "positionAbsolute": {"x": 820, "y": 150}}, {"width": 228, "height": 196, "id": "vis-heart-disease", "type": "vis", "data": {"input": "eval-heart-disease"}, "position": {"x": 1200, "y": 250}, "positionAbsolute": {"x": 1200, "y": 250}}, {"width": 302, "height": 260, "id": "inspect-heart-disease", "type": "inspect", "data": {"input": "prompt-heart-disease"}, "position": {"x": 820, "y": 400}, "positionAbsolute": {"x": 820, "y": 400}}, {"width": 423, "height": 417, "id": "table-heart-disease", "type": "table", "data": {"rows": [{"prompt": "Age: 40 years, Sex: Male, Chest pain type: Atypical Angina, Resting blood pressure: 140 mm Hg, Serum cholesterol: 289 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting ECG results: Normal, Max heart rate achieved: 172, Exercise induced angina: No, Oldpeak: 0, ST Slope: Upsloping", "ideal": "0"}, {"prompt": "Age: 49 years, Sex: Female, Chest pain type: Non-Anginal Pain, Resting blood pressure: 160 mm Hg, Serum cholesterol: 180 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting ECG results: Normal, Max heart rate achieved: 156, Exercise induced angina: No, Oldpeak: 1, ST Slope: Flat", "ideal": "1"}, {"prompt": "Age: 37 years, Sex: Male, Chest pain type: Atypical Angina, Resting blood pressure: 130 mm Hg, Serum cholesterol: 283 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting ECG results: ST-T wave abnormality, Max heart rate achieved: 98, Exercise induced angina: No, Oldpeak: 0, ST Slope: Upsloping", "ideal": "0"}, {"prompt": "Age: 48 years, Sex: Female, Chest pain type: Asymptomatic, Resting blood pressure: 138 mm Hg, Serum cholesterol: 214 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting ECG results: Normal, Max heart rate achieved: 108, Exercise induced angina: Yes, Oldpeak: 1.5, ST Slope: Flat", "ideal": "1"}, {"prompt": "Age: 54 years, Sex: Male, Chest pain type: Non-Anginal Pain, Resting blood pressure: 150 mm Hg, Serum cholesterol: 195 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting ECG results: Normal, Max heart rate achieved: 122, Exercise induced angina: No, Oldpeak: 0, ST Slope: Upsloping", "ideal": "0"}, {"prompt": "Age: 39 years, Sex: Male, Chest pain type: Non-Anginal Pain, Resting blood pressure: 120 mm Hg, Serum cholesterol: 339 mg/dl, Fasting blood sugar: <= 120 mg/dl, Resting