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Patched bug: unbound client in Azure OpenAI func
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@ -1,15 +1,15 @@
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{
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"files": {
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"main.css": "/static/css/main.98db168d.css",
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"main.js": "/static/js/main.ac46f286.js",
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"main.js": "/static/js/main.c56530db.js",
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"static/js/787.4c72bb55.chunk.js": "/static/js/787.4c72bb55.chunk.js",
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"index.html": "/index.html",
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"main.98db168d.css.map": "/static/css/main.98db168d.css.map",
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"main.ac46f286.js.map": "/static/js/main.ac46f286.js.map",
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"main.c56530db.js.map": "/static/js/main.c56530db.js.map",
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"787.4c72bb55.chunk.js.map": "/static/js/787.4c72bb55.chunk.js.map"
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},
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"entrypoints": [
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"static/css/main.98db168d.css",
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"static/js/main.ac46f286.js"
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"static/js/main.c56530db.js"
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]
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}
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@ -1 +1 @@
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>Chainforge</title><script defer="defer" src="/static/js/main.ac46f286.js"></script><link href="/static/css/main.98db168d.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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<!doctype html><html lang="en"><head><meta charset="utf-8"/><link rel="icon" href="/favicon.ico"/><meta name="viewport" content="width=device-width,initial-scale=1"/><meta name="theme-color" content="#000000"/><meta name="description" content="Web site created using create-react-app"/><link rel="apple-touch-icon" href="/logo192.png"/><link rel="manifest" href="/manifest.json"/><title>Chainforge</title><script defer="defer" src="/static/js/main.c56530db.js"></script><link href="/static/css/main.98db168d.css" rel="stylesheet"></head><body><noscript>You need to enable JavaScript to run this app.</noscript><div id="root"></div></body></html>
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@ -230,10 +230,10 @@ export async function call_azure_openai(prompt: string, model: LLM, n: number =
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let arg2: Array<Dict | string>;
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let openai_call: any;
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if (model_type === 'text-completion') {
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openai_call = client.getCompletions;
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openai_call = client.getCompletions.bind(client);
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arg2 = [prompt];
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} else {
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openai_call = client.getChatCompletions;
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openai_call = client.getChatCompletions.bind(client);
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arg2 = [
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{"role": "system", "content": system_msg},
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{"role": "user", "content": prompt},
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