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Browse files- index.html +166 -53
index.html
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<meta property="og:title" content="Quardo's OpenAI proxy">
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<meta property="og:description" content="Documentation for Quardo's OpenAI proxy">
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<meta property="og:type" content="website">
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<meta property="og:url" content="https://
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<meta property="og:image" content="https://tenor.com/view/cat-cat-e-cat-meme-cat-face-gif-23642589">
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Quardo's OpenAI proxy">
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@@ -126,65 +126,179 @@
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<li>Privacy: Please avoid sharing any personal information.</li>
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</ul>
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<p>By continuing to use our API, you explicitly consent to the collection, use, and potential sharing of your data as described above. If you disagree with our data collection, usage, and sharing practices, we advise you not to use our API.</p>
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<textarea id="example1" name="example1">#
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messages=[
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{
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"role": "user",
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"content": "Say this is a test",
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}
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],
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)
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)
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<hr/>
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<textarea id="
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const
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-
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})()
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</textarea>
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<hr/>
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<div>
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@@ -197,8 +311,7 @@ const openai = new (require('openai')).OpenAI({
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</div>
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<script>
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CodeMirror.fromTextArea(document.getElementById("example1"), { lineNumbers: true, mode: "python", theme: "monokai", readOnly: true });
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CodeMirror.fromTextArea(document.getElementById("example2"), { lineNumbers: true, mode: "
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CodeMirror.fromTextArea(document.getElementById("example3"), { lineNumbers: true, mode: "javascript", theme: "monokai", readOnly: true });
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</script>
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</body>
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</html>
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<meta property="og:title" content="Quardo's OpenAI proxy">
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<meta property="og:description" content="Documentation for Quardo's OpenAI proxy">
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<meta property="og:type" content="website">
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<meta property="og:url" content="https://https://quardo-gpt-4o-mini.hf.space/api/v1/docs">
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<meta property="og:image" content="https://tenor.com/view/cat-cat-e-cat-meme-cat-face-gif-23642589">
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<meta name="twitter:card" content="summary_large_image">
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<meta name="twitter:title" content="Quardo's OpenAI proxy">
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<li>Privacy: Please avoid sharing any personal information.</li>
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</ul>
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<p>By continuing to use our API, you explicitly consent to the collection, use, and potential sharing of your data as described above. If you disagree with our data collection, usage, and sharing practices, we advise you not to use our API.</p>
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<textarea id="example1" name="example1"># For Python3:
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import asyncio
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import aiohttp
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import json
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base_url = "https://cow.rip/api/v1"
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key = "sk-quardo-..." # You can get a key by logging in at https://cow.rip/api/v1/oauth/hf
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params = {
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# Model to use for the chat. You can view the models at https://cow.rip/api/v1/models in your browser
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'model': "gpt-4o-mini",
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# List of messages to send to the API. Each message should be a dictionary with 'role' and 'content'.
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'messages': [
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{'role': 'user', 'content': 'Hello!'}
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],
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# Boolean to enable or disable streaming of the response.
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'stream': True
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# For any other paramater please take a look at https://platform.openai.com/docs/api-reference/chat
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}
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async def chat(params):
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"""
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Function to interact with the chat API.
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Args:
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params (dict): Parameters to be sent to the API. Must include 'model', 'messages', and optionally any other paramaters that OpenAI supports (https://platform.openai.com/docs/api-reference/chat).
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Yields:
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str: The content of the response message from the API.
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"""
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async with aiohttp.ClientSession() as session:
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async with session.post(
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f'{base_url}/chat/completions',
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headers={
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'Content-Type': 'application/json',
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'Authorization': f'Bearer {key}'
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},
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json=params,
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timeout=10 # Timeout for the request in seconds
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) as response:
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# Check if the response has a content body
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if not response.content:
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raise Exception('No response body received')
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# If streaming is enabled, process the response line by line
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if params.get('stream', False):
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async for line in response.content:
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data = line.decode('utf-8').strip()
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if data.startswith("data: ") and (msg := data[6:]) != "[DONE]":
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try:
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parsed = json.loads(msg)
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if 'choices' in parsed:
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choice = parsed['choices'][0]
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if 'delta' in choice and 'content' in choice['delta']:
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yield choice['delta']['content']
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except json.JSONDecodeError as e:
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print(f"Failed to parse JSON event: {e}")
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else:
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# If streaming is not enabled, process the entire response at once
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result = await response.json()
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if 'choices' in result:
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choice = result['choices'][0]
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if 'message' in choice:
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yield choice['message']['content']
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else:
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yield "{Invalid response received}"
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else:
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yield "{Invalid response received}"
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async def main():
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"""
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Main function to initiate the chat interaction.
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This function sets up the parameters for the chat API call and processes the response.
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"""
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async for msg in chat(params):
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print(msg, end="", flush=True)
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print()
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if __name__ == "__main__":
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asyncio.run(main())</textarea>
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<hr/>
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<textarea id="example2" name="example2">// For Node.JS:
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const baseUrl = "https://cow.rip/api/v1";
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const key = "sk-quardo-..."; // You can get a key by logging in at https://cow.rip/api/v1/oauth/hf
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const params = {
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// Model to use for the chat. You can view the models at https://cow.rip/api/v1/models in your browser or use the models() function.
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model: "gpt-4o-mini",
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// List of messages to send to the API. Each message should be a dictionary with 'role' and 'content'.
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messages: [
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{ role: "user", content: "Hello!" }
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],
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// Boolean to enable or disable streaming of the response.
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stream: true
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// For any other parameter please take a look at https://platform.openai.com/docs/api-reference/chat
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};
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/**
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* Function to interact with the chat API.
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*
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* @param {Object} params - Parameters to be sent to the API. Must include 'model', 'messages', and optionally any other paramaters that OpenAI supports (https://platform.openai.com/docs/api-reference/chat).
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* @yields {string} - The content of the response message from the API.
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*/
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async function* chat(params) {
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const response = await fetch(`${baseUrl}/chat/completions`, {
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method: 'POST',
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headers: {
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'Content-Type': 'application/json',
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'Authorization': `Bearer ${key}`
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},
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body: JSON.stringify(params)
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});
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if (!response.body) {
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throw new Error('No response body received');
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}
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if (params.stream) {
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const reader = response.body.getReader();
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let done, value, buffer = '';
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while (!done) {
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({ value, done } = await reader.read());
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if (value) {
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buffer += new TextDecoder().decode(value);
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let boundaryIndex;
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while ((boundaryIndex = buffer.indexOf("\n\n")) !== -1) {
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const chunk = buffer.slice(0, boundaryIndex + 2);
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buffer = buffer.slice(boundaryIndex + 2);
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if (chunk.trim().startsWith("data: ")) {
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const data = chunk.substring(6).trim();
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if (data !== "[DONE]") {
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try {
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const parsed = JSON.parse(data);
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if (parsed.choices && parsed.choices[0] && parsed.choices[0].delta) {
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yield parsed.choices[0].delta.content || "";
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}
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} catch (e) {
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console.error(`Failed to parse JSON event: ${e.message}`);
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}
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}
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}
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}
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}
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}
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} else {
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const result = await response.json();
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if (result.choices && result.choices[0] && result.choices[0].message) {
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yield result.choices[0].message.content || "{Invalid response received}";
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} else {
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yield "{Invalid response received}";
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}
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}
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}
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/**
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* Main function to initiate the chat interaction.
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*
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* This function sets up the parameters for the chat API call and processes the response.
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*/
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async function main() {
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for await (const msg of chat(params)) {
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process.stdout.write(msg);
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}
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process.stdout.write("\n");
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}
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main().catch(console.error);
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</textarea>
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<hr/>
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<div>
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</div>
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<script>
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CodeMirror.fromTextArea(document.getElementById("example1"), { lineNumbers: true, mode: "python", theme: "monokai", readOnly: true });
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CodeMirror.fromTextArea(document.getElementById("example2"), { lineNumbers: true, mode: "javascript", theme: "monokai", readOnly: true });
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</script>
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</body>
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</html>
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