Add examples

Author: Graden Rea

examples/chat_completion.js

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+const Groq = require('groq');
+
+const groq = new Groq();
+
+async function main() {
+  groq.chat.completions.create({
+    //
+    // Required parameters
+    //
+    messages: [
+      // Set an optional system message. This sets the behavior of the
+      // assistant and can be used to provide specific instructions for
+      // how it should behave throughout the conversation.
+      {
+        "role": "system",
+        "content": "you are a helpful assistant."
+      },
+      // Set a user message for the assistant to respond to.
+      {
+        "role": "user",
+        "content": "Explain the importance of low latency LLMs",
+      }
+    ],
+
+    // The language model which will generate the completion.
+    model: "mixtral-8x7b-32768",
+
+    //
+    // Optional parameters
+    //
+
+    // Controls randomness: lowering results in less random completions.
+    // As the temperature approaches zero, the model will become deterministic
+    // and repetitive.
+    temperature: 0.5,
+
+    // The maximum number of tokens to generate. Requests can use up to
+    // 2048 tokens shared between prompt and completion.
+    max_tokens: 1024,
+
+    // Controls diversity via nucleus sampling: 0.5 means half of all
+    // likelihood-weighted options are considered.
+    top_p: 1,
+
+    // A stop sequence is a predefined or user-specified text string that
+    // signals an AI to stop generating content, ensuring its responses
+    // remain focused and concise. Examples include punctuation marks and
+    // markers like "[end]".
+    stop: null,
+
+    // If set, partial message deltas will be sent.
+    stream: false,
+  }).then((chatCompletion) => {
+    process.stdout.write(chatCompletion.choices[0]?.message?.content || '');
+  })
+}
+
+main();

examples/chat_completion_stop.js

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+const Groq = require('groq');
+
+const groq = new Groq();
+
+async function main() {
+  const stream = await groq.chat.completions.create({
+    //
+    // Required parameters
+    //
+    messages: [
+      // Set an optional system message. This sets the behavior of the
+      // assistant and can be used to provide specific instructions for
+      // how it should behave throughout the conversation.
+      {
+        "role": "system",
+        "content": "you are a helpful assistant."
+      },
+      // Set a user message for the assistant to respond to.
+      {
+        "role": "user",
+        "content": "Start at 1 and count to 10.  Separate each number with a comma and a space"
+      }
+    ],
+
+    // The language model which will generate the completion.
+    model: "mixtral-8x7b-32768",
+
+    //
+    // Optional parameters
+    //
+
+    // Controls randomness: lowering results in less random completions.
+    // As the temperature approaches zero, the model will become deterministic
+    // and repetitive.
+    temperature: 0.5,
+
+    // The maximum number of tokens to generate. Requests can use up to
+    // 2048 tokens shared between prompt and completion.
+    max_tokens: 1024,
+
+    // Controls diversity via nucleus sampling: 0.5 means half of all
+    // likelihood-weighted options are considered.
+    top_p: 1,
+
+    // A stop sequence is a predefined or user-specified text string that
+    // signals an AI to stop generating content, ensuring its responses
+    // remain focused and concise. Examples include punctuation marks and
+    // markers like "[end]".
+    //
+    // For this example, we will use ", 6" so that the llm stops counting at 5.
+    // If multiple stop values are needed, an array of string may be passed,
+    // stop: [", 6", ", six", ", Six"]
+    stop: ", 6",
+
+    // If set, partial message deltas will be sent.
+    stream: true,
+  });
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.choices[0]?.delta?.content || '');
+  }
+}
+
+main();

examples/chat_completion_streaming.js

@@ -0,0 +1,59 @@
+const Groq = require('groq');
+
+const groq = new Groq();
+
+async function main() {
+  const stream = await groq.chat.completions.create({
+    //
+    // Required parameters
+    //
+    messages: [
+      // Set an optional system message. This sets the behavior of the
+      // assistant and can be used to provide specific instructions for
+      // how it should behave throughout the conversation.
+      {
+        "role": "system",
+        "content": "you are a helpful assistant."
+      },
+      // Set a user message for the assistant to respond to.
+      {
+        "role": "user",
+        "content": "Explain the importance of low latency LLMs",
+      }
+    ],
+
+    // The language model which will generate the completion.
+    model: "mixtral-8x7b-32768",
+
+    //
+    // Optional parameters
+    //
+
+    // Controls randomness: lowering results in less random completions.
+    // As the temperature approaches zero, the model will become deterministic
+    // and repetitive.
+    temperature: 0.5,
+
+    // The maximum number of tokens to generate. Requests can use up to
+    // 2048 tokens shared between prompt and completion.
+    max_tokens: 1024,
+
+    // Controls diversity via nucleus sampling: 0.5 means half of all
+    // likelihood-weighted options are considered.
+    top_p: 1,
+
+    // A stop sequence is a predefined or user-specified text string that
+    // signals an AI to stop generating content, ensuring its responses
+    // remain focused and concise. Examples include punctuation marks and
+    // markers like "[end]".
+    stop: null,
+
+    // If set, partial message deltas will be sent.
+    stream: true,
+  });
+  for await (const chunk of stream) {
+    process.stdout.write(chunk.choices[0]?.delta?.content || '');
+  }
+}
+
+main();