Add initial code examples

README.md

@@ -1 +1,11 @@
-# codespaces-models
+# GitHub Models
+
+Welcome to your shiny new Codespace for interacting with GitHub Models! We've got everything fired up and running for you to explore.
+
+You've got a blank canvas to work on from a git perspective as well. There's a single initial commit with the what you're seeing right now - where you go from here is up to you!
+
+Everything you do here is contained within this one codespace. There is no repository on GitHub yet. If and when you’re ready you can click "Publish Branch" and we’ll create your repository and push up your project. If you were just exploring then and have no further need for this code then you can simply delete your codespace and it's gone forever.
+
+## Getting Started
+
+There are a few basic examples that are ready for you to run. You can find them in the [samples directory](/samples/README.md). Each sample is a standalone script that demonstrates how to interact with GitHub Models.

samples/README.md

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+# GitHub Models Samples
+
+This folder contains samples for interacting with GitHub Models. Each subfolder contains examples for a specific language: JavaScript, Python, and cURL.
+
+## Running a sample
+
+When you're ready to run a sample, you can run it from your terminal. For example, to run a JavaScript sample:
+
+```bash
+# samples/js/multi_turn.sh
+
+$ node samples/js/multi_turn.js
+```
+
+To run a Python sample:
+
+```bash
+# samples/python/multi_turn.py
+
+$ python samples/python/multi_turn.py
+```
+
+To run a cURL sample:
+
+```bash
+# samples/curl/multi_turn.sh
+
+$ ./samples/curl/multi_turn.sh
+```

samples/curl/basic.sh

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+curl -X POST "https://models.inference.ai.azure.com/chat/completions" \
+    -H "Content-Type: application/json" \
+    -H "Authorization: Bearer $GITHUB_TOKEN" \
+    -d '{
+        "messages": [
+            {
+                "role": "system",
+                "content": "You are a helpful assistant."
+            },
+            {
+                "role": "user",
+                "content": "What is the capital of France?"
+            }
+        ],
+        "model": "gpt-4o"
+    }'

samples/curl/multi_turn.sh

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+curl -X POST "https://models.inference.ai.azure.com/chat/completions" \
+    -H "Content-Type: application/json" \
+    -H "Authorization: Bearer $GITHUB_TOKEN" \
+    -d '{
+        "messages": [
+            {
+                "role": "system",
+                "content": "You are a helpful assistant."
+            },
+            {
+                "role": "user",
+                "content": "What is the capital of France?"
+            },
+            {
+                "role": "assistant",
+                "content": "The capital of France is Paris."
+            },
+            {
+                "role": "user",
+                "content": "What about Spain?"
+            }
+        ],
+        "model": "gpt-4o"
+    }'

samples/curl/streaming.sh

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+curl -X POST "https://models.inference.ai.azure.com/chat/completions" \
+    -H "Content-Type: application/json" \
+    -H "Authorization: Bearer $GITHUB_TOKEN" \
+    -d '{
+        "messages": [
+            {
+                "role": "system",
+                "content": "You are a helpful assistant."
+            },
+            {
+                "role": "user",
+                "content": "Give me 5 good reasons why I should exercise every day."
+            }
+        ],
+        "stream": true,
+        "model": "gpt-4o"
+    }'

samples/js/basic.js

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+import ModelClient from "@azure-rest/ai-inference";
+import { AzureKeyCredential } from "@azure/core-auth";
+
+const token = process.env["GITHUB_TOKEN"];
+const endpoint = "https://models.inference.ai.azure.com";
+const modelName = "gpt-4o";
+
+export async function main() {
+
+  const client = new ModelClient(endpoint, new AzureKeyCredential(token));
+
+  const response = await client.path("/chat/completions").post({
+    body: {
+      messages: [
+        { role:"system", content: "You are a helpful assistant." },
+        { role:"user", content: "What is the capital of France?" }
+      ],
+      model: modelName
+    }
+  });
+
+  if (response.status !== "200") {
+    throw response.body.error;
+  }
+  console.log(response.body.choices[0].message.content);
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});

samples/js/multi_turn.js

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+import ModelClient from "@azure-rest/ai-inference";
+import { AzureKeyCredential } from "@azure/core-auth";
+
+const token = process.env["GITHUB_TOKEN"];
+const endpoint = "https://models.inference.ai.azure.com";
+const modelName = "gpt-4o";
+
+export async function main() {
+
+  const client = new ModelClient(endpoint, new AzureKeyCredential(token));
+
+  const response = await client.path("/chat/completions").post({
+    body: {
+      messages: [
+        { role: "system", content: "You are a helpful assistant." },
+        { role: "user", content: "What is the capital of France?" },
+        { role: "assistant", content: "The capital of France is Paris." },
+        { role: "user", content: "What about Spain?" },
+      ],
+      model: modelName,
+    }
+  });
+
+  if (response.status !== "200") {
+    throw response.body.error;
+  }
+
+  for (const choice of response.body.choices) {
+    console.log(choice.message.content);
+  }
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});

samples/js/streaming.js

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+import ModelClient from "@azure-rest/ai-inference";
+import { AzureKeyCredential } from "@azure/core-auth";
+import { createSseStream } from "@azure/core-sse";
+
+const token = process.env["GITHUB_TOKEN"];
+const endpoint = "https://models.inference.ai.azure.com";
+const modelName = "gpt-4o";
+
+export async function main() {
+
+  const client = new ModelClient(endpoint, new AzureKeyCredential(token));
+
+  const response = await client.path("/chat/completions").post({
+    body: {
+      messages: [
+        { role: "system", content: "You are a helpful assistant." },
+        { role: "user", content: "Give me 5 good reasons why I should exercise every day." },
+      ],
+      model: modelName,
+      stream: true
+    }
+  }).asNodeStream();
+
+  const stream = response.body;
+  if (!stream) {
+    throw new Error("The response stream is undefined");
+  }
+
+  if (response.status !== "200") {
+    throw new Error(`Failed to get chat completions: ${response.body.error}`);
+  }
+
+  const sseStream = createSseStream(stream);
+
+  for await (const event of sseStream) {
+    if (event.data === "[DONE]") {
+      return;
+    }
+    for (const choice of (JSON.parse(event.data)).choices) {
+        process.stdout.write(choice.delta?.content ?? ``);
+    }
+  }
+}
+
+main().catch((err) => {
+  console.error("The sample encountered an error:", err);
+});

samples/python/basic.py

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+import os
+from azure.ai.inference import ChatCompletionsClient
+from azure.ai.inference.models import SystemMessage, UserMessage
+from azure.core.credentials import AzureKeyCredential
+
+endpoint = "https://models.inference.ai.azure.com"
+model_name = "gpt-4o"
+token = os.environ["GITHUB_TOKEN"]
+
+client = ChatCompletionsClient(
+    endpoint=endpoint,
+    credential=AzureKeyCredential(token),
+)
+
+response = client.complete(
+    messages=[
+        SystemMessage(content="You are a helpful assistant."),
+        UserMessage(content="What is the capital of France?"),
+    ],
+    model=model_name,
+)
+
+print(response.choices[0].message.content)

samples/python/multi_turn.py

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+import os
+from azure.ai.inference import ChatCompletionsClient
+from azure.ai.inference.models import AssistantMessage, SystemMessage, UserMessage
+from azure.core.credentials import AzureKeyCredential
+
+token = os.environ["GITHUB_TOKEN"]
+endpoint = "https://models.inference.ai.azure.com"
+model_name = "gpt-4o"
+
+client = ChatCompletionsClient(
+    endpoint=endpoint,
+    credential=AzureKeyCredential(token),
+)
+
+messages = [
+    SystemMessage(content="You are a helpful assistant."),
+    UserMessage(content="What is the capital of France?"),
+    AssistantMessage(content="The capital of France is Paris."),
+    UserMessage(content="What about Spain?"),
+]
+
+response = client.complete(messages=messages, model=model_name)
+
+print(response.choices[0].message.content)

samples/python/streaming.py

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+import os
+from azure.ai.inference import ChatCompletionsClient
+from azure.ai.inference.models import SystemMessage, UserMessage
+from azure.core.credentials import AzureKeyCredential
+
+token = os.environ["GITHUB_TOKEN"]
+endpoint = "https://models.inference.ai.azure.com"
+model_name = "gpt-4o"
+
+client = ChatCompletionsClient(
+    endpoint=endpoint,
+    credential=AzureKeyCredential(token),
+)
+
+response = client.complete(
+    stream=True,
+    messages=[
+        SystemMessage(content="You are a helpful assistant."),
+        UserMessage(content="Give me 5 good reasons why I should exercise every day."),
+    ],
+    model=model_name,
+)
+
+for update in response:
+    if update.choices:
+        print(update.choices[0].delta.content or "", end="")
+
+client.close()