update project structure

crates/local_inference_engine/openai_api_test.js

@@ -0,0 +1,176 @@
+// Test requests for the OpenAI-compatible endpoint in the inference server
+// This file contains IIFE (Immediately Invoked Function Expression) JavaScript requests
+// to test the /v1/chat/completions endpoint
+
+// Basic chat completion request
+(async function testBasicChatCompletion() {
+  console.log("Test 1: Basic chat completion request");
+  try {
+    const response = await fetch('http://localhost:3777/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: "gemma-2-2b-it",
+        messages: [
+          {
+            role: "user",
+            content: "Who was the 16th president of the United States?"
+          }
+        ],
+        max_tokens: 100
+      })
+    });
+
+    const data = await response.json();
+    console.log("Response:", JSON.stringify(data, null, 2));
+  } catch (error) {
+    console.error("Error:", error);
+  }
+})();
+
+// Multi-turn conversation
+(async function testMultiTurnConversation() {
+  console.log("\nTest 2: Multi-turn conversation");
+  try {
+    const response = await fetch('http://localhost:3777/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: "gemma-2-2b-it",
+        messages: [
+          {
+            role: "system",
+            content: "You are a helpful assistant that provides concise answers."
+          },
+          {
+            role: "user",
+            content: "What is machine learning?"
+          },
+          {
+            role: "assistant",
+            content: "Machine learning is a subset of artificial intelligence that enables systems to learn and improve from experience without being explicitly programmed."
+          },
+          {
+            role: "user",
+            content: "Give me an example of a machine learning algorithm."
+          }
+        ],
+        max_tokens: 150
+      })
+    });
+
+    const data = await response.json();
+    console.log("Response:", JSON.stringify(data, null, 2));
+  } catch (error) {
+    console.error("Error:", error);
+  }
+})();
+
+// Request with temperature and top_p parameters
+(async function testTemperatureAndTopP() {
+  console.log("\nTest 3: Request with temperature and top_p parameters");
+  try {
+    const response = await fetch('http://localhost:3777/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: "gemma-2-2b-it",
+        messages: [
+          {
+            role: "user",
+            content: "Write a short poem about artificial intelligence."
+          }
+        ],
+        max_tokens: 200,
+        temperature: 0.8,
+        top_p: 0.9
+      })
+    });
+
+    const data = await response.json();
+    console.log("Response:", JSON.stringify(data, null, 2));
+  } catch (error) {
+    console.error("Error:", error);
+  }
+})();
+
+// Request with streaming enabled
+(async function testStreaming() {
+  console.log("\nTest 4: Request with streaming enabled");
+  try {
+    const response = await fetch('http://localhost:3777/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: "gemma-2-2b-it",
+        messages: [
+          {
+            role: "user",
+            content: "Explain quantum computing in simple terms."
+          }
+        ],
+        max_tokens: 150,
+        stream: true
+      })
+    });
+
+    // Note: Streaming might not be implemented yet, this is to test the API's handling of the parameter
+    if (response.headers.get('content-type')?.includes('text/event-stream')) {
+      console.log("Streaming response detected. Reading stream...");
+      const reader = response.body.getReader();
+      const decoder = new TextDecoder();
+
+      while (true) {
+        const { done, value } = await reader.read();
+        if (done) break;
+
+        const chunk = decoder.decode(value);
+        console.log("Chunk:", chunk);
+      }
+    } else {
+      const data = await response.json();
+      console.log("Non-streaming response:", JSON.stringify(data, null, 2));
+    }
+  } catch (error) {
+    console.error("Error:", error);
+  }
+})();
+
+// Request with a different model
+(async function testDifferentModel() {
+  console.log("\nTest 5: Request with a different model");
+  try {
+    const response = await fetch('http://localhost:3777/v1/chat/completions', {
+      method: 'POST',
+      headers: {
+        'Content-Type': 'application/json',
+      },
+      body: JSON.stringify({
+        model: "gemma-2-2b-it", // Using a different model if available
+        messages: [
+          {
+            role: "user",
+            content: "What are the benefits of renewable energy?"
+          }
+        ],
+        max_tokens: 150
+      })
+    });
+
+    const data = await response.json();
+    console.log("Response:", JSON.stringify(data, null, 2));
+  } catch (error) {
+    console.error("Error:", error);
+  }
+})();
+
+console.log("\nAll test requests have been sent. Check the server logs for more details.");
+console.log("To run the server, use: cargo run --bin local_inference_engine -- --server");