Feature: Multi-LLM Provider Support

README.md

@@ -37,27 +37,26 @@ Assertify is an intelligent testing assistant that analyzes your project descrip
 - Next.js 14
 - TypeScript
 - Tailwind CSS
-- OpenAI API
+- Multi-LLM Support (OpenAI, Anthropic Claude, Google Gemini)
 
 ## Installation
 
 1. Install dependencies: `npm install`
-2. Copy the environment file: `cp .env.example .env.local`
-3. Add your OpenAI API key to `.env.local`
-4. Start the dev server: `npm run dev`
-5. Open http://localhost:3000 in your browser
+2. Start the dev server: `npm run dev`
+3. Open http://localhost:3000 in your browser
+4. **Enter your API key in the UI**. Keys are stored in your browser's `sessionStorage` in plaintext for convenience; they are not encrypted or transmitted to our servers. Be aware that browser extensions or any cross-site scripting (XSS) vulnerability in this tab could potentially access this session data.
 
 ## How to Use
 
-1. Provide your project description from the landing page; the app automatically classifies the category.
-2. Answer the context questions (or skip) so the generator can tailor scenarios to your needs.
-3. Review generated tests on the results page, filter by type or priority, and inspect the suggested testing strategy and risk areas.
-4. Generate boilerplate code for your preferred frameworks or export the dataset as JSON/CSV.
-5. Manage settings at `/settings` to define default context, disable frameworks, and control boilerplate sample sizes.
+1. Select your preferred LLM provider (OpenAI, Anthropic, or Gemini) and model from the landing page or settings.
+2. Provide your project description from the landing page; the app automatically classifies the category.
+3. Answer the context questions (or skip) so the generator can tailor scenarios to your needs.
+4. Review generated tests on the results page, filter by type or priority, and inspect the suggested testing strategy and risk areas.
+5. Generate boilerplate code for your preferred frameworks or export the dataset as JSON/CSV.
+6. Manage settings at `/settings` to define default context, disable frameworks, and control boilerplate sample sizes.
 
 ## Future Improvements
 
-- Allow selecting different LLM providers and models per generation so teams can optimize for latency or cost.
 - Offer more granular configuration for question generation (e.g., required question count, tone, or domain presets).
 - Optimize large test suites by streaming responses and deduplicating similar scenarios before persistence.
 - Provide deeper integrations with CI/CD by exporting ready-to-run suites or syncing with test management tools.

app/api/classify/route.ts

@@ -1,9 +1,9 @@
 import { NextRequest, NextResponse } from "next/server";
-import { OpenAI } from "openai";
+import { createProvider, isValidProviderKey, normalizeProviderError } from "@/lib/llm";
 
 export async function POST(req: NextRequest) {
   try {
-    const { projectDescription, apiKey } = await req.json();
+    const { projectDescription, apiKey, provider = "openai", model } = await req.json();
 
     if (!projectDescription) {
       return NextResponse.json({ error: "Project description required" }, { status: 400 });
@@ -13,9 +13,11 @@ export async function POST(req: NextRequest) {
       return NextResponse.json({ error: "API key required" }, { status: 400 });
     }
 
-    const openai = new OpenAI({
-      apiKey: apiKey,
-    });
+    if (!isValidProviderKey(provider)) {
+      return NextResponse.json({ error: `Unsupported provider: "${provider}"` }, { status: 400 });
+    }
+
+    const llm = createProvider(provider, apiKey, model);
 
     const categories = [
       "backend-api",
@@ -26,39 +28,38 @@ export async function POST(req: NextRequest) {
       "data-pipeline",
     ];
 
-    const message = await openai.chat.completions.create({
-      model: "gpt-4",
-      messages: [
-        {
-          role: "system",
-          content: `You are a project classifier. Classify the given project description into one of these categories: ${categories.join(
-            ", "
-          )}. Respond with ONLY the category name, nothing else.`,
-        },
-        {
-          role: "user",
-          content: projectDescription,
-        },
-      ],
-    });
+    const content = await llm.chatCompletion([
+      {
+        role: "system",
+        content: `You are a project classifier. Classify the given project description into one of these categories: ${categories.join(
+          ", "
+        )}. Respond with ONLY the category name, nothing else.`,
+      },
+      {
+        role: "user",
+        content: projectDescription,
+      },
+    ]);
 
-    let category = (message.choices[0].message.content || "other").trim().toLowerCase();
+    let category = (content || "other").trim().toLowerCase();
 
     if (!categories.includes(category)) {
       category = "other";
     }
 
     return NextResponse.json({ category });
-  } catch (error: any) {
+  } catch (error: unknown) {
     console.error("Classification error:", error);
 
-    if (error.status === 401) {
+    const normalized = normalizeProviderError(error);
+
+    if (normalized.isAuthError) {
       return NextResponse.json({ error: "Unauthorized: Invalid API key" }, { status: 401 });
     }
 
     return NextResponse.json(
-      { error: "Classification failed", details: String(error.message) },
-      { status: 500 }
+      { error: "Classification failed", details: normalized.message },
+      { status: normalized.status }
     );
   }
 }

app/api/generate-questions/route.ts

@@ -1,13 +1,14 @@
 import { NextRequest, NextResponse } from "next/server";
-import { OpenAI } from "openai";
+import { createProvider, isValidProviderKey, normalizeProviderError } from "@/lib/llm";
 
 export async function POST(req: NextRequest) {
   try {
-    const { projectDescription, category, apiKey } = await req.json();
+    const { projectDescription, category, apiKey, provider = "openai", model } = await req.json();
 
     console.log("Received:", {
       projectDescription: !!projectDescription,
       category,
+      provider,
       apiKey: !!apiKey,
     });
 
@@ -22,9 +23,11 @@ export async function POST(req: NextRequest) {
       return NextResponse.json({ error: "API key required" }, { status: 400 });
     }
 
-    const openai = new OpenAI({
-      apiKey: apiKey,
-    });
+    if (!isValidProviderKey(provider)) {
+      return NextResponse.json({ error: `Unsupported provider: "${provider}"` }, { status: 400 });
+    }
+
+    const llm = createProvider(provider, apiKey, model);
 
     const prompt = `You are a QA expert. Based on the following project description and category, generate exactly 10 specific, actionable questions that a developer should answer to help write comprehensive tests for this project.
 
@@ -42,9 +45,8 @@ Format your response as a JSON array of strings, like this:
 
 Respond ONLY with the JSON array, no additional text or markdown.`;
 
-    const message = await openai.chat.completions.create({
-      model: "gpt-4",
-      messages: [
+    const content = await llm.chatCompletion(
+      [
         {
           role: "system",
           content:
@@ -55,10 +57,8 @@ Respond ONLY with the JSON array, no additional text or markdown.`;
           content: prompt,
         },
       ],
-      temperature: 0.7,
-    });
-
-    const content = message.choices[0].message.content || "[]";
+      { temperature: 0.7 }
+    );
 
     let questions;
     try {
@@ -84,16 +84,18 @@ Respond ONLY with the JSON array, no additional text or markdown.`;
     }
 
     return NextResponse.json({ questions });
-  } catch (error: any) {
+  } catch (error: unknown) {
     console.error("Generate questions error:", error);
 
-    if (error.status === 401) {
+    const normalized = normalizeProviderError(error);
+
+    if (normalized.isAuthError) {
       return NextResponse.json({ error: "Unauthorized: Invalid API key" }, { status: 401 });
     }
 
     return NextResponse.json(
-      { error: "Failed to generate questions", details: String(error.message) },
-      { status: 500 }
+      { error: "Failed to generate questions", details: normalized.message },
+      { status: normalized.status }
     );
   }
 }

app/api/generate/route.ts

@@ -1,9 +1,16 @@
 import { NextRequest, NextResponse } from "next/server";
-import { OpenAI } from "openai";
+import { createProvider, isValidProviderKey, normalizeProviderError } from "@/lib/llm";
 
 export async function POST(req: NextRequest) {
   try {
-    const { projectDescription, category, answers, apiKey } = await req.json();
+    const {
+      projectDescription,
+      category,
+      answers,
+      apiKey,
+      provider = "openai",
+      model,
+    } = await req.json();
 
     if (!projectDescription || !category || !answers) {
       return NextResponse.json({ error: "Missing required fields" }, { status: 400 });
@@ -13,9 +20,11 @@ export async function POST(req: NextRequest) {
       return NextResponse.json({ error: "API key required" }, { status: 400 });
     }
 
-    const openai = new OpenAI({
-      apiKey: apiKey,
-    });
+    if (!isValidProviderKey(provider)) {
+      return NextResponse.json({ error: `Unsupported provider: "${provider}"` }, { status: 400 });
+    }
+
+    const llm = createProvider(provider, apiKey, model);
 
     const prompt = `You are a QA expert. Generate comprehensive test cases for the following project:
 
@@ -52,9 +61,8 @@ Generate 12-15 diverse test cases covering:
 
 Respond ONLY with valid JSON, no markdown or extra text.`;
 
-    const message = await openai.chat.completions.create({
-      model: "gpt-4",
-      messages: [
+    const content = await llm.chatCompletion(
+      [
         {
           role: "system",
           content:
@@ -65,10 +73,8 @@ Respond ONLY with valid JSON, no markdown or extra text.`;
           content: prompt,
         },
       ],
-      temperature: 0.7,
-    });
-
-    const content = message.choices[0].message.content || "{}";
+      { temperature: 0.7 }
+    );
 
     let parsedResponse;
     try {
@@ -83,16 +89,18 @@ Respond ONLY with valid JSON, no markdown or extra text.`;
     }
 
     return NextResponse.json(parsedResponse);
-  } catch (error: any) {
+  } catch (error: unknown) {
     console.error("Generation error:", error);
 
-    if (error.status === 401) {
+    const normalized = normalizeProviderError(error);
+
+    if (normalized.isAuthError) {
       return NextResponse.json({ error: "Unauthorized: Invalid API key" }, { status: 401 });
     }
 
     return NextResponse.json(
-      { error: "Test case generation failed", details: String(error.message) },
-      { status: 500 }
+      { error: "Test case generation failed", details: normalized.message },
+      { status: normalized.status }
     );
   }
 }