File size: 12,348 Bytes
c10f8f8
 
 
 
 
 
5c71dae
c10f8f8
 
 
 
5131535
c10f8f8
f9c67bc
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
5131535
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
e710a1b
 
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d071fc0
c10f8f8
 
6769a8e
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
f9c67bc
3baaafe
f9c67bc
d071fc0
f9c67bc
 
 
 
c10f8f8
 
 
5c71dae
c10f8f8
 
 
f9c67bc
c10f8f8
 
 
6769a8e
 
 
c10f8f8
 
f9c67bc
c10f8f8
 
 
 
d7b37e7
 
 
 
 
 
 
 
 
 
 
c10f8f8
 
 
d7b37e7
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d7b37e7
c10f8f8
 
5131535
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
d7b37e7
c10f8f8
d7b37e7
 
 
 
17234c8
d7b37e7
 
 
 
 
 
 
17234c8
d7b37e7
 
 
c10f8f8
d7b37e7
 
c10f8f8
d7b37e7
 
 
 
0b02673
d7b37e7
 
 
 
0b02673
d7b37e7
 
 
 
 
0b02673
d7b37e7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
0b02673
d7b37e7
0b02673
c10f8f8
d7b37e7
 
 
 
 
c10f8f8
 
d7b37e7
 
 
c10f8f8
 
 
d7b37e7
 
 
 
 
c10f8f8
d7b37e7
 
 
 
 
 
 
 
 
 
 
c10f8f8
d7b37e7
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
c10f8f8
35ef307
d7b37e7
26c5e3c
d7b37e7
 
 
26c5e3c
d4c5d1a
d7b37e7
d4c5d1a
d7b37e7
c10f8f8
 
 
 
 
 
 
 
 
 
 
 
 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
293
294
295
296
297
298
299
300
301
302
303
304
305
306
307
308
309
310
311
312
313
314
315
316
317
318
319
320
321
322
323
324
325
326
327
328
329
330
331
332
333
334
335
336
337
338
339
340
341
342
343
344
345
346
347
348
349
350
351
352
353
354
355
356
357
358
359
360
361
362
363
364
365
366
367
368
369
370
371
372
373
374
375
376
377
378
379
380
381
382
383
384
385
386
387
388
389
390
391
392
393
394
395
396
397
398
399
400
401
402
403
404
405
/* eslint-disable @typescript-eslint/no-explicit-any */
import type { NextRequest } from "next/server";
import { NextResponse } from "next/server";
import { headers } from "next/headers";
import { InferenceClient } from "@huggingface/inference";

import { MODELS } from "@/lib/providers";
import {
  FOLLOW_UP_SYSTEM_PROMPT,
  INITIAL_SYSTEM_PROMPT,
  MAX_REQUESTS_PER_IP,
  PROMPT_FOR_PROJECT_NAME,
} from "@/lib/prompts";
import { calculateMaxTokens, estimateInputTokens, getProviderSpecificConfig } from "@/lib/max-tokens";
import MY_TOKEN_KEY from "@/lib/get-cookie-name";
import { Page } from "@/types";
import { isAuthenticated } from "@/lib/auth";
import { getBestProvider } from "@/lib/best-provider";

const ipAddresses = new Map();

export async function POST(request: NextRequest) {
  const authHeaders = await headers();
  const userToken = request.cookies.get(MY_TOKEN_KEY())?.value;

  const body = await request.json();
  const { prompt, provider, model, redesignMarkdown, enhancedSettings, pages } = body;

  if (!model || (!prompt && !redesignMarkdown)) {
    return NextResponse.json(
      { ok: false, error: "Missing required fields" },
      { status: 400 }
    );
  }

  const selectedModel = MODELS.find(
    (m) => m.value === model || m.label === model
  );

  if (!selectedModel) {
    return NextResponse.json(
      { ok: false, error: "Invalid model selected" },
      { status: 400 }
    );
  }

  let token: string | null = null;
  if (userToken) token = userToken;
  let billTo: string | null = null;

  /**
   * Handle local usage token, this bypass the need for a user token
   * and allows local testing without authentication.
   * This is useful for development and testing purposes.
   */
  if (process.env.HF_TOKEN && process.env.HF_TOKEN.length > 0) {
    token = process.env.HF_TOKEN;
  }

  const ip = authHeaders.get("x-forwarded-for")?.includes(",")
    ? authHeaders.get("x-forwarded-for")?.split(",")[1].trim()
    : authHeaders.get("x-forwarded-for");

  if (!token) {
    ipAddresses.set(ip, (ipAddresses.get(ip) || 0) + 1);
    if (ipAddresses.get(ip) > MAX_REQUESTS_PER_IP) {
      return NextResponse.json(
        {
          ok: false,
          openLogin: true,
          message: "Log In to continue using the service",
        },
        { status: 429 }
      );
    }

    token = process.env.DEFAULT_HF_TOKEN as string;
    billTo = "huggingface";
  }

  const selectedProvider = await getBestProvider(selectedModel.value, provider)

  let rewrittenPrompt = redesignMarkdown ? `Here is my current design as a markdown:\n\n${redesignMarkdown}\n\nNow, please create a new design based on this markdown. Use the images in the markdown.` : prompt;

  if (enhancedSettings.isActive) {
    // rewrittenPrompt = await rewritePrompt(rewrittenPrompt, enhancedSettings, { token, billTo }, selectedModel.value, selectedProvider.provider);
  }

  try {
    const encoder = new TextEncoder();
    const stream = new TransformStream();
    const writer = stream.writable.getWriter();

    const response = new NextResponse(stream.readable, {
      headers: {
        "Content-Type": "text/plain; charset=utf-8",
        "Cache-Control": "no-cache",
        Connection: "keep-alive",
      },
    });

    (async () => {
      // let completeResponse = "";
      try {
        const client = new InferenceClient(token);
        
        const systemPrompt = INITIAL_SYSTEM_PROMPT;
        
        const userPrompt = rewrittenPrompt;
        const estimatedInputTokens = estimateInputTokens(systemPrompt, userPrompt);
        const dynamicMaxTokens = calculateMaxTokens(selectedProvider, estimatedInputTokens, true);
        const providerConfig = getProviderSpecificConfig(selectedProvider, dynamicMaxTokens);
        
        const chatCompletion = client.chatCompletionStream(
          {
            model: selectedModel.value,
            provider: selectedProvider.provider,
            messages: [
              {
                role: "system",
                content: systemPrompt,
              },
              {
                role: "user",
                content: userPrompt + (enhancedSettings.isActive ? `1. I want to use the following primary color: ${enhancedSettings.primaryColor} (eg: bg-${enhancedSettings.primaryColor}-500).
2. I want to use the following secondary color: ${enhancedSettings.secondaryColor} (eg: bg-${enhancedSettings.secondaryColor}-500).
3. I want to use the following theme: ${enhancedSettings.theme} mode.` : "")
              },
            ],
            ...providerConfig,
          },
          billTo ? { billTo } : {}
        );

        while (true) {
          const { done, value } = await chatCompletion.next()
          if (done) {
            break;
          }

          const chunk = value.choices[0]?.delta?.content;
          if (chunk) {
            await writer.write(encoder.encode(chunk));
          }
        }
        
        await writer.close();
      } catch (error: any) {
        if (error.message?.includes("exceeded your monthly included credits")) {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                openProModal: true,
                message: error.message,
              })
            )
          );
        } else if (error?.message?.includes("inference provider information")) {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                openSelectProvider: true,
                message: error.message,
              })
            )
          );
        }
        else {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                message:
                  error.message ||
                  "An error occurred while processing your request.",
              })
            )
          );
        }
      } finally {
        try {
          await writer?.close();
        } catch {
        }
      }
    })();

    return response;
  } catch (error: any) {
    return NextResponse.json(
      {
        ok: false,
        openSelectProvider: true,
        message:
          error?.message || "An error occurred while processing your request.",
      },
      { status: 500 }
    );
  }
}

export async function PUT(request: NextRequest) {
  const user = await isAuthenticated();
  if (user instanceof NextResponse || !user) {
    return NextResponse.json({ message: "Unauthorized" }, { status: 401 });
  }

  const authHeaders = await headers();

  const body = await request.json();
  const { prompt, provider, selectedElementHtml, model, pages, files, repoId, isNew } =
    body;

  if (!prompt || pages.length === 0) {
    return NextResponse.json(
      { ok: false, error: "Missing required fields" },
      { status: 400 }
    );
  }

  const selectedModel = MODELS.find(
    (m) => m.value === model || m.label === model
  );
  if (!selectedModel) {
    return NextResponse.json(
      { ok: false, error: "Invalid model selected" },
      { status: 400 }
    );
  }

  let token = user.token as string;
  let billTo: string | null = null;

  /**
   * Handle local usage token, this bypass the need for a user token
   * and allows local testing without authentication.
   * This is useful for development and testing purposes.
   */
  if (process.env.HF_TOKEN && process.env.HF_TOKEN.length > 0) {
    token = process.env.HF_TOKEN;
  }

  const ip = authHeaders.get("x-forwarded-for")?.includes(",")
    ? authHeaders.get("x-forwarded-for")?.split(",")[1].trim()
    : authHeaders.get("x-forwarded-for");

  if (!token) {
    ipAddresses.set(ip, (ipAddresses.get(ip) || 0) + 1);
    if (ipAddresses.get(ip) > MAX_REQUESTS_PER_IP) {
      return NextResponse.json(
        {
          ok: false,
          openLogin: true,
          message: "Log In to continue using the service",
        },
        { status: 429 }
      );
    }

    token = process.env.DEFAULT_HF_TOKEN as string;
    billTo = "huggingface";
  }

  const selectedProvider = await getBestProvider(selectedModel.value, provider);

  try {
    const encoder = new TextEncoder();
    const stream = new TransformStream();
    const writer = stream.writable.getWriter();

    const response = new NextResponse(stream.readable, {
      headers: {
        "Content-Type": "text/plain; charset=utf-8",
        "Cache-Control": "no-cache",
        Connection: "keep-alive",
      },
    });

    (async () => {
      try {
        const client = new InferenceClient(token);

        const systemPrompt = FOLLOW_UP_SYSTEM_PROMPT + (isNew ? PROMPT_FOR_PROJECT_NAME : "");
        const userContext = "You are modifying the HTML file based on the user's request.";

        const allPages = pages || [];
        const pagesContext = allPages
          .map((p: Page) => `- ${p.path}\n${p.html}`)
          .join("\n\n");

        const assistantContext = `${selectedElementHtml
            ? `\n\nYou have to update ONLY the following element, NOTHING ELSE: \n\n\`\`\`html\n${selectedElementHtml}\n\`\`\` Could be in multiple pages, if so, update all the pages.`
            : ""
          }. Current pages (${allPages.length} total): ${pagesContext}. ${files?.length > 0 ? `Available images: ${files?.map((f: string) => f).join(', ')}.` : ""}`;

        const estimatedInputTokens = estimateInputTokens(systemPrompt, prompt, userContext + assistantContext);
        const dynamicMaxTokens = calculateMaxTokens(selectedProvider, estimatedInputTokens, false);
        const providerConfig = getProviderSpecificConfig(selectedProvider, dynamicMaxTokens);

        const chatCompletion = client.chatCompletionStream(
          {
            model: selectedModel.value,
            provider: selectedProvider.provider,
            messages: [
              {
                role: "system",
                content: systemPrompt,
              },
              {
                role: "user",
                content: userContext,
              },
              {
                role: "assistant",
                content: assistantContext,
              },
              {
                role: "user",
                content: prompt,
              },
            ],
            ...providerConfig,
          },
          billTo ? { billTo } : {}
        );

        // Stream the response chunks to the client
        while (true) {
          const { done, value } = await chatCompletion.next();
          if (done) {
            break;
          }

          const chunk = value.choices[0]?.delta?.content;
          if (chunk) {
            await writer.write(encoder.encode(chunk));
          }
        }

        await writer.write(encoder.encode(`\n___METADATA_START___\n${JSON.stringify({
          repoId,
          isNew,
          userName: user.name,
        })}\n___METADATA_END___\n`));

        await writer.close();
      } catch (error: any) {
        if (error.message?.includes("exceeded your monthly included credits")) {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                openProModal: true,
                message: error.message,
              })
            )
          );
        } else if (error?.message?.includes("inference provider information")) {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                openSelectProvider: true,
                message: error.message,
              })
            )
          );
        } else {
          await writer.write(
            encoder.encode(
              JSON.stringify({
                ok: false,
                message:
                  error.message ||
                  "An error occurred while processing your request.",
              })
            )
          );
        }
      } finally {
        try {
          await writer?.close();
        } catch {
          // ignore
        }
      }
    })();

    return response;
  } catch (error: any) {
    return NextResponse.json(
      {
        ok: false,
        openSelectProvider: true,
        message:
          error.message || "An error occurred while processing your request.",
      },
      { status: 500 }
    );
  }
}