added 2 new routes and fixed ad support for images

app.py

@@ -163,7 +163,7 @@ async def groqgenerate(json_data: Dict[str, Any]):
         # Create streaming response
         stream = client.chat.completions.create(
             messages=messages,
-            model="meta-llama/llama-4-scout-17b-16e-instruct",
+            model=json_data.get("model", "meta-llama/llama-4-scout-17b-16e-instruct"),
             temperature=json_data.get("temperature", 0.7),
             max_completion_tokens=json_data.get("max_tokens", 1024),
             top_p=json_data.get("top_p", 1),
@@ -181,7 +181,7 @@ async def groqgenerate(json_data: Dict[str, Any]):
                     "id": chunk_id,
                     "object": "chat.completion.chunk",
                     "created": created,
-                    "model": json_data.get("model", "llama-3.3-70b-versatile"),
+                    "model": json_data.get("model", "meta-llama/llama-4-scout-17b-16e-instruct"),
                     "choices": [{
                         "index": 0,
                         "text": content,
@@ -197,7 +197,7 @@ async def groqgenerate(json_data: Dict[str, Any]):
             "id": chunk_id,
             "object": "chat.completion.chunk",
             "created": created,
-            "model": json_data.get("model", "llama-3.3-70b-versatile"),
+            "model": json_data.get("model", "meta-llama/llama-4-scout-17b-16e-instruct"),
             "choices": [],
             "usage": {
                 "prompt_tokens": len(messages),
@@ -230,9 +230,11 @@ async def vercelXaigenerate(json_data: Dict[str, Any]):
     request_data = {
         "id": "".join(random.choices("0123456789abcdef", k=16)),
         "messages": messages,
-        "selectedModel": "grok-2-1212"
+        "selectedModel": json_data.get("model", "grok-2-1212"),
     }
 
+    print(request_data)
+
     chunk_id = "xai-" + "".join(random.choices("0123456789abcdef", k=32))
     created = int(asyncio.get_event_loop().time())
     total_tokens = 0
@@ -314,7 +316,7 @@ async def vercelGroqgenerate(json_data: Dict[str, Any]):
     request_data = {
         "id": "".join(random.choices("0123456789abcdef", k=16)),
         "messages": messages,
-        "selectedModel": "deepseek-r1-distill-llama-70b"
+        "selectedModel": json_data.get("model", "deepseek-r1-distill-llama-70b"),
     }
 
     chunk_id = "vercel-groq-" + "".join(random.choices("0123456789abcdef", k=32))
@@ -344,7 +346,7 @@ async def vercelGroqgenerate(json_data: Dict[str, Any]):
                                     "id": chunk_id,
                                     "object": "chat.completion.chunk",
                                     "created": created,
-                                    "model": json_data.get("model", "grok-2-1212"),
+                                    "model": json_data.get("model", "deepseek-r1-distill-llama-70b"),
                                     "choices": [{
                                         "index": 0,
                                         "text": text,
@@ -360,7 +362,7 @@ async def vercelGroqgenerate(json_data: Dict[str, Any]):
                                     "id": chunk_id,
                                     "object": "chat.completion.chunk", 
                                     "created": created,
-                                    "model": json_data.get("model", "llama-8b"),
+                                    "model": json_data.get("model", "deepseek-r1-distill-llama-70b"),
                                     "choices": [],
                                     "usage": {
                                         "prompt_tokens": len(messages),
@@ -438,3 +440,85 @@ async def scrape_md(request: Request):
 
     return {"markdown": data}
 
+@app.post("/v1/generate")
+async def api_generate(request: Request):
+    data = await request.json()
+    messages = data["messages"]
+    model = data["model"]
+    if not messages:
+        return {"error": "messages is required"}
+    elif not model:
+        return {"error": "Model is required"}
+
+    try:
+        json_data = {
+            'model': model,
+            'max_tokens': None,
+            'temperature': 0.7,
+            'top_p': 0.7,
+            'top_k': 50,
+            'repetition_penalty': 1,
+            'stream_tokens': True,
+            'stop': ['<|eot_id|>', '<|eom_id|>'],
+            'messages': messages,
+            'stream': True,
+        }
+
+        xaimodels = ["grok-3-mini", "grok-2-1212", "grok-3", "grok-3-fast", "grok-3-mini-fast"]
+
+        if model in xaimodels:
+            return StreamingResponse(vercelXaigenerate(json_data), media_type='text/event-stream')
+        else:
+            try:
+                return StreamingResponse(vercelGroqgenerate(json_data), media_type='text/event-stream')
+            except Exception as e:
+                try:
+                    return StreamingResponse(generate(json_data), media_type='text/event-stream')    
+                except Exception as e:
+                    return StreamingResponse(groqgenerate(json_data), media_type='text/event-stream')
+    except Exception as e:
+        return {"error": str(e)}    
+    
+@app.post("/v1/generate-images")
+async def generate_images(request: Request):
+    data = await request.json()
+    prompt = data.get("prompt")
+    provider = data.get("provider")
+    modelId = data.get("modelId")
+
+    if not prompt:
+        return {"error": "Prompt is required"}
+    if not provider:
+        return {"error": "Provider is required"}
+    if not modelId:
+        return {"error": "Model ID is required"}
+    
+    headers = {
+        'accept': '*/*',
+        'accept-language': 'en-US,en;q=0.9,ja;q=0.8',
+        'content-type': 'application/json',
+        'origin': 'https://fal-image-generator.vercel.app',
+        'priority': 'u=1, i',
+        'referer': 'https://fal-image-generator.vercel.app/',
+        'sec-ch-ua': '"Google Chrome";v="135", "Not-A.Brand";v="8", "Chromium";v="135"',
+        'sec-ch-ua-mobile': '?0',
+        'sec-ch-ua-platform': '"macOS"',
+        'sec-fetch-dest': 'empty',
+        'sec-fetch-mode': 'cors',
+        'sec-fetch-site': 'same-origin',
+        'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36',
+    }
+
+    json_data = {
+        'prompt': prompt,
+        'provider': 'fal',
+        'modelId': 'fal-ai/fast-sdxl',
+    }
+
+    async with httpx.AsyncClient() as client:
+        response = await client.post(
+            'https://fal-image-generator.vercel.app/api/generate-images', 
+            headers=headers, 
+            json=json_data
+        )
+        return response.json()

test.py

@@ -1,22 +1,33 @@
-from curl_cffi import requests as req
-from bs4 import BeautifulSoup
-import html2text
+import requests
+import json
 
-url = 'https://www.firecrawl.dev/'
+messages = [
+    {"role": "user", "content": "helo"},
+    {"role": "assistant", "content": "Hello! How can I assist you today?"},
+    {"role": "user", "content": "who are you and give me a breif description of who you are"}
+]
 
-# Fetch HTML content
-response = req.get(url)
-soup = BeautifulSoup(response.text, 'html.parser')
+model = "grok-3"
+url = "http://127.0.0.1:8000/v1/generate"
+payload = {
+    "messages": messages,
+    "model": model
+}
 
-# Optional: Clean up unwanted tags
-for tag in soup(['script', 'style', 'noscript', 'svg']):
-    tag.decompose()
+response = requests.post(url, json=payload, stream=True)
 
-# Extract cleaned HTML
-clean_html = str(soup)
-
-# Convert to Markdown
-markdown = html2text.html2text(clean_html)
-
-# Output
-print(markdown)
+if response.status_code == 200:
+    for line in response.iter_lines():
+        if line:
+            decoded_line = line.decode('utf-8')
+            if decoded_line.startswith('data: '):
+                try:
+                    # Remove 'data: ' prefix and parse JSON
+                    json_data = json.loads(decoded_line[6:])
+                    # Check if there are choices and text
+                    if json_data["choices"] and "text" in json_data["choices"][0]:
+                        print(json_data["choices"][0]["text"], end='')
+                except json.JSONDecodeError:
+                    continue
+else:
+    print(f"Request failed with status code {response.status_code}")

test2.py

@@ -0,0 +1,27 @@
+import requests
+
+headers = {
+    'accept': '*/*',
+    'accept-language': 'en-US,en;q=0.9,ja;q=0.8',
+    'content-type': 'application/json',
+    'origin': 'https://fal-image-generator.vercel.app',
+    'priority': 'u=1, i',
+    'referer': 'https://fal-image-generator.vercel.app/',
+    'sec-ch-ua': '"Google Chrome";v="135", "Not-A.Brand";v="8", "Chromium";v="135"',
+    'sec-ch-ua-mobile': '?0',
+    'sec-ch-ua-platform': '"macOS"',
+    'sec-fetch-dest': 'empty',
+    'sec-fetch-mode': 'cors',
+    'sec-fetch-site': 'same-origin',
+    'user-agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36',
+}
+
+json_data = {
+    'prompt': 'A frog meditating on a lotus leaf in a tranquil forest pond at dawn, surrounded by fireflies, in the style of anime',
+    'provider': 'fal',
+    'modelId': 'fal-ai/fast-sdxl',
+}
+
+response = requests.post('http://127.0.0.1:8000/v1/generate-images', headers=headers, json=json_data)
+
+print(response.json())