Upload 38 files

app.py

@@ -5,6 +5,7 @@ from models.text.together.main import TogetherAPI
 from models.text.vercel.main import XaiAPI, GroqAPI, DeepinfraAPI
 from models.image.vercel.main import FalAPI
 from models.image.together.main import TogetherImageAPI
+from models.text.deepinfra.main import OFFDeepInfraAPI
 from models.fetch import FetchModel
 from auth.key import NimbusAuthKey
 from tools.googlesearch.main import search
@@ -78,7 +79,8 @@ async def get_models():
                 'together': TogetherAPI().get_model_list(),
                 'xai': XaiAPI().get_model_list(),
                 'groq': GroqAPI().get_model_list(),
-                'deepinfra': DeepinfraAPI().get_model_list()
+                'deepinfra': DeepinfraAPI().get_model_list(),
+                "official_deepinfra": OFFDeepInfraAPI().get_model_list() 
             },
             'image': {
                 'fal': FalAPI().get_model_list(),
@@ -162,6 +164,7 @@ async def text_generate(request: Request):
         xai_models = XaiAPI().get_model_list()
         groq_models = GroqAPI().get_model_list()
         deepinfra_models = DeepinfraAPI().get_model_list()
+        official_deepinfra_models = OFFDeepInfraAPI().get_model_list()
 
         if model in together_models:
             streamModel = TogetherAPI()
@@ -171,6 +174,8 @@ async def text_generate(request: Request):
             streamModel = GroqAPI()
         elif model in deepinfra_models:
             streamModel = DeepinfraAPI()
+        elif model in official_deepinfra_models:
+            streamModel = OFFDeepInfraAPI()
         else:
             return {"error": f"Model '{model}' is not supported."}
 

models/fetch.py

@@ -107,11 +107,11 @@ class FetchModel:
             model = random.choice(options)
             return model
         elif id == "llama-3.3-70b":
-            options = ['meta-llama/Llama-3.3-70B-Instruct-Turbo', 'llama-3.3-70b-versatile']
+            options = ['meta-llama/Llama-3.3-70B-Instruct-Turbo', 'llama-3.3-70b-versatile', 'meta-llama/Llama-3.3-70B-Instruct-Turbo']
             model = random.choice(options)
             return model
         elif id == "deepseek-r1":
-            options = ['deepseek-ai/DeepSeek-R1', 'deepseek-r1-distill-llama-70b']
+            options = ['deepseek-ai/DeepSeek-R1', 'deepseek-r1-distill-llama-70b', 'deepseek-ai/DeepSeek-R1-Turbo', 'deepseek-ai/DeepSeek-R1-Distill-Llama-70B', 'deepseek-ai/DeepSeek-R1-Distill-Qwen-32B']
             model = random.choice(options)
             return model
         elif id == "deepseek-v3":

models/text/deepinfra/main.py

@@ -0,0 +1,99 @@
+import random
+import httpx
+import asyncio
+import json
+
+class OFFDeepInfraAPI:
+
+    headers = {
+        'Accept-Language': 'en-US,en;q=0.9,ja;q=0.8',
+        'Connection': 'keep-alive',
+        'Content-Type': 'application/json',
+        'Origin': 'https://deepinfra.com',
+        'Referer': 'https://deepinfra.com/',
+        'Sec-Fetch-Dest': 'empty',
+        'Sec-Fetch-Mode': 'cors',
+        'Sec-Fetch-Site': 'same-site',
+        'User-Agent': 'Mozilla/5.0 (Linux; Android 6.0; Nexus 5 Build/MRA58N) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/136.0.0.0 Mobile Safari/537.36',
+        'X-Deepinfra-Source': 'web-embed',
+        'accept': 'text/event-stream',
+        'sec-ch-ua': '"Chromium";v="136", "Google Chrome";v="136", "Not.A/Brand";v="99"',
+        'sec-ch-ua-mobile': '?1',
+        'sec-ch-ua-platform': '"Android"',
+    }
+
+    def __init__(self):
+        self.base_url = "https://api.deepinfra.com/v1/openai/chat/completions"
+
+    def get_model_list(self):
+       models = ['meta-llama/Llama-3.3-70B-Instruct-Turbo', 'deepseek-ai/DeepSeek-R1-Turbo', 'deepseek-ai/DeepSeek-R1-Distill-Llama-70B', 'deepseek-ai/DeepSeek-R1-Distill-Qwen-32B']
+       return models
+    
+
+    async def generate(self, json_data: dict):
+        messages = json_data
+
+        request_data = {
+            "id": "".join(random.choices("0123456789abcdef", k=16)),
+            "messages": messages,
+            "selectedModel": json_data.get("model", "deepseek-r1-distill-llama-70b"),
+        }
+
+        chunk_id = "chipling-deepinfraoff-" + "".join(random.choices("0123456789abcdef", k=32))
+        created = int(asyncio.get_event_loop().time())
+        total_tokens = 0
+
+        try:
+            async with httpx.AsyncClient(timeout=None) as client:
+                async with client.stream(
+                    "POST",
+                    "https://api.deepinfra.com/v1/openai/chat/completions",
+                    headers=OFFDeepInfraAPI.headers,
+                    json=request_data
+                ) as request_ctx:
+                    print(request_ctx.status_code)
+                    if request_ctx.status_code == 200:
+                        async for line in request_ctx.aiter_lines():
+                            if line:
+                                if line.startswith('0:'):
+                                    # Clean up the text and properly escape JSON characters
+                                    text = line[2:].strip()
+                                    if text.startswith('"') and text.endswith('"'):
+                                        text = text[1:-1]
+                                    text = text.replace('\\n', '\n').replace('\\', '')
+                                    
+                                    response = {
+                                        "id": chunk_id,
+                                        "object": "chat.completion.chunk",
+                                        "created": created,
+                                        "model": json_data.get("model", "deepseek-r1-distill-llama-70b"),
+                                        "choices": [{
+                                            "index": 0,
+                                            "text": text,
+                                            "logprobs": None,
+                                            "finish_reason": None
+                                        }],
+                                        "usage": None
+                                    }
+                                    yield f"data: {json.dumps(response)}\n\n"
+                                    total_tokens += 1
+                                elif line.startswith('d:'):
+                                    final = {
+                                        "id": chunk_id,
+                                        "object": "chat.completion.chunk", 
+                                        "created": created,
+                                        "model": json_data.get("model", "deepseek-r1-distill-llama-70b"),
+                                        "choices": [],
+                                        "usage": {
+                                            "prompt_tokens": len(messages),
+                                            "completion_tokens": total_tokens,
+                                            "total_tokens": len(messages) + total_tokens
+                                        }
+                                    }
+                                    yield f"data: {json.dumps(final)}\n\n"
+                                    yield "data: [DONE]\n\n"
+                        return
+                    else:
+                        yield f"data: [Unexpected status code: {request_ctx.status_code}]\n\n"
+        except Exception as e:
+            yield f"data: [Connection error: {str(e)}]\n\n"

models/text/together/main.py

@@ -40,7 +40,7 @@ class TogetherAPI:
         self.base_url = "https://api.together.ai/inference"
 
     def get_model_list(self):
-       models = ['meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8', 'meta-llama/Llama-4-Scout-17B-16E-Instruct', 'deepseek-ai/DeepSeek-R1', 'deepseek-ai/DeepSeek-V3', 'Qwen/Qwen2.5-VL-72B-Instruct', 'google/gemma-2-27b-it']
+       models = ['meta-llama/Llama-4-Maverick-17B-128E-Instruct-FP8', 'meta-llama/Llama-4-Scout-17B-16E-Instruct', 'deepseek-ai/DeepSeek-R1', 'deepseek-ai/DeepSeek-V3', 'Qwen/Qwen2.5-VL-72B-Instruct', 'google/gemma-2-27b-it', 'meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo']
        return models
     
     async def generate(self, json_data: dict):

runchecks.py

@@ -0,0 +1,38 @@
+import json
+import requests
+
+
+def check(loop, model, messages):
+    model = "deepseek-r1"
+
+    url = "https://chipling-api.hf.space/api/v1/text/generate"
+
+    payload = {
+        "messages": messages,
+        "model": model,
+        "api_key":"test"
+    }
+
+    response = requests.post(url, json=payload, stream=True)
+
+    if response.status_code == 200:
+        for line in response.iter_lines():
+            if line:
+                print(line)
+                decoded_line = line.decode('utf-8')
+                if decoded_line.startswith('data: [DONE]'):
+                    break
+                elif decoded_line.startswith('data: '):
+                    try:
+                        json_data = json.loads(decoded_line[6:])
+                        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}")
+
+
+
+
+

test.py

@@ -1,53 +1,61 @@
-# import requests
-# import json
-
-# 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 created you "}
-# ]
-
-# model = "Qwen/Qwen2.5-72B-Instruct"
-
-# url = "https://chipling-api.hf.space/api/v1/generate"
-
-# payload = {
-#     "messages": messages,
-#     "model": model
-# }
+import requests
+import json
+
+messages = [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "Depending on this image Create tell me a image generation prompt to create this:"
+                },
+            ]
+        },
+]
+
+model = "deepseek-r1"
+
+url = "https://chipling-api.hf.space/api/v1/text/generate"
+
+payload = {
+    "messages": messages,
+    "model": model,
+    "api_key":"test"
+}
 
-# response = requests.post(url, json=payload, stream=True)
+response = requests.post(url, json=payload, stream=True)
 
-# if response.status_code == 200:
-#     for line in response.iter_lines():
-#         if line:
-#             decoded_line = line.decode('utf-8')
-#             if decoded_line.startswith('data: [DONE]'):
-#                 break
-#             elif decoded_line.startswith('data: '):
-#                 try:
-#                     json_data = json.loads(decoded_line[6:])
-#                     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}")
+if response.status_code == 200:
+    for line in response.iter_lines():
+        if line:
+            print(line)
+            decoded_line = line.decode('utf-8')
+            if decoded_line.startswith('data: [DONE]'):
+                break
+            elif decoded_line.startswith('data: '):
+                try:
+                    json_data = json.loads(decoded_line[6:])
+                    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}")
 
 
-import requests
+# import requests
 
-url = 'https://chipling-api.hf.space/api/v1/generate-images'
+# url = 'https://chipling-api.hf.space/api/v1/generate-images'
 
-query = {
-    'prompt': 'a beautiful landscape',
-    'model': 'fal-ai/fast-sdxl',
-    'api_key': 'your_api_key_here',
-}
+# query = {
+#     'prompt': 'a beautiful landscape',
+#     'model': 'fal-ai/fast-sdxl',
+#     'api_key': 'your_api_key_here',
+# }
 
-response = requests.post(url, json=query)
-if response.status_code == 200:
-    data = response.json()['image']
-    print(data)
-else:   
-    print(f"Error: {response.status_code} - {response.text}")
+# response = requests.post(url, json=query)
+# if response.status_code == 200:
+#     data = response.json()['image']
+#     print(data)
+# else:   
+#     print(f"Error: {response.status_code} - {response.text}")

test2.py

@@ -1,50 +1,50 @@
-# import requests
-# import json
+import requests
+import json
 
-# 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 created you "}
-# ]
+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 created you "}
+]
 
-# model = "llama-4-scout-17b"
+model = "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo"
 
-# url = "http://127.0.0.1:8000/api/v1/text/generate"
+url = "http://127.0.0.1:8000/api/v1/text/generate"
 
-# payload = {
-#     "messages": messages,
-#     "model": model,
-#     "api_key": ""
-# }
+payload = {
+    "messages": messages,
+    "model": model,
+    "api_key": ""
+}
 
-# response = requests.post(url, json=payload, stream=True)
-
-# if response.status_code == 200:
-#     for line in response.iter_lines():
-#         if line:
-#             print(line)
-#             decoded_line = line.decode('utf-8')
-#             if decoded_line.startswith('data: [DONE]'):
-#                 break
-#             elif decoded_line.startswith('data: '):
-#                 try:
-#                     json_data = json.loads(decoded_line[6:])
-#                     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}")
+response = requests.post(url, json=payload, stream=True)
+
+if response.status_code == 200:
+    for line in response.iter_lines():
+        if line:
+            print(line)
+            decoded_line = line.decode('utf-8')
+            if decoded_line.startswith('data: [DONE]'):
+                break
+            elif decoded_line.startswith('data: '):
+                try:
+                    json_data = json.loads(decoded_line[6:])
+                    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}")
 
-import requests
+# import requests
 
-url = "http://127.0.0.1:8000/api/v1/tools/google-search"
+# url = "http://127.0.0.1:8000/api/v1/tools/google-search"
 
-payload = {
-    "query": "who are you and give me a breif description of who created you",
-    "num_results": 5,
-}
+# payload = {
+#     "query": "who are you and give me a breif description of who created you",
+#     "num_results": 5,
+# }
 
-response = requests.get(url, json=payload)
+# response = requests.get(url, json=payload)
 
-print(response.json())
+# print(response.json())

test3.py

@@ -0,0 +1,29 @@
+{
+    "model": "meta-llama/Llama-3.2-90B-Vision-Instruct-Turbo",
+    "messages": [
+        {
+            "role": "user",
+            "content": [
+                {
+                    "type": "text",
+                    "text": "Depending on this image Create tell me a image generation prompt to create this:"
+                },
+                {
+                    "type": "image_url",
+                    "image_url": {
+                        "url": "https://together-ai-uploaded-user-images-prod.s3.us-west-2.amazonaws.com/7106a4de-0635-4c07-a27e-f2678db81227.webp?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Content-Sha256=UNSIGNED-PAYLOAD&X-Amz-Credential=ASIAYWZW4HVCFP2GC22O%2F20250502%2Fus-west-2%2Fs3%2Faws4_request&X-Amz-Date=20250502T213211Z&X-Amz-Expires=3600&X-Amz-Security-Token=IQoJb3JpZ2luX2VjEEYaCXVzLXdlc3QtMiJIMEYCIQDrhm91rv4lvFFpewlhfHc5eQo0ecttb0YYfpdJle%2BrBQIhAMUiHP2IlXFjlFGZXGKoDPSpw%2BfvhZUqIre9xvIb1s7RKo8FCN%2F%2F%2F%2F%2F%2F%2F%2F%2F%2F%2FwEQABoMNTk4NzI2MTYzNzgwIgy5YGbDhU%2BNUpTvRZ8q4wTeYh%2FUIV5VVQehrmbFs5D%2FBxsWjCnY2qHMmn3OzHjPPzLWVHGDfIDvOTV%2FMgmUczCBts0vN6qaRFWw8URe066v%2B7o9wOd5Q6PTGThr9%2BGZVm5eyJsDVV0YBpz8jdCB3lzDcKnXu9L075MKP2macxHZLA%2BqVqHG9V6u77MH3C7jHgEkA13cBZikPWOTYIdQoJPaICLz1svZUixikAcVHpiqn4iXB3D12d8BPr1HDXf1JwYzwcvM3VoBh2KM7I3EwH%2Bo6%2BR2b0TwyzoUprH5qStp8Bh1f9fRlPvelnoEIrgu5ExTzFf4A%2B3wNXnQC4dJjTAr9Xc4frOXZCXUm1aCTBwLcBa%2B70AHyWsiSJps34MwwUyJxPlaULgbrZhTQCTreNcWT6pounWBjVPAnsvkJJqVYJ6J7%2FvGKmoi%2Bh6%2F%2Boo2MlhPH9FoeWel9rOCPpDv0jN4%2BYaXgAp82JaSfIO4oF7Gwa1co7hARReAgy7ZJ9T03IzAqFX20%2FDdDAmrwSQhnPcKkHwhQAtbWANPR69mvH6XDyJ1U0azsXU5MURVDaLqe%2FzAsTqmFHFzF6r2Qc2RhdRmU98f4rxx2a3fKhCNkCfPI8K0ghjN9L%2BIa8xaZcd2B6YQQ6IcYgro2%2BlBXLtC%2FJ%2FipKxx2msTz3JpNvbA9wE7tURi7nsta2cn4mNNXgALWSznuUCB5%2F%2BSYePKxdGS1%2BqVWNl89VdibVP8RGILmysKDJa8xJp9RALA8GZgCBlXoD6hQKxvKeMvla4s8wRSSu1mRyvzlWLIGNucS0kFGlp%2BHtQ2QZlpyFeJ4gZ68CiOSdN5BTDb89TABjqZAd7%2FMVEES0SB%2Faqz2k7MLmmOlxYimpU%2B1A%2FEVUzTNMM4xiQjBWcguYMantTXqvmklQkQXeVMFg48LQpz7Q2uGo0mNGwBg%2FJDRD8bX76Nge3fhs%2FDilM8tNN%2FKBI%2BEw8iIn%2BJl6j2nNqCgLWcUmcgI9ErMbqxE93Y4mDegI2FnElXvGo%2FSiQJ9fzBSvWvUdzqkEFdkqjLPtlovw%3D%3D&X-Amz-Signature=0204b843552605e28d4f9481402ae283ad5cb552212d92583f3bc3dab639e7eb&X-Amz-SignedHeaders=host&x-id=GetObject"
+                    }
+                }
+            ]
+        },
+        {
+            "role": "assistant",
+            "content": "The image depicts a man standing in front of a carpeted floor, with the words \"Clickbait!\" displayed prominently. The purpose of this image is likely to grab the viewer's attention and entice them to click on a related article or video.\n\nTo create an image generation prompt based on this input, I would suggest the following:\n\n*   **Image Description:** A man standing in front of a carpeted floor with the words \"Clickbait!\" written in bold letters.\n*   **Key Elements:**\n    *   Man\n    *   Carpeted floor\n    *   Words \"Clickbait!\"\n*   **Color Scheme:**\n    *   Main color palette: Gray, white, and red\n    *   Accent colors: Black and orange\n*   **Style:**\n    *   Realistic\n    *   Detailed\n*   **Additional Elements:**\n    *   A red arrow pointing to the words \"Clickbait!\"\n    *   A black border around the image\n\nWith these details, an AI image generator can create an image that accurately represents the original input."
+        },
+        {
+            "role": "user",
+            "content": "nic"
+        }
+    ],
+    "stream": true
+}

tools/fetch.py

@@ -35,3 +35,5 @@ class Tools:
         ]
 
         return data
+
+