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78904ef b115eb7 a11c262 b115eb7 78904ef | 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 | import os
import json
from flask import Flask, request, jsonify, Response, stream_with_context
from huggingface_hub import InferenceClient
app = Flask(__name__)
HF_TOKEN = os.environ.get("HF_TOKEN", "")
DEFAULT_MODEL = os.environ.get("DEFAULT_MODEL", "Qwen/Qwen2.5-72B-Instruct")
client = InferenceClient(token=HF_TOKEN)
@app.route("/", methods=["GET"])
def index():
return jsonify({"status": "ok", "message": "InfinityLLM API is running"})
@app.route("/v1/models", methods=["GET"])
def models():
return jsonify({
"object": "list",
"data": [
{"id": "Qwen/Qwen2.5-72B-Instruct", "object": "model"},
{"id": "Qwen/Qwen2.5-7B-Instruct", "object": "model"},
{"id": "Qwen/Qwen2.5-Coder-32B-Instruct", "object": "model"},
{"id": "meta-llama/Llama-3.3-70B-Instruct", "object": "model"},
{"id": "meta-llama/Llama-3.1-8B-Instruct", "object": "model"},
{"id": "deepseek-ai/DeepSeek-R1-Distill-Qwen-7B", "object": "model"},
{"id": "deepseek-ai/DeepSeek-R1-Distill-Llama-70B","object": "model"},
{"id": "moonshotai/Kimi-K2.6", "object": "model"},
{"id": "MiniMaxAI/MiniMax-M2.7", "object": "model"},
{"id": "Qwen/Qwen3-Coder-30B-A3B-Instruct", "object": "model"}, ]
})
@app.route("/v1/chat/completions", methods=["POST"])
def chat():
data = request.json
if not data:
return jsonify({"error": "No JSON body"}), 400
messages = data.get("messages", [])
model = data.get("model", DEFAULT_MODEL)
max_tokens = int(data.get("max_tokens", 2048))
temperature = float(data.get("temperature", 0.7))
stream = data.get("stream", False)
try:
if stream:
def generate():
full_content = ""
try:
for chunk in client.chat_completion(
model=model,
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
stream=True,
):
delta_content = ""
if chunk.choices and chunk.choices[0].delta:
delta_content = chunk.choices[0].delta.content or ""
full_content += delta_content
chunk_data = {
"id": "chatcmpl-hf",
"object": "chat.completion.chunk",
"model": model,
"choices": [{
"index": 0,
"delta": {"role": "assistant", "content": delta_content},
"finish_reason": None
}]
}
yield f"data: {json.dumps(chunk_data)}\n\n"
final = {
"id": "chatcmpl-hf",
"object": "chat.completion.chunk",
"model": model,
"choices": [{
"index": 0,
"delta": {},
"finish_reason": "stop"
}]
}
yield f"data: {json.dumps(final)}\n\n"
yield "data: [DONE]\n\n"
except Exception as e:
yield f"data: {json.dumps({'error': str(e)})}\n\n"
return Response(
stream_with_context(generate()),
mimetype="text/event-stream",
headers={
"Cache-Control": "no-cache",
"X-Accel-Buffering": "no"
}
)
else:
response = client.chat_completion(
model=model,
messages=messages,
max_tokens=max_tokens,
temperature=temperature,
stream=False,
)
content = ""
if response.choices and len(response.choices) > 0:
choice = response.choices[0]
if hasattr(choice, "message") and choice.message:
content = choice.message.content or ""
if not content:
return jsonify({"error": "Empty response from model"}), 500
return jsonify({
"id": "chatcmpl-hf",
"object": "chat.completion",
"model": model,
"choices": [{
"index": 0,
"message": {
"role": "assistant",
"content": content
},
"finish_reason": "stop"
}],
"usage": {
"prompt_tokens": 0,
"completion_tokens": 0,
"total_tokens": 0
}
})
except Exception as e:
return jsonify({
"error": str(e),
"choices": [{
"index": 0,
"message": {"role": "assistant", "content": f"Error: {str(e)}"},
"finish_reason": "stop"
}]
}), 500
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860, debug=False) |