Add application file

app.py

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+from fastapi import FastAPI, HTTPException
+from pydantic import BaseModel
+from llama_cpp import Llama
+from typing import Optional
+import uvicorn
+
+app = FastAPI(
+	title="OmniVLM API",
+	description="API for text generation using OmniVLM model",
+	version="1.0.0"
+)
+
+# Initialize the model
+llm = Llama.from_pretrained(
+	repo_id="NexaAIDev/OmniVLM-968M",
+	filename="omnivision-text-optimized-llm-Q8_0.gguf",
+)
+
+class GenerationRequest(BaseModel):
+	prompt: str
+	max_tokens: Optional[int] = 100
+	temperature: Optional[float] = 0.7
+	top_p: Optional[float] = 0.9
+
+class GenerationResponse(BaseModel):
+	generated_text: str
+
+@app.post("/generate", response_model=GenerationResponse)
+async def generate_text(request: GenerationRequest):
+	try:
+		output = llm(
+			request.prompt,
+			max_tokens=request.max_tokens,
+			temperature=request.temperature,
+			top_p=request.top_p
+		)
+		
+		return GenerationResponse(generated_text=output["choices"][0]["text"])
+	except Exception as e:
+		raise HTTPException(status_code=500, detail=str(e))
+
+@app.get("/health")
+async def health_check():
+	return {"status": "healthy"}
+
+if __name__ == "__main__":
+	uvicorn.run(app, host="0.0.0.0", port=8000)

requirements.txt

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+fastapi==0.104.1
+uvicorn==0.24.0
+pydantic==2.4.2
+llama-cpp-python==0.1.76