Upload app.py

app.py

@@ -1,13 +1,27 @@
 from fastapi import FastAPI
 from transformers import pipeline
 
-## create a new FASTAPI app instance
-app=FastAPI()
 
-# Initialize the text generation pipeline
-pipe = pipeline("image-text-to-text", model="deepseek-ai/deepseek-vl2-small")
+from llama_cpp import Llama
+
+llm = Llama.from_pretrained(
+	repo_id="hugging-quants/Llama-3.2-1B-Instruct-Q8_0-GGUF",
+	filename="llama-3.2-1b-instruct-q8_0.gguf",
+)
 
+check  = llm.create_chat_completion(
+	messages = [
+		{
+			"role": "user",
+			"content": "What is the capital of France?"
+		}
+	]
+)
 
+print(check['choices'][0]['message']['content'])
+
+## create a new FASTAPI app instance
+app=FastAPI()
 @app.get("/")
 def home():
     return {"message":"Hello World"}
@@ -18,7 +32,14 @@ def home():
 @app.get("/generate")
 def generate(text:str):
     ## use the pipeline to generate text from given input text
-    output=pipe(text)
+    output= llm.create_chat_completion(
+	messages = [
+		{
+			"role": "user",
+			"content": f"{text}"
+		}
+	]
+)
 
     ## return the generate text in Json reposnfe
     return {"output":output[0]['generated_text']}