Update main.py

main.py

@@ -1,7 +1,10 @@
 from fastapi import FastAPI, HTTPException
 from fastapi.responses import PlainTextResponse
 from pydantic import BaseModel
-from llm_func import mdl
+from llm_func import llm_normal,llm_agent,name_age,llm_functioncalling,search,llm_search
+from llama_cpp import Llama
+
+llm = Llama.from_pretrained(repo_id="HuggingFaceTB/SmolLM2-360M-Instruct-GGUF",filename="*smollm2-360m-instruct-q8_0.gguf",verbose=False,n_ctx=500) 
 
 app = FastAPI()
 
@@ -9,10 +12,36 @@ class TextInput(BaseModel):
     text: str
 
 
-@app.post("/llm/", response_class=PlainTextResponse)
-async def convert_to_llm(input_data: TextInput):
+@app.post("/llm_normal/", response_class=PlainTextResponse)
+async def to_llm_normal(input_data: TextInput):
+    if not input_data.text:
+        raise HTTPException(status_code=400, detail="The text can't be empty.")
+    output_data = llm_normal(input_data.text,llm)
+    return output_data
+
+
+@app.post("/llm_agent/", response_class=PlainTextResponse)
+async def to_llm_agent(input_data: TextInput):
+    if not input_data.text:
+        raise HTTPException(status_code=400, detail="The text can't be empty.")
+    output_data = llm_agent(input_data.text,llm)
+    return output_data
+
+
+@app.post("/llm_functioncalling/", response_class=PlainTextResponse)
+async def to_llm_functioncalling(input_data: TextInput):
+    if not input_data.text:
+        raise HTTPException(status_code=400, detail="The text can't be empty.")
+    output_data = llm_functioncalling(input_data.text,llm)
+    return output_data
+
+
+@app.post("/llm_search/", response_class=PlainTextResponse)
+async def to_llm_search(input_data: TextInput):
     if not input_data.text:
-        raise HTTPException(status_code=400, detail="O texto não pode estar vazio.")
-    
-    output_data = mdl(input_data.text)
+        raise HTTPException(status_code=400, detail="The text can't be empty.")
+    output_data = llm_search(input_data.text,llm)
     return output_data
+
+
+