added new changes

.gitignore

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+__pycache__
+venv

load_meta_data.py

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+import torch
+from transformers import AutoModelForCausalLM, AutoTokenizer
+from pydantic import BaseModel
+from fastapi import HTTPException
+
+class UserQuery(BaseModel):
+    user_query: str
+
+
+class ChatBot:
+    def __init__(self):
+        self.tokenizer = None 
+        self.model = None 
+    
+    def load_from_hub(self,model_id: str):
+        self.tokenizer =  AutoTokenizer.from_pretrained(model_id,
+                                          device_map = 'auto')
+        self.model = AutoModelForCausalLM.from_pretrained(model_id,
+                                             device_map='auto')
+        
+    def get_response(self,text: UserQuery) -> str:
+        if not self.model or not self.tokenizer:
+            raise HTTPException(status_code=400, detail="Model is not loaded")
+            
+        inputs = self.tokenizer(text,return_tensors='pt')
+        outputs = self.model.generate(**inputs,
+                                 max_new_tokens = 100,
+                                )
+        response = self.tokenizer.decode(outputs[0],skip_special_tokens=True)
+        response = self.get_clean_response(response) 
+        return response
+
+    def get_clean_response(self,response:list[str] | str) -> str:
+        if type(response) == list:
+            response = response[0].split("\n")
+        else:
+            response = response.split("\n")
+
+        ans = ''
+        cnt = 0 # to verify if we have seen Human before 
+        for answer in response:
+            if answer.startswith("[|Human|]"): cnt += 1
+
+            elif answer.startswith('[|AI|]'):
+                answer = answer.split(' ')
+                ans += ' '.join(char for char in answer[1:])
+                ans += '\n'
+
+            elif cnt:
+                ans += answer + '\n'
+        return ans

requirements.txt

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+transformers
+fastapi