Update app.py

app.py

@@ -84,10 +84,20 @@ embedding_model = HuggingFaceEmbeddings(
 #)
 
 # Initialize Hugging Face LLM
-llm = HuggingFaceHub(
-    repo_id="meta-llama/Meta-Llama-3-8B-Instruct",  # or mistralai/Mistral-7B-Instruct-v0.3
-    huggingfacehub_api_token=os.environ["HF_TOKEN"],
-    model_kwargs={"temperature": 0.2, "max_new_tokens": 512}
+from langchain_community.chat_models import ChatHuggingFace
+from transformers import pipeline
+
+pipe = pipeline(
+    "text-generation",
+    model="meta-llama/Meta-Llama-3-8B-Instruct",
+    token=os.environ["HF_TOKEN"],
+    max_new_tokens=512,
+    temperature=0.0
+)
+
+llm = ChatHuggingFace(
+    pipeline=pipe,
+    model_id="meta-llama/Meta-Llama-3-8B-Instruct"
 )
 
 # This initializes the Chat OpenAI model with the provided endpoint, API key, deployment name, and a temperature setting of 0 (to control response variability).
@@ -569,12 +579,23 @@ class SpiritualBot:
         #)
 
         # Initialize Hugging Face client
-        self.client = HuggingFaceHub(
-        repo_id="meta-llama/Meta-Llama-3-8B-Instruct",
-        huggingfacehub_api_token=os.environ["HF_TOKEN"],
-        model_kwargs={"temperature": 0.0, "max_new_tokens": 512}
+        from langchain_community.chat_models import ChatHuggingFace
+        from transformers import pipeline
+
+        pipe = pipeline(
+        "text-generation",
+        model="meta-llama/Meta-Llama-3-8B-Instruct",
+        token=os.environ["HF_TOKEN"],
+        max_new_tokens=512,
+        temperature=0.0
         )
 
+        # Assign to self.client
+        self.client = ChatHuggingFace(
+        pipeline=pipe,
+        model_id="meta-llama/Meta-Llama-3-8B-Instruct"
+        )
+        
         # Define tools available to the chatbot, such as web search
         tools = [agentic_rag]