change local llm to huggingface inference API

data/sim_history.csv

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:adc5c709bdd68b50b40654913a0dbbd68040e2f95e1155a3e0fca503a8bd80ed
-size 3085
+oid sha256:1233d86c355f1f2a726e937fe03be88a8654c69724c776526d3a4125408ee213
+size 3485

tabs/business.py

@@ -101,8 +101,9 @@ def render():
                 gr.Plot(plot_activity_heatmap(new_features_df))
 
             with gr.Column(elem_classes="card ai-chat"):
-                # gr.HTML("<h3>🤖 Scenario Chat</h3>")
+                gr.HTML("<h3> Scenario Chat : What-If Analysis</h3>")
                 respond,title = ai_chat_factory("Business Insights & What-If Analysis")
-                gr.ChatInterface(fn=respond, chatbot=gr.Chatbot(label=title,height=290))
+                # gr.ChatInterface(fn=respond, chatbot=gr.Chatbot(label=title,height=290))
+                gr.ChatInterface(fn=respond, chatbot=gr.Chatbot(type="messages",height=250))
 
     # gr.HTML(f"<style>{css}</style>")

tabs/shared_ai.py

@@ -18,6 +18,9 @@ from pydantic import BaseModel, ValidationError
 # LangChain components
 from langchain_community.chat_models import ChatOllama, ChatHuggingFace
 from langchain_community.llms import HuggingFaceHub
+
+from langchain_community.chat_models import ChatOllama
+from langchain_huggingface import ChatHuggingFace, HuggingFaceEndpoint
 # from langchain.prompts import PromptTemplate
 
 # Local utilities

utils/models.py

@@ -18,26 +18,29 @@ def load_model(model_path: str = "app_best.joblib"):
     Loads a trained scikit-learn model (.pkl or .joblib) from disk.
     Automatically searches in the /models folder if a relative path is provided.
     """
-    # # Try direct path first
-    # if os.path.exists(model_path):
-    #     return joblib.load(model_path)
-
-    # # Try inside models/ folder
-    # candidate_path = os.path.join("models", model_path)
-    # if os.path.exists(candidate_path):
-    #     return joblib.load(candidate_path)
-    # raise FileNotFoundError(
-    #     f"❌ Model file not found. Tried: {model_path_hf} and {model_path_hf}"
-    # )
-    # Download model dynamically from Hugging Face model repo
-    model_path_hf = hf_hub_download(
-        repo_id="VasTk/user-churn-models",
-        filename=model_path
-    )
-    model = joblib.load(model_path_hf)
     
+    # Download model dynamically from Hugging Face model repo
+    if os.getenv("SPACE_ID"):  # Running inside a Hugging Face Space
+        model_path_hf = hf_hub_download(
+            repo_id="VasTk/user-churn-models",
+            filename=model_path
+        )
+        model = joblib.load(model_path_hf)
+        return model
+    else:
+        # Try direct path first
+        if os.path.exists(model_path):
+            return joblib.load(model_path)
+
+        # Try inside models/ folder
+        candidate_path = os.path.join("models", model_path)
+        if os.path.exists(candidate_path):
+            return joblib.load(candidate_path)
+        raise FileNotFoundError(
+            f"❌ Model file not found. Tried: {model_path_hf} and {model_path_hf}"
+        )
+        
     
-    return model
 
 # ------------------------------------------------------------
 # 📊 Example placeholder metrics and visuals