Update app.py

app.py

@@ -1,21 +1,50 @@
+import os
+import json
 import subprocess
-import streamlit as st
-from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, AutoModel, RagRetriever, AutoModelForSeq2SeqLM
+import re
+import ast
+import requests
+from datetime import datetime
+
+import gradio as gr
+from transformers import (pipeline, AutoModelForCausalLM, AutoTokenizer, TextGenerationPipeline, 
+                          TrainingArguments, Trainer, AutoModel, RagRetriever, AutoModelForSeq2SeqLM)
+import torch
+import tree_sitter
+from tree_sitter import Language, Parser
 import black
 from pylint import lint
 from io import StringIO
 import sys
-import torch
-from huggingface_hub import hf_hub_url, cached_download, HfApi
+from huggingface_hub import Repository, hf_hub_url, HfApi, snapshot_download
+import tempfile
 
-# Set your Hugging Face API key here
-hf_token = "YOUR_HUGGING_FACE_API_KEY"  # Replace with your actual token
 
-HUGGING_FACE_REPO_URL = "https://huggingface.co/spaces/acecalisto3/DevToolKit"
+# Constants
+MODEL_NAME = "bigscience/bloom"
 PROJECT_ROOT = "projects"
 AGENT_DIRECTORY = "agents"
+AVAILABLE_CODE_GENERATIVE_MODELS = [
+    "bigcode/starcoder",  
+    "Salesforce/codegen-350M-mono",  
+    "microsoft/CodeGPT-small",  
+    "google/flan-t5-xl",
+    "facebook/bart-large-cnn", 
+]
+
+
+# Load Models and Resources
+tokenizer = AutoTokenizer.from_pretrained(MODEL_NAME)
+model = AutoModelForCausalLM.from_pretrained(MODEL_NAME, torch_dtype=torch.float16)
+pipe = TextGenerationPipeline(model=model, tokenizer=tokenizer)
+
+# Build Tree-sitter parser libraries (if not already built)
+Language.build_library('build/my-languages.so', ['tree-sitter-python', 'tree-sitter-javascript'])
+PYTHON_LANGUAGE = Language('build/my-languages.so', 'python')
+JAVASCRIPT_LANGUAGE = Language('build/my-languages.so', 'javascript')
+parser = Parser()
 
-# Global state to manage communication between Tool Box and Workspace Chat App
+# Session State Initialization
 if 'chat_history' not in st.session_state:
     st.session_state.chat_history = []
 if 'terminal_history' not in st.session_state:
@@ -30,6 +59,7 @@ if 'current_state' not in st.session_state:
         'workspace_chat': {}
     }
 
+
 # List of top downloaded free code-generative models from Hugging Face Hub
 AVAILABLE_CODE_GENERATIVE_MODELS = [
     "bigcode/starcoder",  # Popular and powerful
@@ -461,19 +491,7 @@ elif app_mode == "Workspace Chat App":
         # Function to create a Space on Hugging Face
 def create_space(api, name, description, public, files, entrypoint="launch.py"):
     url = f"{hf_hub_url()}spaces/{name}/prepare-repo"
-    headers = {"Authorization": f"Bearer {api.access_token}"}````
-
-i need to integrate logic from these below, into my existing app.py above: 
-````import os
-import subprocess
-import streamlit as st
-from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, AutoModel, RagRetriever, AutoModelForSeq2SeqLM
-import black
-from pylint import lint
-from io import StringIO
-import sys
-import torch
-from huggingface_hub import hf_hub_url, cached_download, HfApi
+    headers = {"Authorization": f"Bearer {api.access_token}"}
 
 # Set your Hugging Face API key here
 hf_token = "YOUR_HUGGING_FACE_API_KEY"  # Replace with your actual token