Update app.py

app.py

@@ -5,13 +5,12 @@ from transformers import pipeline, AutoModelForCausalLM, AutoTokenizer, AutoMode
 import black
 from pylint import lint
 from io import StringIO
-import openai
 import sys
 import torch
 from huggingface_hub import hf_hub_url, cached_download, HfApi
 
-# Set your OpenAI API key here
-openai.api_key = "YOUR_OPENAI_API_KEY"
+# 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"
 PROJECT_ROOT = "projects"
@@ -41,6 +40,36 @@ AVAILABLE_CODE_GENERATIVE_MODELS = [
     "facebook/bart-large-cnn",  # Good for text-to-code tasks
 ]
 
+# Load pre-trained RAG retriever
+rag_retriever = RagRetriever.from_pretrained("facebook/rag-token-base")  # Use a Hugging Face RAG model
+
+# Load pre-trained chat model
+chat_model = AutoModelForSeq2SeqLM.from_pretrained("microsoft/DialoGPT-medium")  # Use a Hugging Face chat model
+
+# Load tokenizer
+tokenizer = AutoTokenizer.from_pretrained("microsoft/DialoGPT-medium")
+
+def process_input(user_input):
+    # Input pipeline: Tokenize and preprocess user input
+    input_ids = tokenizer(user_input, return_tensors="pt").input_ids
+    attention_mask = tokenizer(user_input, return_tensors="pt").attention_mask
+
+    # RAG model: Generate response
+    with torch.no_grad():
+        output = rag_retriever(input_ids, attention_mask=attention_mask)
+        response = output.generator_outputs[0].sequences[0]
+
+    # Chat model: Refine response
+    chat_input = tokenizer(response, return_tensors="pt")
+    chat_input["input_ids"] = chat_input["input_ids"].unsqueeze(0)
+    chat_input["attention_mask"] = chat_input["attention_mask"].unsqueeze(0)
+    with torch.no_grad():
+        chat_output = chat_model(**chat_input)
+        refined_response = chat_output.sequences[0]
+
+    # Output pipeline: Return final response
+    return refined_response
+
 class AIAgent:
     def __init__(self, name, description, skills):
         self.name = name
@@ -430,4 +459,8 @@ elif app_mode == "Workspace Chat App":
 
         # Use the hf_token to interact with the Hugging Face API
         api = HfApi(token=hf_token)
-        # ... (your logic to deploy the Space using the API)
+        # 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}"}
+    </s>