Create app.py

app.py

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+import os
+import streamlit as st
+from groq import Groq
+from transformers import AutoTokenizer
+import faiss
+import numpy as np
+
+# Set the Hugging Face API Key
+os.environ["GROQ_API_KEY"] = "MY_API_KEY"  # Replace with your Hugging Face API Key
+client = Groq(api_key=os.environ.get("GROQ_API_KEY"))
+
+# Supported Microcontrollers/Processors
+devices = {
+    "Arduino": {
+        "template": """
+        // Arduino Syntax Template
+        void setup() {
+          // Setup code here, to run once:
+        }
+
+        void loop() {
+          // Main code here, to run repeatedly:
+        }
+        """,
+    },
+    "PIC18": {
+        "template": """
+        // PIC18 Syntax Template
+        #include <xc.h>
+        void main() {
+          // Initialization code
+          while(1) {
+            // Main program loop
+          }
+        }
+        """,
+    },
+    "8085": {
+        "template": """
+        ; 8085 Assembly Language Template
+        START:  MVI A, 00H ; Load Accumulator with 0
+                OUT PORT1  ; Output data to port
+                HLT        ; Halt program
+        """,
+    },
+}
+
+# Function to Generate Code using Groq API
+def generate_code(prompt, model="llama-3.3-70b-versatile"):
+    chat_completion = client.chat.completions.create(
+        messages=[{"role": "user", "content": prompt}],
+        model=model,
+    )
+    return chat_completion.choices[0].message.content
+
+# Function to Chunk and Tokenize Code
+def tokenize_and_chunk_code(code, model_name="gpt2", max_length=512):
+    tokenizer = AutoTokenizer.from_pretrained(model_name)
+    tokens = tokenizer(code, truncation=True, return_tensors="pt")
+    chunks = [
+        tokens.input_ids[0][i : i + max_length]
+        for i in range(0, len(tokens.input_ids[0]), max_length)
+    ]
+    return chunks
+
+# Function to Store Code in FAISS
+def store_code_in_faiss(chunks):
+    dimension = 512
+    embeddings = [np.random.rand(dimension) for _ in chunks]  # Replace with actual embeddings
+    faiss_index = faiss.IndexFlatL2(dimension)
+    faiss_index.add(np.array(embeddings, dtype=np.float32))
+    return faiss_index
+
+# Streamlit App
+def main():
+    st.title("Microcontroller Code Generator")
+    st.write("Select the microcontroller and provide code requirements.")
+
+    # Step 1: Ask User for Microcontroller/Processor Selection
+    device = st.selectbox("Select a microcontroller/processor", options=["Arduino", "PIC18", "8085"])
+
+    # Step 2: Show Syntax Template
+    st.subheader("Coding Syntax Template")
+    st.code(devices[device]["template"])
+
+    # Step 3: Get User Prompt and Generate Code
+    prompt = st.text_input("Enter your code requirements:")
+
+    if prompt:
+        st.write("Generating code...")
+        code = generate_code(f"Write {device} code for: {prompt}")
+        
+        # Step 4: Chunk, Tokenize, and Store Code in FAISS
+        chunks = tokenize_and_chunk_code(code)
+        store_code_in_faiss(chunks)
+        
+        # Step 5: Display Generated Code
+        st.subheader("Generated Code")
+        st.code(code)
+
+# Run the Streamlit App
+if __name__ == "__main__":
+    main()