Update app.py

app.py

@@ -8,55 +8,53 @@ import anthropic
 import gradio as gr
 import subprocess
 
+load_dotenv()
 
+# Set API keys from .env or HF secrets
 os.environ['OPENAI_API_KEY'] = os.environ.get('OPENAI_API_KEY')
 os.environ['ANTHROPIC_API_KEY'] = os.environ.get('ANTHROPIC_API_KEY')
 deepseek_api_key = os.environ.get('DEEPSEEK_API_KEY')
 
-
-
 openai = OpenAI()
 claude = anthropic.Anthropic()
-deepseek = OpenAI(
-    api_key=deepseek_api_key, 
-    base_url="https://api.deepseek.com/v1"
-)
+deepseek = OpenAI(api_key=deepseek_api_key, base_url="https://api.deepseek.com/v1")
 
 OPENAI_MODEL = "gpt-4o"
 CLAUDE_MODEL = "claude-3-5-sonnet-20240620"
 DEEPSEEK_MODEL = 'deepseek-coder'
 
-system_message = "You are an assistant that reimplements Python code in high performance C++ for an M1 Mac. "
-system_message += "Respond only with C++ code; use comments sparingly and do not provide any explanation other than occasional comments. "
-system_message += "The C++ response needs to produce an identical output in the fastest possible time."
-
+system_message = (
+    "You are an assistant that reimplements Python code in high performance C++ for an M1 Mac. "
+    "Respond only with C++ code; use comments sparingly and do not provide any explanation other than occasional comments. "
+    "The C++ response needs to produce an identical output in the fastest possible time."
+)
 
 def user_prompt_for(python):
-    user_prompt = "Rewrite this Python code in C++ with the fastest possible implementation that produces identical output in the least time. "
-    user_prompt += "Respond only with C++ code; do not explain your work other than a few comments. "
-    user_prompt += "Pay attention to number types to ensure no int overflows. Remember to #include all necessary C++ packages such as iomanip.\n\n"
-    user_prompt += python
-    return user_prompt
+    return (
+        "Rewrite this Python code in C++ with the fastest possible implementation that produces identical output in the least time. "
+        "Respond only with C++ code; do not explain your work other than a few comments. "
+        "Pay attention to number types to ensure no int overflows. Remember to #include all necessary C++ packages such as iomanip.\n\n"
+        + python
+    )
 
 def messages_for(python):
     return [
         {"role": "system", "content": system_message},
         {"role": "user", "content": user_prompt_for(python)}
     ]
-# write to a file called optimized.cpp
 
 def write_output(cpp):
-    code = cpp.replace("```cpp","").replace("```","")
+    code = cpp.replace("```cpp", "").replace("```", "")
     with open("optimized.cpp", "w") as f:
         f.write(code)
 
-def stream_gpt(python):    
+def stream_gpt(python):
     stream = openai.chat.completions.create(model=OPENAI_MODEL, messages=messages_for(python), stream=True)
     reply = ""
     for chunk in stream:
         fragment = chunk.choices[0].delta.content or ""
         reply += fragment
-        yield reply.replace('```cpp\n','').replace('```','')
+        yield reply.replace('```cpp\n', '').replace('```', '')
 
 def stream_claude(python):
     result = claude.messages.stream(
@@ -69,44 +67,61 @@ def stream_claude(python):
     with result as stream:
         for text in stream.text_stream:
             reply += text
-            yield reply.replace('```cpp\n','').replace('```','')
+            yield reply.replace('```cpp\n', '').replace('```', '')
 
 def stream_deepseek(python):
     stream = deepseek.chat.completions.create(
-        model = DEEPSEEK_MODEL,
-        messages = messages_for(python),
+        model=DEEPSEEK_MODEL,
+        messages=messages_for(python),
         stream=True
     )
     reply = ""
     for chunk in stream:
         fragment = chunk.choices[0].delta.content or ""
         reply += fragment
-        yield reply.replace('```cpp\n','').replace('```','')
+        yield reply.replace('```cpp\n', '').replace('```', '')
 
 def optimize(python, model):
-    if model=="GPT":
+    if model == "GPT":
         result = stream_gpt(python)
-    elif model=="Claude":
+    elif model == "Claude":
         result = stream_claude(python)
     elif model == "DeepSeek":
         result = stream_deepseek(python)
     else:
         raise ValueError("Unknown model")
     for stream_so_far in result:
-        yield stream_so_far        
+        yield stream_so_far
 
 def execute_python(code):
     try:
         output = io.StringIO()
         sys.stdout = output
-        exec(code)
+        local_scope = {}
+        exec(code, local_scope, local_scope)
+    except Exception as e:
+        return f"Python error:\n{e}"
     finally:
         sys.stdout = sys.__stdout__
     return output.getvalue()
 
-#example python code
-python_hard = """# Be careful to support large number sizes
+def execute_cpp(code):
+    write_output(code)
+    try:
+        compile_cmd = ["g++", "-Ofast", "-std=c++17", "-o", "optimized", "optimized.cpp"]
+        subprocess.run(compile_cmd, check=True, text=True, capture_output=True)
+        run_cmd = ["./optimized"]
+        run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True)
+        return run_result.stdout
+    except subprocess.CalledProcessError as e:
+        return f"C++ error:\n{e.stderr}"
+
+css = """
+.python {background-color: #306998;}
+.cpp {background-color: #050;}
+"""
 
+example_code = '''# Be careful to support large number sizes
 def lcg(seed, a=1664525, c=1013904223, m=2**32):
     value = seed
     while True:
@@ -133,47 +148,24 @@ def total_max_subarray_sum(n, initial_seed, min_val, max_val):
         total_sum += max_subarray_sum(n, seed, min_val, max_val)
     return total_sum
 
-# Parameters
-n = 10000         # Number of random numbers
-initial_seed = 42 # Initial seed for the LCG
-min_val = -10     # Minimum value of random numbers
-max_val = 10      # Maximum value of random numbers
-
-# Timing the function
 import time
+n = 10000
+initial_seed = 42
+min_val = -10
+max_val = 10
 start_time = time.time()
 result = total_max_subarray_sum(n, initial_seed, min_val, max_val)
 end_time = time.time()
-
 print("Total Maximum Subarray Sum (20 runs):", result)
-print("Execution Time: {:.6f} seconds".format(end_time - start_time))
-"""
-
-
-def execute_cpp(code):
-    write_output(code)
-    try:
-        # Modified compiler flags to be more generic and compatible with Linux environments
-        compile_cmd = ["g++", "-Ofast", "-std=c++17", "-march=native", "-o", "optimized", "optimized.cpp"]
-        compile_result = subprocess.run(compile_cmd, check=True, text=True, capture_output=True)
-        run_cmd = ["./optimized"]
-        run_result = subprocess.run(run_cmd, check=True, text=True, capture_output=True)
-        return run_result.stdout
-    except subprocess.CalledProcessError as e:
-        return f"An error occurred:\n{e.stderr}"
-
-css = """
-.python {background-color: #306998;}
-.cpp {background-color: #050;}
-"""
+print("Execution Time: {:.6f} seconds".format(end_time - start_time))'''
 
 with gr.Blocks(css=css) as ui:
-    gr.Markdown("## Convert code from Python to C++")
+    gr.Markdown("## 🔁 Python To C++ Converter")
     with gr.Row():
-        python = gr.Textbox(label="Python code:", value=python_hard, lines=10)
-        cpp = gr.Textbox(label="C++ code:", lines=10)
+        python = gr.Textbox(label="Python code:", value=example_code, lines=12)
+        cpp = gr.Textbox(label="C++ code:", lines=12)
     with gr.Row():
-        model = gr.Dropdown(["GPT", "Claude","DeepSeek"], label="Select model", value="Claude")
+        model = gr.Dropdown(["GPT", "Claude", "DeepSeek"], label="Select model", value="Claude")
     with gr.Row():
         convert = gr.Button("Convert code")
     with gr.Row():
@@ -187,4 +179,4 @@ with gr.Blocks(css=css) as ui:
     python_run.click(execute_python, inputs=[python], outputs=[python_out])
     cpp_run.click(execute_cpp, inputs=[cpp], outputs=[cpp_out])
 
-ui.launch(inbrowser=True)
+ui.launch(share=True)