Create app.py

app.py

@@ -0,0 +1,136 @@
+import os
+import gradio as gr
+from transformers import ReactCodeAgent, HfEngine, Tool
+from gradio_agentchatbot import (
+    AgentChatbot,
+    stream_from_transformers_agent,
+    ChatMessage,
+)
+from dotenv import load_dotenv
+from huggingface_hub import login
+from transformers.agents.default_tools import (
+    BASE_PYTHON_TOOLS,
+    LIST_SAFE_MODULES,
+    evaluate_python_code,
+)
+
+# to load SerpAPI key
+load_dotenv()
+login(os.getenv("HUGGINGFACEHUB_API_KEY"))
+
+
+llm_engine = HfEngine(model="meta-llama/Meta-Llama-3-70B-Instruct")
+
+authorized_imports = ["numpy"]
+
+agent = ReactCodeAgent(
+    llm_engine=llm_engine,
+    tools=[],
+    additional_authorized_imports=authorized_imports,
+    max_iterations=10,
+)
+
+class FinalAnswerToolWithVerification(Tool):
+    name = "final_answer"
+    description = "Provides a final answer to the given problem"
+    inputs = {
+        "answer": {"type": "text", "description": "The final answer to the problem"}
+    }
+    output_type = "any"
+
+    def forward(self, answer):
+        if "def test" not in answer:
+            raise Exception(
+                "I can only accept from you a code snippet answer that defines test functions in python, anything else will not work. PLEASE PROVIDE ME A FULL CODE SNIPPET CONTAINING THE DEFINITION OF THE TESTS."
+            )
+        return answer
+
+final_answer_tool = FinalAnswerToolWithVerification()
+
+agent._toolbox.update_tool(final_answer_tool)
+
+function = """import numpy as np
+def moving_average(x, w):
+    return np.convolve(x, np.ones(w), 'valid') / w"""
+
+task = """I will give you a basic function that I've created.
+Now I want you to generate a set of unit tests for these functions, check that they run, and give them to me.
+Please follow these steps in order:
+1. Define and run the function given o you, so that it gets defined in your interpreter.
+2. Generate one test function as a python blob, with assert statements
+3. Run the test function in a code snippet and make sure the tests pass
+4. Return to me the complete TEST function (not the original function) as a string code snippet.
+---
+Example:
+Here is your function:
+```py
+def get_even_numbers(numbers):
+    even_numbers = []
+    for number in numbers:
+        if number % 2 == 0:
+            even_numbers.append(number)
+    return even_numbers
+```
+Now generate test functions for me!
+Thought: Let's re-define the given function and generate a test.
+Code:
+```py
+def get_even_numbers(numbers):
+    even_numbers = []
+    for number in numbers:
+        if number % 2 == 0:
+            even_numbers.append(number)
+    return even_numbers
+def test_get_even_numbers():
+    assert get_even_numbers([1, 2, 3, 4, 5]) == [2, 4]
+    print("No error found!")
+test_get_even_numbers()
+```
+Observation: "No error found!"
+Thought: the interpreter ran tests with no error. So we can return the function IN A TEXT SNIPPET.
+Code:
+```py
+fianl_answer_snippet = \"\"\"
+def test_get_even_numbers():
+    assert get_even_numbers([1, 2, 3, 4, 5]) == [2, 4]
+    print("No error found!")
+\"\"\"
+final_answer(final_answer_snippet)
+```
+---
+Now proceed!
+Here is your function:
+```py
+<<function>>
+```
+Now generate test functions for me!
+"""
+
+
+def interact_with_agent(prompt):
+    full_prompt = task.replace("<<function>>", prompt)
+    messages = []
+    messages.append(ChatMessage(role="user", content=full_prompt))
+    yield messages
+    for msg in stream_from_transformers_agent(agent, full_prompt):
+        messages.append(msg)
+        yield messages
+    yield messages
+
+
+with gr.Blocks(theme="soft") as demo:
+    gr.Markdown("""### Python test generator
+Write your function in the left textbox, and the agent on the right will generate tests for you!""")
+    with gr.Row():
+        with gr.Column():
+            text_input = gr.Textbox(
+                lines=1, label="Your function to test", value=function
+            )
+            submit = gr.Button("Generate tests!")
+        with gr.Column():
+            chatbot = AgentChatbot(label="Agent")
+
+    submit.click(interact_with_agent, [text_input], [chatbot])
+
+if __name__ == "__main__":
+    demo.launch()