Update app.py

app.py

@@ -1,42 +1,87 @@
-# app.py
 
-# ------------------------------------------------------------------------------
-# Import necessary parts of our AI framework.
-# CodeAgent helps us build our helper agent.
-# HfApiModel sets up the model (the "brain") that processes text.
-# The @tool decorator marks functions as "tools" that our agent can use.
+# Import the parts of the AI framework we need.
+# - CodeAgent: Helps build our agent (the digital helper).
+# - HfApiModel: Sets up the model (the "brain") that processes text.
+# - @tool: Marks functions as "tools" our agent can use.
 from smolagents import CodeAgent, HfApiModel, tool
 
 # ------------------------------------------------------------------------------
-# Import YAML to load additional instructions from a file.
+# Import YAML to load extra instructions from a file.
 import yaml
 
 # ------------------------------------------------------------------------------
-# Import our helper tool for preparing the final answer and the user interface.
-# FinalAnswerTool packages the final answer to show to the user.
-# GradioUI creates a simple webpage for user interaction.
+# Import our helper modules.
+# - FinalAnswerTool: Packages the final answer for the user.
+# - GradioUI: Creates a simple webpage so users can interact with our agent.
 from tools.final_answer import FinalAnswerTool
 from Gradio_UI import GradioUI
 
 # ------------------------------------------------------------------------------
-# Set up our AI model (the "brain" of our agent).
-# The model processes text prompts and generates responses.
+# Set up our AI model.
+# The model processes text and returns answers.
 model = HfApiModel(
-    max_tokens=2096,  # Maximum length of the generated answer.
-    temperature=0.5,  # Controls how creative or focused the response is.
-    # We use an alternative model endpoint if the primary model is busy.
+    max_tokens=2096,      # Maximum length of the answer.
+    temperature=0.5,      # How creative or focused the answer is.
+    # Use this endpoint as our model's address.
     model_id='https://pflgm2locj2t89co.us-east-1.aws.endpoints.huggingface.cloud',
-    # (To revert to the original model, use: model_id='Qwen/Qwen2.5-Coder-32B-Instruct')
+    # (To use the original model instead, change the model_id to 'Qwen/Qwen2.5-Coder-32B-Instruct')
     custom_role_conversions=None
 )
 
 # ------------------------------------------------------------------------------
 # Define the simplify_text tool.
-# This tool takes technical text and instructs the LLM to explain it in plain language.
-# It tells the model to break down complex ideas into simple sentences and explain technical terms in simple words.
+# This tool takes technical text and asks the model to convert it into plain language.
+# The prompt instructs the model to break down complex ideas into short sentences and to define any technical terms in simple words.
 @tool
 def simplify_text(text: str) -> str:
     """
     Converts technical text into plain, everyday language.
-    It explains any technical terms (by providing a simple definition in parentheses)
-    and breaks down complex ideas into short, clear senten
+    It explains technical terms using simple definitions (in parentheses)
+    and breaks complex ideas into short, clear sentences.
+
+    Args:
+        text: A technical sentence or paragraph.
+
+    Returns:
+        A simplified explanation of the text.
+    """
+    # Build a detailed prompt for the model:
+    prompt = (
+        "Please convert the following technical text into plain, everyday language as if you were talking to someone with little technical knowledge. "
+        "Break down complex ideas into simple, short sentences. If you need to use any technical terms, provide a brief definition in parentheses right after the term. "
+        "Do not use confusing jargon; instead, use simple words. \n\n"
+        f"Technical text:\n{text}\n\n"
+        "Simplified explanation:"
+    )
+    # Call the model with our prompt and get its response.
+    response = model(prompt)
+    return response
+
+# ------------------------------------------------------------------------------
+# Load additional instructions from the prompts.yaml file.
+# This file contains extra guidance for how the model should behave.
+with open("prompts.yaml", 'r') as stream:
+    prompt_templates = yaml.safe_load(stream)
+
+# ------------------------------------------------------------------------------
+# Create our AI agent by combining the model and our tools.
+# Our agent uses:
+#   - FinalAnswerTool to package the final answer.
+#   - simplify_text to convert technical text into plain language.
+agent = CodeAgent(
+    model=model,
+    tools=[
+        FinalAnswerTool(),
+        simplify_text
+    ],
+    max_steps=6,           # Limit the number of steps in reasoning.
+    verbosity_level=1,     # Keep internal debug details minimal.
+    prompt_templates=prompt_templates
+)
+
+# ------------------------------------------------------------------------------
+# Launch the interactive user interface.
+# GradioUI creates a webpage so users can type in technical text and see the simplified version.
+# The launch command includes share=True so the app remains active with a public URL.
+if __name__ == "__main__":
+    GradioUI(agent).launch(server_name="0.0.0.0", server_port=7860, share=True)