Update app.py

app.py

@@ -1,64 +1,79 @@
+# Python's OS interface for accessing environment variables
+import os
+# Intropesction utilities, you can auto-wrap it as a tool later.
+import inspect
+# HTTP client, Make REST calls for endpoints
+import requests
+# Parses CSV/Excel files
+import pandas as pd 
+# Gradio - Provides the web format front-end you see in the Space-text boxes, logs, "Run Agent" button etc.
 import gradio as gr
-from huggingface_hub import InferenceClient
+# smolagent - minimalist agent framework for LLMs with tools
+# CodeAgent - Orchestrate ReAct loop, logs each step
+# Tool - a base class and a decorator (@tool)
+# InferenceClientModel - Wrapper for HF's Serverless Inference API so you dont need to stand up your own TGI/LLM endpoint
+from smolagents import CodeAgent, DuckDuckGoSearchTool, Tool, InferenceClientModel
+# Programmatic huggingface-cli login, so the app can: pull private models, call paid-tier inference, push artefacts
+from huggingface_hub import login
+# Quick helper to pull LangChain's built-in tools so you can blend them with smolagent tools if you wish.
+from langchain.agents import load_tools
 
-"""
-For more information on `huggingface_hub` Inference API support, please check the docs: https://huggingface.co/docs/huggingface_hub/v0.22.2/en/guides/inference
-"""
-client = InferenceClient("HuggingFaceH4/zephyr-7b-beta")
 
+# Configuration constant
+# Unit-4 scoring micro-services where your agent submits answers and receivess a JSON score.
+# --- Constants
+DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-def respond(
-    message,
-    history: list[tuple[str, str]],
-    system_message,
-    max_tokens,
-    temperature,
-    top_p,
-):
-    messages = [{"role": "system", "content": system_message}]
+# --- Basic Agent Definition ---
+# ---- THIS IS WHERE YOU CAN BUILD WHAT YOU WANT ----
+class BasicAgent:
+    def __init__(self):
+        # Pull a HF access token from the Space's secrets or your local shell. You can download private models, call paid-tier Inference endpoints, push artefacts
+        hf_token = os.getenv("HUGGINGFACE_HUB_TOKEN") or os.getenv("HF_TOKEN")
+        # IF IT WORKS LOGIN INTO HF HUB VIA THIS TOKEN
+        if hf_token:
+            login(token=hf_token)
+        else:
+            try:
+                login()
+            except Exception as e:
+                raise Exception(
+                    # helpful, course-style message
+                    "Authentication failed. Please enter:\n"
+                    "1. Run 'huggingface-cli login' in your terminal, or\n"
+                    "2. Set HUGGINGFACE_HUB_TOKEN environment variable with your token, or\n"
+                    "3. Get a token from https://huggingface.co/settings/tokens"
+                ) from e
+    
+    # Warps the servesless inference endpoint for the chosen model
+    # Initialize the model
+    # InferenceClientModel handles throttling, batching, and streaming under the hood
+    self.model = InferenceClientModel("Qwen/Qwen2.5-Code-32B-Instruct")
+    
+    # Add a first tool
+    # Initialize the search tool
+    # DuckDuckGoSearchTool - Gives the agent web-search super-powers it can pull fresh facts during its reasoning loop.
+    self.search_tool = DuckDuckGoSearchTool()
 
-    for val in history:
-        if val[0]:
-            messages.append({"role": "user", "content": val[0]})
-        if val[1]:
-            messages.append({"role": "assistant", "content": val[1]})
+    # smolagents's flagship class - 
+    # Code Agent follows a ReAct-style loop, literally write Python code, executes it in a sandbox, inspects the result, then decides its next step
+    self.agent = CodeAgent(
+        model=self.model,
+        tools=[self.search_tool],
+        # drops in a small standard library (Python REPL, JSON loader etc.) so you can solve many tasks without defining anything else.
+        add_base_tools=True # - python_repl, browser, math etc.
+    )
 
-    messages.append({"role": "user", "content": message})
-
-    response = ""
-
-    for message in client.chat_completion(
-        messages,
-        max_tokens=max_tokens,
-        stream=True,
-        temperature=temperature,
-        top_p=top_p,
-    ):
-        token = message.choices[0].delta.content
-
-        response += token
-        yield response
-
-
-"""
-For information on how to customize the ChatInterface, peruse the gradio docs: https://www.gradio.app/docs/chatinterface
-"""
-demo = gr.ChatInterface(
-    respond,
-    additional_inputs=[
-        gr.Textbox(value="You are a friendly Chatbot.", label="System message"),
-        gr.Slider(minimum=1, maximum=2048, value=512, step=1, label="Max new tokens"),
-        gr.Slider(minimum=0.1, maximum=4.0, value=0.7, step=0.1, label="Temperature"),
-        gr.Slider(
-            minimum=0.1,
-            maximum=1.0,
-            value=0.95,
-            step=0.05,
-            label="Top-p (nucleus sampling)",
-        ),
-    ],
-)
-
-
-if __name__ == "__main__":
-    demo.launch()
+    # Send a single "bootstrap" run whose only job is lock in behaviour rules:
+    self.response = self.agent.run(
+        """
+        You are a general AI assistant.
+        I will ask you a question. Report your thoughts, and finish your answer with the following template: [FINAL ANSWER].
+        YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
+        If you are asked for a number, do not use comma to write your number neither use units such as $ or percent sign unless specified otherwise. 
+        If you are asked for a string, do not use articles, neither abbreviations (e.g. for cities), and write the digits in plain text unless specified otherwise.
+        If you are asked for a comma separated list, apply the above rules depending of whether the element to be put in the list is a number or a string. 
+        You have access to the following tools:
+        Tool Name: search_tool, description:  lets you search and browse the internet for accessing the most updated information out there.
+        If you require more tools to get a correct answer, create your own tools to utilize.    
+        """)