Update app.py

app.py

@@ -1,85 +1,47 @@
+""" Basic Agent Evaluation Runner"""
 import os
+import inspect
 import gradio as gr
 import requests
-import inspect
 import pandas as pd
-from agent import SmolAgent
-import json
+from langchain_core.messages import HumanMessage
+from agent import build_graph
+
 
+
+# (Keep Constants as is)
 # --- Constants ---
 DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
 
-USE_CACHE = False  # Set to False to disable caching
-CACHE_FILE = "cache/answers_cache.json"
-QUESTIONS_CACHE_FILE = "cache/questions_cache.json"
+# --- Basic Agent Definition ---
+# ----- THIS IS WERE YOU CAN BUILD WHAT YOU WANT ------
 
 
-def load_cache(filename):
-    if not USE_CACHE:
-        print(f"Caching is disabled. Not loading from {filename}.")
-        return None
-    else:
-        if os.path.exists(filename):
-            try:
-                with open(filename, "r") as f:
-                    return json.load(f)
-            except Exception as e:
-                print(f"Failed to load cache from {filename}: {e}")
-        return None
+class BasicAgent:
+    """A langgraph agent."""
+    def __init__(self):
+        print("BasicAgent initialized.")
+        self.graph = build_graph()
 
-
-def save_cache(filename, data):
-    if not USE_CACHE:
-        print(f"Caching is disabled. Not loading from {filename}.")
-        return None
-    else:
-        try:
-            with open(filename, "w") as f:
-                json.dump(data, f)
-        except Exception as e:
-            print(f"Failed to save cache to {filename}: {e}")
-
-
-def download_file(task_id):
-    """
-    Downloads a file for the given task_id from the /files/{task_id} endpoint,
-    extracts the filename from the Content-Disposition header, and saves it to disk.
-    Returns the local file path if successful, else None.
-    """
-    api_url = DEFAULT_API_URL
-    file_url = f"{api_url}/files/{task_id}"
-    try:
-        response = requests.get(file_url, stream=True, timeout=30)
-        response.raise_for_status()
-        content_disp = response.headers.get("content-disposition", "")
-        filename = None
-        if "filename=" in content_disp:
-            filename = content_disp.split("filename=")[-1].strip('"; ')
-        if not filename:
-            filename = f"{task_id}.txt"
-        os.makedirs("cache", exist_ok=True)
-        file_path = os.path.join("cache", filename)
-        with open(file_path, "wb") as f:
-            for chunk in response.iter_content(chunk_size=8192):
-                if chunk:
-                    f.write(chunk)
-        print(f"Downloaded file for task {task_id} to {file_path}")
-        return file_path
-    except Exception as e:
-        print(f"Failed to download file for task {task_id}: {e}")
-        return None
+    def __call__(self, question: str) -> str:
+        print(f"Agent received question (first 50 chars): {question[:50]}...")
+        # Wrap the question in a HumanMessage from langchain_core
+        messages = [HumanMessage(content=question)]
+        messages = self.graph.invoke({"messages": messages})
+        answer = messages['messages'][-1].content
+        return answer[14:]
 
 
-def run_and_submit_all(profile: gr.OAuthProfile | None):
+def run_and_submit_all( profile: gr.OAuthProfile | None):
     """
     Fetches all questions, runs the BasicAgent on them, submits all answers,
     and displays the results.
     """
     # --- Determine HF Space Runtime URL and Repo URL ---
-    space_id = os.getenv("SPACE_ID")  # Get the SPACE_ID for sending link to the code
+    space_id = os.getenv("SPACE_ID") # Get the SPACE_ID for sending link to the code
 
     if profile:
-        username = f"{profile.username}"
+        username= f"{profile.username}"
         print(f"User logged in: {username}")
     else:
         print("User not logged in.")
@@ -91,7 +53,7 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
     # 1. Instantiate Agent ( modify this part to create your agent)
     try:
-        agent = SmolAgent()
+        agent = BasicAgent()
     except Exception as e:
         print(f"Error instantiating agent: {e}")
         return f"Error initializing agent: {e}", None
@@ -99,36 +61,30 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
     agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
     print(agent_code)
 
-    # 2. Fetch Questions (with caching)
-    questions_data = load_cache(QUESTIONS_CACHE_FILE)
-    if questions_data:
-        print(f"Loaded {len(questions_data)} questions from cache.")
-    else:
-        print(f"Fetching questions from: {questions_url}")
-        try:
-            response = requests.get(questions_url, timeout=15)
-            response.raise_for_status()
-            questions_data = response.json()
-            if not questions_data:
-                print("Fetched questions list is empty.")
-                return "Fetched questions list is empty or invalid format.", None
-            print(f"Fetched {len(questions_data)} questions.")
-            save_cache(QUESTIONS_CACHE_FILE, questions_data)
-        except requests.exceptions.RequestException as e:
-            print(f"Error fetching questions: {e}")
-            return f"Error fetching questions: {e}", None
-        except requests.exceptions.JSONDecodeError as e:
-            print(f"Error decoding JSON response from questions endpoint: {e}")
-            print(f"Response text: {response.text[:500]}")
-            return f"Error decoding server response for questions: {e}", None
-        except Exception as e:
-            print(f"An unexpected error occurred fetching questions: {e}")
-            return f"An unexpected error occurred fetching questions: {e}", None
+    # 2. Fetch Questions
+    print(f"Fetching questions from: {questions_url}")
+    try:
+        response = requests.get(questions_url, timeout=15)
+        response.raise_for_status()
+        questions_data = response.json()
+        if not questions_data:
+             print("Fetched questions list is empty.")
+             return "Fetched questions list is empty or invalid format.", None
+        print(f"Fetched {len(questions_data)} questions.")
+    except requests.exceptions.RequestException as e:
+        print(f"Error fetching questions: {e}")
+        return f"Error fetching questions: {e}", None
+    except requests.exceptions.JSONDecodeError as e:
+         print(f"Error decoding JSON response from questions endpoint: {e}")
+         print(f"Response text: {response.text[:500]}")
+         return f"Error decoding server response for questions: {e}", None
+    except Exception as e:
+        print(f"An unexpected error occurred fetching questions: {e}")
+        return f"An unexpected error occurred fetching questions: {e}", None
 
-    # 3. Run your Agent (with answer caching)
+    # 3. Run your Agent
     results_log = []
     answers_payload = []
-    answers_cache = load_cache(CACHE_FILE) or {}
     print(f"Running agent on {len(questions_data)} questions...")
     for item in questions_data:
         task_id = item.get("task_id")
@@ -136,50 +92,24 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
         if not task_id or question_text is None:
             print(f"Skipping item with missing task_id or question: {item}")
             continue
-        file_name = item.get("file_name")
-
-        # Check if answer is cached
-        if task_id in answers_cache:
-            submitted_answer = answers_cache[task_id]
-            print(f"Loaded cached answer for task {task_id}")
-        else:
-            try:
-                if len(file_name) > 0:
-                    file = download_file(task_id)
-                    print(f"File for task {file_name} downloaded: {file}")
-                    submitted_answer = agent.run(question_text, file_path=file)
-                else:
-                    submitted_answer = agent.run(question_text)
-                answers_cache[task_id] = submitted_answer
-                save_cache(CACHE_FILE, answers_cache)
-            except Exception as e:
-                print(f"Error running agent on task {task_id}: {e}")
-                submitted_answer = f"AGENT ERROR: {e}"
-        answers_payload.append(
-            {"task_id": task_id, "submitted_answer": submitted_answer}
-        )
-        results_log.append(
-            {
-                "Task ID": task_id,
-                "Question": question_text,
-                "Submitted Answer": submitted_answer,
-            }
-        )
+        try:
+            submitted_answer = agent(question_text)
+            answers_payload.append({"task_id": task_id, "submitted_answer": submitted_answer})
+            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": submitted_answer})
+        except Exception as e:
+             print(f"Error running agent on task {task_id}: {e}")
+             results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"AGENT ERROR: {e}"})
 
     if not answers_payload:
         print("Agent did not produce any answers to submit.")
         return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
 
-    # 4. Prepare Submission
-    submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code,
-        "answers": answers_payload,
-    }
+    # 4. Prepare Submission 
+    submission_data = {"username": username.strip(), "agent_code": agent_code, "answers": answers_payload}
     status_update = f"Agent finished. Submitting {len(answers_payload)} answers for user '{username}'..."
     print(status_update)
 
-    # # 5. Submit
+    # 5. Submit
     print(f"Submitting {len(answers_payload)} answers to: {submit_url}")
     try:
         response = requests.post(submit_url, json=submission_data, timeout=60)
@@ -193,7 +123,6 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
             f"Message: {result_data.get('message', 'No message received.')}"
         )
         print("Submission successful.")
-        print(final_status)
         results_df = pd.DataFrame(results_log)
         return final_status, results_df
     except requests.exceptions.HTTPError as e:
@@ -226,14 +155,9 @@ def run_and_submit_all(profile: gr.OAuthProfile | None):
 
 # --- Build Gradio Interface using Blocks ---
 with gr.Blocks() as demo:
-    gr.Markdown("# Robin's Basic Agent Evaluation Space")
+    gr.Markdown("# Basic Agent Evaluation Runner")
     gr.Markdown(
         """
-        ### Description
-        My submission for the final assigment of the huggingface agent course.
-        I chose to use the smolagents library to create a simple agent and stay away from the bigger multimodel models. 
-        By providing specifc tools to handle image and audio files.
-        ### Original Instructions
         **Instructions:**
         1.  Please clone this space, then modify the code to define your agent's logic, the tools, the necessary packages, etc ...
         2.  Log in to your Hugging Face account using the button below. This uses your HF username for submission.
@@ -249,19 +173,20 @@ with gr.Blocks() as demo:
 
     run_button = gr.Button("Run Evaluation & Submit All Answers")
 
-    status_output = gr.Textbox(
-        label="Run Status / Submission Result", lines=5, interactive=False
-    )
+    status_output = gr.Textbox(label="Run Status / Submission Result", lines=5, interactive=False)
     # Removed max_rows=10 from DataFrame constructor
     results_table = gr.DataFrame(label="Questions and Agent Answers", wrap=True)
 
-    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+    run_button.click(
+        fn=run_and_submit_all,
+        outputs=[status_output, results_table]
+    )
 
 if __name__ == "__main__":
-    print("\n" + "-" * 30 + " App Starting " + "-" * 30)
+    print("\n" + "-"*30 + " App Starting " + "-"*30)
     # Check for SPACE_HOST and SPACE_ID at startup for information
     space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")  # Get SPACE_ID at startup
+    space_id_startup = os.getenv("SPACE_ID") # Get SPACE_ID at startup
 
     if space_host_startup:
         print(f"✅ SPACE_HOST found: {space_host_startup}")
@@ -269,18 +194,14 @@ if __name__ == "__main__":
     else:
         print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
 
-    if space_id_startup:  # Print repo URLs if SPACE_ID is found
+    if space_id_startup: # Print repo URLs if SPACE_ID is found
         print(f"✅ SPACE_ID found: {space_id_startup}")
         print(f"   Repo URL: https://huggingface.co/spaces/{space_id_startup}")
-        print(
-            f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main"
-        )
+        print(f"   Repo Tree URL: https://huggingface.co/spaces/{space_id_startup}/tree/main")
     else:
-        print(
-            "ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined."
-        )
+        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
 
-    print("-" * (60 + len(" App Starting ")) + "\n")
+    print("-"*(60 + len(" App Starting ")) + "\n")
 
     print("Launching Gradio Interface for Basic Agent Evaluation...")
     demo.launch(debug=True, share=False)