Update agent.py

agent.py

@@ -1,130 +1,43 @@
-import os
-import gradio as gr
-import requests
-import pandas as pd
-from agent import GaiaAgent
-
-DEFAULT_API_URL = "https://agents-course-unit4-scoring.hf.space"
-
-def run_and_submit_all(profile: gr.OAuthProfile | None):
-    space_id = os.getenv("SPACE_ID")
-
-    if profile:
-        username = f"{profile.username}"
-        print(f"User logged in: {username}")
-    else:
-        print("User not logged in.")
-        return "Please Login to Hugging Face with the button.", None
-
-    api_url = DEFAULT_API_URL
-    questions_url = f"{api_url}/questions"
-    submit_url = f"{api_url}/submit"
-
-    try:
-        agent = GaiaAgent()
-    except Exception as e:
-        return f"Error initializing agent: {e}", None
-
-    agent_code = f"https://huggingface.co/spaces/{space_id}/tree/main"
-
-    try:
-        response = requests.get(questions_url, timeout=15)
-        response.raise_for_status()
-        questions_data = response.json()
-    except Exception as e:
-        return f"Error fetching questions: {e}", None
-
-    results_log = []
-    answers_payload = []
-
-    print("\n--- STARTING AGENT RUN ---")
-    for item in questions_data:
-        task_id = item.get("task_id")
-        question_text = item.get("question")
-        if not task_id or question_text is None:
-            continue
-        try:
-            final_answer, trace = agent(question_text)
-
-            print("\n--- QUESTION ---")
-            print(f"Task ID: {task_id}")
-            print(f"Question: {question_text}")
-            print("\n--- REASONING TRACE ---")
-            print(trace)
-            print("\n--- FINAL ANSWER (SUBMITTED) ---")
-            print(final_answer)
-
-            answers_payload.append({
-                "task_id": task_id,
-                "submitted_answer": final_answer,
-                "reasoning_trace": trace
-            })
-            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": final_answer})
-        except Exception as e:
-            results_log.append({"Task ID": task_id, "Question": question_text, "Submitted Answer": f"ERROR: {e}"})
-
-    if not answers_payload:
-        return "Agent did not produce any answers to submit.", pd.DataFrame(results_log)
-
-    submission_data = {
-        "username": username.strip(),
-        "agent_code": agent_code,
-        "answers": answers_payload
-    }
-
-    try:
-        response = requests.post(submit_url, json=submission_data, timeout=60)
-        response.raise_for_status()
-        result_data = response.json()
-        final_status = (
-            f"Submission Successful!\n"
-            f"User: {result_data.get('username')}\n"
-            f"Overall Score: {result_data.get('score', 'N/A')}% "
-            f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
-            f"Message: {result_data.get('message', 'No message received.')}"
+from transformers import pipeline
+from tools.asr_tool import transcribe_audio
+from tools.excel_tool import analyze_excel
+from tools.search_tool import search_duckduckgo
+import mimetypes
+
+
+class GaiaAgent:
+    def __init__(self):
+        print("Loading model...")
+        self.model = pipeline(
+            "text2text-generation",
+            model="MBZUAI/LaMini-Flan-T5-783M",
+            tokenizer="MBZUAI/LaMini-Flan-T5-783M"
         )
-        results_df = pd.DataFrame(results_log)
-        return final_status, results_df
-    except Exception as e:
-        return f"Submission Failed: {e}", pd.DataFrame(results_log)
-
-
-with gr.Blocks() as demo:
-    gr.Markdown("# GAIA Agent Submission Interface")
-    gr.Markdown("""
-        Logga in och kör agenten.\n
-        Du behöver INTE en OpenAI API-nyckel längre. Agenten kör en lokal modell.
-    """)
-    gr.LoginButton()
-
-    run_button = gr.Button("Run Evaluation & Submit All Answers")
-    status_output = gr.Textbox(label="Submission Result")
-    results_table = gr.DataFrame(label="Answers")
+        print("Model loaded.")
 
-    run_button.click(fn=run_and_submit_all, outputs=[status_output, results_table])
+    def __call__(self, query):
+        trace = ""
+        final_answer = ""
 
-if __name__ == "__main__":
-    print("\n" + "-"*30 + " App Starting " + "-"*30)
-    space_host_startup = os.getenv("SPACE_HOST")
-    space_id_startup = os.getenv("SPACE_ID")
+        # Försök identifiera om det är en filreferens
+        if isinstance(query, str) and (query.endswith(".mp3") or query.endswith(".wav")):
+            trace = "Detected audio file. Transcribing..."
+            final_answer = transcribe_audio(query)
 
-    if space_host_startup:
-        print(f"✅ SPACE_HOST found: {space_host_startup}")
-        print(f"   Runtime URL should be: https://{space_host_startup}.hf.space")
-    else:
-        print("ℹ️  SPACE_HOST environment variable not found (running locally?).")
+        elif isinstance(query, str) and (query.endswith(".xls") or query.endswith(".xlsx")):
+            trace = "Detected Excel file. Analyzing..."
+            final_answer = analyze_excel(query)
 
-    if space_id_startup:
-        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")
-    else:
-        print("ℹ️  SPACE_ID environment variable not found (running locally?). Repo URL cannot be determined.")
+        elif "http" in query:
+            trace = "Detected URL or web reference. Performing search..."
+            final_answer = search_duckduckgo(query)
 
-    print("-"*(60 + len(" App Starting ")) + "\n")
+        else:
+            trace = "General question. Using local model..."
+            output = self.model(query, max_new_tokens=128)
+            final_answer = output[0]["generated_text"].strip()
 
-    print("Launching Gradio Interface for Basic Agent Evaluation...")
-    demo.launch(debug=True, share=False)
+        return final_answer, trace