ajout de quelques agents / fonctions

agent.py

@@ -13,6 +13,7 @@ from pydantic import BaseModel
 from typing import List, Dict
 import pandas as pd
 
+from fonctions import clean_response, response_from_agent
 class ToolInput(BaseModel):
     data: List[Dict]
     question: str
@@ -132,11 +133,7 @@ def divide(a: float, b: float):
     return a / b
 
 
-@tool
-def open_xlsx_doc(path: str) -> pd.DataFrame:
-    """ Open a pandas DataFrame from a xlsx file path"""
-    df = pd.read_excel(path)
-    return df.to_dict(orient="records")
+
 @tool
 def create_agent_and_answer(input: ToolInput) -> str:
     """ From a dataframe, can anwser any question
@@ -146,8 +143,8 @@ def create_agent_and_answer(input: ToolInput) -> str:
     """
     df = pd.DataFrame(input.data)
     question = input.question
-    agent_excel = create_pandas_dataframe_agent(llm_4o, df, verbose=True, allow_dangerous_code=True)
-    text = agent_excel.run(question)
+    agent_excel_inter = create_pandas_dataframe_agent(llm_4o, df, verbose=True, allow_dangerous_code=True)
+    text = agent_excel_inter.run(question)
 
     return text
 
@@ -202,15 +199,15 @@ math_agent = create_react_agent(
 
     name="math_agent")
 
-agent_excel = create_react_agent(
+agent_excel = create_pandas_dataframe_agent(
     model=llm_4o,
 
-    tools=[open_xlsx_doc, create_agent_and_answer, ],
+    tools=[create_agent_and_answer],
     prompt=(
         "You are an agent specialized with Excel files.\n\n"
         "INSTRUCTIONS:\n"
         "- Assist ONLY when an Excel file is mentionned \n"
-        "- First, when you receive an Excel file path, you have to use the 'open_xlsx_doc' tool. Then you use the 'create_agent_and_answer'\n"
+        "- You will receive the path of a dataframe. '\n"
         "- The output of the first tool  is a part of the input of the second tool\n"
 
         "- Once you have got a response from the 'create_agent_and_answer_tool', transmit it to your supervisor \n"
@@ -253,20 +250,4 @@ supervisor = create_supervisor(
     add_handoff_back_messages=True,
     output_mode="full_history",
 ).compile()
-def clean_response(response):
-    match = re.search(r'FINAL ANSWER:\s*(.+)', response['supervisor']['messages'][-1].content)
-    answer = match.group(1).strip() if match else None
-    if answer is None :
-        answer = "pas de réponse"
-    return answer
-def response_from_agent(question):
-
-    for chunk in supervisor.stream(
-            {"messages": [{"role": "user", "content": question}]}
-    ):
-
-        response = chunk
-
 
-    response = clean_response(response)
-    return response

app.py

@@ -78,7 +78,7 @@ def run_and_submit_all( profile: gr.OAuthProfile | None):
             print(f'la question est {question_text}')
             if filename :
                 print('fichier attaché : ', filename)
-            submitted_answer = response_from_agent(question_text + 'The file_name (path) is : ' + filename)
+            submitted_answer = response_from_agent(supervisor,question_text + 'The file_name (path) is : ' + filename)
             print('submitted_answer:', submitted_answer)
             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})

apt.txt

@@ -0,0 +1 @@
+ffmpeg

fonctions.py

@@ -0,0 +1,49 @@
+from io import BytesIO
+from pydub import AudioSegment
+import requests
+import re
+import pandas as pd
+
+def clean_response(response):
+    match = re.search(r'FINAL ANSWER:\s*(.+)', response['supervisor']['messages'][-1].content)
+    answer = match.group(1).strip() if match else None
+    if answer is None :
+        answer = "pas de réponse"
+    return answer
+def response_from_agent(supervisor, question):
+
+    for chunk in supervisor.stream(
+            {"messages": [{"role": "user", "content": question}]}
+    ):
+
+        response = chunk
+
+
+    response = clean_response(response)
+    return response
+def load_data(question):
+    task_id = question['task_id']
+    file_name = question['file_name']
+
+    if file_name == "":
+        return 'There is no attached file'
+
+    files_response = requests.get(f"https://agents-course-unit4-scoring.hf.space/files/{task_id}")
+    if files_response.status_code == 404:
+        return 'Le lien ne fonctionne pas'
+    if file_name.endswith('.xlsx'):
+        excel_data = BytesIO(files_response.content)
+        df = pd.read_excel(excel_data, engine='openpyxl')
+        return df
+
+    elif file_name.endswith('.png'):
+        filename = f"fichier_{task_id}.png"
+        with open(filename, "wb") as f:
+            f.write(files_response.content)
+        return filename
+
+    elif file_name.endswith('.mp3'):
+        audio_bytes = BytesIO(files_response.content)
+        audio = AudioSegment.from_file(audio_bytes, format="mp3")
+
+        return audio

requirements.txt

@@ -10,4 +10,7 @@ arxiv
 pymupdf
 langchain-experimental
 tabulate
-pandas
+pandas
+pydub
+torch
+numpy