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fix: last preparations for meetup/devfest
Browse files- README.md +2 -2
- agents/__init__.py +1 -1
- agents/assistant_agent.py +9 -7
- agents/assistant_tools.py +48 -12
- app.py +2 -2
- pyproject.toml +1 -1
README.md
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@@ -1,5 +1,5 @@
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---
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title:
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emoji: 🕵🏻♂️
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colorFrom: indigo
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colorTo: indigo
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@@ -11,7 +11,7 @@ hf_oauth: true
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hf_oauth_expiration_minutes: 480
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---
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# 🕵🏻♂️
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LangGraph-powered agent with web search capabilities and tool integration.
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---
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title: GAÏA Agent LangGraph
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emoji: 🕵🏻♂️
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colorFrom: indigo
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colorTo: indigo
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hf_oauth_expiration_minutes: 480
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---
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# 🕵🏻♂️ GAÏA Agent
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LangGraph-powered agent with web search capabilities and tool integration.
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agents/__init__.py
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"""Agents package for the
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from agents.assistant_agent import AwesomeAgent
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"""Agents package for the GAÏA Agent."""
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from agents.assistant_agent import AwesomeAgent
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agents/assistant_agent.py
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@@ -88,7 +88,7 @@ WEB & SEARCH:
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CALCULATIONS:
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- calculator: Basic arithmetic (+, -, *, /)
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- advanced_math: Advanced math functions (sqrt, log, trig)
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- python_repl: Execute Python code
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TEXT PROCESSING:
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- reverse_text: Reverse text character by character
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@@ -156,8 +156,9 @@ def build_langgraph(
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file = state["input_file"]
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sys_msg = SystemMessage(
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content=f"""
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You are a LLM agent.
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-
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take time to analyse the steps to answer the question.
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# Input File
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Here is the question: {state.get(state["messages"][0].content)}
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-
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- YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
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- If the question asked for a number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. Write numbers using digits.
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- If the question asked for a string, don't use articles,
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- If the question 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.
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Here is the content to format:
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"""
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)
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CALCULATIONS:
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- calculator: Basic arithmetic (+, -, *, /)
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- advanced_math: Advanced math functions (sqrt, log, trig)
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- python_repl: Execute Python code from path to file (use carefully)
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TEXT PROCESSING:
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- reverse_text: Reverse text character by character
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file = state["input_file"]
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sys_msg = SystemMessage(
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content=f"""
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You are a LLM agent.
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You will be given a question.
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Your task it to answer the question using the tools.
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take time to analyse the steps to answer the question.
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# Input File
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Here is the question: {state.get(state["messages"][0].content)}
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Format the answer with the following rules:
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- YOUR FINAL ANSWER should be a number OR as few words as possible OR a comma separated list of numbers and/or strings.
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- If the question asked for a number, write only the number, don't use comma to write your number neither use units such as $ or percent sign unless specified otherwise. Write numbers using digits.
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- If the question asked for a string, don't use articles, no abbreviations (e.g: write "Saint" rather than "St."), and write the digits in plain text unless specified otherwise.
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- If the question 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.
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WRITE ONLY THE ANSWER, no sentence, no explanation, no context
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Here is the content to format:
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"""
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)
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agents/assistant_tools.py
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@@ -23,7 +23,6 @@ from langchain_google_genai import ChatGoogleGenerativeAI
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# ---
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from langchain_community.tools import ShellTool
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from langchain_experimental.tools import PythonREPLTool
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from langchain_community.document_loaders import AssemblyAIAudioTranscriptLoader
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from langchain_community.document_loaders.assemblyai import TranscriptFormat
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return f"Transcription error: {str(e)}"
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def build_tools():
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"""
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Initialize and return a list of built-in and custom LangChain tools.
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# Initialize built-in LangChain tools
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# SECURITY: Python REPL Tool
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# Should implement:
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# - Use RestrictedPython library to restrict dangerous operations
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# - Block dangerous built-ins: __import__, eval, exec, open, file operations
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# - Block system calls: os.system, subprocess, sys.exit
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# - Block network access: socket, urllib, requests
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# - Allow only safe modules: math, json, datetime, collections, etc.
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# - AST-based validation before execution to catch dangerous patterns
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python_repl = PythonREPLTool()
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-
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# SECURITY: Shell Tool
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# Should implement:
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# - Command whitelist: Only allow safe commands (ls, cat, grep, find, etc.)
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# Combine built-in tools with custom tools
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all_tools = [
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# Built-in LangChain tools
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python_repl,
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shell_tool,
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# Web search subagent (replaces individual web/search tools for isolated context)
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web_search_agent,
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# Custom tools for specialized tasks
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read_excel_file,
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get_youtube_transcript_tool,
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get_youtube_title_description,
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# ---
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from langchain_community.tools import ShellTool
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from langchain_community.document_loaders import AssemblyAIAudioTranscriptLoader
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from langchain_community.document_loaders.assemblyai import TranscriptFormat
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return f"Transcription error: {str(e)}"
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@tool
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def execute_python_file(file_path: str) -> str:
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"""
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Execute Python code from the provided file path and return its stdout/stderr output.
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"""
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import subprocess
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import sys
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if not isinstance(file_path, str) or not file_path.strip():
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return "Error: file_path must be a non-empty string."
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file_path = file_path.strip()
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if not os.path.isfile(file_path):
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return f"Error: file not found at '{file_path}'."
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if not file_path.endswith(".py"):
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return "Error: only '.py' files are supported."
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try:
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with open(file_path, "r", encoding="utf-8") as f:
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f.read()
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except Exception as e:
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return f"Error reading file: {str(e)}"
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try:
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completed = subprocess.run(
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[sys.executable, file_path],
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capture_output=True,
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text=True,
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check=False,
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)
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except Exception as e:
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return f"Execution error: {str(e)}"
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stdout_content = (completed.stdout or "").strip()
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stderr_content = (completed.stderr or "").strip()
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if stdout_content and stderr_content:
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return f"STDOUT:\n{stdout_content}\n\nSTDERR:\n{stderr_content}"
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if stdout_content:
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return stdout_content
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if stderr_content:
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return f"STDERR:\n{stderr_content}"
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return "Execution completed with no output."
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def build_tools():
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"""
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Initialize and return a list of built-in and custom LangChain tools.
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# Initialize built-in LangChain tools
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# SECURITY: Shell Tool
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# Should implement:
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# - Command whitelist: Only allow safe commands (ls, cat, grep, find, etc.)
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# Combine built-in tools with custom tools
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all_tools = [
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# Built-in LangChain tools
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shell_tool,
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# Web search subagent (replaces individual web/search tools for isolated context)
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web_search_agent,
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# Custom tools for specialized tasks
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execute_python_file,
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read_excel_file,
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get_youtube_transcript_tool,
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get_youtube_title_description,
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app.py
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# TODO: REMOVE THIS PART - AVOID ASKING 50 QUESTIONS
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# questions_data = questions_data[:5] # the top 5
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# questions_data = [questions_data[18]] # the 19th question
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keep = {1, 3, 7,
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questions_data[:] = [x for i, x in enumerate(questions_data, start=1) if i in keep]
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############################################################################################################
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f"User: {result_data.get('username')}\n"
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# f"Overall Score: {result_data.get('score', 'N/A')}% "
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f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
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f"Message: {result_data.get('message', 'No message received.')}"
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)
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print("Submission successful.")
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results_df = pd.DataFrame(results_log)
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# TODO: REMOVE THIS PART - AVOID ASKING 50 QUESTIONS
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# questions_data = questions_data[:5] # the top 5
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# questions_data = [questions_data[18]] # the 19th question
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keep = {1, 3, 7, 12, 16}
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questions_data[:] = [x for i, x in enumerate(questions_data, start=1) if i in keep]
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############################################################################################################
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f"User: {result_data.get('username')}\n"
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# f"Overall Score: {result_data.get('score', 'N/A')}% "
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f"({result_data.get('correct_count', '?')}/{result_data.get('total_attempted', '?')} correct)\n"
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# f"Message: {result_data.get('message', 'No message received.')}"
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)
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print("Submission successful.")
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results_df = pd.DataFrame(results_log)
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pyproject.toml
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[project]
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name = "final-assignment-agents-course"
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version = "0.1.0"
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description = "
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readme = "README.md"
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requires-python = "==3.10.*"
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dependencies = [
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[project]
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name = "final-assignment-agents-course"
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version = "0.1.0"
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description = "GAÏA Agent LangGraphHugging Face agents course"
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readme = "README.md"
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requires-python = "==3.10.*"
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dependencies = [
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