Agent Improvment

agents/advanced_validation_agent.py

@@ -2,16 +2,12 @@ import os
 import logging
 import json
 from typing import List, Dict, Optional, Union
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 # Assuming research_agent might be needed for handoff, but not directly imported
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 

agents/agent_types.py

@@ -1,32 +0,0 @@
-# agent_types.py
-from enum import Enum
-from datetime import datetime
-from typing import Any, Dict
-from pydantic import BaseModel
-import uuid
-
-class AgentRole(str, Enum):
-    USER = "user"
-    PLANNER = "planner"
-    ROUTER = "router"
-    # tu complèteras plus tard (research, reasoning, …)
-
-class AgentMessage(BaseModel):
-    id: str
-    role: AgentRole
-    parent_id: str | None
-    task: str               # phrase courte qui décrit l’action
-    payload: Dict[str, Any] # données brutes (texte, url, …)
-    metadata: Dict[str, Any] = {}
-    status: str = "created" # created / done / error …
-    timestamp: str = datetime.utcnow().isoformat()
-
-def new_message(role: AgentRole, task: str, payload: Dict[str, Any] | str = "",
-                parent_id: str | None = None) -> AgentMessage:
-    return AgentMessage(
-        id=str(uuid.uuid4()),
-        role=role,
-        parent_id=parent_id,
-        task=task,
-        payload=payload if isinstance(payload, dict) else {"text": payload},
-    )

agents/code_agent.py

@@ -1,6 +1,5 @@
 import os
 import logging
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import CodeActAgent, ReActAgent
 from llama_index.core.tools import FunctionTool
@@ -8,9 +7,6 @@ from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.llms.openai import OpenAI
 from llama_index.tools.code_interpreter import CodeInterpreterToolSpec
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 
@@ -47,12 +43,10 @@ def generate_python_code(prompt: str) -> str:
     
     # Configuration for code generation LLM
     gen_llm_model = os.getenv("CODE_GEN_LLM_MODEL", "o4-mini")
-    gen_api_key_env = os.getenv("CODE_GEN_API_KEY_ENV", "ALPAFLOW_OPENAI_API_KEY")
-    gen_api_key = os.getenv(gen_api_key_env)
+    gen_api_key = os.getenv("OPENAI_API_KEY")
 
     if not gen_api_key:
-        logger.error(f"{gen_api_key_env} not found in environment variables for code generation LLM.")
-        raise ValueError(f"{gen_api_key_env} must be set for code generation")
+        raise ValueError("OPENAI_API_KEY environment variable is not set.")
 
     # Load the prompt template
     default_gen_prompt_template = ("You are a helpful assistant that writes Python code. "
@@ -68,7 +62,10 @@ def generate_python_code(prompt: str) -> str:
     try:
         llm = OpenAI(
             model=gen_llm_model,
-            api_key=gen_api_key
+            api_key=gen_api_key,
+            reasoning_effort="high",
+            temperature=0.25,
+            max_tokens=16384
         )
         logger.info(f"Using code generation LLM: {gen_llm_model}")
         generated_code = llm.complete(input_prompt)

agents/figure_interpretation_agent.py

@@ -1,16 +1,11 @@
 import os
 import logging
-from typing import List, Dict, Optional, Union
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.schema import ImageDocument
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 

agents/image_analyzer_agent.py

@@ -1,13 +1,9 @@
 import os
 import logging
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import FunctionAgent
 from llama_index.llms.google_genai import GoogleGenAI
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 

agents/long_context_management_agent.py

@@ -2,7 +2,6 @@ import os
 import logging
 import json
 from typing import List, Dict, Optional, Union, Literal
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool, QueryEngineTool
@@ -12,8 +11,6 @@ from llama_index.core.node_parser import SentenceSplitter
 from llama_index.core.query_engine import RetrieverQueryEngine
 from llama_index.core.retrievers import VectorIndexRetriever
 
-# Load environment variables
-load_dotenv()
 
 # Setup logging
 logger = logging.getLogger(__name__)

agents/math_agent.py

@@ -1,14 +1,13 @@
 import os
 import logging
-from typing import List, Optional, Union, Dict
-from dotenv import load_dotenv
+from typing import List, Dict
 
 import sympy as sp
 import numpy as np
 import scipy.linalg as la
 import scipy.special as special
 from llama_index.tools.code_interpreter import CodeInterpreterToolSpec
-from scipy.integrate import odeint, quad
+from scipy.integrate import quad
 from scipy.stats import binom, norm, poisson
 import numpy.fft as fft
 
@@ -17,9 +16,6 @@ from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.tools.wolfram_alpha import WolframAlphaToolSpec
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 

agents/planner_agent.py

@@ -1,14 +1,11 @@
 import os
 import logging
 from typing import List, Dict
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 
-# Load environment variables
-load_dotenv()
 
 # Setup logging
 logger = logging.getLogger(__name__)

agents/reasoning_agent.py

@@ -1,15 +1,11 @@
 import os
 import logging
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.llms.openai import OpenAI
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 
@@ -45,7 +41,7 @@ def reasoning_tool_fn(context: str) -> str:
     
     # Configuration for the reasoning LLM (OpenAI in the original)
     reasoning_llm_model = os.getenv("REASONING_LLM_MODEL", "gpt-4o-mini") # Use gpt-4o-mini as default
-    openai_api_key = os.getenv("ALPAFLOW_OPENAI_API_KEY") # Specific key from original code
+    openai_api_key = os.getenv("OPENAI_API_KEY")
     
     if not openai_api_key:
         logger.error("ALPAFLOW_OPENAI_API_KEY not found for reasoning tool LLM.")

agents/research_agent.py

@@ -3,7 +3,6 @@ import time
 import logging
 import re # Import regex for video ID extraction
 from typing import List, Optional, Dict # Added Dict
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool
@@ -27,8 +26,6 @@ except ImportError:
     logging.warning("Selenium or Helium not installed. Browser interaction tools will be unavailable.")
     SELENIUM_AVAILABLE = False
 
-# Load environment variables
-load_dotenv()
 
 # Setup logging
 logger = logging.getLogger(__name__)

agents/role_agent.py

@@ -1,6 +1,5 @@
 import os
 import logging
-from dotenv import load_dotenv
 
 import datasets
 from llama_index.core import Document, VectorStoreIndex
@@ -14,8 +13,6 @@ from llama_index.core.postprocessor import SentenceTransformerRerank
 from llama_index.llms.google_genai import GoogleGenAI
 from llama_index.retrievers.bm25 import BM25Retriever
 
-# Load environment variables
-load_dotenv()
 
 # Setup logging
 logger = logging.getLogger(__name__)

agents/router.py

@@ -1,25 +0,0 @@
-# router.py
-from typing import List
-from agent_types import AgentMessage, AgentRole
-import logging
-
-logger = logging.getLogger(__name__)
-
-def route(messages: List[AgentMessage]) -> None:
-    for msg in messages:
-        if msg.role != AgentRole.PLANNER:
-            continue     # autre type de lettre → plus tard
-        logger.info(f"Routing task: {msg.task}")
-        # Appel de l’agent existant (il attend un string)
-        # answer = research(msg.task)
-        # Ici on pourrait créer une nouvelle AgentMessage 'answer', mais on garde ça pour S-2
-
-
-if __name__ == '__main__':
-    from planner_agent import plan
-
-    objective = "Comparer l’impact écologique des voitures électriques et thermiques."
-    plan_msgs = plan(objective)
-    assert isinstance(plan_msgs[0].task, str)
-    route(plan_msgs)
-    print("✅  Premier voyage des AgentMessages réussi !")

agents/text_analyzer_agent.py

@@ -3,7 +3,6 @@ import certifi
 import logging
 import subprocess # For calling ffmpeg if needed
 from typing import List, Dict, Optional
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import ReActAgent
 from llama_index.core.tools import FunctionTool
@@ -19,8 +18,6 @@ except ImportError:
     logging.warning("openai-whisper not installed. Audio transcription tool will be unavailable.")
     WHISPER_AVAILABLE = False
 
-# Load environment variables
-load_dotenv()
 
 # Setup logging
 logger = logging.getLogger(__name__)

agents/verifier_agent.py

@@ -2,15 +2,11 @@ import os
 import logging
 import re
 from typing import List
-from dotenv import load_dotenv
 
 from llama_index.core.agent.workflow import FunctionAgent, ReActAgent
 from llama_index.core.tools import FunctionTool
 from llama_index.llms.google_genai import GoogleGenAI
 
-# Load environment variables
-load_dotenv()
-
 # Setup logging
 logger = logging.getLogger(__name__)
 

agents/video_analyzer_agent.py

@@ -9,7 +9,6 @@ from typing import Optional
 
 import cv2
 import yt_dlp
-from dotenv import load_dotenv
 from llama_index.core.agent.workflow import FunctionAgent
 from llama_index.core.base.llms.types import TextBlock, ImageBlock, ChatMessage
 from llama_index.core.tools import FunctionTool
@@ -20,7 +19,6 @@ from youtube_transcript_api import YouTubeTranscriptApi, TranscriptsDisabled, No
 # ---------------------------------------------------------------------------
 # Environment setup & logging
 # ---------------------------------------------------------------------------
-load_dotenv()
 logger = logging.getLogger(__name__)
 
 

app.py

@@ -1,9 +1,6 @@
 import os
 import logging
 import mimetypes
-from cgitb import handler
-
-from dotenv import load_dotenv
 
 from typing import Any, List
 
@@ -58,9 +55,6 @@ except ImportError as e:
         # ... set all others to None ...
         raise RuntimeError(f"Failed to import agent modules: {e2}")
 
-os.environ["TOKENIZERS_PARALLELISM"] = "false"
-load_dotenv() # Load environment variables from .env file
-
 # Setup logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)