Delete agent.py

agent.py

@@ -1,148 +0,0 @@
-# import smolagents.models as sm_models
-
-# _orig_roles = sm_models.MessageRole.roles
-
-# @classmethod
-# def _roles_with_control(cls):
-#     return _orig_roles() + ["control"]
-
-# sm_models.MessageRole.roles = _roles_with_control
-
-
-
-from smolagents import (CodeAgent, 
-                        GradioUI, 
-                        LiteLLMModel, 
-                        OpenAIServerModel, 
-                        ChatMessage, 
-                        ToolCallingAgent)
-from smolagents.default_tools import (DuckDuckGoSearchTool, 
-                                      VisitWebpageTool, 
-                                      WikipediaSearchTool, 
-                                      SpeechToTextTool,
-                                      PythonInterpreterTool)
-import yaml
-from tools.final_answer import FinalAnswerTool, check_reasoning, ensure_formatting
-from tools.tools import (youtube_frames_to_images, use_vision_model, 
-                         read_file, download_file_from_url, 
-                         extract_text_from_image, analyze_csv_file, 
-                         analyze_excel_file, youtube_transcribe,
-                         transcribe_audio, review_youtube_video)
-import os
-from dotenv import load_dotenv
-import time
-
-load_dotenv()
-
-# Load prompts from YAML file
-with open("prompts.yaml", 'r') as stream:
-    prompt_templates = yaml.safe_load(stream)
-
-
-# class ThinkingLiteLLMModel(LiteLLMModel):
-#     def __init__(self, *args, **kwargs):
-#         # ensure the Litellm client also maps "control" → "control"
-#         cr = kwargs.pop("custom_role_conversions", {})
-#         cr["control"] = "control"
-#         super().__init__(*args, custom_role_conversions=cr, **kwargs)
-
-#     def __call__(self, messages, **kwargs) -> ChatMessage:
-        # NOTE: content must be a list of {type, text} dicts
-#         thinking_msg = {
-#             "role": "control",
-#             "content": [{"type": "text", "text": "thinking"}]
-#         }
-#         # prepend onto whatever messages the Agent built
-#         return super().__call__([thinking_msg] + messages, **kwargs)
-    
-class SlowLiteLLMModel(LiteLLMModel):
-    def __init__(self, *args, **kwargs):
-        super().__init__(*args, **kwargs)
-
-    def __call__(self, messages, **kwargs) -> ChatMessage:
-        time.sleep(15)
-        # prepend onto whatever messages the Agent built
-        return super().__call__(messages, **kwargs)
-
-# # search_model_name = 'granite3.3:latest'
-# search_model_name = 'cogito:14b'
-# # search_model_name = 'qwen2:7b'
-# search_model = ThinkingLiteLLMModel(model_id=f'ollama_chat/{search_model_name}',
-#                              flatten_messages_as_text=True)
-
-# web_agent = CodeAgent(
-#     model=search_model,
-#     tools=[DuckDuckGoSearchTool(), VisitWebpageTool(), FinalAnswerTool()],
-#     max_steps=6,
-#     verbosity_level=1,
-#     grammar=None,
-#     planning_interval=6,
-#     name="web_agent",
-#     description="Searches the web using the and reviews web pages to find information.",
-#     additional_authorized_imports=['bs4', 'requests', 'io', 'wiki'],
-#     prompt_templates=prompt_templates
-# )
-
-# image_model_name = 'llama3.2-vision'
-# image_model = OpenAIServerModel(model_id=image_model_name,
-#                                 api_base='http://localhost:11434/v1/',
-#                                 api_key='ollama',
-#                             flatten_messages_as_text=False)
-# image_agent = ToolCallingAgent(
-#     model=image_model,
-#     tools=[FinalAnswerTool()],
-#     max_steps=4,
-#     verbosity_level=2,
-#     grammar=None,
-#     planning_interval=6,
-#     #additional_authorized_imports=["PIL", "requests", "io", "numpy"],
-#     name="image_agent",
-#     description="Review images and videos for answers to questions based on visual data",
-#     prompt_templates=prompt_templates
-# )
-
-# react_model_name = 'qwen2:7b'
-# # Initialize the chat model
-# react_model = OpenAIServerModel(model_id=react_model_name,
-#                                 api_base='http://localhost:11434/v1/',
-#                                 api_key='ollama',
-#                             flatten_messages_as_text=False)
-
-react_model_name = "gemini/gemini-2.5-flash-preview-04-17"
-react_model = LiteLLMModel(model_id=react_model_name, 
-                           api_key=os.getenv("GEMINI_KEY"),
-                           temperature=0.2
-                           )
-
-
-manager_agent = CodeAgent(
-    model=react_model,
-    tools=[FinalAnswerTool(), 
-           DuckDuckGoSearchTool(), 
-           VisitWebpageTool(max_output_length=500000), 
-           WikipediaSearchTool(extract_format='HTML'),
-           SpeechToTextTool(),
-           youtube_frames_to_images,
-           youtube_transcribe,
-           use_vision_model,
-           read_file, download_file_from_url, 
-           extract_text_from_image, 
-           analyze_csv_file, analyze_excel_file,
-           transcribe_audio,
-           review_youtube_video
-           ],
-    managed_agents=[],
-    additional_authorized_imports=['os', 'pandas', 'numpy', 'PIL', 'tempfile', 'PIL.Image'],
-    max_steps=20,
-    verbosity_level=1,
-    planning_interval=6,
-    name="Manager",
-    description="The manager of the team, responsible for overseeing and guiding the team's work.",
-    final_answer_checks=[check_reasoning, ensure_formatting],
-    prompt_templates=prompt_templates
-)
-
-
-
-if __name__ == "__main__":
-    GradioUI(manager_agent).launch()