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app.py
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import os
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import warnings
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from typing import *
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from dotenv import load_dotenv
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from transformers import logging
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from langgraph.checkpoint.memory import MemorySaver
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from langchain_openai import ChatOpenAI
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from langgraph.checkpoint.memory import MemorySaver
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from langchain_openai import ChatOpenAI
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from interface import create_demo
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from medrax.agent import *
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from medrax.tools import *
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from medrax.utils import *
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warnings.filterwarnings("ignore")
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logging.set_verbosity_error()
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_ = load_dotenv()
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def initialize_agent(
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prompt_file,
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tools_to_use=None,
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model_dir="./model-weights",
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temp_dir="temp",
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device="cuda",
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model="gpt-4o-mini",
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temperature=0.7,
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top_p=0.95,
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openai_kwargs={}
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):
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"""Initialize the MedRAX agent with specified tools and configuration.
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Args:
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prompt_file (str): Path to file containing system prompts
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tools_to_use (List[str], optional): List of tool names to initialize. If None, all tools are initialized.
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model_dir (str, optional): Directory containing model weights. Defaults to "/model-weights".
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temp_dir (str, optional): Directory for temporary files. Defaults to "temp".
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device (str, optional): Device to run models on. Defaults to "cuda".
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model (str, optional): Model to use. Defaults to "chatgpt-4o-latest".
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temperature (float, optional): Temperature for the model. Defaults to 0.7.
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top_p (float, optional): Top P for the model. Defaults to 0.95.
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openai_kwargs (dict, optional): Additional keyword arguments for OpenAI API, such as API key and base URL.
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Returns:
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Tuple[Agent, Dict[str, BaseTool]]: Initialized agent and dictionary of tool instances
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"""
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prompts = load_prompts_from_file(prompt_file)
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prompt = prompts["MEDICAL_ASSISTANT"]
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all_tools = {
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"ChestXRayClassifierTool": lambda: ChestXRayClassifierTool(device=device),
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"ChestXRaySegmentationTool": lambda: ChestXRaySegmentationTool(device=device),
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"LlavaMedTool": lambda: LlavaMedTool(cache_dir=model_dir, device=device, load_in_8bit=True),
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"XRayVQATool": lambda: XRayVQATool(cache_dir=model_dir, device=device),
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"ChestXRayReportGeneratorTool": lambda: ChestXRayReportGeneratorTool(
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cache_dir=model_dir, device=device
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),
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"XRayPhraseGroundingTool": lambda: XRayPhraseGroundingTool(
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cache_dir=model_dir, temp_dir=temp_dir, load_in_8bit=True, device=device
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),
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"ChestXRayGeneratorTool": lambda: ChestXRayGeneratorTool(
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model_path=f"{model_dir}/roentgen", temp_dir=temp_dir, device=device
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),
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"ImageVisualizerTool": lambda: ImageVisualizerTool(),
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"DicomProcessorTool": lambda: DicomProcessorTool(temp_dir=temp_dir),
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}
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# Initialize only selected tools or all if none specified
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tools_dict = {}
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tools_to_use = tools_to_use or all_tools.keys()
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for tool_name in tools_to_use:
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if tool_name in all_tools:
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tools_dict[tool_name] = all_tools[tool_name]()
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checkpointer = MemorySaver()
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model = ChatOpenAI(model=model, temperature=temperature, top_p=top_p, **openai_kwargs)
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agent = Agent(
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model,
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tools=list(tools_dict.values()),
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log_tools=True,
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log_dir="logs",
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system_prompt=prompt,
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checkpointer=checkpointer,
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)
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print("Agent initialized")
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return agent, tools_dict
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if __name__ == "__main__":
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"""
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This is the main entry point for the MedRAX application.
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It initializes the agent with the selected tools and creates the demo.
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"""
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print("Starting server...")
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# Example: initialize with only specific tools
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# Here three tools are commented out, you can uncomment them to use them
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selected_tools = [
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"ImageVisualizerTool",
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"DicomProcessorTool",
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"ChestXRayClassifierTool",
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"ChestXRaySegmentationTool",
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"ChestXRayReportGeneratorTool",
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"XRayVQATool",
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# "LlavaMedTool",
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# "XRayPhraseGroundingTool",
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# "ChestXRayGeneratorTool",
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]
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# Collect the ENV variables
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openai_kwargs = {}
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if api_key := os.getenv("OPENAI_API_KEY"):
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openai_kwargs["api_key"] = api_key
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if base_url := os.getenv("OPENAI_BASE_URL"):
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openai_kwargs["base_url"] = base_url
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agent, tools_dict = initialize_agent(
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"medrax/docs/system_prompts.txt",
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tools_to_use=selected_tools,
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model_dir="./model-weights", # Change this to the path of the model weights
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temp_dir="temp", # Change this to the path of the temporary directory
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device="cuda", # Change this to the device you want to use
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model="gpt-4o-mini", # Change this to the model you want to use, e.g. gpt-4o-mini
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temperature=0.7,
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top_p=0.95,
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openai_kwargs=openai_kwargs
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)
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demo = create_demo(agent, tools_dict)
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# demo.launch(server_name="0.0.0.0", server_port=8585, share=True)
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demo.launch(debug=True, ssr_mode=False)
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