How to manage multiple versions of the same library in one project?

Running two different versions of the same library within a single FastAPI application can be tricky due to dependency conflicts. However, you can achieve this by using separate virtual environments and subprocesses. Here’s a step-by-step guide:

1. Create Virtual Environments: Set up two separate virtual environments, each with the required version of the transformers library.

2. Install Dependencies:

   # For transformers==4.32.8
   python -m venv env1
   source env1/bin/activate
   pip install transformers==4.32.8
   deactivate
   
   # For transformers==5.32.8
   python -m venv env2
   source env2/bin/activate
   pip install transformers==5.32.8
   deactivate
   

3. Create Python Scripts: Write separate Python scripts for each function that uses the respective version of the transformers library.

   # script1.py (uses transformers==4.32.8)
   import transformers
   
   def function1():
       # Your code here
       return "Result from transformers 4.32.8"
   

   # script2.py (uses transformers==5.32.8)
   import transformers
   
   def function2():
       # Your code here
       return "Result from transformers 5.32.8"
   

4. Use Subprocesses in FastAPI: In your FastAPI application, use the subprocess module to call these scripts.

   from fastapi import FastAPI
   import subprocess
   
   app = FastAPI()
   
   @app.get("/function1")
   def run_function1():
       result = subprocess.run(["env1/bin/python", "script1.py"], capture_output=True, text=True)
       return {"result": result.stdout}
   
   @app.get("/function2")
   def run_function2():
       result = subprocess.run(["env2/bin/python", "script2.py"], capture_output=True, text=True)
       return {"result": result.stdout}
   

5. Run the FastAPI Application:

   uvicorn main:app --reload
   

This setup allows you to run each function in its own isolated environment, avoiding dependency conflicts. Let me know if you need further assistance!