| def llm_lib_installer_v1(imported_libs: str, python_version: str, task: str, api_key: str, libraries: str, model = 'openai/gpt-oss-20b'): | |
| ''' | |
| imported_libs: Give all the imports made in the current session of the notebook | |
| api_key: Generated groq api key | |
| task: The type of task being executed in the session notebook | |
| model: choose the groq model. Default is GPT OSS | |
| ''' | |
| from groq import Groq | |
| import streamlit as st | |
| client = Groq(api_key=api_key) | |
| completion = client.chat.completions.create( | |
| model=model, | |
| messages=[ | |
| { | |
| "role": "user", | |
| "content": f'''Assume we have imported a few libraries in the google colab environment: {imported_libs}. | |
| Generate a manual !pip install command for the imported libraries for the task: {task}. Take into account the current libraries: {libraries} | |
| Make sure there are no conflicts in the library versions even if the libraries are not imported. for instance opencv is dependent on the version of numpy. | |
| Suggest a version install for that as well even if it is not imported. In a similar way check all library dependencies. Try to take the latest libraries as far as possible. | |
| Suggest downgrades only if there is no other choice taking in consideration the python version in the environment is: {python_version}. | |
| Otherwise try and use the latest versions of the libraries. | |
| Use the "~=" symbol if needed to allow for backward compatibility between the installed libraries.''' | |
| } | |
| ], | |
| temperature=0, | |
| max_completion_tokens=8192, | |
| top_p=1, | |
| reasoning_effort="medium", | |
| stream=True, | |
| stop=None | |
| ) | |
| response_content = "" | |
| for chunk in completion: | |
| response_content+=chunk.choices[0].delta.content or "" | |
| return response_content |