career_enhancer / github_analytics /singular_analysis_chat.py
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Create singular_analysis_chat.py
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from groq import Groq
import os
from dotenv import load_dotenv
load_dotenv()
def predict_2vars(data_a, data_b, a, b):
client = Groq(api_key=os.getenv("GROQ_API_KEY"))
completion = client.chat.completions.create(
model="llama3-70b-8192",
messages=[
{
"role": "system",
"content": f"""You are a Mentor proficient in GitHub.
Based on github repo data you have to suggest them things,
what repo should they contribute more to? Or which language they should do
more or where they lack.
Give Repo Contribution Suggestions
If you see any trends or patterns, do let me know.
for example: Trends & Patterns in your github profile:
Tell them Strength and Weaknesses of their data
Explicitly tell them what job are they suitable for in bullet points based on data
""",
},
{
"role": "user",
"content": f"""These are list of two data in which
{a} : {data_a} and {b} :{data_b}
Display the data in a tabular format way
Map it as indexes co-relate
"""
}
],
max_tokens=2048,
)
response = completion.choices[0].message.content
return response
def predict_df(df):
client = Groq(api_key=os.getenv("GROQ_API_KEY"))
completion = client.chat.completions.create(
model="llama3-70b-8192",
messages=[
{
"role": "system",
"content": f"""You are a Mentor proficient in GitHub.
Based on github repo data you have to suggest them things,
what repo should they contribute more to?
If you see any trends or patterns, do let me know.
for example: Trends & Patterns in your github profile:
Give Repo Contribution Suggestions
Tell them Strength and Weaknesses of their data.
Explicitly tell them what job are they suitable for in bullet points based on data
""",
},
{
"role": "user",
"content": f""" This is the list of data {df}
In it the columns are repo names, stars, forks, days since repo was created.
Display the entire data in a tabular format way
If you see any trends or patterns, do let me know.
For example: sometimes, a repo with less days is doing good,
so you can advise to mae it better so that it does even better
Map it as indexes co-relate.
Display the data in a tabular format way
"""
}
],
max_tokens=2048,
)
response = completion.choices[0].message.content
return response