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import streamlit as st
from groq import Groq
from github_analytics.chat_github import analyze_github_data
import os
from dotenv import load_dotenv
load_dotenv()
def predict(domain, content):
client = Groq(api_key=os.getenv("GROQ_API_KEY_PR"))
completion = client.chat.completions.create(
model="llama3-70b-8192",
messages=[
{
"role": "system",
"content": f"""You are a Mentor proficient in the {domain} that provides project recommendations
in a rabular format to users based on their domain, area of interest, experience level,
years of experience, tech stack, and prior projects.
Strictly give the output in a tabular format
""",
},
{
"role": "user",
"content": content,
}
],
max_tokens=2048,
)
response = completion.choices[0].message.content
return response
def project_recommendation():
st.title("Project Recommender Chatbot")
domain = st.text_input("Enter your domain:")
area_of_interest = st.text_input("Enter your area of interest:")
experience_level = st.selectbox("Select your current role", ['Student', 'Working professional', 'Freelancer'])
if experience_level in ["Working professional", "Freelancer"]:
years_of_experience = st.number_input("Enter your years of experience:")
else:
years_of_experience = 0
skill_level = st.selectbox("Select your skill level", ['Beginner', 'Intermediate', 'Advanced'])
tech_stack = st.text_input("Enter your technology stack/ list of tools you use for your project:")
prior_projects = st.text_input("If you have any prior projects, please enter:")
hours_in_hand = st.number_input("How many hours do you have for one project?")
content = f"""This is my information:
Domain: {domain}
Area of Interest: {area_of_interest}
Experience Level: {experience_level}
Years of Experience: {years_of_experience}
Skill level : {skill_level}
Tech Stack: {tech_stack}
Prior Projects: {prior_projects}
Hours in Hand: {hours_in_hand}
Based on this information, please provide a list of 5 project recommendations
that would be suitable for me.
Consider my domain, area of interest, years of experience, hours in hand, experience level, tech stack,
skill level, and any prior projects I have worked on.
Tailor the recommendations to my specific interests and skill level.
You have an explicit instruction to follow the hours in hand criteria and
not overestimate/underestimate the time
For each project recommendation, provide the following details in a tabular format:
1. Project Title
2. Brief Project Description
3. Relevant Technologies/Skills Required
4. Steps to achieve the recommendation
If it is a technology related domain, in 4th point above,
please mention the step by step modules/files/subprojects that one can make and progress in a project
Your response should be structured in a clear and concise manner, do not use </br> anywhere
with each project recommendation presented as a separate section or bullet point."""
if st.button("Send"):
answer = predict(domain, content)
st.write("Result:", answer)
st.write("If you are from a technical field and you want to analyze your github, press this button")
username = st.text_input("Enter your Github Username: ")
if username:
# user_data, repo_data = fetch_user_data(username)
output_of_analysis = analyze_github_data(username, domain, area_of_interest, experience_level,
years_of_experience, skill_level, tech_stack, prior_projects,
hours_in_hand)
st.write("Result:", output_of_analysis)
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