Spaces:
Running
Running
Commit
•
b098a37
1
Parent(s):
09cf909
Update app.py
Browse files
app.py
CHANGED
@@ -1,5 +1,6 @@
|
|
1 |
import streamlit as st
|
2 |
import os
|
|
|
3 |
import warnings
|
4 |
from crewai import Agent, Task, Crew
|
5 |
from langchain_google_genai import ChatGoogleGenerativeAI
|
@@ -11,16 +12,23 @@ os.environ['OPENAI_API_KEY'] = 'dummy_key'
|
|
11 |
# Warning control
|
12 |
warnings.filterwarnings('ignore')
|
13 |
|
14 |
-
# Set the Google API key
|
15 |
google_api_key = "AIzaSyCeZHse0Jr8PXBQoKFJg7fZkV_t5w6ViBM"
|
16 |
|
17 |
-
#
|
18 |
-
|
19 |
-
|
20 |
-
|
21 |
-
|
22 |
-
|
23 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
24 |
|
25 |
# Initialize tools
|
26 |
search_tool = SerperDevTool()
|
@@ -33,7 +41,12 @@ researcher = Agent(
|
|
33 |
goal="Make sure to do amazing analysis on job posting to help job applicants",
|
34 |
tools=[scrape_tool, search_tool],
|
35 |
verbose=True,
|
36 |
-
|
|
|
|
|
|
|
|
|
|
|
37 |
)
|
38 |
|
39 |
profiler = Agent(
|
@@ -41,7 +54,12 @@ profiler = Agent(
|
|
41 |
goal="Do incredible research on job applicants to help them stand out in the job market",
|
42 |
tools=[scrape_tool, search_tool, read_resume],
|
43 |
verbose=True,
|
44 |
-
|
|
|
|
|
|
|
|
|
|
|
45 |
)
|
46 |
|
47 |
resume_strategist = Agent(
|
@@ -49,7 +67,11 @@ resume_strategist = Agent(
|
|
49 |
goal="Find all the best ways to make a resume stand out in the job market.",
|
50 |
tools=[scrape_tool, search_tool, read_resume],
|
51 |
verbose=True,
|
52 |
-
|
|
|
|
|
|
|
|
|
53 |
)
|
54 |
|
55 |
interview_preparer = Agent(
|
@@ -57,7 +79,12 @@ interview_preparer = Agent(
|
|
57 |
goal="Create interview questions and talking points based on the resume and job requirements",
|
58 |
tools=[scrape_tool, search_tool, read_resume],
|
59 |
verbose=True,
|
60 |
-
|
|
|
|
|
|
|
|
|
|
|
61 |
)
|
62 |
|
63 |
# Define tasks
|
@@ -116,48 +143,31 @@ interview_preparation_task = Task(
|
|
116 |
agent=interview_preparer
|
117 |
)
|
118 |
|
119 |
-
#
|
120 |
job_application_crew = Crew(
|
121 |
agents=[researcher, profiler, resume_strategist, interview_preparer],
|
122 |
tasks=[research_task, profile_task, resume_strategy_task, interview_preparation_task],
|
123 |
verbose=True
|
124 |
)
|
125 |
|
126 |
-
#
|
127 |
-
|
128 |
-
|
129 |
-
|
130 |
-
|
131 |
-
|
132 |
-
|
133 |
-
|
134 |
-
Prathamesh
|
135 |
-
|
136 |
-
|
137 |
-
|
138 |
-
|
139 |
-
|
140 |
-
|
141 |
-
|
142 |
-
|
143 |
-
|
144 |
-
|
145 |
-
|
146 |
-
|
147 |
-
|
148 |
-
try:
|
149 |
-
# Kickoff the Crew Execution
|
150 |
-
result = job_application_crew.kickoff(inputs=job_application_inputs)
|
151 |
-
st.success("Process completed successfully!")
|
152 |
-
|
153 |
-
# Display results
|
154 |
-
with open("tailored_resume.md", "r") as f:
|
155 |
-
st.markdown(f.read())
|
156 |
-
|
157 |
-
with open("interview_materials.md", "r") as f:
|
158 |
-
st.markdown(f.read())
|
159 |
-
|
160 |
-
except httpx.ConnectError as e:
|
161 |
-
st.error(f"Connection error occurred: {e}")
|
162 |
-
except Exception as e:
|
163 |
-
st.error(f"An error occurred: {e}")
|
|
|
1 |
import streamlit as st
|
2 |
import os
|
3 |
+
import asyncio
|
4 |
import warnings
|
5 |
from crewai import Agent, Task, Crew
|
6 |
from langchain_google_genai import ChatGoogleGenerativeAI
|
|
|
12 |
# Warning control
|
13 |
warnings.filterwarnings('ignore')
|
14 |
|
15 |
+
# Set the Google API key directly in the code
|
16 |
google_api_key = "AIzaSyCeZHse0Jr8PXBQoKFJg7fZkV_t5w6ViBM"
|
17 |
|
18 |
+
# Function to initialize the Gemini model with an event loop
|
19 |
+
async def initialize_llm():
|
20 |
+
return ChatGoogleGenerativeAI(
|
21 |
+
model="gemini-1.5-flash",
|
22 |
+
verbose=True,
|
23 |
+
temperature=0.5,
|
24 |
+
google_api_key=google_api_key
|
25 |
+
)
|
26 |
+
|
27 |
+
# Run the initialization within the event loop
|
28 |
+
if not hasattr(st, 'llm'):
|
29 |
+
loop = asyncio.new_event_loop()
|
30 |
+
asyncio.set_event_loop(loop)
|
31 |
+
st.llm = loop.run_until_complete(initialize_llm())
|
32 |
|
33 |
# Initialize tools
|
34 |
search_tool = SerperDevTool()
|
|
|
41 |
goal="Make sure to do amazing analysis on job posting to help job applicants",
|
42 |
tools=[scrape_tool, search_tool],
|
43 |
verbose=True,
|
44 |
+
backstory=(
|
45 |
+
"As a Job Researcher, your prowess in navigating and extracting critical "
|
46 |
+
"information from job postings is unmatched. Your skills help pinpoint the necessary "
|
47 |
+
"qualifications and skills sought by employers, forming the foundation for effective application tailoring."
|
48 |
+
),
|
49 |
+
llm=st.llm
|
50 |
)
|
51 |
|
52 |
profiler = Agent(
|
|
|
54 |
goal="Do incredible research on job applicants to help them stand out in the job market",
|
55 |
tools=[scrape_tool, search_tool, read_resume],
|
56 |
verbose=True,
|
57 |
+
backstory=(
|
58 |
+
"Equipped with analytical prowess, you dissect and synthesize information "
|
59 |
+
"from diverse sources to craft comprehensive personal and professional profiles, laying the "
|
60 |
+
"groundwork for personalized resume enhancements."
|
61 |
+
),
|
62 |
+
llm=st.llm
|
63 |
)
|
64 |
|
65 |
resume_strategist = Agent(
|
|
|
67 |
goal="Find all the best ways to make a resume stand out in the job market.",
|
68 |
tools=[scrape_tool, search_tool, read_resume],
|
69 |
verbose=True,
|
70 |
+
backstory=(
|
71 |
+
"With a strategic mind and an eye for detail, you excel at refining resumes to highlight the most "
|
72 |
+
"relevant skills and experiences, ensuring they resonate perfectly with the job's requirements."
|
73 |
+
),
|
74 |
+
llm=st.llm
|
75 |
)
|
76 |
|
77 |
interview_preparer = Agent(
|
|
|
79 |
goal="Create interview questions and talking points based on the resume and job requirements",
|
80 |
tools=[scrape_tool, search_tool, read_resume],
|
81 |
verbose=True,
|
82 |
+
backstory=(
|
83 |
+
"Your role is crucial in anticipating the dynamics of interviews. With your ability to formulate key questions "
|
84 |
+
"and talking points, you prepare candidates for success, ensuring they can confidently address all aspects of the "
|
85 |
+
"job they are applying for."
|
86 |
+
),
|
87 |
+
llm=st.llm
|
88 |
)
|
89 |
|
90 |
# Define tasks
|
|
|
143 |
agent=interview_preparer
|
144 |
)
|
145 |
|
146 |
+
# Crew Setup
|
147 |
job_application_crew = Crew(
|
148 |
agents=[researcher, profiler, resume_strategist, interview_preparer],
|
149 |
tasks=[research_task, profile_task, resume_strategy_task, interview_preparation_task],
|
150 |
verbose=True
|
151 |
)
|
152 |
|
153 |
+
# Job Application Inputs
|
154 |
+
job_application_inputs = {
|
155 |
+
'job_posting_url': 'https://www.linkedin.com/jobs/search/?alertAction=viewjobs¤tJobId=3971168247&distance=25&f_TPR=a1720706267-&f_WT=1%2C3%2C2&geoId=105524837&keywords=data%20scientist&origin=JOB_ALERT_IN_APP_NOTIFICATION&originToLandingJobPostings=3971106469&savedSearchId=1741028074&sortBy=R',
|
156 |
+
'github_url': 'https://github.com/Pk-Kolhapurkar',
|
157 |
+
'linkedin_url': 'https://www.linkedin.com/in/prathamesh-khade-434615217/',
|
158 |
+
'personal_writeup': """
|
159 |
+
Prathamesh Khade is an accomplished Software Engineering Leader with experience in managing teams,
|
160 |
+
specializing in multiple programming languages and frameworks. He holds a strong background in AI and data science.
|
161 |
+
Prathamesh has successfully led major tech initiatives, proving his ability to drive innovation and growth in the tech industry.
|
162 |
+
Ideal for leadership roles that require a strategic and innovative approach."""
|
163 |
+
}
|
164 |
+
|
165 |
+
# Kickoff the Crew Execution
|
166 |
+
result = job_application_crew.kickoff(inputs=job_application_inputs)
|
167 |
+
|
168 |
+
# Display results
|
169 |
+
st.markdown("# Tailored Resume")
|
170 |
+
st.markdown(open("tailored_resume.md").read())
|
171 |
+
|
172 |
+
st.markdown("# Interview Materials")
|
173 |
+
st.markdown(open("interview_materials.md").read())
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|