Spaces:
Runtime error
Runtime error
File size: 5,338 Bytes
d99aef2 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 | import os
import yaml
import gradio as gr
from dotenv import load_dotenv
from agno.agent import Agent
from agno.models.nebius import Nebius
from agno.tools.github import GithubTools
from agno.tools.exa import ExaTools
from agno.tools.thinking import ThinkingTools
from agno.tools.reasoning import ReasoningTools
# Load environment variables from .env if present
load_dotenv()
# Load prompts from YAML file
with open("hiring_prompts.yaml", "r", encoding="utf-8") as f:
prompts = yaml.safe_load(f)
# Extract prompt sections
description_multi = prompts.get("description_for_multi_candidates", "")
instructions_multi = prompts.get("instructions_for_multi_candidates", "")
description_single = prompts.get("description_for_single_candidate", "")
instructions_single = prompts.get("instructions_for_single_candidate", "")
def analyze_multi(github_usernames, job_role, nebius_api_key, model_id, github_api_key, exa_api_key):
"""
Analyze multiple GitHub users for a given job role.
github_usernames: string with newline separated usernames.
Returns a markdown report.
"""
if not github_usernames or not job_role:
return "Please provide GitHub usernames and job role."
usernames = [u.strip() for u in github_usernames.split("\n") if u.strip()]
if not usernames:
return "No valid GitHub usernames found."
query = f"Evaluate GitHub candidates for role '{job_role}': {', '.join(usernames)}"
agent = Agent(
description=description_multi,
instructions=instructions_multi,
model=Nebius(id=model_id, api_key=nebius_api_key),
name="CandilyzerMulti",
tools=[
ThinkingTools(think=True, instructions="Strict GitHub candidate evaluation"),
GithubTools(access_token=github_api_key),
ExaTools(api_key=exa_api_key, include_domains=["github.com"], type="keyword"),
ReasoningTools(add_instructions=True),
],
markdown=True,
show_tool_calls=True,
)
stream = agent.run(query, stream=True)
output = ""
for chunk in stream:
if hasattr(chunk, "content") and isinstance(chunk.content, str):
output += chunk.content
return output
def analyze_single(github_username, linkedin_url, job_role, nebius_api_key, model_id, github_api_key, exa_api_key):
"""
Analyze a single GitHub (and optional LinkedIn) candidate for a given job role.
"""
if not github_username or not job_role:
return "Please provide GitHub username and job role."
query = f"Analyze candidate for {job_role}. GitHub: {github_username}"
if linkedin_url:
query += f", LinkedIn: {linkedin_url}"
agent = Agent(
description=description_single,
instructions=instructions_single,
model=Nebius(id=model_id, api_key=nebius_api_key),
name="CandilyzerSingle",
tools=[
ThinkingTools(add_instructions=True),
GithubTools(access_token=github_api_key),
ExaTools(api_key=exa_api_key, include_domains=["linkedin.com", "github.com"], type="keyword"),
ReasoningTools(add_instructions=True),
],
markdown=True,
show_tool_calls=True,
add_datetime_to_instructions=True,
)
stream = agent.run(query, stream=True)
output = ""
for chunk in stream:
if hasattr(chunk, "content") and isinstance(chunk.content, str):
output += chunk.content
return output
with gr.Blocks() as demo:
gr.Markdown("# Candilyzer\nAI Candidate Analyzer using Agno and Nebius AI")
with gr.Tab("Multi-Candidate Analyzer"):
github_usernames = gr.Textbox(label="GitHub Usernames (one per line)", lines=4, placeholder="username1\nusername2\n...")
job_role = gr.Textbox(label="Job Role", placeholder="Backend Engineer")
nebius_api_key = gr.Textbox(label="Nebius API Key", type="password")
model_id = gr.Textbox(label="Model ID", placeholder="meta-llama/Llama-3-70B-Instruct")
github_api_key = gr.Textbox(label="GitHub API Key", type="password")
exa_api_key = gr.Textbox(label="Exa API Key", type="password")
multi_button = gr.Button("Analyze Candidates")
multi_output = gr.Markdown()
multi_button.click(analyze_multi, inputs=[github_usernames, job_role, nebius_api_key, model_id, github_api_key, exa_api_key], outputs=multi_output)
with gr.Tab("Single Candidate Analyzer"):
github_username = gr.Textbox(label="GitHub Username", placeholder="username")
linkedin_url = gr.Textbox(label="LinkedIn Profile (optional)", placeholder="https://linkedin.com/in/...")
job_role2 = gr.Textbox(label="Job Role", placeholder="ML Engineer")
nebius_api_key2 = gr.Textbox(label="Nebius API Key", type="password")
model_id2 = gr.Textbox(label="Model ID", placeholder="meta-llama/Llama-3-70B-Instruct")
github_api_key2 = gr.Textbox(label="GitHub API Key", type="password")
exa_api_key2 = gr.Textbox(label="Exa API Key", type="password")
single_button = gr.Button("Analyze Candidate")
single_output = gr.Markdown()
single_button.click(analyze_single, inputs=[github_username, linkedin_url, job_role2, nebius_api_key2, model_id2, github_api_key2, exa_api_key2], outputs=single_output)
demo.launch()
|