Prompt Templates

from utils.prompt_templates import PromptTemplates

prompt = PromptTemplates.first_question_generation(
    cv_text="5+ years Python development experience...",
    job_description="Looking for senior backend engineer...",
    job_title="Senior Backend Engineer",
    company_name="TechCorp"
)

prompt = PromptTemplates.first_question_generation(
    cv_text="Senior developer with Django and Flask experience",
    job_description="We need a Python expert for backend development",
    job_title="Senior Python Developer",
    company_name="Acme Inc"
)

# The AI will receive a prompt like:
# "You are an experienced interviewer starting an interview for Senior Python Developer at Acme Inc.
# ...
# Generate the opening question now:"

prompt = PromptTemplates.followup_question_generation(
    conversation_history="Interviewer: Tell me about Python\nCandidate: I've used it for 5 years...",
    cv_text="5+ years Python development...",
    job_description="Backend engineer role...",
    question_count=1,
    max_questions=8
)

formatted_history = PromptTemplates.format_conversation_history([
    {"role": "assistant", "content": "Tell me about your Python experience"},
    {"role": "user", "content": "I've worked with Python for 5 years"}
])

prompt = PromptTemplates.followup_question_generation(
    conversation_history=formatted_history,
    cv_text=cv_text,
    job_description=job_desc,
    question_count=1,
    max_questions=8
)

prompt = PromptTemplates.feedback_generation(
    conversation_history="Interviewer: ...\nCandidate: ...",
    cv_text="5+ years Python development...",
    job_description="Backend engineer role...",
    job_title="Senior Backend Engineer"
)

{
  "score": 8,
  "strengths": "• Strong technical depth in Python\n• Clear communication style\n• Good examples from past projects",
  "weaknesses": "• Could elaborate more on system design\n• Limited discussion of testing practices",
  "cv_improvements": "• Add metrics to achievements\n• Highlight distributed systems experience\n• Include more backend-specific keywords"
}

from utils.prompt_templates import PromptTemplates

convo = [
    {"role": "assistant", "content": "Tell me about your Python experience"},
    {"role": "user", "content": "I've built REST APIs with Flask and Django"},
    {"role": "assistant", "content": "Describe a challenging project"},
    {"role": "user", "content": "I redesigned our microservices architecture..."}
]

formatted = PromptTemplates.format_conversation_history(convo)

prompt = PromptTemplates.feedback_generation(
    conversation_history=formatted,
    cv_text=cv_text,
    job_description=job_desc,
    job_title="Senior Backend Engineer"
)

# Use this prompt with AIClient.generate_feedback()

messages = [
    {"role": "assistant", "content": "What is your Python experience?"},
    {"role": "user", "content": "I have 5 years of experience"}
]

formatted = PromptTemplates.format_conversation_history(messages)
print(formatted)
# Output:
# Interviewer: What is your Python experience?
#
# Candidate: I have 5 years of experience

from utils.prompt_templates import PromptTemplates

conversation = [
    {"role": "assistant", "content": "Tell me about yourself"},
    {"role": "user", "content": "I'm a software engineer with 5 years experience"},
    {"role": "assistant", "content": "What technologies do you use?"},
    {"role": "user", "content": "Primarily Python, Django, and PostgreSQL"}
]

transcript = PromptTemplates.format_conversation_history(conversation)

# Use in other template methods
prompt = PromptTemplates.followup_question_generation(
    conversation_history=transcript,
    cv_text="...",
    job_description="...",
    question_count=2,
    max_questions=8
)

from utils.prompt_templates import PromptTemplates
from client.ai_client import AIClient
from client.ai_provider_manager import ProviderManager
from client.gemini_provider import GeminiProvider
import os

# Setup
provider = GeminiProvider(api_key=os.getenv("GEMINI_API_KEY"))
manager = ProviderManager(providers=[provider])
client = AIClient(provider_manager=manager)

# Interview data
cv_text = "Senior Python Developer with 5 years experience..."
job_desc = "Looking for backend engineer skilled in Python and Django..."
job_title = "Senior Backend Engineer"
company = "TechCorp"

# 1. Generate first question
first_q = client.generate_first_question(
    cv_text=cv_text,
    job_desc=job_desc,
    job_title=job_title,
    company_name=company
)

conversation = [
    {"role": "assistant", "content": first_q},
    {"role": "user", "content": "I've built REST APIs with Django..."}
]

# 2. Generate follow-up questions
for i in range(3):
    followup = client.generate_followup_question(
        convo_history=conversation,
        cv_text=cv_text,
        job_desc=job_desc,
        question_count=i + 1,
        max_questions=8
    )
    
    conversation.append({"role": "assistant", "content": followup})
    # Get candidate answer (from user input in real app)
    conversation.append({"role": "user", "content": "[answer]"})

# 3. Generate feedback
feedback = client.generate_feedback(
    convo_history=conversation,
    cv_text=cv_text,
    job_desc=job_desc,
    job_title=job_title
)

print(f"Score: {feedback['score']}/10")
print(f"Strengths:\n{feedback['strengths']}")
print(f"Weaknesses:\n{feedback['weaknesses']}")
print(f"CV Improvements:\n{feedback['cv_improvements']}")