ds-fire-fighter/docs/prev.py

import os
import requests
from dotenv import load_dotenv
from langchain_openai import ChatOpenAI
from langchain_core.prompts.prompt import PromptTemplate
from langchain_core.output_parsers import StrOutputParser, JsonOutputParser
from langchain_openai import OpenAIEmbeddings
from langchain_core.documents import Document
from uuid import uuid4
import json
import getpass
import numpy as np
from concurrent.futures import ThreadPoolExecutor, as_completed
from sklearn.metrics.pairwise import cosine_similarity
from typing import List
import time
from datetime import datetime
import pytz
import logging
load_dotenv()

os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")

llm_temp = ChatOpenAI(model="gpt-4o-mini", temperature=0.7)
def generate_theme(conversation_data, resume, full_history, form_response=None, feedback=None, previous_result=None) -> dict:
    try:
        # Define prompt for summarizing and extracting the required fields
        theme_prompt = PromptTemplate(
            template="""
<|begin_of_text|><|start_header_id|>system<|end_header_id|>
You are a Fire Fighter Interview preparation assistant that generates STARTPOP FORMAT based on user interaction with AI.
Your responsibilities include carefully analyzing user interactions, themes, resumes,Onboarding questions and answers and work history to generate detailed STARTPOP formats for specific themes.

### Context and Guidelines:
1. **Purpose**: Generate a single behavioral question with a detailed STARTPOP format.
2. **Input Sources**:
   - Current theme
   - User interaction with AI
   - User resume
   - Full work history
   - Onboarding questions and answers for additional context
3. **Output Format**: JSON object with the following fields:
   - `theme_title`: Title of the theme provided.
   - `question`: Behavioral question aligned with the theme.
   - `Situation`: A bulleted list (75-100 words).
   - `Task`: A bulleted list (50 words).
   - `Action`: A bulleted list (2 negative actions and 2 positive actions).
   - `Results and Transitions`: A bulleted list (25-50 words).
   - `Personal Lessons`: A bulleted list (25-50 words).
   - `Observations of Others`: A bulleted list (25 words).
   - `Professional Connection`: A bulleted list (25-50 words). Additionally:
     - Connect to the theme of the question.
     - Creatively express why you should be part of their team.

### Key Concepts in Firefighting:
Throughout most Probationary Firefighter Interviews, evaluators assess alignment with the **7 Main Concepts of Firefighting**:
- **High Performance Teams**
- **Situational Awareness**
- **Being a Great Problem Solver**
- **Customer Service**
- **Building Construction, Mechanical Aptitude**
- **Emergency Medicine Experience**
- **Mental and Physical Health**

Additionally, they evaluate communication skills, competence, and likability.

### 20 Important Themes:
These themes are used for behavioral questions:
- Customer Service
- Conflict
- Challenge
- Leadership
- Stress
- Successful Team
- Diversity
- Mistake
- Unsuccessful Team
- Disagreement
- Bent a Rule
- Delivered a Difficult Message
- Displayed Integrity
- Took a Shortcut
- Didn’t Follow the Rules
- Emergency Response
- Dealt with Disabilities
- Solved a Big Problem
- Continuous Improvement
- Handled Sensitive Information

### Behavioral Question Starters:
Behavioral questions often begin with phrases like:
- "Tell me a time when..."
- "Can you tell me about a time when you..."
- "Describe a situation where you had to..."
- "Give me an example of how you..."
- "Have you ever been in a position where you needed to..."
- "Walk me through a time when you..."

### STARTPOP Framework:
The STARTPOP framework enhances the traditional STAR method. It includes:
1. **Situation**: Set up the scenario concisely (include dates, ages, places, and circumstances).
2. **Task**: Explain what needed to be done and why.
3. **Actions**: Outline both negative and positive approaches.
4. **Results and Transitions**: Share outcomes and ensure coherence.
5. **Personal Lessons**: Reflect on what you learned.
6. **Observations of Others**: Share insights about others involved.
7. **Professional Connection**: Relate the experience to firefighting and express your desire to join the team.

### Example STARTPOP:
**Question**: Tell me a time when you made a mistake and how you fixed it?

- **Situation**:
  - In the Fall, my business, Tiger Building Services, does eavestrough cleaning.
  - In 2019, we were working on a job late in the day, tired and running out of sunlight.
  - I used handheld blowers without checking the wetness of debris, creating a muddy mess on the customer's deck.
  - The customer was upset, and I realized my mistake.

- **Task**:
  - Defuse the situation and clean up the mess quickly.
  - Protect my company's reputation and ensure good customer experiences.

- **Actions**:
  - Negative: Matching the customer's anger or ignoring the problem.
  - Positive: Getting off the roof safely, apologizing, and switching strategies.
  - Positive: Cleaning the gutters by hand and offering a free soft wash service.

- **Results and Transitions**:
  - The job took longer than expected, but we waived fees due to the inconvenience.
  - The customer was satisfied after our resolution plan.

- **Personal Lessons**:
  - I learned to own up to mistakes, stay empathetic, and de-escalate tense situations.

- **Observations of Others**:
  - People are entitled to their emotions, and following SOPs prevents mistakes.

- **Professional Connection**:
  - Mistakes happen, but learning from them is crucial.
  - I align with Markham Fire's values of transparency and accountability.

### JSON Output Requirements:
Generate a well-structured JSON output with the following fields:
- `theme_title`
- `question`
- `Situation`
- `Task`
- `Action`
- `Results and Transitions`
- `Personal Lessons`
- `Observations of Others`
- `Professional Connection`

### Review Process:
1. Ensure all news items align with the specified theme and meet relevance criteria.
2. Verify the JSON format is flawless, comprehensive, and well-structured.

### Additional Notes:
- You may be provided with feedback and previous results if the user is dissatisfied.
- Use this feedback to refine and regenerate the STARTPOP.

<|eot_id|><|start_header_id|>user<|end_header_id|>
Rules for Generating Each Component:
1. Situation: 75-100 words.
2. Task: 50 words.
3. Actions: 2 negative actions and 2 positive actions.
4. Results: 25-50 words.
5. Personal Lessons: 25-50 words.
6. Observations of Others: 25 words.
7. Professional Connection: 25-50 words + creative connection to the theme and team invitation.
NOTE: MAKE SURE THE OUT IS WELL  DETAILED
CONVERSATION DATA: {conversation_data}
FEEDBACK: {feedback}
PREVIOUS RESULT: {previous_result}
USER RESUME: {resume}
FULL WORK HISTORY: {full_history}
Onboarding questions and answers for additional context: {form_response}
<|start_header_id|>assistant<|end_header_id|>
Return just the JSON output without any other explanation or comments.
Thank you for your thorough and precise processing!

""",
            input_variables=["resume", "conversation_data", "feedback","form_response" "previous_result", "full_history"],
        )

        # Pipeline to process the prompt and parse output
        theme_router = theme_prompt | llm_temp | JsonOutputParser()

        # Call the pipeline and generate the cohesive output
        output = theme_router.invoke({
            "conversation_data": conversation_data,
            "feedback": feedback,
            "previous_result": previous_result,
            "resume": resume,
            "full_history": full_history,
            "form_response":form_response
        })

        print(f"Output: {output}")
        return output

    except Exception as e:
        print(f"Error: {e}")
        return {}




from fastapi import Response, HTTPException, Depends
from typing import Optional
import os
import requests
import datetime
import base64  # For encoding the PDF content in Base64

@app.post("/rescue-career/generate-theme")
async def generate_pdf_endpoint(
    request: GeneratePDFRequest,
    api_key: str = Depends(get_api_key)
):
    
    try:
        # Fetch conversation data using the conversation_id
        conversation_data = await get_conversation_data(request.conversation_id)
        
        if not conversation_data:
            raise HTTPException(
                status_code=404,
                detail=f"No conversation found with ID {request.conversation_id}"
            )
        
        resume_docs = ""
        if request.resume_url:
            docs = load_document(request.resume_url)
            if not docs:
                raise HTTPException(
                    status_code=400, 
                    detail="Invalid resume URL: Unable to fetch document"
                )
            resume_docs = "\n".join(f"- {doc.page_content}" for doc in docs)

        full_history_docs = ""
        if request.full_history_url:
            docs = load_document(request.full_history_url)
            if not docs:
                raise HTTPException(
                    status_code=400, 
                    detail="Invalid full_history URL: Unable to fetch document"
                )
            full_history_docs = "\n".join(f"- {doc.page_content}" for doc in docs)

        form_response_docs = ""
        if request.form_id:
            try:
                x_api_key = os.getenv("BACKEND_XAPI_KEY")
                url = f"{os.getenv('BACKEND_BASE_URL')}/v3/api/custom/theme-document/answer/{request.form_id}?x-project={x_api_key}"
                result = requests.get(url)
                form_response = result.json()  # Return response in JSON format
                form_response_docs = "\n".join(f"- {form_response}")
            except:
                raise HTTPException(
                    status_code=400, 
                    detail="Unable to fetch onboarding data"
                )

        # Generate theme data using the generate_theme function
        theme_data = generate_theme(
            conversation_data=conversation_data,
            feedback=request.feedback,
            previous_result=request.previous_results,
            resume=resume_docs,
            form_response=form_response_docs,
            full_history=full_history_docs
        )  

        if not theme_data:
            raise HTTPException(
                status_code=500,
                detail="Failed to generate theme data"
            )
        
        # Generate the PDF using the create_pdf function
        pdf_content = create_pdf(theme_data)
        
        # Encode the PDF content in Base64
        pdf_base64 = base64.b64encode(pdf_content).decode("utf-8")
        
        # Create filename with timestamp
        timestamp = datetime.datetime.now().strftime("%Y%m%d_%H%M%S")
        filename = f"theme_{timestamp}.pdf"
        
        # Return both the PDF (as Base64) and the theme data in a JSON response
        return {
            "theme_data": theme_data,
            "pdf": {
                "filename": filename,
                "content": pdf_base64
            }
        }
    
    except Exception as e:
        raise HTTPException(
            status_code=500,
            detail=f"Error generating PDF: {str(e)}"
        )