import pandas as pd

from ollama import Client
import json


def worker_extraction(row, host, model):

    
    # Instantiate local client for this specific worker/thread
    local_client = Client(host=host)
    
    return ollama_keyword_extraction(
        content=row['content'], 
        tag=row['tag'], 
        client=local_client, 
        model=model
    )


def ollama_keyword_extraction(content, tag, client: Client, model) -> list:
    """
    Perform sentiment analysis using Ollama model.

    Parameters:
    - content: Text content to analyze
    - tag: Tag indicating the type of sentiment analysis (e.g., 'VT - Positive')

    Returns:
    - sentiment score and reason
    """
    
    # Construct prompt for Ollama model
    prompt = f"""
### Role
You are a qualitative data analyst. Your task is to extract keywords from a user quote to build a semantic word cluster.

### Guidelines
1. **Quantity:** Extract **1-5** high-value keywords. If the quote only contains 1 valid insight, return only 1 keyword. Do not force extra words.
2. **Specificity:** Avoid vague, single nouns (e.g., "tech", "choice", "system"). Instead, capture the descriptor (e.g., "tech-forward", "payment choice", "legacy system").
3. **Adjectives:** Standalone adjectives are acceptable if they are strong descriptors (e.g., "reliable", "trustworthy", "professional").
4. **Normalize:** Convert verbs to present tense and nouns to singular.
5. **Output Format:** Return a single JSON object with the key "keywords" containing a list of strings.

### Examples

**Input Context:** Chase as a Brand
**Input Quote:** "I would describe it as, you know, like the next big thing, like, you know, tech forward, you know, customer service forward, and just hating that availability."
**Output:** {{ "keywords": ["tech forward", "customer service focused", "availability"] }}

**Input Context:** App Usability
**Input Quote:** "There are so many options when I try to pay, it's confusing."
**Output:** {{ "keywords": ["confusing", "payment options"] }}

**Input Context:** Investment Tools
**Input Quote:** "It is just really reliable."
**Output:** {{ "keywords": ["reliable"] }}

### Input Data
**Context/Theme:** {tag}
**Quote:** "{content}"

### Output
```json
"""

    max_retries = 3
    for attempt in range(max_retries):
        try:
            resp = client.generate(
                model=model,
                prompt=prompt,
                format='json',
            )
            
            response_text = resp.response.strip()

            # Extract JSON from response
            start_index = response_text.find('{')
            
            if start_index == -1:
                raise ValueError("No JSON found")

            response_json, _ = json.JSONDecoder().raw_decode(response_text[start_index:])
            keywords = response_json.get('keywords', [])
            return [keywords]
        
        except Exception as e:
            print(f"Attempt {attempt + 1}/{max_retries} failed: {e}. Output was: {response_text}")
            if attempt == max_retries - 1:
                return [[]]