tools/perplexity_tools.py

import requests
import json

def call_perplexity_api(query: str, api_key: str, model: str):
    """Calls the Perplexity API with the provided query and parameters."""
    if not api_key:
        return "Error: Perplexity API not initialized. Please initialize it first."
    
    url = "https://api.perplexity.ai/chat/completions"
    
    # System prompt
    system_prompt = """
    You are a helpful AI assistant.

    Rules:
    1. Provide only the final answer. It is important that you do not include any explanation on the steps below.
    2. Do not show the intermediate steps information.

    Steps:
    1. Decide if the answer should be a brief sentence or a list of suggestions.
    2. If it is a list of suggestions, first, write a brief and natural introduction based on the original query.
    3. Followed by a list of suggestions, each suggestion should be split by two newlines.
    """
    
    payload = {
        "model": model,  # Use the selected model
        "messages": [
            {
                "role": "system",
                "content": system_prompt.strip()  # Add the system prompt
            },
            {
                "role": "user",
                "content": query
            }
        ],
        "max_tokens": 8000 if model in ["sonar-reasoning-pro", "sonar-pro"] else 1000,
        "temperature": 0.2,
        "top_p": 0.9,
        "search_domain_filter": None,
        "return_images": False,
        "return_related_questions": False,
        "search_recency_filter": "month",  # Limit recency of search to this month
        "top_k": 0,
        "stream": False,
        "presence_penalty": 0,
        "frequency_penalty": 1,
        "response_format": None
    }
    headers = {
        "Authorization": f"Bearer {api_key}",
        "Content-Type": "application/json"
    }
    
    try:
        response = requests.post(url, json=payload, headers=headers)
        response.raise_for_status()  # Raise HTTPError for bad responses (4xx or 5xx)
        return response.json()  # Return the JSON response
    except requests.exceptions.RequestException as e:
        # Provide detailed error information
        error_details = {
            "error_type": type(e).__name__,
            "error_message": str(e),
            "response_status_code": getattr(e.response, "status_code", None),
            "response_text": getattr(e.response, "text", None),
            "request_payload": payload,
            "request_headers": headers
        }
        return f"Request failed. Details:\n{json.dumps(error_details, indent=2)}"

def get_ai_research_papers(query: str, api_key: str, model: str) -> str:
    """A tool that fetches relevant AI research papers using Perplexity API."""
    try:
        response_json = call_perplexity_api(f"search AI research papers about: {query}", api_key, model)
        if isinstance(response_json, str):  # Error message
            return response_json
        
        if response_json and "choices" in response_json:
            content = response_json["choices"][0]["message"]["content"]
            citations = response_json.get("citations", [])
            citation_string = "\n".join([f"{i+1}. {citation}" for i, citation in enumerate(citations)])
            
            return f"AI Research Papers:\n{content}\n\nCitations:\n{citation_string if citation_string else 'No citations found.'}"
            
        return f"No relevant AI papers found for your query: {query}"
    except Exception as e:
        return f"Error fetching research papers: {str(e)}"

def summarize_paper(paper_title: str, api_key: str, model: str) -> str:
    """A tool that summarizes an AI research paper."""
    try:
        response_json = call_perplexity_api(f"Summarize AI research paper: {paper_title}", api_key, model)
        if isinstance(response_json, str):  # Error message
            return response_json
        
        if response_json and "choices" in response_json:
            content = response_json["choices"][0]["message"]["content"]
            return f"Summary of '{paper_title}':\n{content}"
        return f"Could not summarize paper '{paper_title}'"
    except Exception as e:
        return f"Error summarizing paper: {str(e)}"

def get_citation(paper_title: str, api_key: str, model: str) -> str:
    """A tool that generates a citation for an AI research paper."""
    try:
        response_json = call_perplexity_api(f"Generate citation for AI research paper: {paper_title}", api_key, model)
        if isinstance(response_json, str):  # Error message
            return response_json
         
        if response_json and "choices" in response_json:
            content = response_json["choices"][0]["message"]["content"]
            return f"Citation for '{paper_title}':\n{content}"
        return f"Could not generate citation for '{paper_title}'"
    except Exception as e:
        return f"Error generating citation: {str(e)}"

def explain_concept(concept: str, api_key: str, model: str) -> str:
    """A tool that explains an AI-related concept in simple terms."""
    try:
        response_json = call_perplexity_api(f"Explain the AI concept: {concept}", api_key, model)
        if isinstance(response_json, str):  # Error message
            return response_json
         
        if response_json and "choices" in response_json:
            content = response_json["choices"][0]["message"]["content"]
            return f"Explanation of {concept}:\n{content}"
        return f"Could not explain the concept '{concept}'"
    except Exception as e:
        return f"Error explaining concept: {str(e)}"