🧠

Model

Perplexity Ai

Name: Perplexity Ai
Author: helallao

by helallao gh-model--helallao--perplexity-ai

Nexus Index

47.0 Top 100%

S: Semantic 50

A: Authority 0

P: Popularity 69

R: Recency 94

Q: Quality 50

Tech Context

Vital Performance

0 DL / 30D

0.0%

Source →

Audited 47 FNI Score

Tiny - Params

- Context

0 Downloads

Commercial MIT License

Model Information Summary
Entity Passport
Registry ID	gh-model--helallao--perplexity-ai
License	MIT
Provider	github

📜

Cite this model

Academic & Research Attribution

BibTeX

@misc{gh_model__helallao__perplexity_ai,
  author = {helallao},
  title = {Perplexity Ai Model},
  year = {2026},
  howpublished = {\url{https://github.com/helallao/perplexity-ai}},
  note = {Accessed via Free2AITools Knowledge Fortress}
}

APA Style

helallao. (2026). Perplexity Ai [Model]. Free2AITools. https://github.com/helallao/perplexity-ai

🔬Technical Deep Dive

Full Specifications [+]

Quick Commands

🐙 Git Clone

git clone https://github.com/helallao/perplexity-ai

⚖️ Nexus Index V2.0

Methodology Index Protocol

47.0

TOP 100% SYSTEM IMPACT

Semantic (S) 50

Authority (A) 0

Popularity (P) 69

Recency (R) 94

Quality (Q) 50

💬 Index Insight

FNI V2.0 for Perplexity Ai: Semantic (S:50), Authority (A:0), Popularity (P:69), Recency (R:94), Quality (Q:50).

Free2AITools Nexus Index

Verification Authority

HuggingFace API GitHub Metadata Arxiv Citation DB System Audit

Unbiased Data Node Refresh: VFS Live

---

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⚡

Technical Deep Dive

Perplexity AI

Perplexity AI is a Python module that leverages Emailnator to generate new accounts for unlimited pro queries. It supports both synchronous and asynchronous APIs, as well as a web interface for users who prefer a GUI-based approach.

Features

Account Generation: Automatically generate Gmail accounts using Emailnator
Unlimited Pro Queries: Bypass query limits by creating new accounts
Web Interface: Automate account creation and usage via a browser
Sync & Async APIs: Full support for both synchronous and asynchronous programming
Type Safety: Complete type hints for better IDE support
Robust Error Handling: Custom exceptions for better error management
Comprehensive Logging: Structured logging for debugging
File Upload: Support for document analysis and Q&A
Streaming Responses: Real-time response streaming
Retry Logic: Automatic retry with exponential backoff
Rate Limiting: Built-in rate limiting to prevent abuse

Installation

Basic Installation

bash

pip install -e .

With Driver Support (Web Interface)

bash

pip install -e ".[driver]"
patchright install chromium

With MCP Server

bash

pip install -e ".[mcp]"

Development Installation

bash

pip install -e ".[dev]"

This includes testing tools (pytest, pytest-cov, pytest-asyncio), linting (flake8, black, isort, mypy), and all optional dependencies.

MCP Server

This project includes an MCP (Model Context Protocol) server that exposes Perplexity search as tools for Claude Code and other MCP clients. It works without an API key by using the same reverse-engineered web interface as the rest of this library.

Installation

bash

pip install -e ".[mcp]"

Running the Server

The server supports two transports, controlled by the MCP_TRANSPORT environment variable (default: stdio).

stdio (default)

Used by local MCP clients like Claude Code and Claude Desktop. The client spawns the process directly.

bash

perplexity-mcp

Add to Claude Code:

bash

claude mcp add perplexity -- perplexity-mcp

Manual config:

json

{
  "mcpServers": {
    "perplexity": {
      "command": "perplexity-mcp",
      "env": {
        "PERPLEXITY_COOKIES": "{\"next-auth.session-token\": \"...\"}"
      }
    }
  }
}

HTTP (network/remote)

Runs a persistent HTTP server that multiple clients can connect to over the network. Use this when you want to share one server instance across multiple clients or machines.

1. Start the server:

bash

MCP_TRANSPORT=http perplexity-mcp

Defaults to 127.0.0.1:8000. To bind to all interfaces or change the port:

bash

MCP_TRANSPORT=http MCP_HOST=0.0.0.0 MCP_PORT=9000 perplexity-mcp

To include cookies:

bash

MCP_TRANSPORT=http PERPLEXITY_COOKIES='{"next-auth.session-token": "..."}' perplexity-mcp

The MCP endpoint will be available at http://<host>:<port>/mcp.

2. Add to Claude Code:

bash

claude mcp add --transport http perplexity http://127.0.0.1:8000/mcp

Adjust the URL if you changed the host or port. For a remote machine, replace 127.0.0.1 with its address.

3. Verify:

bash

claude mcp list

The PERPLEXITY_COOKIES environment variable is optional for both transports. If not set, the server runs anonymously with access to free (auto mode) queries only. Set it to a JSON string of your Perplexity cookies to enable pro, reasoning, and deep research modes. See How To Get Cookies for instructions.

Available Tools

Tool	Mode	Description
`perplexity_ask`	`auto`	General-purpose question answering
`perplexity_research`	`deep research`	In-depth research on a topic
`perplexity_reason`	`reasoning`	Step-by-step reasoning through a problem
`perplexity_search`	`pro` + web sources	Web search

Differences from the Official MCP

The official @perplexity-ai/mcp-server requires a paid Perplexity API key. This server uses the reverse-engineered web interface instead. As a result, the following features available in the official MCP are not supported here:

Feature	Official MCP	This server
No API key required	No	Yes
`messages` array input	Yes	No (single `query` string only)
`search_recency_filter`	Yes	No
`search_domain_filter`	Yes	No
`search_context_size`	Yes	No
`reasoning_effort`	Yes	No
`strip_thinking`	Yes	No
Structured search results (citations, images)	Yes	No (plain text answer only)

Quick Start

Basic Usage

python

import perplexity

# Create client
client = perplexity.Client()

# Make a query
response = client.search("What is artificial intelligence?")
print(response['answer'])

With Account (for enhanced features)

python

import perplexity

# Your Perplexity cookies
cookies = {
    'next-auth.csrf-token': 'your-token',
    'next-auth.session-token': 'your-session',
}

client = perplexity.Client(cookies)

# Use enhanced modes
response = client.search(
    "Complex query here",
    mode='pro',
    model='gpt-5.2',
    sources=['scholar']
)

Streaming Responses

python

for chunk in client.search("Explain quantum computing", stream=True):
    if 'answer' in chunk:
        print(chunk['answer'], end='', flush=True)

Async Usage

python

import asyncio
import perplexity_async

async def main():
    client = await perplexity_async.Client()
    response = await client.search("What is machine learning?")
    print(response['answer'])

asyncio.run(main())

Documentation

Examples - Practical examples for common use cases
Changelog - Bug fixes and changes history
Improvements - Suggested improvements and roadmap
API Reference - Complete API documentation

Usage

Web Interface

The web interface automates account creation and usage in a browser. Patchright uses "Chrome User Data Directory" to be completely undetected, it's C:\Users\YourName\AppData\Local\Google\Chrome\User Data for Windows, as shown below:

python

import os
from perplexity.driver import Driver

cli = Driver()
cli.run(rf'C:\\Users\\{os.getlogin()}\\AppData\\Local\\Google\\Chrome\\User Data')

To use your own Chrome instance, enable remote debugging (it may enter dead loop in Cloudflare):

Add --remote-debugging-port=9222 to Chrome's shortcut target.
Pass the port to the Driver.run() method:

python

cli.run(rf'C:\\Users\\{os.getlogin()}\\AppData\\Local\\Google\\Chrome\\User Data', port=9222)

API Usage

Synchronous API

Below is an example code for simple usage, without using your own account or generating new accounts.

python3

import perplexity

perplexity_cli = perplexity.Client()

# model = model for mode, which can only be used in own accounts, that is {
#     'auto': [None],
#     'pro': [None, 'sonar', 'gpt-5.2', 'claude-4.5-sonnet', 'grok-4-1'],
#     'reasoning': [None, 'gpt-5.2-thinking', 'claude-4.5-sonnet-thinking', 'gemini-3.0-pro', 'kimi-k2-thinking', 'grok-4.1-reasoning'],
#     'deep research': [None]
# }
# sources = ['web', 'scholar', 'social']
# files = a dictionary which has keys as filenames and values as file data
# stream = returns a generator when enabled and just final response when disabled
# language = ISO 639 code of language you want to use
# follow_up = last query info for follow-up queries, you can directly pass response from a query, look at second example below
# incognito = Enables incognito mode, for people who are using their own account
resp = perplexity_cli.search('Your query here', mode='auto', model=None, sources=['web'], files={}, stream=False, language='en-US', follow_up=None, incognito=False)
print(resp)

# second example to show how to use follow-up queries and stream response
for i in perplexity_cli.search('Your query here', stream=True, follow_up=resp):
    print(i)

And this is how you use your own account, you need to get your cookies in order to use your own account. Look at How To Get Cookies,

python3

import perplexity

perplexity_cookies = { 
    
}

perplexity_cli = perplexity.Client(perplexity_cookies)

resp = perplexity_cli.search('Your query here', mode='reasoning', model='gpt-5.2-thinking', sources=['web'], files={'myfile.txt': open('file.txt').read()}, stream=False, language='en-US', follow_up=None, incognito=False)
print(resp)

And finally account generating, you need to get cookies for Emailnator to use this feature. Look at How To Get Cookies,

python3

import perplexity

emailnator_cookies = { 
    
}

perplexity_cli = perplexity.Client()
perplexity_cli.create_account(emailnator_cookies) # Creates a new gmail, so your 5 pro queries will be renewed.

resp = perplexity_cli.search('Your query here', mode='reasoning', model=None, sources=['web'], files={'myfile.txt': open('file.txt').read()}, stream=False, language='en-US', follow_up=None, incognito=False)
print(resp)

Asynchronous API

Below is an example code for simple usage, without using your own account or generating new accounts.

python3

import asyncio
import perplexity_async

async def test():
    perplexity_cli = await perplexity_async.Client()

    # mode = ['auto', 'pro', 'reasoning', 'deep research']
    # model = model for mode, which can only be used in own accounts, that is {
    #     'auto': [None],
    #     'pro': [None, 'sonar', 'gpt-5.2', 'claude-4.5-sonnet', 'grok-4-1'],
    #     'reasoning': [None, 'gpt-5.2-thinking', 'claude-4.5-sonnet-thinking', 'gemini-3.0-pro', 'kimi-k2-thinking', 'grok-4.1-reasoning'],
    #     'deep research': [None]
    # }
    # sources = ['web', 'scholar', 'social']
    # files = a dictionary which has keys as filenames and values as file data
    # stream = returns a generator when enabled and just final response when disabled
    # language = ISO 639 code of language you want to use
    # follow_up = last query info for follow-up queries, you can directly pass response from a query, look at second example below
    # incognito = Enables incognito mode, for people who are using their own account
    resp = await perplexity_cli.search('Your query here', mode='auto', model=None, sources=['web'], files={}, stream=False, language='en-US', follow_up=None, incognito=False)
    print(resp)

    # second example to show how to use follow-up queries and stream response
    async for i in await perplexity_cli.search('Your query here', stream=True, follow_up=resp):
        print(i)

asyncio.run(test())

And this is how you use your own account, you need to get your cookies in order to use your own account. Look at How To Get Cookies,

python3

import asyncio
import perplexity_async

perplexity_cookies = { 
    
}

async def test():
    perplexity_cli = await perplexity_async.Client(perplexity_cookies)

    resp = await perplexity_cli.search('Your query here', mode='reasoning', model='gpt-5.2-thinking', sources=['web'], files={'myfile.txt': open('file.txt').read()}, stream=False, language='en-US', follow_up=None, incognito=False)
    print(resp)

asyncio.run(test())

And finally account generating, you need to get cookies for emailnator to use this feature. Look at How To Get Cookies,

python3

import asyncio
import perplexity_async

emailnator_cookies = { 
    
}

async def test():
    perplexity_cli = await perplexity_async.Client()
    await perplexity_cli.create_account(emailnator_cookies) # Creates a new gmail, so your 5 pro queries will be renewed.

    resp = await perplexity_cli.search('Your query here', mode='reasoning', model=None, sources=['web'], files={'myfile.txt': open('file.txt').read()}, stream=False, language='en-US', follow_up=None, incognito=False)
    print(resp)

asyncio.run(test())

How to Get Cookies

Perplexity (to use your own account)

Open Perplexity.ai website and login to your account.
Click F12 or Ctrl + Shift + I to open inspector.
Go to the "Network" tab in the inspector.
Refresh the page, right click the first request, hover on "Copy" and click to "Copy as cURL (bash)".
Now go to the CurlConverter and paste your code here. The cookies dictionary will appear, copy and use it in your codes.

Emailnator (for account generating)

Open Emailnator website and verify you're human.
Click F12 or Ctrl + Shift + I to open inspector.
Go to the "Network" tab in the inspector.
Refresh the page, right click the first request, hover on "Copy" and click to "Copy as cURL (bash)".
Now go to the CurlConverter and paste your code here. The cookies dictionary will appear, copy and use it in your codes.
Cookies for Emailnator are temporary, you need to renew them continuously.

API Reference

Client Class

python

class Client:
    def __init__(self, cookies: Optional[Dict[str, str]] = None):
        """
        Initialize Perplexity client.
        
        Args:
            cookies: Optional Perplexity account cookies for enhanced features
        """
    
    def search(
        self,
        query: str,
        mode: str = 'auto',
        model: Optional[str] = None,
        sources: List[str] = ['web'],
        files: Dict[str, Union[str, bytes]] = {},
        stream: bool = False,
        language: str = 'en-US',
        follow_up: Optional[Dict] = None,
        incognito: bool = False
    ) -> Union[Dict, Generator]:
        """
        Search with Perplexity AI.
        
        Args:
            query: Search query
            mode: Search mode ('auto', 'pro', 'reasoning', 'deep research')
            model: Model to use (depends on mode)
            sources: Information sources (['web', 'scholar', 'social'])
            files: Files to upload {filename: content}
            stream: Enable streaming responses
            language: ISO 639 language code
            follow_up: Previous query for context
            incognito: Enable incognito mode
            
        Returns:
            Response dict with 'answer' key, or generator if stream=True
        """
    
    def create_account(self, emailnator_cookies: Dict[str, str]):
        """
        Create new account using Emailnator.
        
        Args:
            emailnator_cookies: Emailnator cookies for account creation
        """

Available Models

python

{
    'auto': [None],
    'pro': [None, 'sonar', 'gpt-5.2', 'claude-4.5-sonnet', 'grok-4-1'],
    'reasoning': [None, 'gpt-5.2-thinking', 'claude-4.5-sonnet-thinking', 'gemini-3.0-pro', 'kimi-k2-thinking', 'grok-4.1-reasoning'],
    'deep research': [None]
}

Custom Exceptions

python

from perplexity.exceptions import (
    PerplexityError,          # Base exception
    AuthenticationError,      # Authentication failed
    RateLimitError,          # Rate limit exceeded
    NetworkError,            # Network issues
    ValidationError,         # Invalid parameters
    ResponseParseError,      # Failed to parse response
    AccountCreationError,    # Account creation failed
    FileUploadError,         # File upload failed
)

Testing

Run All Tests

bash

pytest tests/ -v

With Coverage

bash

pytest tests/ --cov=perplexity --cov=perplexity_async --cov-report=html

Run Specific Tests

bash

pytest tests/test_utils.py -v
pytest tests/test_config.py -v

Development

Setup Development Environment

bash

# Clone repository
git clone https://github.com/yourusername/perplexity-ai.git
cd perplexity-ai

# Install in development mode
pip install -e ".[dev]"

# Run tests
pytest

# Format code
black perplexity perplexity_async

# Check types
mypy perplexity perplexity_async

# Lint
flake8 perplexity perplexity_async

Contributing

Fork the repository
Create a feature branch (git checkout -b feature/amazing-feature)
Make your changes
Run tests and linting
Commit your changes (git commit -m 'Add amazing feature')
Push to the branch (git push origin feature/amazing-feature)
Open a Pull Request

Troubleshooting

Common Issues

Issue: Response returns None

Solution: The API structure may have changed. Check Changelog for updates.

Issue: Account creation fails

Solution: Emailnator cookies expire frequently. Get fresh cookies from Emailnator.com.

Issue: File upload fails

Solution: Ensure you have a valid Perplexity account with file upload quota available.

Issue: Rate limiting

Solution: Use built-in rate limiting or wait between requests. Consider using async API for better concurrency.

Getting Help

Check the examples/ directory for working code
Read the documentation
Open an issue on GitHub

Changelog

See CHANGELOG.md for detailed changes and bug fixes.

Roadmap

See IMPROVEMENTS.md for planned improvements and features.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Acknowledgments

Perplexity.ai for the amazing AI search engine
Emailnator for temporary email service
All contributors who help improve this project

Disclaimer

This is an unofficial API wrapper. Use responsibly and respect Perplexity.ai's terms of service. This project is for educational purposes only.

🚀 Quick Start

bash

pip install -e .

⚠️ Incomplete Data

Some information about this model is not available. Use with Caution - Verify details from the original source before relying on this data.

View Original Source →

📝 Limitations & Considerations

• Benchmark scores may vary based on evaluation methodology and hardware configuration.
• VRAM requirements are estimates; actual usage depends on quantization and batch size.
• FNI scores are relative rankings and may change as new models are added.
⚠ License Unknown: Verify licensing terms before commercial use.

Social Proof

GitHub Repository

1.5KStars

Repo Issues

🐙 Data Source: GitHub ↗

🔄 Daily sync (03:00 UTC)

AI Summary: Based on GitHub metadata. Not a recommendation.

📊 FNI Methodology 📚 Knowledge Baseℹ️ Verify with original source

🛡️ Model Transparency Report

Technical metadata sourced from upstream repositories.

Open Metadata

🆔 Identity & Source

id: gh-model--helallao--perplexity-ai
slug: helallao--perplexity-ai
source: github
author: helallao
license: MIT
tags: ai, api, artificial-intelligence, chatgpt, gpt, language-model, language-models, perplexity, python

⚙️ Technical Specs

architecture: null
params billions: null
context length: null
pipeline tag: text-generation

📊 Engagement & Metrics

downloads: 0
stars: 1,515
forks: 0

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Smart Search

FNI Score

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Cite this model

🔬Technical Deep Dive

Quick Commands

⚖️ Nexus Index V2.0

💬 Index Insight

Verification Authority

🚀 What's Next?

Find Training Datasets

Compare Benchmarks

Deployment Guide

Technical Deep Dive

Perplexity AI

Features

Installation

Basic Installation

With Driver Support (Web Interface)

With MCP Server

Development Installation

MCP Server

Installation

Running the Server

stdio (default)

HTTP (network/remote)

Available Tools

Differences from the Official MCP

Quick Start

Basic Usage

With Account (for enhanced features)

Streaming Responses

Async Usage

Documentation

Usage

Web Interface

API Usage

Synchronous API

Asynchronous API

How to Get Cookies

Perplexity (to use your own account)

Emailnator (for account generating)

API Reference

Client Class

Available Models

Custom Exceptions

Testing

Run All Tests

With Coverage

Run Specific Tests

Development

Setup Development Environment

Contributing

Troubleshooting

Common Issues

Getting Help

Changelog

Roadmap

License

Acknowledgments

Disclaimer

🚀 Quick Start

⚠️ Incomplete Data

📝 Limitations & Considerations

Social Proof

🛡️ Model Transparency Report

🆔 Identity & Source

⚙️ Technical Specs

📊 Engagement & Metrics