name updated

Signed-off-by: aritroCoder <ogcodinggod@gmail.com>

Author: aritroCoder

LICENSE

@@ -1,6 +1,6 @@
 MIT License
 
-Copyright (c) 2025 PromptLayer Contributors
+Copyright (c) 2025 PromptShift Contributors
 
 Permission is hereby granted, free of charge, to any person obtaining a copy
 of this software and associated documentation files (the "Software"), to deal

README.md

@@ -1,14 +1,14 @@
-# PromptLayer
+# PromptShift
 
-[![CI Status](https://github.com/aritroCoder/promptlayer/workflows/test/badge.svg)](https://github.com/aritroCoder/promptlayer/actions)
+[![CI Status](https://github.com/aritroCoder/PromptShift/workflows/test/badge.svg)](https://github.com/aritroCoder/PromptShift/actions)
 [![Coverage](https://img.shields.io/badge/coverage-95%25-brightgreen.svg)](htmlcov/index.html)
-[![PyPI version](https://img.shields.io/badge/pypi-1.0.0-blue.svg)](https://pypi.org/project/promptlayer/)
+[![PyPI version](https://img.shields.io/badge/pypi-1.0.0-blue.svg)](https://pypi.org/project/PromptShift/)
 [![Python 3.9+](https://img.shields.io/badge/python-3.9+-blue.svg)](https://www.python.org/downloads/)
 [![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
 
 **Reliable structured output from LLMs with deterministic generation**
 
-PromptLayer is a Python library that provides a simple, reliable way to get structured outputs from Large Language Models (LLMs). Built on top of Pydantic for schema validation and designed for deterministic, production-ready results.
+PromptShift is a Python library that provides a simple, reliable way to get structured outputs from Large Language Models (LLMs). Built on top of Pydantic for schema validation and designed for deterministic, production-ready results.
 
 ## Features
 
@@ -25,15 +25,15 @@ PromptLayer is a Python library that provides a simple, reliable way to get stru
 Coming soon - will be available via pip:
 
 ```bash
-pip install promptlayer
+pip install PromptShift
 ```
 
 For detailed installation instructions and development setup, see the [full documentation](docs/index.md).
 
 ## Quick Start
 
 ```python
-from promptlayer import Client
+from PromptShift import Client
 from pydantic import BaseModel
 
 # Define your output schema
@@ -57,11 +57,11 @@ print(f"{result.name} is {result.age} years old and works as a {result.occupatio
 
 ## Logging
 
-PromptLayer provides detailed logging to help you debug and monitor LLM interactions. Retry attempts are logged at **INFO** level by default, making them visible without additional configuration.
+PromptShift provides detailed logging to help you debug and monitor LLM interactions. Retry attempts are logged at **INFO** level by default, making them visible without additional configuration.
 
 ### Default Logging Behavior
 
-When retry attempts occur, PromptLayer logs the following information at INFO level:
+When retry attempts occur, PromptShift logs the following information at INFO level:
 
 **Successful attempt example:**
 ```
@@ -115,19 +115,19 @@ logging.basicConfig(level=logging.CRITICAL)
 
 ### Library-Specific Logger
 
-To configure only PromptLayer logs without affecting other libraries:
+To configure only PromptShift logs without affecting other libraries:
 
 ```python
 import logging
 
-# Get PromptLayer logger
-pl_logger = logging.getLogger("promptlayer")
+# Get PromptShift logger
+pl_logger = logging.getLogger("PromptShift")
 
-# Set level for PromptLayer only
+# Set level for PromptShift only
 pl_logger.setLevel(logging.DEBUG)
 
 # Add custom handler
-handler = logging.FileHandler("promptlayer.log")
+handler = logging.FileHandler("PromptShift.log")
 handler.setFormatter(logging.Formatter("%(asctime)s - %(name)s - %(levelname)s - %(message)s"))
 pl_logger.addHandler(handler)
 ```
@@ -144,7 +144,7 @@ pl_logger.addHandler(handler)
 
 ```python
 import logging
-from promptlayer import Client
+from PromptShift import Client
 
 # Production configuration - only errors and critical issues
 logging.basicConfig(
@@ -165,7 +165,7 @@ result = client.generate("Generate data", MySchema)
 
 ```python
 import logging
-from promptlayer import Client
+from PromptShift import Client
 
 # Development configuration - see everything
 logging.basicConfig(
@@ -180,7 +180,7 @@ result = client.generate("Generate data", MySchema)
 
 ## Deterministic Generation
 
-PromptLayer is designed for **100% reproducible outputs** to enable reliable testing, debugging, and production deployments. Every generation is deterministic by default.
+PromptShift is designed for **100% reproducible outputs** to enable reliable testing, debugging, and production deployments. Every generation is deterministic by default.
 
 ### Why Determinism Matters
 
@@ -191,7 +191,7 @@ PromptLayer is designed for **100% reproducible outputs** to enable reliable tes
 
 ### How Determinism Works
 
-PromptLayer achieves deterministic outputs through three mechanisms:
+PromptShift achieves deterministic outputs through three mechanisms:
 
 1. **Temperature = 0.0**: Always uses temperature 0.0 for deterministic sampling
 2. **Automatic Seed Generation**: Creates deterministic seed from hash(prompt + JSON schema)
@@ -200,7 +200,7 @@ PromptLayer achieves deterministic outputs through three mechanisms:
 ### Basic Deterministic Usage
 
 ```python
-from promptlayer import Client
+from PromptShift import Client
 from pydantic import BaseModel
 
 class Person(BaseModel):
@@ -257,13 +257,13 @@ def test_person_generation():
 
 ### API Documentation
 
-For more details on seed parameter and determinism options, see the [API Reference](https://promptlayer.readthedocs.io/api/client/).
+For more details on seed parameter and determinism options, see the [API Reference](https://PromptShift.readthedocs.io/api/client/).
 
 **Groq API Seed Documentation**: [Groq API Docs](https://console.groq.com/docs/api-reference#seed)
 
 ## Performance
 
-PromptLayer is designed for **minimal overhead** - the library adds less than 1ms to your requests (excluding the actual LLM API call).
+PromptShift is designed for **minimal overhead** - the library adds less than 1ms to your requests (excluding the actual LLM API call).
 
 ### Performance Characteristics
 
@@ -282,7 +282,7 @@ PromptLayer is designed for **minimal overhead** - the library adds less than 1m
 ### Performance Example
 
 ```python
-from promptlayer import Client
+from PromptShift import Client
 from pydantic import BaseModel
 import time
 
@@ -349,8 +349,8 @@ For detailed performance analysis, see [docs/performance.md](docs/performance.md
 
 1. Clone the repository:
 ```bash
-git clone https://github.com/aritroCoder/promptlayer.git
-cd promptlayer
+git clone https://github.com/aritroCoder/PromptShift.git
+cd PromptShift
 ```
 
 2. Install uv (if not already installed):
@@ -385,7 +385,7 @@ uv run pytest
 uv run pytest tests/unit/
 
 # Run tests with coverage
-uv run pytest --cov=src/promptlayer --cov-report=html
+uv run pytest --cov=src/PromptShift --cov-report=html
 
 # Format code
 uv run black src/ tests/
@@ -470,5 +470,5 @@ This project is licensed under the MIT License - see the [LICENSE](LICENSE) file
 
 ## Support
 
-- 📫 Issues: [GitHub Issues](https://github.com/aritroCoder/promptlayer/issues)
-- 💬 Discussions: [GitHub Discussions](https://github.com/aritroCoder/promptlayer/discussions)
+- 📫 Issues: [GitHub Issues](https://github.com/aritroCoder/PromptShift/issues)
+- 💬 Discussions: [GitHub Discussions](https://github.com/aritroCoder/PromptShift/discussions)

pyproject.toml

@@ -1,9 +1,9 @@
 [project]
-name = "promptlayer"
+name = "PromptShift"
 version = "1.0.0"
 description = "Reliable structured output from LLMs with deterministic generation"
 authors = [
-    {name = "PromptLayer Contributors", email = "contributors@promptlayer.dev"}
+    {name = "PromptShift Contributors", email = "contributors@PromptShift.dev"}
 ]
 readme = "README.md"
 license = {text = "MIT"}
@@ -47,17 +47,17 @@ docs = [
 ]
 
 [project.urls]
-Homepage = "https://github.com/aritroCoder/promptlayer"
-Documentation = "https://promptlayer.readthedocs.io"
-Repository = "https://github.com/aritroCoder/promptlayer"
-Issues = "https://github.com/aritroCoder/promptlayer/issues"
+Homepage = "https://github.com/aritroCoder/PromptShift"
+Documentation = "https://PromptShift.readthedocs.io"
+Repository = "https://github.com/aritroCoder/PromptShift"
+Issues = "https://github.com/aritroCoder/PromptShift/issues"
 
 [build-system]
 requires = ["hatchling"]
 build-backend = "hatchling.build"
 
 [tool.hatch.build.targets.wheel]
-packages = ["src/promptlayer"]
+packages = ["src/PromptShift"]
 
 [tool.black]
 line-length = 100
@@ -113,7 +113,7 @@ exclude = [
 ]
 
 [tool.ruff.isort]
-known-first-party = ["promptlayer"]
+known-first-party = ["PromptShift"]
 
 [tool.mypy]
 python_version = "3.9"
@@ -145,7 +145,7 @@ python_functions = ["test_*"]
 addopts = [
     "-v",
     "--strict-markers",
-    "--cov=src/promptlayer",
+    "--cov=src/PromptShift",
     "--cov-report=html",
     "--cov-report=term-missing",
 ]
@@ -155,7 +155,7 @@ markers = [
 ]
 
 [tool.coverage.run]
-source = ["src/promptlayer"]
+source = ["src/PromptShift"]
 omit = ["tests/*", "**/__pycache__/*"]
 branch = true
 

src/promptlayer/__init__.py src/promptshift/__init__.pysrc/promptlayer/__init__.py renamed to src/promptshift/__init__.py

@@ -1,4 +1,4 @@
-"""PromptLayer: Reliable structured output from LLMs with deterministic generation."""
+"""PromptShift: Reliable structured output from LLMs with deterministic generation."""
 
 from __future__ import annotations
 
@@ -8,7 +8,7 @@
     AuthenticationError,
     CacheError,
     ModelCapabilityError,
-    PromptLayerError,
+    PromptShiftError,
     ProviderError,
     RateLimitError,
     RetryExhaustedError,
@@ -27,7 +27,7 @@
     "CacheKeyGenerator",
     "Client",
     "ModelCapabilityError",
-    "PromptLayerError",
+    "PromptShiftError",
     "ProviderError",
     "RateLimitError",
     "ResponseCache",

src/promptlayer/cache.py src/promptshift/cache.pysrc/promptlayer/cache.py renamed to src/promptshift/cache.py

@@ -27,7 +27,7 @@
 
 from pydantic import BaseModel
 
-from promptlayer.utils import pydantic_to_json_schema
+from promptshift.utils import pydantic_to_json_schema
 
 logger = logging.getLogger(__name__)
 

src/promptlayer/client.py src/promptshift/client.pysrc/promptlayer/client.py renamed to src/promptshift/client.py

@@ -1,4 +1,4 @@
-"""Core client class for PromptLayer library.
+"""Core client class for PromptShift library.
 
 This module provides the Client class, which is the primary user-facing API
 for generating structured output from LLMs.
@@ -71,7 +71,7 @@ class Client:
         Use separate Client instances for multi-threaded applications.
 
     Example:
-        >>> from promptlayer import Client
+        >>> from PromptShift import Client
         >>> from pydantic import BaseModel
         >>>
         >>> class Person(BaseModel):