Uv integration

api/routes/openai_route.py

@@ -1,5 +1,5 @@
 from fastapi import APIRouter, Depends, HTTPException
-from src.providers import get_provider
+from async_llm.providers import get_provider
 from models.openai_request_models import ChatCompletionRequest , FunctionCallRequest
 import json 
 import os

async_llm/__init__.py

@@ -0,0 +1 @@
+from async_llm import providers

src/providers/anthropic_provider.py → async_llm/providers/anthropic_provider.py

@@ -1,4 +1,4 @@
-from src.providers.abstract_basellm import BaseLLMProvider
+from async_llm.providers.abstract_basellm import BaseLLMProvider
 import httpx
 from typing import List, Dict
 import json

src/providers/google_provider.py → async_llm/providers/google_provider.py

@@ -1,24 +1,26 @@
-from src.providers.abstract_basellm import BaseLLMProvider
+from async_llm.providers.abstract_basellm import BaseLLMProvider
 import httpx
 from typing import List, Dict
-import json
 from urllib.parse import urljoin, urlencode
 
 class GoogleProvider(BaseLLMProvider):
     def __init__(self, api_key: str) -> None:
         super().__init__()
-        base_url = "https://generativelanguage.googleapis.com/v1beta/"
-        endpoint = "models/gemini-1.5-flash:generateContent"
-        query_params = {"key": api_key}
-
-        self.base_url = urljoin(base_url, endpoint) + "?" + urlencode(query_params)
         self.api_key = api_key
         self.headers = {
             "Content-Type": "application/json",
         }
 
-    async def chat_completion(self, messages: List[Dict[str, str]]):
-        url = self.base_url
+    def _create_base_url(self, model:str="gemini-1.5-flash"):
+        base_url = "https://generativelanguage.googleapis.com/v1beta/"
+        endpoint = f"models/{model}:generateContent"
+        query_params = {"key": self.api_key}
+        base_url = urljoin(base_url, endpoint) + "?" + urlencode(query_params)
+        return base_url
+
+    async def chat_completion(self, model:str, messages: List[Dict[str, str]]):
+        self.model = model
+        url = self._create_base_url(model)
         headers = self.headers
         data = {
             "contents": [

src/providers/openai_provider.py → async_llm/providers/openai_provider.py

@@ -1,5 +1,5 @@
-from src.providers.abstract_basellm import BaseLLMProvider
-from src.utils.pydantic_to_json import transform_schema
+from async_llm.providers.abstract_basellm import BaseLLMProvider
+from async_llm.utils.pydantic_to_json import transform_schema
 import httpx 
 from typing import List , Dict
 import json 

examples/anthropic_provider.py

@@ -2,7 +2,7 @@
 import logging
 import os
 from dotenv import load_dotenv
-from src.providers import get_provider  # Adjust this import based on your project structure
+from async_llm.providers import get_provider  # Adjust this import based on your project structure
 
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
 logger = logging.getLogger(__name__)

examples/openai_provider.py

@@ -1,7 +1,7 @@
 import asyncio
 import os
 from dotenv import load_dotenv
-from src.providers import get_provider
+from async_llm.providers import get_provider
 import logging
 from pydantic import BaseModel
 import sys 

pyproject.toml

@@ -0,0 +1,26 @@
+[build-system]
+requires = ["setuptools", "wheel"]
+build-backend = "setuptools.build_meta"
+
+[project]
+name = "async_llm"
+version = "0.0.1"
+description = "A Python package for asynchronous LLM integration."
+readme = "README.md"
+authors = [{ name = "Shamal De Silva", email = "shamalgithub@gmail.com" }, {name = "Sahan Ruwantha", email="sahanr.silva@proton.me"}]
+classifiers = [
+    "Programming Language :: Python :: 3",
+    "License :: OSI Approved :: MIT License",
+    "Operating System :: OS Independent"
+]
+dependencies = [
+    "fastapi>=0.112.2",
+    "httpx>=0.27.2",
+    "pydantic>=2.8.2",
+    "pytest>=8.3.2",
+    "python-dotenv>=1.0.1",
+    "setuptools>=58.1.0",
+    "pipreqs>=0.5.0",
+    "httpx[http2]>=0.27.2",
+    "pytest-asyncio>=0.24.0"
+]

setup.py

@@ -1,3 +1,3 @@
 from setuptools import setup , find_packages
 
-setup(name="AsyncLLM" , version="0.0.1" , packages=find_packages())
+setup(name="async_llm" , version="0.0.1" , packages=find_packages())

test/test_chat_completion_test.py

@@ -1,10 +1,10 @@
 import pytest
 import os
 from dotenv import load_dotenv
-from src.providers import get_provider
-from src.providers.openai_provider import OpenAIProvider
-from src.providers.anthropic_provider import ClaudeProvider
-from src.providers.google_provider import GoogleProvider
+from async_llm.providers import get_provider
+from async_llm.providers.openai_provider import OpenAIProvider
+from async_llm.providers.anthropic_provider import ClaudeProvider
+from async_llm.providers.google_provider import GoogleProvider
 
 load_dotenv()
 

test/test_google.py

@@ -1,4 +1,4 @@
-from src.providers import get_provider
+from async_llm.providers import get_provider
 import os
 from dotenv import load_dotenv
 import pytest
@@ -7,10 +7,11 @@
 
 @pytest.mark.asyncio
 async def test_google_chat_completion():
+    model = "gemini-2.0-flash-exp"
     messages = [
         {"role": "user", "content": "What's the capital of France?"}
     ]
     provider = get_provider("google", api_key=os.getenv("GOOGLE_API_KEY"))
-    result = await provider.chat_completion(messages=messages)
+    result = await provider.chat_completion(model=model, messages=messages)
     print(result)
     assert isinstance(result, dict)