Added Basic Function Calling Support

Author: SreejanPersonal

CHANGELOG.md

@@ -5,6 +5,23 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [0.1.2] - 2024-11-09
+### Added
+- Enhanced Function Calling support with improved tool calls handling
+- Added comprehensive test suite with example usage
+- Added proper error handling for API responses
+
+### Changed
+- Improved URL handling in BaseAPIHandler
+- Enhanced ChatMessage class to handle tool calls and function calls
+- Updated type hints and documentation
+- Restructured code for better maintainability
+
+### Fixed
+- URL joining issues in API requests
+- Stream handling improvements
+- Better error handling for API responses
+
 ## [0.1.1] - 2024-11-08
 ### Added
 - Updated the README file for better visual understanding.
@@ -16,4 +33,6 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 ### Added
 - Initial release
 
-[0.1.0]: https://github.com/SreejanPersonal/openai-unofficial/releases/tag/v1.0.0
+[0.1.2]: https://github.com/SreejanPersonal/openai-unofficial/compare/v0.1.1...v0.1.2
+[0.1.1]: https://github.com/SreejanPersonal/openai-unofficial/compare/v0.1.0...v0.1.1
+[0.1.0]: https://github.com/SreejanPersonal/openai-unofficial/releases/tag/v0.1.0

README.md

@@ -21,6 +21,8 @@ An Free & Unlimited unofficial Python SDK for the OpenAI API, providing seamless
   - [Chat Completion with Audio Preview Model](#chat-completion-with-audio-preview-model)
   - [Image Generation](#image-generation)
   - [Audio Speech Recognition with Whisper Model](#audio-speech-recognition-with-whisper-model)
+  - [Function Calling and Tool Usage](#function-calling-and-tool-usage)
+    - [Basic Function Calling](#basic-function-calling)
 - [Contributing](#contributing)
 - [License](#license)
 
@@ -45,7 +47,7 @@ An Free & Unlimited unofficial Python SDK for the OpenAI API, providing seamless
 Install the package via pip:
 
 ```bash
-pip install openai-unofficial
+pip install -U openai-unofficial
 ```
 
 ---
@@ -203,6 +205,95 @@ with open("speech.mp3", "rb") as audio_file:
 print("Transcription:", transcription.text)
 ```
 
+### Function Calling and Tool Usage
+
+The SDK supports OpenAI's function calling capabilities, allowing you to define and use tools/functions in your conversations. Here are examples of function calling & tool usage:
+
+#### Basic Function Calling
+
+> ⚠️ **Important Note**: In the current version (0.1.2), complex or multiple function calling is not yet fully supported. The SDK currently supports basic function calling capabilities. Support for multiple function calls and more complex tool usage patterns will be added in upcoming releases.
+
+```python
+from openai_unofficial import OpenAIUnofficial
+import json
+
+client = OpenAIUnofficial()
+
+# Define your functions as tools
+tools = [
+    {
+        "type": "function",
+        "function": {
+            "name": "get_current_weather",
+            "description": "Get the current weather in a given location",
+            "parameters": {
+                "type": "object",
+                "properties": {
+                    "location": {
+                        "type": "string",
+                        "description": "The city and state, e.g., San Francisco, CA"
+                    },
+                    "unit": {
+                        "type": "string",
+                        "enum": ["celsius", "fahrenheit"],
+                        "description": "The temperature unit"
+                    }
+                },
+                "required": ["location"]
+            }
+        }
+    }
+]
+
+# Function to actually get weather data
+def get_current_weather(location: str, unit: str = "celsius") -> str:
+    # This is a mock function - replace with actual weather API call
+    return f"The current weather in {location} is 22°{unit[0].upper()}"
+
+# Initial conversation message
+messages = [
+    {"role": "user", "content": "What's the weather like in London?"}
+]
+
+# First API call to get function calling response
+response = client.chat.completions.create(
+    model="gpt-4o-mini-2024-07-18",
+    messages=messages,
+    tools=tools,
+    tool_choice="auto"
+)
+
+# Get the assistant's message
+assistant_message = response.choices[0].message
+messages.append(assistant_message.to_dict())
+
+# Check if the model wants to call a function
+if assistant_message.tool_calls:
+    # Process each tool call
+    for tool_call in assistant_message.tool_calls:
+        function_name = tool_call.function.name
+        function_args = json.loads(tool_call.function.arguments)
+        
+        # Call the function and get the result
+        function_response = get_current_weather(**function_args)
+        
+        # Append the function response to messages
+        messages.append({
+            "role": "tool",
+            "tool_call_id": tool_call.id,
+            "name": function_name,
+            "content": function_response
+        })
+    
+    # Get the final response from the model
+    final_response = client.chat.completions.create(
+        model="gpt-4o-mini-2024-07-18",
+        messages=messages
+    )
+    
+    print("Final Response:", final_response.choices[0].message.content)
+```
+
 ---
 
 ## Contributing

pyproject.toml

@@ -4,17 +4,28 @@ build-backend = "hatchling.build"
 
 [project]
 name = "openai-unofficial"
-version = "0.1.1"
+version = "0.1.2"
 authors = [
   { name="DevsDoCode", email="devsdocode@gmail.com" },
 ]
-description = "Unofficial OpenAI API Python SDK"
+description = "Free & Unlimited Unofficial OpenAI API Python SDK - Supports all OpenAI Models & Endpoints"
 readme = "README.md"
 requires-python = ">=3.7"
+keywords = ["openai", "ai", "machine-learning", "chatgpt", "gpt", "dall-e", "text-to-speech", "api", "tts"]
+license = { text = "MIT" }
 classifiers = [
-    "Programming Language :: Python :: 3",
+    "Development Status :: 4 - Beta",
+    "Intended Audience :: Developers",
     "License :: OSI Approved :: MIT License",
     "Operating System :: OS Independent",
+    "Programming Language :: Python :: 3",
+    "Programming Language :: Python :: 3.7",
+    "Programming Language :: Python :: 3.8",
+    "Programming Language :: Python :: 3.9",
+    "Programming Language :: Python :: 3.10",
+    "Programming Language :: Python :: 3.11",
+    "Topic :: Software Development :: Libraries :: Python Modules",
+    "Topic :: Scientific/Engineering :: Artificial Intelligence",
 ]
 dependencies = [
     "requests>=2.28.0",
@@ -23,9 +34,10 @@ dependencies = [
 [project.urls]
 "Homepage" = "https://github.com/SreejanPersonal/openai-unofficial"
 "Bug Tracker" = "https://github.com/SreejanPersonal/openai-unofficial/issues"
+"Youtube" = "https://www.youtube.com/@DevsDoCode"
+"Instragram" = "https://www.instagram.com/sree.shades_/"
+"LinkedIn" = "https://www.linkedin.com/in/developer-sreejan/"
+"Twitter" = "https://twitter.com/Anand_Sreejan"
 
 [tool.hatch.build.targets.wheel]
-packages = ["src/openai_unofficial"]
-
-# python -m build
-# python -m twine upload dist/*
+packages = ["src/openai_unofficial"]

src/openai_unofficial/__init__.py

@@ -1,4 +1,4 @@
 from .main import OpenAIUnofficial
 
-__version__ = "0.1.1"
+__version__ = "0.1.2"
 __all__ = ["OpenAIUnofficial"]

src/openai_unofficial/main.py

@@ -1,12 +1,11 @@
 import requests
 import json
-from typing import Optional, List, Union, Dict, Any, Iterator, TypeVar, Generic
+from typing import Optional, List, Union, Dict, Any, Iterator, TypeVar
 from abc import ABC, abstractmethod
 from dataclasses import dataclass
 from enum import Enum
 import logging
 from urllib.parse import urljoin
-import base64
 
 # Configure logging
 logging.basicConfig(level=logging.INFO)
@@ -49,7 +48,7 @@ def _create_session(self) -> requests.Session:
         return session
 
     def _make_request(self, method: str, endpoint: str, **kwargs) -> requests.Response:
-        url = urljoin(self.config.base_url, endpoint)
+        url = urljoin(self.config.base_url + '/', endpoint)
         try:
             response = self.session.request(
                 method=method,
@@ -70,25 +69,64 @@ class BaseModel(ABC):
     def to_dict(self) -> Dict[str, Any]:
         pass
 
+class FunctionCall(BaseModel):
+    def __init__(self, data: Dict[str, Any]):
+        self.name = data.get('name')
+        self.arguments = data.get('arguments')
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            'name': self.name,
+            'arguments': self.arguments
+        }
+
+class ToolCall(BaseModel):
+    def __init__(self, data: Dict[str, Any]):
+        self.id = data.get('id')
+        self.type = data.get('type')
+        self.function = FunctionCall(data.get('function', {})) if data.get('function') else None
+    
+    def to_dict(self) -> Dict[str, Any]:
+        return {
+            'id': self.id,
+            'type': self.type,
+            'function': self.function.to_dict() if self.function else None
+        }
+
 class ChatMessage(BaseModel):
     def __init__(self, data: Dict[str, Any]):
         self.role = data.get('role')
         self.content = data.get('content')
+        self.function_call = FunctionCall(data.get('function_call', {})) if data.get('function_call') else None
+        self.tool_calls = [ToolCall(tc) for tc in data.get('tool_calls', [])] if data.get('tool_calls') else []
         self.audio = data.get('audio')
-
+        # For messages of role 'tool', include 'tool_call_id' and 'name'
+        self.tool_call_id = data.get('tool_call_id')
+        self.name = data.get('name')
+        
     def to_dict(self) -> Dict[str, Any]:
-        return {
-            'role': self.role,
-            'content': self.content,
-            **({'audio': self.audio} if self.audio else {})
-        }
+        message_dict = {'role': self.role}
+        if self.content is not None:
+            message_dict['content'] = self.content
+        if self.function_call is not None:
+            message_dict['function_call'] = self.function_call.to_dict()
+        if self.tool_calls:
+            message_dict['tool_calls'] = [tool_call.to_dict() for tool_call in self.tool_calls]
+        if self.audio is not None:
+            message_dict['audio'] = self.audio
+        if self.role == 'tool':
+            if self.tool_call_id:
+                message_dict['tool_call_id'] = self.tool_call_id
+            if self.name:
+                message_dict['name'] = self.name
+        return message_dict
 
 class ChatCompletionChoice(BaseModel):
     def __init__(self, data: Dict[str, Any]):
         self.index = data.get('index')
         self.message = ChatMessage(data.get('message', {}))
         self.finish_reason = data.get('finish_reason')
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'index': self.index,
@@ -104,7 +142,7 @@ def __init__(self, data: Dict[str, Any]):
         self.model = data.get('model')
         self.choices = [ChatCompletionChoice(choice) for choice in data.get('choices', [])]
         self.usage = data.get('usage')
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'id': self.id,
@@ -122,7 +160,7 @@ def __init__(self, data: Dict[str, Any]):
         self.created = data.get('created')
         self.model = data.get('model')
         self.choices = [ChatCompletionChunkChoice(choice) for choice in data.get('choices', [])]
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'id': self.id,
@@ -137,7 +175,7 @@ def __init__(self, data: Dict[str, Any]):
         self.index = data.get('index')
         self.delta = ChatMessage(data.get('delta', {}))
         self.finish_reason = data.get('finish_reason')
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'index': self.index,
@@ -149,7 +187,7 @@ class ImageGenerationResponse(BaseModel):
     def __init__(self, data: Dict[str, Any]):
         self.created = data.get('created')
         self.data = [ImageData(item) for item in data.get('data', [])]
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'created': self.created,
@@ -160,7 +198,7 @@ class ImageData(BaseModel):
     def __init__(self, data: Dict[str, Any]):
         self.url = data.get('url')
         self.b64_json = data.get('b64_json')
-
+    
     def to_dict(self) -> Dict[str, Any]:
         return {
             'url': self.url,
@@ -173,7 +211,7 @@ def __init__(self, api_handler: BaseAPIHandler):
 
     def create(
         self,
-        messages: List[Dict[str, str]],
+        messages: List[Dict[str, Any]],
         model: str = "gpt-4o-mini-2024-07-18",
         temperature: float = 0.7,
         top_p: float = 1.0,
@@ -182,6 +220,8 @@ def create(
         frequency_penalty: float = 0,
         modalities: List[str] = None,
         audio: Dict[str, str] = None,
+        tools: List[Dict[str, Any]] = None,
+        tool_choice: str = None,
         **kwargs
     ) -> Union[ChatCompletionResponse, Iterator[ChatCompletionChunk]]:
         payload = {
@@ -199,6 +239,10 @@ def create(
             payload["modalities"] = modalities
         if audio:
             payload["audio"] = audio
+        if tools:
+            payload["tools"] = tools
+        if tool_choice:
+            payload["tool_choice"] = tool_choice
 
         if stream:
             response = self.api_handler._make_request(
@@ -227,7 +271,7 @@ def _handle_streaming_response(self, response: requests.Response) -> Iterator[Ch
                         line_str = line_str[len('data: '):]
                     data = json.loads(line_str)
                     yield ChatCompletionChunk(data)
-                except:
+                except Exception as e:
                     continue
 
 class Audio: