DeepSeek Launches Advanced Function Calling Capabilities
Published: August 2, 2024
DeepSeek today announced the launch of advanced function calling capabilities, enabling developers to build more sophisticated AI applications with seamless integration to external tools and services.
New Function Calling Features
Enhanced Function Definition
- Structured function schemas with detailed parameter validation
- Nested object support for complex data structures
- Optional and required parameters with default values
- Type validation for improved reliability
Improved Execution
- Parallel function calls for better performance
- Automatic retry mechanisms for failed calls
- Enhanced error handling with detailed diagnostics
- Function call chaining for complex workflows
Advanced Capabilities
- Dynamic function discovery from API specifications
- Function call optimization for reduced latency
- Intelligent parameter mapping from natural language
- Real-time function validation during execution
Technical Implementation
Function Schema Example
json
{
"name": "get_weather",
"description": "Get current weather information for a location",
"parameters": {
"type": "object",
"properties": {
"location": {
"type": "string",
"description": "City name or coordinates"
},
"units": {
"type": "string",
"enum": ["celsius", "fahrenheit"],
"default": "celsius"
},
"include_forecast": {
"type": "boolean",
"description": "Include 5-day forecast",
"default": false
}
},
"required": ["location"]
}
}Parallel Function Calls
python
import asyncio
from deepseek import DeepSeek
client = DeepSeek(api_key="your-api-key")
async def parallel_function_calls():
response = await client.chat.completions.create(
model="deepseek-chat",
messages=[
{
"role": "user",
"content": "Get weather for New York and London, and also search for flights between them"
}
],
functions=[
get_weather_function,
search_flights_function
],
parallel_function_calls=True
)
return response
# Execute multiple functions simultaneously
result = asyncio.run(parallel_function_calls())Use Cases
API Integration
- REST API calls with automatic parameter mapping
- Database queries with natural language interfaces
- Third-party service integration for enhanced functionality
- Webhook triggers for real-time notifications
Workflow Automation
- Multi-step processes with function chaining
- Conditional logic based on function results
- Error handling and recovery for robust workflows
- Data transformation between different formats
Real-time Applications
- Live data retrieval from external sources
- Dynamic content generation based on current information
- Interactive applications with immediate responses
- Streaming updates for real-time experiences
Developer Benefits
Simplified Integration
- No complex parsing of AI responses
- Automatic parameter validation reduces errors
- Standardized error handling across all functions
- Built-in retry logic for improved reliability
Enhanced Performance
- Parallel execution reduces total response time
- Optimized function calls minimize API overhead
- Intelligent caching for frequently used functions
- Reduced token usage through efficient processing
Better User Experience
- More accurate responses with real-time data
- Faster application performance through optimization
- Reliable function execution with error recovery
- Seamless integration with existing systems
Getting Started
Basic Function Call
python
from deepseek import DeepSeek
client = DeepSeek(api_key="your-api-key")
# Define a simple function
def calculate_tip(bill_amount, tip_percentage=15):
"""Calculate tip amount for a bill"""
return {
"tip_amount": bill_amount * (tip_percentage / 100),
"total_amount": bill_amount * (1 + tip_percentage / 100)
}
# Use function in chat
response = client.chat.completions.create(
model="deepseek-chat",
messages=[
{
"role": "user",
"content": "Calculate a 20% tip for a $85 dinner bill"
}
],
functions=[
{
"name": "calculate_tip",
"description": "Calculate tip and total for a bill",
"parameters": {
"type": "object",
"properties": {
"bill_amount": {"type": "number"},
"tip_percentage": {"type": "number", "default": 15}
},
"required": ["bill_amount"]
}
}
]
)
print(response.choices[0].message.content)Advanced Function Chaining
python
# Chain multiple functions for complex workflows
response = client.chat.completions.create(
model="deepseek-chat",
messages=[
{
"role": "user",
"content": "Find the weather in Tokyo, then recommend appropriate clothing"
}
],
functions=[
get_weather_function,
recommend_clothing_function
],
function_call_mode="auto_chain"
)Documentation and Resources
Comprehensive Guides
Pricing
Function calling is included in all DeepSeek API plans with no additional charges. You only pay for the tokens used in the conversation and function definitions.
Token Usage
- Function definitions: Counted once per conversation
- Function calls: Minimal token overhead
- Function responses: Standard token rates apply
Customer Success Stories
E-commerce Platform
"The new function calling capabilities allowed us to integrate real-time inventory checks directly into our customer service chatbot. Response accuracy improved by 40%."
— Lisa Wang, Engineering Manager at ShopFlow
Financial Services
"We can now provide real-time market data and execute trades through natural language interfaces. The parallel function calls feature significantly improved our application performance."
— David Kim, Senior Developer at FinTech Solutions
What's Coming Next
DeepSeek is continuing to enhance function calling capabilities with upcoming features:
- Visual function builders for no-code function creation
- Function marketplace for sharing and discovering functions
- Advanced debugging tools for function development
- Enterprise function management for large-scale deployments
About DeepSeek: DeepSeek is a leading provider of AI APIs and services, empowering developers and enterprises to build intelligent applications with state-of-the-art language models and advanced capabilities.