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const { OpenAI } = require('openai');
const api = new OpenAI({
baseURL: 'https://api.ai.cc/v1',
apiKey: '',
});
const main = async () => {
const result = await api.chat.completions.create({
model: 'codellama/CodeLlama-70b-Python-hf',
messages: [
{
role: 'system',
content: 'You are SQL code assistant.',
},
{
role: 'user',
content: 'Could you please provide me with an example of a database structure that I could use for a project in MySQL?'
}
],
});
const message = result.choices[0].message.content;
console.log(\`Assistant: \${message}\`);
};
main();
import os
from openai import OpenAI
def main():
client = OpenAI(
api_key="",
base_url="https://api.ai.cc/v1",
)
response = client.chat.completions.create(
model="codellama/CodeLlama-70b-Python-hf",
messages=[
{
"role": "system",
"content": "You are SQL code assistant.",
},
{
"role": "user",
"content": "Could you please provide me with an example of a database structure that I could use for a project in MySQL?",
},
],
)
message = response.choices[0].message.content
print(f"Assistant: {message}")
if __name__ == "__main__":
main()
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Product Detail
Code Llama Python (70B): An Advanced AI for Python Development
Code Llama Python (70B) represents a groundbreaking artificial intelligence model meticulously engineered to enhance Python programming workflows. Boasting an impressive 70 billion parameters, this model demonstrates a sophisticated comprehension of coding structures, syntax rules, and logical patterns. It serves as an invaluable asset for developers aiming to generate, optimize, and refine Python code, ultimately leading to the creation of more efficient, robust, and innovative applications.
✨ Why Code Llama Python (70B) Stands Out Among AI Models
Distinguishing itself from conventional models, Code Llama Python (70B) boasts an unparalleled specialized focus on Python development. This dedicated architecture, coupled with its immense parameter count, enables a significantly deeper understanding and superior code generation capabilities compared to models with fewer parameters. This specialization is crucial for effectively tackling complex Python coding challenges and delivering highly accurate, context-aware coding suggestions for Python programmers. (Information adapted from the original section: "How does it compare to other models?")
💡 Maximizing Interaction Quality for Optimal Python Code
To unlock the full potential of Code Llama Python (70B), users are encouraged to provide explicit and concise coding requirements or questions. The model achieves its best performance when supplied with detailed context and specific objectives. This approach ensures the generated or suggested code precisely aligns with the user's intended needs and specifications, leading to highly relevant and effective Python code. (Insights derived from the original section: "Tips for Maximizing Interaction Quality")
💻 Optimizing Code Llama Python (70B) for Diverse Scenarios
The inherent flexibility of Code Llama Python (70B) allows it to seamlessly adapt to a broad spectrum of coding tasks. This ranges from generating simple code snippets to developing complex algorithms and intricate software architecture designs. By tailoring the model for specific coding styles or unique project requirements, developers can fully harness its capabilities to streamline their Python programming endeavors and foster greater innovation across various project types. (Based on the original section: "Optimizing for Different Scenarios")
📄 API Integration Example for Code Llama Python (70B)
For developers interested in integrating Code Llama Python (70B) into their applications, an API example is provided below. This snippet illustrates how to interact with the model for code completion or generation tasks.
from openai import OpenAI
client = OpenAI()
completion = client.chat.completions.create(
model="codellama/CodeLlama-70b-Python-hf",
messages=[
{
"role": "system",
"content": "You are a helpful AI assistant specialized in Python."
},
{
"role": "user",
"content": "Write a Python function to calculate the factorial of a number."
}
],
temperature=0.7,
max_tokens=150
)
print(completion.choices[0].message.content)
❓ Frequently Asked Questions (FAQ) about Code Llama Python (70B)
1. What is Code Llama Python (70B)?
Code Llama Python (70B) is an advanced artificial intelligence model with 70 billion parameters, specifically trained and optimized for various Python programming tasks, including code generation, optimization, and bug fixing.
2. How do its 70 billion parameters enhance its capabilities?
The substantial number of parameters allows the model to achieve a much deeper and more nuanced understanding of Python's intricate patterns and logic. This leads to more accurate, sophisticated, and contextually relevant code suggestions and generations, making it highly effective for complex problems.
3. Can Code Llama Python (70B) assist with large and complex Python projects?
Yes, its specialized focus and vast knowledge base make it exceptionally well-suited for a wide range of tasks, from generating simple code snippets to assisting with complex algorithms, designing software architecture, and providing support for large-scale project development.
4. What are the best practices for optimal interaction with the model?
For the most accurate and relevant outputs, it is recommended to provide clear, concise, and detailed coding requirements or questions. Supplying specific objectives and comprehensive context significantly enhances the model's ability to meet your exact needs.
5. How easy is it to integrate Code Llama Python (70B) into existing development workflows?
While the exact integration process depends on your specific environment, the model is designed to be accessible via standard API calls, similar to other large language models. This allows for straightforward programmatic access, making it relatively easy to incorporate its powerful capabilities into your current development tools and processes.
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