1. The Prompt Struggle is Real 😅
We've all been there—spending countless hours tweaking AI prompts, trying to get the perfect response from language models. Static prompts often lead to inconsistent results, leaving us frustrated and yearning for a smarter solution. ⚡Enter DoCoreAI
2. Introducing DoCoreAI: The Game-Changer 🎯
DoCoreAI is a next-gen open-source AI profiler that optimizes reasoning, creativity, precision, and temperature in a single step—cutting token usage by 15-30% and lowering LLM API costs.
It dynamically adjusts intelligence parameters, tailoring prompts for various AI roles, and ensures more accurate and efficient responses. This means less time spent on manual prompt engineering and more on building impactful applications.
Why Game-Changer?: ⚡ AI Meets Cognitive Intelligence
What if AI could think smarter, not harder? DoCoreAI introduces dynamic intelligence profiling, optimizing LLM interactions with human-like reasoning, creativity, and precision—a game-changer for developers building next-gen AI solutions.
DoCoreAI isn’t just evolving with AI innovation—it’s pioneering a revolution.
3. Under the Hood: How It Works ⚙️
Every DoCoreAI prompt is context-aware, with a role assigned to each query, ensuring accurate intent recognition.
The core cognitive skills of human intelligence— Reasoning, Creativity, and Precision —are dynamically analyzed.
DoCoreAI predicts the optimal levels of these skills based on the context of the prompt.
The carefully crafted system message instructs the AI to predict and assign these values dynamically based on context.
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The temperature (T) is then predicted and set based on these values:
- - C = Creativity
- - P = Precision
- - R = Reasoning
The LLM then generates responses using these intelligence parameters, optimizing for accuracy, coherence, and efficiency—all in a single step.
🔹 What does this mean?
Instead of manual tuning, DoCoreAI self-optimizes prompts, making LLMs more intelligent, cost-efficient, and effective. 🚀
At its core, DoCoreAI utilizes intelligence profiling to fine-tune key parameters:
- Reasoning: Enhances the AI's logical processing capabilities.
- Creativity: Adjusts the model's ability to generate innovative responses.
- Precision: Controls the specificity and accuracy of outputs.
- Temperature: Modulates the randomness of the AI's responses.
By optimizing these parameters dynamically, DoCoreAI ensures that AI responses are contextually appropriate and role-specific.
👉Read more...
Show Me the Code! 🚀
Let's dive into an example to understand basic DoCoreAI:
from docore_ai import intelligence_profiler
# Initialize DoCoreAI with your API key
OPENAI_API_KEY = os.getenv("OPENAI_API_KEY")
# Define your prompt
prompt = "Explain the theory of relativity in simple terms."
# Optimize the prompt for a 'Teacher' role
optimized_prompt = intelligence_profiler(prompt, role='Physics Teacher')
# Get the AI's response
response = clean_response(optimized_prompt)
print(response)In this snippet:
- We initialize DoCoreAI with an OpenAI API key.
- Define a prompt asking for an explanation of the theory of relativity.
- Optimize the prompt for a 'Teacher' role, which adjusts the intelligence parameters accordingly.
- Retrieve and print the AI's response.
This approach ensures that the AI provides a clear and concise explanation suitable for teaching.
4. Why Should You Care? 🤔
Implementing DoCoreAI offers several benefits:
Sharper AI responses: Role-aware optimizations lead to more relevant outputs.
Time-saving for Developers: Reduces the need for manual prompt adjustments.
Cost-efficient: Optimized prompts can cut token usage by 15-30%, lowering API costs.
5. Get Started in 30 Seconds! ⏳
Ready to enhance your AI prompts? Here's how to get started:
- Installation:
pip install docoreaiExplore the 👉GitHub Repository: Check out the DoCoreAI GitHub repo for more details and contribute to the project.
Join the Community: Share your experiences, provide feedback, and collaborate with other developers to improve DoCoreAI.
📺 DoCoreAI: The End of AI Trial & Error Begins Now!
6. The Future of AI Prompting 🚀
Imagine an AI that always knows exactly how to respond, adapting dynamically to various contexts and roles. With tools like DoCoreAI, we're moving closer to that reality, making AI interactions more intuitive and efficient.
Time for Action 🎬:
Fork the repo & experiment 🛠️
Share feedback—what use cases would YOU optimize? 🤔
Drop a comment with your thoughts & improvements!
Let's revolutionize AI prompting together!
To Summarize DoCoreAI:
✔ Analyses the Complexity of the query/user-request
✔ Adds the Intelligence required via intelligence parameters
✔ Responds on Role-based expertise (e.g., technical support vs. creative storytelling)
✔ Automatically decides the response content structure
✔ Predicts the optimal temperature required for your prompt
✔ Efficient Response based on the predefined intelligence parameters
✔ Saves tokens providing monetary benefits
Besides, eliminates the pain of manually tweaking temperature and other parameters
🔬 Experimenting with Intelligence Parameters
We tested DoCoreAI by comparing responses for the same question with and without intelligence profiling.
💡 Eg Query: "How to connect an Apple computer to my network?"
🔍 Conclusion: DoCoreAI enhances responses by tailoring reasoning, creativity, and precision dynamically.
🛠️ Future of DoCoreAI
The journey for DoCoreAI is just beginning...
We envision DoCoreAI as an essential AI tool for redefining prompt engineering, customer support automation, and personalized AI interactions.
Next Steps:
🔹 Work in progress: > Evals & Benchmarks
🔹 Open-source release
🔹 Blog series explaining key use cases
🔹 Optimizations for additional AI providers
🚀 Try DoCoreAI today and let AI think smarter, not just generate text.
📌 Detailed Content:
Want to dive deeper into the concept of Intelligent Prompt Optimization? Check out my detailed write-up on Medium:
Intelligent Prompt Optimization
Pypi: DoCoreAI
Care to ⭐Star the repo:
What do you think about DoCoreAI? Let’s discuss in the comments! 💬🔥
