J.A.R.V.I.S.: Update 2.1.3-0625 to 2025-06-11.

README.md

@@ -7,6 +7,7 @@ base_model:
 tags:
 - jarvis
 - ollama
+- agent
 ---
 
 **J.A.R.V.I.S.**, which stands for "**Just a Rather Very Intelligent System**", is an advanced AI language model inspired by [Iron Man](https://wikipedia.org/wiki/J.A.R.V.I.S.) iconic assistant. This model delivers context-aware, high-fidelity natural language processing capabilities for a wide range of applications.
@@ -16,9 +17,11 @@ tags:
 ## Model Highlights
 
 - **Powerful Text Generation Engine**      
+<video src="https://gitlab.com/hdrjt/assets/-/raw/master/videos/JARVIS_chat.mp4" controls>Your browser does not support the video tag.</video>
 **J.A.R.V.I.S.** serves as the core of an AI solution capable of producing natural and creative text with high quality, ready to help you create inspiring and engaging content.
 
 - **Seamless Integration, Limitless Possibilities**      
+<video src="https://gitlab.com/hdrjt/assets/-/raw/master/videos/JARVIS_demo.mp4" controls>Your browser does not support the video tag.</video>
 Designed with high flexibility, **J.A.R.V.I.S.** can be seamlessly integrated into a wide range of platforms and systems you use, including web applications, chatbots, agent modes, tools, system integrations, and automated workflows, adapting effortlessly to available resource capacities.
 
 - **Scalable & Resource-Aware**      
@@ -28,6 +31,7 @@ Regardless of your computing environment, **J.A.R.V.I.S.** can be optimized for
 Ideal for a wide range of needs, from creative content creation, writing assistance, to developing interactive text-based applications, giving you unlimited freedom to innovate.
 
 - **Agentic Use**      
+<video src="https://gitlab.com/hdrjt/assets/-/raw/master/videos/JARVIS_agent.mp4" controls>Your browser does not support the video tag.</video>
 Example usage, please refer to the [Qwen3 Documentation](https://huggingface.co/dulimov/Qwen3-0.6B-rk3588-1.2.1-unsloth-16k#agentic-use), and the [Qwen-Agent GitHub repository](https://github.com/QwenLM/Qwen-Agent).
 
 **J.A.R.V.I.S.** is not just an AI model, it is an intelligent partner ready to transform your ideas into words with a touch of intelligence and high flexibility.
@@ -106,6 +110,59 @@ with torch.inference_mode():
     )
 ```
 
+## API
+
+**J.A.R.V.I.S.** offers API support for both general users and developers for free.
+
+For **general users**, it can be operated directly through the local terminal on Linux, Termux, macOS, or Windows (WSL) without requiring any special configuration.
+
+```bash
+# Installations.
+# Make sure you have "wget", "python3" and "pip" installed.
+# This package have very small size.
+wget https://huggingface.co/spaces/hadadrjt/ai/raw/main/assets/bin/install.sh && chmod a+x install.sh && ./install.sh
+```
+
+```bash
+# Run J.A.R.V.I.S. in your terminal.
+# Example normal usage.
+./ai Your message here.
+
+# Example with Deep Search.
+./ai -d Your message here.
+```
+
+```bash
+# Linux user's
+# Bonus for more flexible.
+sudo mv ai /bin/
+
+# Now you can run with simple command.
+ai Your message here.
+```
+
+For **developers**, an OpenAI-compatible API is available, facilitating seamless integration with various systems. Additionally, this API endpoint is open source and can be accessed [here](https://huggingface.co/spaces/hadadrjt/api).
+
+<video src="https://gitlab.com/hdrjt/assets/-/raw/master/videos/JARVIS_api.mp4" controls>
+  Your browser does not support the video tag.
+</video>
+
+```bash
+# OpenAI Style (developers only)
+curl https://hadadrjt-api.hf.space/v1/responses \
+  -H "Content-Type: application/json" \
+  -d '{
+    "model": "JARVIS: 2.1.3",
+    "input": "Write a one-sentence bedtime story about a unicorn.",
+    "stream": true
+  }'
+```
+
+```
+# Endpoint
+https://hadadrjt-api.hf.space/v1
+```
+
 ## Responsible Use
 
 Although **J.A.R.V.I.S.** delivers impressive results, it may reflect biases from its training data and occasionally produce incorrect outputs. It is not intended for real-time safety-critical applications without human oversight. I recommend implementing human review workflows, monitoring outputs for fairness and accuracy, and updating the model with domain-specific data over time.

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