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# Stream‑Mode AI Agent
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A lightweight LangChain agent that prints its output **as it is generated** using the `.stream()` API.
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The project demonstrates how to replace a single `.invoke()` call with streaming so that users see partial responses in real time.
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A lightweight LangChain agent that streams its responses token by token using the `rich` library for pretty console output.
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> **Why stream?**
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> When an LLM produces long answers or calls multiple tools, waiting for the whole result can feel like a freeze. Streaming gives instant feedback and improves UX.
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> When an LLM generates a long answer or calls multiple tools, waiting until the entire response is ready can feel like a freeze. Streaming lets you see the answer as it is produced, improving interactivity and user experience.
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---
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## 📦 Project Structure
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## 📦 Features
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```
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.
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├── agent.py # Agent definition with streaming support
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├── client.py # Simple CLI to interact with the agent
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└── README.md
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```
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- **agent.py** – creates an agent that uses a single tool (`get_price`) and streams its output.
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- **client.py** – runs the agent in a loop, reading user queries from stdin.
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- Uses **LangChain** for agent orchestration
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- Powered by **OpenAI GPT‑4o-mini** (or any OpenAI model)
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- Real‑time streaming via `llm.stream(...)`
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- Pretty console output with **rich**
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- Simple, single‑file implementation (`solution.py`)
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---
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## ⚙️ Prerequisites
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| Item | Version |
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|------|---------|
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| Item | Minimum Version |
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|------|-----------------|
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| Python | 3.10+ |
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| pip | latest |
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| LangChain | `>=0.2.0` |
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| Rich | `>=13.0` |
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| pip | – |
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| OpenAI API key | Set as environment variable `OPENAI_API_KEY` |
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> **Tip:** Use a virtual environment to keep dependencies isolated.
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> **Tip:** Create a virtual environment before installing dependencies.
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```bash
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python -m venv .venv
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source .venv/bin/activate # On Windows: .\.venv\Scripts\activate
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```
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---
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## 🚀 Installation
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## 📥 Installation
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```bash
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# Clone the repo (or copy the files)
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git clone https://github.com/your-username/stream-agent.git
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cd stream-agent
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# Create and activate a venv (optional but recommended)
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python -m venv .venv
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source .venv/bin/activate # Windows: .venv\Scripts\activate
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# Clone the repo (or copy solution.py into your project)
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git clone https://github.com/<your-username>/stream-ai-agent.git
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cd stream-ai-agent
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# Install dependencies
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pip install --upgrade pip
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pip install langchain rich
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pip install -r requirements.txt
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```
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> If you plan to use an OpenAI model, set the API key:
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> ```bash
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> export OPENAI_API_KEY="sk-..."
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> ```
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`requirements.txt`:
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```text
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langchain==0.2.*
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openai==1.*
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rich==13.*
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```
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> Adjust the version numbers if you prefer newer releases.
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---
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## 📖 Usage
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Run the client script and type your questions. The agent will stream its answer token‑by‑token.
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## 🚀 Running the Agent
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```bash
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python client.py
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export OPENAI_API_KEY="sk-..." # On Windows: set OPENAI_API_KEY=sk-...
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python solution.py
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```
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Example session:
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```
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$ python client.py
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Enter your query (Ctrl+C to exit):
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> What is the price of Bitcoin today?
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Agent: Checking price...
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Agent: Current BTC price is $42,300.00
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```
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The output appears progressively as the LLM generates it.
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The script will prompt you for a question. Type your query and press **Enter**.
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You’ll see the answer appear token by token in real time.
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---
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## 🛠️ Customization
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## 📄 Example
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- **Add more tools** – decorate a function with `@tool` and pass it to `create_agent`.
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- **Change model** – modify the `model_name` argument in `agent.py`.
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- **Adjust streaming format** – tweak the `stream()` call or use Rich’s live rendering for fancy UI.
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```text
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$ python solution.py
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🤖 What is the capital of France?
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🇫🇷 Paris
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```
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The agent will stream each word (or token) as it arrives, giving a smooth typing‑like effect.
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---
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## 📄 License
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## 🔧 Customization
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MIT © 2026
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- **Change model** – edit `model="gpt-4o-mi"` in `solution.py`.
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- **Add tools** – decorate functions with `@tool` and include them in the agent.
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- **Adjust temperature** – modify `temperature=0` to a higher value for more creativity.
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---
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---
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## 📚 Further Reading
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- [LangChain Docs](https://langchain.com/docs/)
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- [OpenAI API Reference](https://platform.openai.com/docs/api-reference)
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- [Rich Library](https://rich.readthedocs.io/en/stable/)
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---
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Happy streaming! 🚀
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