update readmee

README.md

@@ -10,3 +10,151 @@ pinned: true
 license: apache-2.0
 short_description: deepseek chat - huggingface api
 ---
+Below is the content for a `README.md` file that you can include in your project to provide an overview of the code, its requirements, and how to use it:
+
+---
+
+# 🐳 Chat with DeepSeek 🐳
+
+This is a Streamlit-based web application that allows users to interact with the **DeepSeek-R1-Distill-Qwen-32B** model hosted on Hugging Face. The application uses the Hugging Face Inference API to generate responses to user queries.
+
+---
+## 🧑‍💻 Author
+Sachin Tiwari
+
+---
+## 🚀 Features
+
+- **Interactive Chat Interface**: Users can input questions and receive responses from the DeepSeek model.
+- **Thinking Process Visualization**: If the model's response contains `<think>` tags, the app displays the thinking process in an expandable section.
+- **Secure API Key Input**: Users can securely input their Hugging Face API key to authenticate and use the model.
+
+---
+
+## 📋 Requirements
+
+To run this application, you need the following Python packages:
+
+- `streamlit`: For building the web interface.
+- `huggingface_hub`: For interacting with the Hugging Face Inference API.
+
+You can install the required packages using the following command:
+
+```bash
+pip install streamlit huggingface_hub
+```
+
+---
+
+## 🛠️ How to Use
+
+1. **Clone the Repository**:
+   ```bash
+   git clone <https://github.com/aitiwari/Deepseek_Chat_HF.git>
+   cd <Deepseek_Chat_HF>
+   ```
+
+2. **Run the Application**:
+   Start the Streamlit app by running the following command:
+   ```bash
+   streamlit run app.py
+   ```
+
+3. **Enter Your Hugging Face API Key**:
+   - Open the app in your browser.
+   - In the sidebar, enter your Hugging Face API key in the provided input box.
+
+4. **Chat with DeepSeek**:
+   - Once the API key is entered, you can start chatting with the DeepSeek model by typing your questions in the chat input box.
+
+---
+
+## 🧑‍💻 Code Overview
+
+The application is built using the following components:
+
+- **Streamlit UI**: The interface is created using Streamlit, with a sidebar for API key input and a main area for chat interactions.
+- **Hugging Face Inference API**: The `InferenceClient` from the `huggingface_hub` library is used to send requests to the DeepSeek model.
+- **Response Parsing**: The app checks for `<think>` tags in the model's response and displays the thinking process separately.
+
+Here’s the main code snippet:
+
+```python
+import streamlit as st
+from huggingface_hub import InferenceClient
+
+# Streamlit UI
+st.title("🐳 Chat with DeepSeek 🐳")
+
+with st.sidebar:
+    # Input box for user to enter their Hugging Face API key
+    api_key = st.text_input("Enter your Hugging Face API Key:", type="password")
+
+if api_key:
+    # Initialize the InferenceClient with the user-provided API key
+    client = InferenceClient(api_key=api_key)
+
+    # Input box for user to enter their question
+    user_input = st.chat_input("Enter your question:")
+    
+
+    if user_input:
+        # Prepare the messages for the model
+        messages = [
+            {
+                "role": "user",
+                "content": user_input
+            }
+        ]
+        with st.chat_message("user"):
+            st.write(user_input)
+
+        # Get the completion from the model
+        completion = client.chat.completions.create(
+            model="deepseek-ai/DeepSeek-R1-Distill-Qwen-32B", 
+            messages=messages, 
+        )
+
+        # Get the model's response
+        response = completion.choices[0].message['content']
+
+        # Check if the response contains <think> tags
+        if "<think>" in response and "</think>" in response:
+            # Extract content within <think> tags
+            think_content = response.split("<think>")[1].split("</think>")[0].strip()
+            # Display the thinking content in an expander
+            with st.expander("Thinking..."):
+                st.write(think_content)
+
+            # Extract the rest of the response (outside <think> tags)
+            rest_of_response = response.split("</think>")[1].strip()
+            # Display the rest of the response with an AI icon
+            with st.chat_message("ai"):
+                st.write(rest_of_response)
+        else:
+            # If no <think> tags, display the entire response with an AI icon
+            with st.chat_message("ai"):
+                st.write(rest_of_response)
+else:
+    with st.sidebar:
+        st.warning("Please enter your Hugging Face API Key to proceed.")
+```
+
+---
+
+## Output
+- **Huggingface Space**: [Link](https://huggingface.co/spaces/genaitiwari/Deepseek_Chat)
+
+![alt text](deepseek_output.png)
+## 📝 Notes
+
+- **API Key Security**: Ensure that your Hugging Face API key is kept secure and not shared publicly.
+- **Model Limitations**: The responses generated by the DeepSeek model are based on its training data and may not always be accurate or complete.
+
+---
+
+## 📜 License
+
+This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.
+
+---