# DeepSeek Chat Prompt and Response

The **DeepSeek Chat Prompt Example Flow** demonstrates how to interact with the DeepSeek API to send prompts and retrieve AI-generated chat responses. This flow showcases a complete process, from sending user-defined prompts to receiving, formatting, and storing responses for further use or integration. It includes robust error handling and testing capabilities, making it an ideal solution for incorporating AI-driven chat functionality into various applications.

You can find this template in the Services Catalog under these categories:

* AI, Contextual Basics

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**What's Included:**

* **1 Flow:** Pre-configured for prompt-response interactions with DeepSeek.
* **1 Object Type:** To store structured prompt-response records.
* **1 Connection Template:** For integrating with the DeepSeek API.

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**What You'll Need:**

* Access to the DeepSeek API.
* API Key or credentials for authentication.
* Sample prompts or use cases for testing.

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**Ideas for Using the DeepSeek Chat Prompt Flow:**

1. **Conversational AI:** Automate chat-based interactions for virtual assistants or customer service bots.
2. **Content Generation:** Create engaging content by generating responses to tailored prompts.
3. **Decision Support:** Process complex queries to retrieve insights for informed decision-making.
4. **Education:** Use AI-generated explanations for learning or teaching purposes.

***

#### **Flow Overview**

**Flow Start**

* **Node:** `contextual-start`
* **Purpose:** Triggers the flow, initiated by either an external event, agent, or inject node for testing.

**In-Editor Testing**

* **Nodes:** `Test Prompt`, `Prepare Prompt`
* **Purpose:** Enables in-editor testing with a sample prompt. Modify the sample prompt directly to explore different interactions with the DeepSeek API.

**Code Example: Prepare Prompt Function**

```javascript
msg.payload = {
    model: "deepseek-chat",
    messages: [
        { role: "system", content: "You are a helpful assistant" },
        { role: "user", content: msg.payload.prompt }
    ],
    max_tokens: 4096
};
return msg;
```

**Send Prompt and Receive Response**

* **Nodes:** `Prompt DeepSeek Chat`, `DeepSeek Chat Response`
* **Purpose:** Sends the prepared payload to the DeepSeek API. Logs the response for review and passes it for further processing.

**Code Example: Response Logging**

```javascript
msg.payload.response = {
    aiResponse: msg.payload.response.choices[0].message.content
};
return msg;
```

**Format Response & Create Record**

* **Nodes:** `Prepare Record Data`, `Create AI Response Record`
* **Purpose:** Formats the API response and creates a structured record, including the original prompt and AI-generated response.

**Code Example: Prepare Record Data**

```javascript
let body = {
    prompt: msg.payload.messages[1].content,
    aiResponse: msg.payload.response.choices[0].message.content
};
msg.payload = body;
return msg;
```

**Error Handling**

* **Nodes:** `catch`, `Error Catch Log`, `contextual-error`
* **Purpose:** Captures and logs any errors during the flow execution to ensure efficient debugging and troubleshooting.

**Flow End**

* **Node:** `contextual-end`
* **Purpose:** Successfully concludes the process after records are created or errors are logged.

***

#### **Summary of Flow Steps**

1. **Start:** Trigger the flow manually or externally.
2. **Data Preparation:** Format the prompt for API interaction.
3. **API Interaction:** Submit the prompt and receive the response.
4. **Record Creation:** Structure and store the response.
5. **Error Handling:** Log and manage any issues that arise.
6. **Completion:** Conclude the flow after creating records or logging errors.

***

#### **Key Features**

* **Flexibility:** Can be easily adapted to various use cases.
* **Scalability:** Integrates seamlessly into broader workflows.
* **Customization:** Modify prompts, response handling, and storage to suit specific requirements.

This flow is a robust starting point for leveraging AI-powered chat functionality within your workflows, providing clear examples and extensibility for diverse applications.