Deepseek
Give your AI agent access to DeepSeek's powerful language models for deeper reasoning and more accurate answers. The agent uses DeepSeek-Chat for general conversations and DeepSeek-Reasoner for complex problem-solving, delivering thoughtful responses that go beyond surface-level answers.
Your agent taps into DeepSeek's chat completion and reasoning APIs to produce nuanced, context-aware responses with tool calling, structured output, and thinking mode capabilities.
Deepseek
See how businesses leverage DeepSeek's chain-of-thought reasoning and chat models to deliver expert-level answers through their AI agents.
A developer asks why their API returns a 429 rate limit error intermittently. Your AI Agent activates DeepSeek-Reasoner with thinking mode, which breaks down the issue: examining retry logic, checking if the customer's plan includes rate limit headers, and considering time-based throttling patterns. The customer receives a step-by-step diagnosis with concrete code fixes. Complex technical questions get resolved in the conversation instead of being escalated to engineering.
A shopper describes their home office setup and asks which monitor fits their needs. Your AI Agent uses DeepSeek-Chat to analyze the requirements, call product catalog functions to check inventory, and reason about compatibility with the described setup. The customer gets a tailored recommendation with justification, not a generic product list. Conversion rates improve because the recommendation feels consultative, not algorithmic.
A customer writes in Japanese asking about subscription cancellation policies. Your AI Agent sends the message through DeepSeek's Chat Completion API, which understands the query natively, retrieves the relevant policy details via function calling, and responds fluently in Japanese. No translation layer required. International customers receive the same quality of support as your primary language audience.
Deepseek
FAQs
DeepSeek-Chat is optimized for general conversations, instruction following, and quick responses. DeepSeek-Reasoner excels at complex, multi-step problems requiring chain-of-thought reasoning like math, logic, and technical troubleshooting. Your agent can dynamically select the right model based on the complexity of each customer query.
Thinking mode lets the model reason through a problem step by step before producing the final answer. Enable it via the thinking parameter for complex technical questions, calculations, or scenarios requiring logical deduction. The reasoning process happens server-side and the customer sees only the refined final answer.
Yes. DeepSeek's function calling feature allows the model to identify when external data is needed, specify which tool to call with the correct parameters, and incorporate the results into its response. You can define up to 128 tool functions. The agent orchestrates these calls automatically during the conversation.
DeepSeek offers an API endpoint that accepts requests in the Anthropic Messages format. If your existing systems already use Anthropic's API structure, you can route them through DeepSeek without rewriting integration code. It supports system prompts, tool calling, streaming, and extended thinking in the same familiar format.
Conversation content is processed through DeepSeek's API during active sessions. Tars logs conversation flows for your review in the dashboard but does not independently store raw API payloads. DeepSeek's data handling policies apply to the API layer. Review their privacy documentation for retention details.
DeepSeek charges per token for input and output. Pricing varies by model. The agent can check your current balance using the Get User Balance endpoint before high-volume operations. DeepSeek supports both CNY and USD billing. You manage credits through your DeepSeek platform account.
Yes. The temperature parameter (0 to 2) controls randomness. Lower values produce more deterministic responses for factual queries. Top_p adjusts nucleus sampling for diversity. Frequency and presence penalties reduce repetition. Configure these per request to match the conversation context.
DeepSeek models support extended context windows. The max_tokens parameter controls response length. For long conversation threads, the agent manages context by passing relevant message history. The stop parameter lets you define custom sequences to control where generation ends, keeping responses focused and relevant.
Don't limit your AI Agent to basic conversations. Watch how to configure and add powerful tools making your agent smarter and more functional.
Privacy & Security
At Tars, we take privacy and security very seriously. We are compliant with GDPR, ISO, SOC 2, and HIPAA.
Email - sales@hellotars.com
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