Agent-ready OpenAPI document · curated by JenticAI/MLLanguage Modelsbearer3 EndpointsREST
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For Agents
Generate chat completions with DeepSeek language models using an OpenAI-compatible request format, list available models, and check account balance.
Use for: I want to generate a chat completion with a DeepSeek model, List all DeepSeek models available to my account, Check the remaining balance on my DeepSeek account, Get the response from DeepSeek for a multi-turn conversation
Not supported: Does not handle image generation, audio transcription, fine-tuning, or embeddings - use for DeepSeek chat completions and account state only.
Jentic maintains a curated, agent-optimized OpenAPI specification for DeepSeek API, keeping it validated and agent-ready. DeepSeek provides access to its family of large language models through an OpenAI-compatible chat completions interface, making it straightforward to swap into existing tooling. The API exposes chat completions, model listings, and account balance lookups so agents can generate responses, choose between available DeepSeek models, and monitor remaining credit. Authentication uses Bearer tokens and the surface is intentionally small, with three endpoints covering inference and account state.
Install Jentic One Beta
Connect the DeepSeek API to your agent
Jentic One is a self-hosted execution layer for AI agents. It lets your agent call the DeepSeek API, or any other public or private API you need. You set the rules, the agent never sees your credentials, and every call is logged.
Two steps, two machines. Install the instance in a safe environment, then register your agent from wherever it runs.
1
Step 1: Jentic One Host machine
# On the machine that will host your Jentic One instance:
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fdeepseek.com%2Fdeepseek" | sh2
Step 2: Agent machine
# On the machine where your agent runs (keep this separate from the instance):
curl -fsSL "https://jentic.com/install.sh?src=apis&api=%2Fapis%2Fdeepseek.com%2Fdeepseek" | sh
jentic register # connects your agent to your Jentic One instanceJentic One is in public beta. The setup above keeps your agent separate from the instance, which is what you want before using real credentials: an agent running as the same OS user as Jentic One can read its stored keys directly. Just evaluating? A single local install is fine to start. See the secure deployment guide for the tiers.
Capabilities
What an agent can do with DeepSeek API.
Generate chat completions from prompts using DeepSeek models via POST /chat/completions
List the DeepSeek models available to the calling account through GET /models
Check remaining account balance and granted credit with GET /user/balance
Stream multi-turn assistant responses by reusing the OpenAI-compatible message format
Select between DeepSeek model variants when issuing a chat completion request
Use Cases
Patterns agents use DeepSeek API for, with concrete tasks.
★ OpenAI-Compatible Chat Completions
Drop DeepSeek into an existing OpenAI-compatible client by pointing the base URL at api.deepseek.com and supplying a Bearer token. The /chat/completions endpoint accepts the same message and parameter shape, allowing teams to evaluate DeepSeek outputs against other providers without rewriting their inference layer. This is the fastest way to A/B test model quality and pricing.
Send a chat completion request to /chat/completions with a system prompt and user message, then return the assistant content.
Model Selection and Discovery
Before issuing a chat completion, an agent or developer can call /models to see which DeepSeek model identifiers the account has access to. This avoids hard-coded model names that drift over time and lets agents pick the most appropriate model at runtime. The list is small and stable, suitable for caching for short windows.
Call GET /models, parse the returned model list, and select the first chat-capable model id for the next completion.
Account Balance Monitoring
DeepSeek exposes /user/balance so applications can check remaining credit before issuing expensive completions. This lets agents and dashboards flag low balances, pause non-essential calls, or trigger top-ups. The endpoint returns granted, topped-up, and total balance figures suitable for billing alerts.
Call GET /user/balance and emit a warning if the total balance falls below a configured threshold.
AI Agent Integration via Jentic
Through Jentic, an agent finds DeepSeek by searching for an inference intent rather than reading docs. Jentic returns the matching operation schema for /chat/completions, the agent fills in the messages, and the call executes with the API key resolved from your Jentic One instance. Swapping providers becomes a search query change, not a rewrite.
Use Jentic to search for 'generate text with DeepSeek', load the chat completions schema, and execute a request with a user prompt.
Key Endpoints
3 endpoints — jentic maintains a curated, agent-optimized openapi specification for deepseek api, keeping it validated and agent-ready.
METHOD
PATH
DESCRIPTION
POST
/chat/completions
Create a chat completion
GET
/models
List available DeepSeek models
GET
/user/balance
Get remaining account balance
POST
/chat/completions
Create a chat completion
GET
/models
List available DeepSeek models
GET
/user/balance
Get remaining account balance
Jentic AI Readiness Score
This API is usable in Jentic One now. Its AI-readiness score against Jentic's framework shows where it stands today and where improvements would make it even easier for agents to use.
D
DeepSeek API
- AI-Aware (B)64/100
64
Foundational Compliance56
Developer Experience & Jentic Compatibility49
AI-Readiness & Agent Experience94
Agent Usability60
Security100
AI DiscoverabilityPowered by JenticScoring Framework 1.0.0 | Scoring Engine 0.4.0
Show dimension breakdown
64
Foundational Compliance
Base layer of spec validity and structural soundness.
Grade: BSignals: 4
95%
Lint Results
Aggregated quality score from linter diagnostics, weighted by severity.
100%
Resolution Completeness
Percentage of `$ref` references that resolve successfully.
0%
Specification Validity
Checks whether the API description parses successfully and conforms to its declared specification (e.g., OpenAPI).
60%
Structural Integrity
Structural correctness score based on schema issues using logarithmic dampening.
56
Developer Experience & Jentic Compatibility
Clarity, completeness, and ingestion readiness for developers and tooling.
Grade: CSignals: 4
0%
Example Density
How richly the API is illustrated with examples.
100%
Example Validity
Percentage of examples that conform to their schemas.
25%
Response Coverage
Percentage of operations with complete response definitions (success, client error, server error).
100%
Tooling Readiness
Health of API ingestion, bundling, and resolution within Jentic pipelines.
49
AI-Readiness & Agent Experience
Semantic breadth, depth, and agent comprehension for AI systems.
Grade: D+Signals: 4
47%
Description Coverage
Coverage of descriptions across API elements.
0%
Error Standardization
Coverage of RFC 9457 Problem Details for error responses.
100%
OperationId Quality
Coverage, uniqueness, and casing consistency of operationIds for AI inference.
50%
Summary Coverage
Coverage of summaries across operations/tags/info.
94
Agent Usability
Functional utility, complexity comfort, and AI orchestration readiness.
Grade: A+Signals: 1
94%
Complexity Comfort
Agent comfort level based on API operational and structural complexity.
60
Security
Trust, risk posture, and security compliance.
Grade: B-Signals: 1
60%
Authentication Strength
Average quality of security schemes based on authentication method strength (weakest link for OAuth2).
100
AI Discoverability
Findability, semantic richness, and reasoning readiness.
Grade: A+Signals: 1
100%
Descriptive Richness
Clarity and depth of descriptions across API elements.
Score it yourself
Every API in the directory is allowlisted, so you can re-score it with no key required.
npx @jentic/api-scorecard-cli score <openapi-url>Why Jentic?
What agents get from Jentic-routed access to this vendor.
Setup
Wiring the DeepSeek API by hand means learning its bearer auth, passing the API key as a Bearer token, and mapping chat completions alongside the models and balance reads. Through Jentic you install once, import the DeepSeek API from the API Directory, store the API key once, and your agent calls it.
Permission scoping
DeepSeek carries the prompt and model in the request body rather than as a resource id in the URL path, so limit the agent to the operations it needs, such as generating a chat completion or listing models. Because you pick the operations, the account balance read is included only if you add it.
Credential isolation
Your DeepSeek API key is stored once, encrypted, by your own Jentic One instance and applied as the Bearer token at execution time. It never enters the agent's prompt, logs, or context.
Intent-based discovery
Agents search Jentic by intent such as 'generate a chat completion', and Jentic returns the DeepSeek /chat/completions operation with its full input schema so the agent calls the right endpoint without reading docs.
Related APIs
Alternatives and complements available in the Jentic catalogue.
FAQs
Specific to using DeepSeek API through Jentic.
Which OpenAPI specification does this DeepSeek API page describe?
A curated, agent-optimized Jentic specification covering 3 DeepSeek operations, validated against the live API and kept up to date. DeepSeek's own API reference docs at https://api-docs.deepseek.com/api/deepseek-api are generated from an OpenAPI document DeepSeek maintains internally, which those pages report as version 1.0.0 with HTTP Bearer auth. DeepSeek serves the rendered reference rather than the source file, so there is no vendor URL to fetch it from. Get started with Jentic One, the self-hosted execution layer.
What authentication does the DeepSeek API use?
The DeepSeek API uses HTTP Bearer token authentication. Pass your DeepSeek API key in the Authorization header as `Authorization: Bearer <key>`. Through Jentic, the key is stored in the encrypted vault and never enters the agent's context window.
Can I use the DeepSeek API as a drop-in for OpenAI?
Yes. The /chat/completions endpoint accepts the same messages array and parameters as the OpenAI chat completions API, so most OpenAI client libraries work by changing the base URL to https://api.deepseek.com and supplying a DeepSeek Bearer key.
How do I list the DeepSeek models my account can use?
Call GET /models with your Bearer token. The response contains the DeepSeek model identifiers available for chat completion requests, which you then pass as the `model` field on POST /chat/completions.
How do I check my remaining DeepSeek balance?
Call GET /user/balance. The endpoint returns granted credit, topped-up credit, and total remaining balance, which agents can use to gate expensive inference calls.
How do I generate a DeepSeek chat completion through Jentic?
Run `pip install jentic`, then search for 'generate text with DeepSeek', load the /chat/completions operation, and execute with your messages payload. Jentic resolves the Bearer token from the vault at execution time.
Can I limit what my agent is allowed to do with the DeepSeek API?
Yes. Because Jentic One is self-hosted, you decide which DeepSeek operations your agent may call, so you can allow it to generate chat completions with POST /chat/completions and list models with GET /models while withholding the account balance read at GET /user/balance. DeepSeek carries the prompt and model choice in the request body rather than as a resource id in the URL, so scoping is done at the operation level by only importing the endpoints the agent needs. Your DeepSeek API key stays stored by your own instance and is applied at execution time, never entering the agent's prompt or logs.
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