add

base-config.yaml

@@ -31,6 +31,12 @@ platforms:
     max_tokens: 2000
     max_words: 1000
     max_context_messages: 20
+  deepseek:
+    url: https://api.deepseek.com
+    api_key:
+    model:
+    max_words: 1000
+    max_context_messages: 20
   openai:
     url: https://api.openai.com
     api_key:

maubot_llmplus/thrid_platform.py

@@ -12,6 +12,52 @@ from maubot_llmplus.platforms import Platform, ChatCompletion
 from maubot_llmplus.plugin import AbsExtraConfigPlugin
 
 
+class Deepseek(Platform):
+
+    def __init__(self, config: BaseProxyConfig, http: ClientSession):
+        super().__init__(config, http)
+
+    async def create_chat_completion(self, plugin: AbsExtraConfigPlugin, evt: MessageEvent) -> ChatCompletion:
+        full_context = []
+        context = await maubot_llmplus.platforms.get_context(plugin, self, evt)
+        full_context.extend(list(context))
+
+        headers = {
+            "Content-Type": "application/json",
+            "Authorization": f"Bearer {self.api_key}"
+        }
+        data = {
+            "model": self.model,
+            "messages": full_context,
+        }
+
+        endpoint = f"{self.url}/chat/completions"
+        async with self.http.post(
+            endpoint, headers=headers, data=json.dumps(data)
+        ) as response:
+            if response.status != 200:
+                return ChatCompletion(
+                    result=False,
+                    message={},
+                    finish_reason=f"Error: {await response.text()}",
+                    model=None
+                )
+            response_json = await response.json()
+            choice = response_json["choices"][0]
+            return ChatCompletion(
+                result=True,
+                message=choice["message"],
+                finish_reason=choice["finish_reason"],
+                model=response_json.get("model", None)
+            )
+
+    async def list_models(self) -> List[str]:
+        models = ["deepseek-chat", "deepseek-reasoner"]
+        return [f"- {m}" for m in models]
+
+    def get_type(self) -> str:
+        return "deepseek"
+
 class OpenAi(Platform):
     max_tokens: int
     temperature: int