add Ollama function/tool calling support similar to OpenAI-compatible providers

README.md

@@ -89,6 +89,8 @@ export TUSHARE_TOKEN="<your-token>"
 
 - 通过 Provider 管理供应商连接参数（Base URL、API Key、默认温度/超时/Prompt 模板），并支持在界面内一键调用 `client.models.list()` 拉取可用模型列表，便于扩展本地 Ollama 或各类云端服务（DeepSeek、文心一言、OpenAI 等）。
 - 全局与部门配置直接选择 Provider，并根据需要覆盖模型、温度、Prompt 模板、投票策略；保存后写入 `app/data/config.json`，下次启动自动加载。
+
+Note: Ollama's `/api/chat` endpoint supports function/tool calling. The client forwards `tools` and optional `tool_choice` when the provider is configured as `ollama`, enabling function calls and tool-based workflows similar to OpenAI-compatible providers.
 - Streamlit “数据与设置” 页提供 Provider/全局/部门三栏编辑界面，保存后即时生效，并通过 `llm_config_snapshot()` 输出脱敏检查信息。
 - 支持使用环境变量注入敏感信息：`TUSHARE_TOKEN`、`LLM_API_KEY`。
 

app/llm/client.py

@@ -231,14 +231,20 @@ def call_endpoint_with_messages(
     )
 
     if mode == "ollama":
-        if tools:
-            raise LLMError("当前 provider 不支持函数调用/工具模式")
+        # Ollama supports function/tool calling via the /api/chat endpoint.
+        # Include `tools` and optional `tool_choice` in the payload when provided.
         payload = {
             "model": model,
             "messages": messages,
             "stream": False,
             "options": {"temperature": temperature},
         }
+        if tools:
+            # Ollama expects `tools` at the top level similar to OpenAI-compatible API
+            payload["tools"] = tools
+            if tool_choice is not None:
+                payload["tool_choice"] = tool_choice
+
         start_time = time.perf_counter()
         response = requests.post(
             f"{base_url.rstrip('/')}/api/chat",
@@ -252,6 +258,9 @@ def call_endpoint_with_messages(
         record_call(provider_key, model, duration=duration)
         if enforce_cost and cost_controller:
             cost_controller.record_usage(model or provider_key, 0, 0)
+        # Ollama may return `tool_calls` under message.tool_calls when tools are used.
+        # Return the raw response so callers can handle either OpenAI-like responses or
+        # Ollama's message structure with `tool_calls`.
         return data
 
     if not api_key: