Added many tools

tools/ollama.py

@@ -0,0 +1,158 @@
+from __future__ import annotations
+
+from typing import Any
+import requests
+
+from core.tools.base import BaseTool, ToolContext
+from core.tools.registry import registry
+from core.events import bus
+from core.config import OLLAMA_URL
+
+
+class OllamaTool(BaseTool):
+    """
+    Local LLM interface via Ollama.
+
+    Enables the agent to call local models for reasoning,
+    summarization, and transformation tasks.
+    """
+
+    name = "ollama"
+    description = "Local LLM inference via Ollama"
+
+    # =========================================================
+    # EXECUTE
+    # =========================================================
+
+    def execute(self, payload: dict[str, Any], ctx: ToolContext):
+        action = str(payload.get("action", "generate")).strip()
+
+        bus.log(
+            "OLLAMA",
+            "ollama_execute",
+            "INFO",
+            {"action": action}
+        )
+
+        match action:
+            case "generate":
+                return self.generate(payload, ctx)
+
+            case "chat":
+                return self.chat(payload, ctx)
+
+            case "models":
+                return self.list_models()
+
+            case _:
+                raise ValueError(f"Unknown ollama action: {action}")
+
+    # =========================================================
+    # GENERATE (single prompt)
+    # =========================================================
+
+    def generate(self, payload: dict[str, Any], ctx: ToolContext):
+        model = payload.get("model", "llama3")
+        prompt = payload.get("prompt")
+
+        if not isinstance(prompt, str):
+            raise ValueError("prompt must be string")
+
+        url = f"{OLLAMA_URL}/api/generate"
+
+        data = {
+            "model": model,
+            "prompt": prompt,
+            "stream": False
+        }
+
+        if ctx.dry_run:
+            return {
+                "dry_run": True,
+                "model": model,
+                "prompt_preview": prompt[:200]
+            }
+
+        try:
+            response = requests.post(url, json=data, timeout=(5, 120))
+            response.raise_for_status()
+
+            return {
+                "model": model,
+                "response": response.json().get("response", ""),
+            }
+
+        except requests.exceptions.RequestException as e:
+            return {
+                "status": "error",
+                "error": str(e)
+            }
+
+    # =========================================================
+    # CHAT (multi-message style)
+    # =========================================================
+
+    def chat(self, payload: dict[str, Any], ctx: ToolContext):
+        model = payload.get("model", "llama3")
+        messages = payload.get("messages")
+
+        if not isinstance(messages, list):
+            raise ValueError("messages must be list[dict]")
+
+        url = f"{OLLAMA_URL}/api/chat"
+
+        data = {
+            "model": model,
+            "messages": messages,
+            "stream": False
+        }
+
+        if ctx.dry_run:
+            return {
+                "dry_run": True,
+                "model": model,
+                "message_count": len(messages)
+            }
+
+        try:
+            response = requests.post(url, json=data, timeout=(5, 180))
+            response.raise_for_status()
+
+            return {
+                "model": model,
+                "response": response.json().get("message", {}).get("content", "")
+            }
+
+        except requests.exceptions.RequestException as e:
+            return {
+                "status": "error",
+                "error": str(e)
+            }
+
+    # =========================================================
+    # LIST MODELS
+    # =========================================================
+
+    def list_models(self):
+        url = f"{OLLAMA_URL}/api/tags"
+
+        try:
+            response = requests.get(url, timeout=(3, 10))
+            response.raise_for_status()
+
+            return {
+                "models": response.json().get("models", [])
+            }
+
+        except requests.exceptions.RequestException as e:
+            return {
+                "status": "error",
+                "error": str(e)
+            }
+
+
+# =========================================================
+# REGISTER TOOL
+# =========================================================
+
+registry.register(OllamaTool())