Merge pull request #103 from DagaBhai/agent

feat: simple react agent structure

Author: blkdmr

src/fenn/agents/agent.py

@@ -0,0 +1,37 @@
+from fenn.agents import Flow
+from fenn.agents.node import ThinkNode, ActNode, ObserveNode
+import yaml
+
+class Agent:
+    def __init__(self, config, llm):
+        self.llm = llm
+        with open(config) as f:
+            self.config = yaml.safe_load(f)
+
+        think = ThinkNode()
+        act = ActNode()
+        observe = ObserveNode()
+
+        think - "act"     >> act
+        think - "done"    >> None
+        act   - "observe" >> observe
+        observe - "think" >> think
+        observe - "done"  >> None
+
+        self.flow = Flow(start=think)
+
+    def run(self, user_input):
+        shared = {
+            "llm": self.llm,
+            "messages": [
+                {"role": "system", "content": self.config["agent"]["system_prompt"]},
+                {"role": "user",   "content": user_input}
+            ],
+            "iterations": 0,
+            "max_iterations": self.config["agent"]["max_iterations"],
+            "last_thought": None,
+            "last_observation": None
+        }
+
+        self.flow.run(shared)
+        return shared["messages"][-1]["content"]

src/fenn/agents/llm.py

@@ -0,0 +1,11 @@
+class Client:
+    def __init__(self):
+        self._fn = None
+    
+    def register(self, fn):
+        self._fn = fn
+
+    def chat_complete(self, messages, **kwargs):
+        if self._fn:
+            return self._fn(messages, **kwargs)
+        raise ValueError("No LLM function registered")

src/fenn/agents/node.py

@@ -0,0 +1,53 @@
+from fenn.agents import Node
+from fenn.agents.tools import TOOLS
+
+class ThinkNode(Node):
+    def prep(self, shared):
+        return {"llm": shared["llm"], "messages": shared["messages"]}
+
+    def exec(self, prep_res):
+        llm = prep_res["llm"]
+        response =llm.chat_complete(prep_res["messages"])
+        return response
+    
+    def post(self, shared, prep_res, exec_res):
+        shared["last_thought"] = exec_res
+        shared["messages"].append({"role": "assistant", "content": exec_res})
+        if "Action:" in exec_res:
+            return "act"
+        return "done"
+    
+class ActNode(Node):
+    def prep(self, shared):
+        return shared["last_thought"]
+    
+    def exec(self, thought):
+        line = [l for l in thought.split("\n") if l.startswith("Action:")][0]
+        tool_call = line.replace("Action:", "").strip()
+
+        tool_name = tool_call.split("(")[0]
+        tool_arg  = tool_call.split("(")[1].rstrip(")")
+
+        result = TOOLS[tool_name](tool_arg)
+        return result
+    
+    def post(self, shared, prep_res, exec_res):
+        shared["last_observation"] = exec_res
+        return "observe"
+    
+class ObserveNode(Node):
+    def prep(self, shared):
+        return shared["last_observation"]
+    
+    def exec(self, observation):
+        return observation
+    
+    def post(self, shared, prep_res, exec_res):
+        shared["messages"].append({
+            "role": "user",
+            "content": f"Observation: {exec_res}"
+        })
+        shared["iterations"] += 1
+        if shared["iterations"] >= shared["max_iterations"]:
+            return "done"
+        return "think"

src/fenn/agents/tools.py

@@ -0,0 +1,10 @@
+TOOLS = {
+    "search": lambda query: f"Search result for: {query}",
+    "calculator": lambda expr: str(eval(expr))
+}
+
+# This is what you put in the LLM prompt so it knows what tools exist
+TOOL_DESCRIPTIONS = """
+- search(query): Search the web
+- calculator(expr): Evaluate a math expression
+"""