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nanocode.py

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+#!/usr/bin/env python3
+"""nanocode-dspy - minimal claude code alternative using DSPy ReAct"""
+
+import os
+from modaic import PrecompiledProgram, PrecompiledConfig
+import dspy
+from dspy.utils.callback import BaseCallback
+
+from utils import (
+    RESET, BOLD, DIM, BLUE, CYAN, GREEN, RED, MAGENTA,
+    separator, render_markdown,
+    read_file, write_file, edit_file, glob_files, grep_files, run_bash,
+    AVAILABLE_MODELS, select_model,
+)
+
+
+# --- DSPy Signature ---
+
+class CodingAssistant(dspy.Signature):
+    """You are a concise coding assistant. Help the user with their coding task by using the available tools to read, write, edit files, search the codebase, and run commands."""
+
+    task: str = dspy.InputField(desc="The user's coding task or question")
+    answer: str = dspy.OutputField(desc="Your response to the user after completing the task")
+    affected_files: list[str] = dspy.OutputField(desc="List of files that were written or modified during the task")
+
+# ReAct agent with tools
+
+tools = [read_file, write_file, edit_file, glob_files, grep_files, run_bash]
+
+
+class ToolLoggingCallback(BaseCallback):
+    """Callback that logs tool calls as they happen."""
+    
+    def on_tool_start(self, call_id, instance, inputs):
+        """Log when a tool starts executing."""
+        tool_name = instance.name if hasattr(instance, 'name') else str(instance)
+        # Format args nicely
+        args_str = ", ".join(f"{k}={repr(v)[:50]}" for k, v in inputs.items())
+        print(f"  {MAGENTA}⏺ {tool_name}({args_str}){RESET}", flush=True)
+    
+    def on_tool_end(self, call_id, outputs, exception):
+        """Log when a tool finishes executing."""
+        if exception:
+            print(f"    {RED}Error: {exception}{RESET}", flush=True)
+    
+    def on_module_end(self, call_id, outputs, exception):
+        """Log when the finish tool is called (ReAct completion)."""
+        # Check if this is a ReAct prediction with tool_calls
+        if outputs and 'tool_calls' in outputs:
+            for call in outputs['tool_calls']:
+                args_str = ", ".join(f"{k}={repr(v)[:50]}" for k, v in call.args.items())
+                if call.name == 'finish':
+                    print(f"  {GREEN}⏺ finish{RESET}", flush=True)
+                else:
+                    print(f"  {MAGENTA}⏺ {call.name}({args_str}){RESET}", flush=True)
+
+
+class AgentConfig(PrecompiledConfig):
+    max_iters: int = 15
+    lm: str = "openrouter/anthropic/claude-3.5-sonnet"  # Default fallback
+    api_base: str = "https://openrouter.ai/api/v1"
+    max_tokens: int = 8192
+
+class AgentProgram(PrecompiledProgram):
+    config: AgentConfig
+    
+    def __init__(self, config: AgentConfig, **kwargs):
+        self.config = config
+        super().__init__(config, **kwargs)
+
+        # Configure logging callback globally
+        dspy.settings.configure(callbacks=[ToolLoggingCallback()])
+        
+        agent = dspy.ReAct(CodingAssistant, tools=tools, max_iters=self.config.max_iters)
+        lm = dspy.LM(self.config.lm, api_base=self.config.api_base, max_tokens=self.config.max_tokens)
+        agent.set_lm(lm)
+        self.agent = agent
+        
+    def forward(self, task: str) -> str:
+        assert task, "Task cannot be empty"
+        return self.agent(task=task)
+
+# --- Main ---
+
+
+def main():
+    """Create AgentConfig with selected model."""
+    model = os.getenv("MODEL")
+    if model is None:
+        model = select_model()
+
+    # Add openrouter/ prefix if not already present
+    if not model.startswith("openrouter/"):
+        model = f"openrouter/{model}"
+    
+    config = AgentConfig()
+    config.lm = model
+
+    agent = AgentProgram(config)
+    print(f"{BOLD}nanocode-dspy{RESET} | {DIM}{agent.config.lm} | {os.getcwd()}{RESET}\n")
+
+    # Conversation history for context
+    history = []
+
+    while True:
+        try:
+            print(separator())
+            user_input = input(f"{BOLD}{BLUE}❯{RESET} ").strip()
+            print(separator())
+
+            if not user_input:
+                continue
+            if user_input in ("/q", "exit"):
+                break
+            if user_input == "/c":
+                history = []
+                print(f"{GREEN}⏺ Cleared conversation{RESET}")
+                continue
+
+            # Build context from history
+            context = f"Working directory: {os.getcwd()}\n"
+            if history:
+                context += "\nPrevious conversation:\n"
+                for h in history[-5:]:  # Keep last 5 exchanges
+                    context += f"User: {h['user']}\nAssistant: {h['assistant']}\n\n"
+
+            task = f"{context}\nCurrent task: {user_input}"
+
+            print(f"\n{CYAN}⏺{RESET} Thinking...", flush=True)
+
+            # Run the ReAct agent
+            result = agent(task=task)
+
+            # Display the answer
+            print(f"\n{CYAN}⏺{RESET} {render_markdown(result.answer)}")
+
+            # Save to history
+            history.append({"user": user_input, "assistant": result.answer})
+
+            print()
+
+        except (KeyboardInterrupt, EOFError):
+            break
+        except Exception as err:
+            import traceback
+            traceback.print_exc()
+            print(f"{RED}⏺ Error: {err}{RESET}")
+
+
+if __name__ == "__main__":
+    main()