357 lines
11 KiB
Python
357 lines
11 KiB
Python
#!/usr/bin/env python3
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"""nanocode-dspy - minimal claude code alternative using DSPy ReAct"""
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import os
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import re
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import glob as globlib
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import subprocess
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from modaic import PrecompiledProgram, PrecompiledConfig
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import dspy
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from dspy.utils.callback import BaseCallback
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# --- ANSI colors ---
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RESET = "\033[0m"
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BOLD = "\033[1m"
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DIM = "\033[2m"
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BLUE = "\033[34m"
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CYAN = "\033[36m"
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GREEN = "\033[32m"
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YELLOW = "\033[33m"
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RED = "\033[31m"
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MAGENTA = "\033[35m"
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# --- Display utilities ---
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def separator():
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"""Return a horizontal separator line that fits the terminal width."""
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return f"{DIM}{'─' * min(os.get_terminal_size().columns, 80)}{RESET}"
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def render_markdown(text):
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"""Convert basic markdown bold syntax to ANSI bold."""
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return re.sub(r"\*\*(.+?)\*\*", f"{BOLD}\\1{RESET}", text)
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# --- File operations ---
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def read_file(path: str, offset: int = 0, limit: int = None) -> str:
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"""Read file contents with line numbers.
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Args:
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path: Path to the file to read
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offset: Line number to start from (0-indexed)
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limit: Maximum number of lines to read
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Returns:
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File contents with line numbers
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"""
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lines = open(path).readlines()
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if limit is None:
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limit = len(lines)
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selected = lines[offset : offset + limit]
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return "".join(f"{offset + idx + 1:4}| {line}" for idx, line in enumerate(selected))
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def write_file(path: str, content: str) -> str:
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"""Write content to a file.
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Args:
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path: Path to the file to write
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content: Content to write to the file
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Returns:
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'ok' on success
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"""
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with open(path, "w") as f:
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f.write(content)
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return "ok"
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def edit_file(path: str, old: str, new: str, replace_all: bool = False) -> str:
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"""Replace text in a file.
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Args:
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path: Path to the file to edit
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old: Text to find and replace
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new: Replacement text
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replace_all: If True, replace all occurrences; otherwise old must be unique
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Returns:
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'ok' on success, error message on failure
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"""
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text = open(path).read()
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if old not in text:
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return "error: old_string not found"
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count = text.count(old)
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if not replace_all and count > 1:
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return f"error: old_string appears {count} times, must be unique (use replace_all=True)"
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replacement = text.replace(old, new) if replace_all else text.replace(old, new, 1)
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with open(path, "w") as f:
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f.write(replacement)
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return "ok"
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def glob_files(pattern: str, path: str = ".") -> str:
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"""Find files matching a glob pattern, sorted by modification time.
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Args:
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pattern: Glob pattern to match (e.g., '**/*.py')
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path: Base directory to search in
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Returns:
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Newline-separated list of matching files
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"""
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full_pattern = (path + "/" + pattern).replace("//", "/")
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files = globlib.glob(full_pattern, recursive=True)
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files = sorted(
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files,
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key=lambda f: os.path.getmtime(f) if os.path.isfile(f) else 0,
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reverse=True,
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)
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return "\n".join(files) or "no files found"
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def grep_files(pattern: str, path: str = ".") -> str:
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"""Search files for a regex pattern.
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Args:
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pattern: Regular expression pattern to search for
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path: Base directory to search in
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Returns:
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Matching lines in format 'filepath:line_num:content'
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"""
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regex = re.compile(pattern)
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hits = []
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for filepath in globlib.glob(path + "/**", recursive=True):
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try:
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for line_num, line in enumerate(open(filepath), 1):
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if regex.search(line):
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hits.append(f"{filepath}:{line_num}:{line.rstrip()}")
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except Exception:
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pass
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return "\n".join(hits[:50]) or "no matches found"
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# --- Shell operations ---
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def run_bash(cmd: str) -> str:
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"""Run a shell command and return output.
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Args:
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cmd: Shell command to execute
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Returns:
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Command output (stdout and stderr combined)
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"""
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proc = subprocess.Popen(
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cmd, shell=True,
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stdout=subprocess.PIPE, stderr=subprocess.STDOUT,
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text=True
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)
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output_lines = []
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try:
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while True:
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line = proc.stdout.readline()
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if not line and proc.poll() is not None:
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break
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if line:
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print(f" {DIM}│ {line.rstrip()}{RESET}", flush=True)
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output_lines.append(line)
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proc.wait(timeout=30)
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except subprocess.TimeoutExpired:
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proc.kill()
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output_lines.append("\n(timed out after 30s)")
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return "".join(output_lines).strip() or "(empty output)"
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# --- Model selection ---
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AVAILABLE_MODELS = {
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"1": ("Claude 3.5 Sonnet", "anthropic/claude-3.5-sonnet"),
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"2": ("Claude 3.5 Haiku", "anthropic/claude-3.5-haiku"),
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"3": ("GPT-4o", "openai/gpt-4o"),
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"4": ("GPT-4o mini", "openai/gpt-4o-mini"),
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"5": ("Gemini Pro 1.5", "google/gemini-pro-1.5"),
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"6": ("Llama 3.1 405B", "meta-llama/llama-3.1-405b-instruct"),
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"7": ("DeepSeek V3", "deepseek/deepseek-chat"),
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"8": ("Qwen 2.5 72B", "qwen/qwen-2.5-72b-instruct"),
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}
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def select_model():
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"""Interactive model selection or use environment variable."""
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model_env = os.getenv("MODEL")
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if model_env:
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print(f"{GREEN}⏺ Using model from environment: {model_env}{RESET}")
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return model_env
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print(f"\n{BOLD}Select a model:{RESET}")
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for key, (name, model_id) in AVAILABLE_MODELS.items():
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print(f" {BLUE}{key}{RESET}. {name} ({DIM}{model_id}{RESET})")
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print(f" {BLUE}c{RESET}. Custom model (enter manually)")
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while True:
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try:
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choice = input(f"\n{BOLD}{BLUE}❯{RESET} Enter choice (1-8 or c): ").strip().lower()
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if choice in AVAILABLE_MODELS:
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name, model_id = AVAILABLE_MODELS[choice]
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print(f"{GREEN}⏺ Selected: {name}{RESET}")
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return model_id
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elif choice == "c":
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custom_model = input(f"{BOLD}{BLUE}❯{RESET} Enter model ID (e.g., openai/gpt-4): ").strip()
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if custom_model:
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print(f"{GREEN}⏺ Selected custom model: {custom_model}{RESET}")
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return custom_model
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else:
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print(f"{RED}⏺ Invalid model ID{RESET}")
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else:
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print(f"{RED}⏺ Invalid choice. Please enter 1-8 or c{RESET}")
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except (KeyboardInterrupt, EOFError):
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print(f"\n{RED}⏺ Model selection cancelled{RESET}")
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exit(1)
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# --- DSPy Signature ---
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class CodingAssistant(dspy.Signature):
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"""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."""
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task: str = dspy.InputField(desc="The user's coding task or question")
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answer: str = dspy.OutputField(desc="Your response to the user after completing the task")
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affected_files: list[str] = dspy.OutputField(desc="List of files that were written or modified during the task")
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# ReAct agent with tools
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tools = [read_file, write_file, edit_file, glob_files, grep_files, run_bash]
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class ToolLoggingCallback(BaseCallback):
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"""Callback that logs tool calls as they happen."""
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def on_tool_start(self, call_id, instance, inputs):
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"""Log when a tool starts executing."""
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tool_name = instance.name if hasattr(instance, 'name') else str(instance)
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# Format args nicely
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args_str = ", ".join(f"{k}={repr(v)[:50]}" for k, v in inputs.items())
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print(f" {MAGENTA}⏺ {tool_name}({args_str}){RESET}", flush=True)
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def on_tool_end(self, call_id, outputs, exception):
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"""Log when a tool finishes executing."""
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if exception:
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print(f" {RED}Error: {exception}{RESET}", flush=True)
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def on_module_end(self, call_id, outputs, exception):
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"""Log when the finish tool is called (ReAct completion)."""
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# Check if this is a ReAct prediction with tool_calls
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if outputs and 'tool_calls' in outputs:
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for call in outputs['tool_calls']:
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args_str = ", ".join(f"{k}={repr(v)[:50]}" for k, v in call.args.items())
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if call.name == 'finish':
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print(f" {GREEN}⏺ finish{RESET}", flush=True)
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else:
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print(f" {MAGENTA}⏺ {call.name}({args_str}){RESET}", flush=True)
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class AgentConfig(PrecompiledConfig):
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max_iters: int = 15
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lm: str = "openrouter/anthropic/claude-3.5-sonnet" # Default fallback
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api_base: str = "https://openrouter.ai/api/v1"
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max_tokens: int = 8192
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class AgentProgram(PrecompiledProgram):
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config: AgentConfig
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def __init__(self, config: AgentConfig, **kwargs):
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self.config = config
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super().__init__(config, **kwargs)
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# Configure logging callback globally
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dspy.settings.configure(callbacks=[ToolLoggingCallback()])
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agent = dspy.ReAct(CodingAssistant, tools=tools, max_iters=self.config.max_iters)
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lm = dspy.LM(self.config.lm, api_base=self.config.api_base, max_tokens=self.config.max_tokens)
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agent.set_lm(lm)
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self.agent = agent
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def forward(self, task: str) -> str:
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assert task, "Task cannot be empty"
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return self.agent(task=task)
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# --- Main ---
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def main():
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"""Create AgentConfig with selected model."""
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model = os.getenv("MODEL")
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if model is None:
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model = select_model()
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# Add openrouter/ prefix if not already present
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if not model.startswith("openrouter/"):
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model = f"openrouter/{model}"
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config = AgentConfig()
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config.lm = model
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agent = AgentProgram(config)
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print(f"{BOLD}nanocode-dspy{RESET} | {DIM}{agent.config.lm} | {os.getcwd()}{RESET}\n")
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# Conversation history for context
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history = []
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while True:
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try:
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print(separator())
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user_input = input(f"{BOLD}{BLUE}❯{RESET} ").strip()
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print(separator())
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if not user_input:
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continue
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if user_input in ("/q", "exit"):
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break
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if user_input == "/c":
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history = []
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print(f"{GREEN}⏺ Cleared conversation{RESET}")
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continue
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# Build context from history
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context = f"Working directory: {os.getcwd()}\n"
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if history:
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context += "\nPrevious conversation:\n"
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for h in history[-5:]: # Keep last 5 exchanges
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context += f"User: {h['user']}\nAssistant: {h['assistant']}\n\n"
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task = f"{context}\nCurrent task: {user_input}"
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print(f"\n{CYAN}⏺{RESET} Thinking...", flush=True)
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# Run the ReAct agent
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result = agent(task=task)
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# Display the answer
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print(f"\n{CYAN}⏺{RESET} {render_markdown(result.answer)}")
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# Save to history
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history.append({"user": user_input, "assistant": result.answer})
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print()
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except (KeyboardInterrupt, EOFError):
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break
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except Exception as err:
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import traceback
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traceback.print_exc()
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print(f"{RED}⏺ Error: {err}{RESET}")
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if __name__ == "__main__":
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agent = AgentProgram(AgentConfig(lm="openai/gpt-5.2-codex"))
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agent.push_to_hub("farouk1/nanocode")
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#main()
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