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|
"""Claude Code backend.
Shells out to `claude -p` for non-interactive turns. Claude Code handles its
own persona discovery (CLAUDE.md / SOUL.md from the workspace) and its own MCP
tool dispatch internally; this backend just formats the prompt and parses
the response.
"""
import os
import subprocess
from pathlib import Path
from .base import ModelBackend, ModelRequest, ModelResponse
_ROLE_LABELS = {
"user": "User",
"assistant": "Assistant",
"tool": "Tool",
"system": "System",
}
class ClaudeCodeBackend(ModelBackend):
def __init__(
self,
workspace: Path = Path(os.environ.get("SENIA_WORKSPACE", "/workspace")),
timeout: int = 300,
allowed_tools: str = "mcp__senia__*",
):
self.workspace = workspace
self.timeout = timeout
self.allowed_tools = allowed_tools
def call(self, request: ModelRequest) -> ModelResponse:
prompt = self._format_prompt(request)
result = subprocess.run(
[
"claude", "-p", prompt,
"--output-format", "text",
"--allowedTools", self.allowed_tools,
],
cwd=self.workspace,
capture_output=True,
text=True,
timeout=self.timeout,
)
if result.returncode != 0:
raise RuntimeError(
f"claude exited {result.returncode}: {result.stderr.strip()}"
)
return ModelResponse(content=result.stdout.strip())
def _format_prompt(self, request: ModelRequest) -> str:
"""Flatten messages + dynamic context into a single prompt string.
Claude Code's -p mode takes one big prompt, not a structured
conversation. We render the conversation as a readable transcript with
the per-turn context prepended. Persona is NOT here; Claude Code
finds it in the workspace itself.
"""
parts = []
if request.turn_context:
parts.append(f"## Context for this turn\n\n{request.turn_context}\n")
for msg in request.messages:
parts.append(f"## {_ROLE_LABELS[msg.role]}\n\n{msg.content}\n")
parts.append("## Assistant\n\n")
return "\n".join(parts)
|
