94 lines
3.1 KiB
Python
94 lines
3.1 KiB
Python
import subprocess
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import json
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import sys
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import time
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import os
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class GeminiCliAdapter:
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def __init__(self, binary_path="gemini"):
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self.binary_path = binary_path
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self.last_usage = None
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self.session_id = None
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self.last_latency = 0.0
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def send(self, message):
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"""
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Sends a message to the Gemini CLI and processes the streaming JSON output.
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"""
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start_time = time.time()
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# On Windows, using shell=True allows executing .cmd/.bat files and
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# handles command strings with arguments more gracefully.
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# We pass the message via stdin to avoid command-line length limits.
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command = f'{self.binary_path} run --output-format stream-json'
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if self.session_id:
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command += f' --resume {self.session_id}'
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accumulated_text = ""
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tool_calls = []
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env = os.environ.copy()
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env["GEMINI_CLI_HOOK_CONTEXT"] = "manual_slop"
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process = subprocess.Popen(
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command,
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stdin=subprocess.PIPE,
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stdout=subprocess.PIPE,
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stderr=subprocess.PIPE,
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text=True,
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shell=True,
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env=env
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)
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try:
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# Send message to stdin and close it
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process.stdin.write(message)
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process.stdin.close()
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# Read stdout line by line
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for line in process.stdout:
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line = line.strip()
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if not line:
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continue
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try:
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data = json.loads(line)
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msg_type = data.get("type")
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if msg_type == "message":
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# Append message text to results
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accumulated_text += data.get("text", "")
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elif msg_type == "result":
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# Capture final usage and session persistence
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# Support both mock ('usage') and real ('stats') keys
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self.last_usage = data.get("usage") or data.get("stats")
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self.session_id = data.get("session_id")
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elif msg_type == "tool_use":
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# Collect tool_use messages
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tool_calls.append(data)
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# Log status/tool_use to stderr for debugging
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sys.stderr.write(f"GeminiCliAdapter [{msg_type}]: {line}\n")
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sys.stderr.flush()
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elif msg_type == "status":
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# Log status to stderr for debugging
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sys.stderr.write(f"GeminiCliAdapter [{msg_type}]: {line}\n")
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sys.stderr.flush()
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except json.JSONDecodeError:
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# Skip lines that are not valid JSON
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continue
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process.wait()
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except Exception as e:
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process.kill()
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raise e
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finally:
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self.last_latency = time.time() - start_time
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return {
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"text": accumulated_text,
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"tool_calls": tool_calls
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}
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