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SKILL.md
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SKILL.md
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---
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name: gemini-deep-research
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description: "使用Gemini深度研究代理执行复杂、长期的研究任务。在被要求研究需要多源综合、竞争分析、市场调研或全面技术调查的主题时使用，这些主题受益于系统的网络搜索和分析。"
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metadata: {"clawdbot":{"emoji":"🔬","requires":{"env":["GEMINI_API_KEY"]},"primaryEnv":"GEMINI_API_KEY"}}
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---
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# Gemini Deep Research
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Use Gemini's Deep Research Agent to perform complex, long-running context gathering and synthesis tasks.
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## Prerequisites
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- `GEMINI_API_KEY` environment variable (from Google AI Studio)
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- **Note**: This does NOT work with Antigravity OAuth tokens. Requires a direct Gemini API key.
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## How It Works
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Deep Research is an agent that:
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1. Breaks down complex queries into sub-questions
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2. Searches the web systematically
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3. Synthesizes findings into comprehensive reports
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4. Provides streaming progress updates
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## Usage
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### Basic Research
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```bash
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scripts/deep_research.py --query "Research the history of Google TPUs"
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```
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### Custom Output Format
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```bash
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scripts/deep_research.py --query "Research the competitive landscape of EV batteries" \
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--format "1. Executive Summary\n2. Key Players (include data table)\n3. Supply Chain Risks"
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```
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### With File Search (optional)
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```bash
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scripts/deep_research.py --query "Compare our 2025 fiscal year report against current public web news" \
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--file-search-store "fileSearchStores/my-store-name"
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```
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### Stream Progress
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```bash
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scripts/deep_research.py --query "Your research topic" --stream
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```
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## Output
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The script saves results to timestamped files:
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- `deep-research-YYYY-MM-DD-HH-MM-SS.md` - Final report in markdown
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- `deep-research-YYYY-MM-DD-HH-MM-SS.json` - Full interaction metadata
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## API Details
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- **Endpoint**: `https://generativelanguage.googleapis.com/v1beta/interactions`
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- **Agent**: `deep-research-pro-preview-12-2025`
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- **Auth**: `x-goog-api-key` header (NOT OAuth Bearer token)
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## Limitations
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- Requires Gemini API key (get from [Google AI Studio](https://aistudio.google.com/apikey))
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- Does NOT work with Antigravity OAuth authentication
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- Long-running tasks (minutes to hours depending on complexity)
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- May incur API costs depending on your quota
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_meta.json
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_meta.json
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{
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"ownerId": "kn7azq5e6sw0fbwwzdpcwvvjzd7z0x4z",
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"slug": "gemini-deep-research",
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"version": "1.0.0",
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"publishedAt": 1768845281114
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}
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scripts/deep_research.py
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scripts/deep_research.py
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#!/usr/bin/env python3
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"""
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Gemini Deep Research API client
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Performs complex, long-running research tasks via Gemini's Deep Research Agent
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"""
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import argparse
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import json
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import os
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import sys
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import time
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from datetime import datetime
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from pathlib import Path
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import requests
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API_BASE = "https://generativelanguage.googleapis.com/v1beta"
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AGENT_MODEL = "deep-research-pro-preview-12-2025"
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def create_interaction(api_key, query, output_format=None, file_search_store=None):
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"""Start a new deep research interaction"""
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headers = {
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"Content-Type": "application/json",
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"x-goog-api-key": api_key
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}
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payload = {
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"input": query,
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"agent": AGENT_MODEL,
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"background": True
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}
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if output_format:
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payload["input"] = f"{query}\n\nFormat the output as follows:\n{output_format}"
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if file_search_store:
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payload["tools"] = [{
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"type": "file_search",
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"file_search_store_names": [file_search_store]
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}]
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response = requests.post(
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f"{API_BASE}/interactions",
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headers=headers,
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json=payload
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)
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if response.status_code != 200:
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print(f"Error creating interaction: {response.status_code}", file=sys.stderr)
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print(response.text, file=sys.stderr)
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sys.exit(1)
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return response.json()
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def poll_interaction(api_key, interaction_id, stream=False):
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"""Poll for interaction updates"""
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headers = {
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"x-goog-api-key": api_key
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}
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while True:
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response = requests.get(
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f"{API_BASE}/interactions/{interaction_id}",
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headers=headers
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)
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if response.status_code != 200:
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print(f"Error polling interaction: {response.status_code}", file=sys.stderr)
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print(response.text, file=sys.stderr)
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sys.exit(1)
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data = response.json()
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status = data.get("status", "UNKNOWN")
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if stream:
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# Show progress updates
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if "statusMessage" in data:
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print(f"[{status}] {data['statusMessage']}", file=sys.stderr)
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if status == "completed":
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return data
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elif status == "failed":
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print(f"Research failed: {data.get('error', 'Unknown error')}", file=sys.stderr)
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sys.exit(1)
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time.sleep(10) # Poll every 10 seconds
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def extract_report(interaction_data):
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"""Extract the final report from interaction data"""
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if "output" in interaction_data:
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output = interaction_data["output"]
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if isinstance(output, dict) and "text" in output:
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return output["text"]
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elif isinstance(output, str):
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return output
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# Fallback: look in messages
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messages = interaction_data.get("messages", [])
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for msg in reversed(messages):
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if msg.get("role") == "model" and "parts" in msg:
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for part in msg["parts"]:
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if "text" in part:
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return part["text"]
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return None
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def main():
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parser = argparse.ArgumentParser(description="Gemini Deep Research API Client")
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parser.add_argument("--query", required=True, help="Research query")
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parser.add_argument("--format", help="Custom output format instructions")
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parser.add_argument("--file-search-store", help="File search store name (optional)")
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parser.add_argument("--stream", action="store_true", help="Show streaming progress updates")
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parser.add_argument("--output-dir", default=".", help="Output directory for results")
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parser.add_argument("--api-key", help="Gemini API key (overrides GEMINI_API_KEY env var)")
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args = parser.parse_args()
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# Get API key
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api_key = args.api_key or os.environ.get("GEMINI_API_KEY")
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if not api_key:
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print("Error: No API key provided.", file=sys.stderr)
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print("Please either:", file=sys.stderr)
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print(" 1. Provide --api-key argument", file=sys.stderr)
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print(" 2. Set GEMINI_API_KEY environment variable", file=sys.stderr)
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sys.exit(1)
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# Start research
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print(f"Starting deep research: {args.query}", file=sys.stderr)
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interaction = create_interaction(
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api_key,
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args.query,
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output_format=args.format,
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file_search_store=args.file_search_store
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)
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interaction_id = interaction.get("id")
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if not interaction_id:
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print(f"Error: No interaction ID in response: {interaction}", file=sys.stderr)
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sys.exit(1)
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print(f"Interaction started: {interaction_id}", file=sys.stderr)
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# Poll for completion
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print("Polling for results (this may take several minutes)...", file=sys.stderr)
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result = poll_interaction(api_key, interaction_id, stream=args.stream)
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# Extract report
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report = extract_report(result)
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if not report:
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print("Warning: Could not extract report text from response", file=sys.stderr)
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report = json.dumps(result, indent=2)
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# Save results
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timestamp = datetime.now().strftime("%Y-%m-%d-%H-%M-%S")
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output_dir = Path(args.output_dir)
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output_dir.mkdir(parents=True, exist_ok=True)
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md_path = output_dir / f"deep-research-{timestamp}.md"
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json_path = output_dir / f"deep-research-{timestamp}.json"
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md_path.write_text(report)
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json_path.write_text(json.dumps(result, indent=2))
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print(f"\nResearch complete!", file=sys.stderr)
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print(f"Report saved: {md_path}", file=sys.stderr)
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print(f"Full data saved: {json_path}", file=sys.stderr)
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# Print report to stdout
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print(report)
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if __name__ == "__main__":
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main()
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