feat: created new graph-based deep-research agent
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#!/usr/bin/env python3
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"""Entry router for deep-research.
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Reads the caller's prompt from state. If it contains a usable research
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topic, stores it as `topic` and falls through to the static `next`
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(plan). If the prompt is empty, routes to `ask_topic` so the user can
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supply one interactively.
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Routing (`_next`):
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- prompt present -> (no _next; static next: plan)
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- prompt empty -> ask_topic
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"""
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import json
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import os
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def load_state():
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path = os.environ.get("GRAPH_STATE_FILE")
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if path:
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with open(path) as f:
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return json.load(f)
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return json.loads(os.environ.get("GRAPH_STATE", "{}"))
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def main():
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state = load_state()
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prompt = (state.get("initial_prompt") or "").strip()
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if prompt:
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print(json.dumps({"topic": prompt}))
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else:
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print(json.dumps({"_next": "ask_topic"}))
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if __name__ == "__main__":
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main()
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