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Add --quick and --deep flags for research depth

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- quick: 8-12 sources each, faster response
- default: 20-30 sources each (unchanged behavior)
- deep: 50-70 Reddit, 40-60 X for comprehensive research

Adjusts API timeouts based on depth. Cache keys include depth
so different depths are cached separately.

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
Matt Van Horn
2026-01-23 13:41:55 -08:00
parent 19d2c41161
commit f603323ca8
4 changed files with 69 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files
scripts/lib/openai_reddit.py
+17 -3
View File
@@ -8,9 +8,16 @@ from . import http
OPENAI_RESPONSES_URL = "https://api.openai.com/v1/responses"
# Depth configurations: (min, max) threads to request
DEPTH_CONFIG = {
"quick": (8, 12),
"default": (20, 30),
"deep": (50, 70),
}
REDDIT_SEARCH_PROMPT = """Search Reddit for discussions about: {topic}
Focus on threads from the last 30 days. Find 15-30 high-quality, relevant threads.
Focus on threads from the last 30 days. Find {min_items}-{max_items} high-quality, relevant threads.
IMPORTANT: Return ONLY valid JSON in this exact format, no other text:
{{
@@ -38,6 +45,7 @@ def search_reddit(
api_key: str,
model: str,
topic: str,
depth: str = "default",
mock_response: Optional[Dict] = None,
) -> Dict[str, Any]:
"""Search Reddit for relevant threads using OpenAI Responses API.
@@ -46,6 +54,7 @@ def search_reddit(
api_key: OpenAI API key
model: Model to use
topic: Search topic
depth: Research depth - "quick", "default", or "deep"
mock_response: Mock response for testing
Returns:
@@ -54,11 +63,16 @@ def search_reddit(
if mock_response is not None:
return mock_response
min_items, max_items = DEPTH_CONFIG.get(depth, DEPTH_CONFIG["default"])
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
# Adjust timeout based on depth
timeout = 60 if depth == "quick" else 90 if depth == "default" else 120
payload = {
"model": model,
"tools": [
@@ -70,10 +84,10 @@ def search_reddit(
}
],
"include": ["web_search_call.action.sources"],
"input": REDDIT_SEARCH_PROMPT.format(topic=topic),
"input": REDDIT_SEARCH_PROMPT.format(topic=topic, min_items=min_items, max_items=max_items),
}
return http.post(OPENAI_RESPONSES_URL, payload, headers=headers, timeout=60)
return http.post(OPENAI_RESPONSES_URL, payload, headers=headers, timeout=timeout)
def parse_reddit_response(response: Dict[str, Any]) -> List[Dict[str, Any]]:
scripts/lib/xai_x.py
+18 -2
View File
@@ -9,9 +9,16 @@ from . import http
# xAI uses chat completions endpoint
XAI_CHAT_URL = "https://api.x.ai/v1/chat/completions"
# Depth configurations: (min, max) posts to request
DEPTH_CONFIG = {
"quick": (8, 12),
"default": (20, 30),
"deep": (40, 60),
}
X_SEARCH_PROMPT = """You have access to real-time X (Twitter) data. Search for posts about: {topic}
Focus on posts from {from_date} to {to_date}. Find 15-30 high-quality, relevant posts.
Focus on posts from {from_date} to {to_date}. Find {min_items}-{max_items} high-quality, relevant posts.
IMPORTANT: Return ONLY valid JSON in this exact format, no other text:
{{
@@ -47,6 +54,7 @@ def search_x(
topic: str,
from_date: str,
to_date: str,
depth: str = "default",
mock_response: Optional[Dict] = None,
) -> Dict[str, Any]:
"""Search X for relevant posts using xAI API with live search.
@@ -57,6 +65,7 @@ def search_x(
topic: Search topic
from_date: Start date (YYYY-MM-DD)
to_date: End date (YYYY-MM-DD)
depth: Research depth - "quick", "default", or "deep"
mock_response: Mock response for testing
Returns:
@@ -65,11 +74,16 @@ def search_x(
if mock_response is not None:
return mock_response
min_items, max_items = DEPTH_CONFIG.get(depth, DEPTH_CONFIG["default"])
headers = {
"Authorization": f"Bearer {api_key}",
"Content-Type": "application/json",
}
# Adjust timeout based on depth
timeout = 60 if depth == "quick" else 90 if depth == "default" else 120
# Use chat completions format with search enabled
payload = {
"model": model,
@@ -84,6 +98,8 @@ def search_x(
topic=topic,
from_date=from_date,
to_date=to_date,
min_items=min_items,
max_items=max_items,
),
}
],
@@ -95,7 +111,7 @@ def search_x(
},
}
return http.post(XAI_CHAT_URL, payload, headers=headers, timeout=90)
return http.post(XAI_CHAT_URL, payload, headers=headers, timeout=timeout)
def parse_x_response(response: Dict[str, Any]) -> List[Dict[str, Any]]: