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feat: add ephemeral prefill messages and system prompt loading

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- Implemented functionality to load ephemeral prefill messages from a JSON file, enhancing few-shot priming capabilities for the agent.
- Introduced a mechanism to load an ephemeral system prompt from environment variables or configuration files, ensuring dynamic prompt adjustments at API-call time.
- Updated the CLI and agent initialization to utilize the new prefill messages and system prompt, improving the overall interaction experience.
- Enhanced configuration options with new environment variables for prefill messages and system prompts, allowing for greater customization without persistence.
This commit is contained in:
teknium1 2026-02-23 23:55:42 -08:00
parent a183827128
commit 2bf96ad244
7 changed files with 218 additions and 36 deletions
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16
tools/web_tools.py
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@ -159,7 +159,7 @@ async def process_content_with_llm(
return processed_content
except Exception as e:
logger.error("Error processing content with LLM: %s", e)
logger.debug("Error processing content with LLM: %s", e)
return f"[Failed to process content: {str(e)[:100]}. Content size: {len(content):,} chars]"
@ -318,7 +318,7 @@ async def _process_large_content_chunked(
summaries.append(f"## Section {chunk_idx + 1}\n{summary}")
if not summaries:
logger.error("All chunk summarizations failed")
logger.debug("All chunk summarizations failed")
return "[Failed to process large content: all chunk summarizations failed]"
logger.info("Got %d/%d chunk summaries", len(summaries), len(chunks))
@ -532,7 +532,7 @@ def web_search_tool(query: str, limit: int = 5) -> str:
except Exception as e:
error_msg = f"Error searching web: {str(e)}"
logger.error("%s", error_msg)
logger.debug("%s", error_msg)
debug_call_data["error"] = error_msg
_debug.log_call("web_search_tool", debug_call_data)
@ -673,7 +673,7 @@ async def web_extract_tool(
})
except Exception as scrape_err:
logger.error("Error scraping %s: %s", url, scrape_err)
logger.debug("Scrape failed for %s: %s", url, scrape_err)
results.append({
"url": url,
"title": "",
@ -799,7 +799,7 @@ async def web_extract_tool(
except Exception as e:
error_msg = f"Error extracting content: {str(e)}"
logger.error("%s", error_msg)
logger.debug("%s", error_msg)
debug_call_data["error"] = error_msg
_debug.log_call("web_extract_tool", debug_call_data)
@ -892,7 +892,7 @@ async def web_crawl_tool(
**crawl_params
)
except Exception as e:
logger.error("Crawl API call failed: %s", e)
logger.debug("Crawl API call failed: %s", e)
raise
pages: List[Dict[str, Any]] = []
@ -1092,7 +1092,7 @@ async def web_crawl_tool(
except Exception as e:
error_msg = f"Error crawling website: {str(e)}"
logger.error("%s", error_msg)
logger.debug("%s", error_msg)
debug_call_data["error"] = error_msg
_debug.log_call("web_crawl_tool", debug_call_data)
@ -1227,7 +1227,7 @@ WEB_SEARCH_SCHEMA = {
WEB_EXTRACT_SCHEMA = {
"name": "web_extract",
"description": "Extract content from web page URLs. Pages under 5000 chars return raw content; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. Use browser tools only when pages require interaction or dynamic content.",
"description": "Extract content from web page URLs. Returns page content in markdown format. Pages under 5000 chars return full markdown; larger pages are LLM-summarized and capped at ~5000 chars per page. Pages over 2M chars are refused. If a URL fails or times out, use the browser tool to access it instead.",
"parameters": {
"type": "object",
"properties": {