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feat: template-based prompt rendering with dynamic namespace injection (#2091)

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* feat: template-based prompt rendering with dynamic namespace injection

* refactor: improve template engine initialization with clearer formatting

* refactor: streamline ReActAgent methods and improve content extraction logic

feat: enhance error handling in NamespaceManager and TemplateEngine

fix: update NewAgent component to ensure consistent form data submission

test: modify tests for ReActAgent and prompt renderer to reflect method changes and improve coverage

* feat: tools namespace + three-tier token budget

* refactor: remove unused variable assignment in message building tests

* Enhance prompt customization and tool pre-fetching functionality

* ruff lint fix

* refactor: cleaner error handling and reduce code clutter

---------

Co-authored-by: Alex <a@tushynski.me>
This commit is contained in:
Siddhant Rai
2025-10-31 18:17:44 +05:30
committed by GitHub
parent a7d61b9d59
commit 21e5c261ef
33 changed files with 2917 additions and 646 deletions
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15
application/utils.py
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@@ -74,6 +74,17 @@ def count_tokens_docs(docs):
return tokens
def calculate_doc_token_budget(
gpt_model: str = "gpt-4o", history_token_limit: int = 2000
) -> int:
total_context = settings.LLM_TOKEN_LIMITS.get(
gpt_model, settings.DEFAULT_LLM_TOKEN_LIMIT
)
reserved = sum(settings.RESERVED_TOKENS.values())
doc_budget = total_context - history_token_limit - reserved
return max(doc_budget, 1000)
def get_missing_fields(data, required_fields):
"""Check for missing required fields. Returns list of missing field names."""
return [field for field in required_fields if field not in data]
@@ -141,8 +152,8 @@ def limit_chat_history(history, max_token_limit=None, gpt_model="docsgpt"):
max_token_limit
if max_token_limit
and max_token_limit
< settings.LLM_TOKEN_LIMITS.get(gpt_model, settings.DEFAULT_MAX_HISTORY)
else settings.LLM_TOKEN_LIMITS.get(gpt_model, settings.DEFAULT_MAX_HISTORY)
< settings.LLM_TOKEN_LIMITS.get(gpt_model, settings.DEFAULT_LLM_TOKEN_LIMIT)
else settings.LLM_TOKEN_LIMITS.get(gpt_model, settings.DEFAULT_LLM_TOKEN_LIMIT)
)
if not history: