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feat: add support for multiple sources in agent configuration and update related components

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This commit is contained in:
Siddhant Rai
2025-09-08 22:10:08 +05:30
parent 07d59b6640
commit 2f88890c94
5 changed files with 592 additions and 158 deletions
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14
application/retriever/classic_rag.py
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@@ -46,7 +46,7 @@ class ClassicRAG(BaseRetriever):
user_api_key=self.user_api_key,
decoded_token=decoded_token,
)
if "active_docs" in source and source["active_docs"] is not None:
if isinstance(source["active_docs"], list):
self.vectorstores = source["active_docs"]
@@ -54,7 +54,6 @@ class ClassicRAG(BaseRetriever):
self.vectorstores = [source["active_docs"]]
else:
self.vectorstores = []
self.question = self._rephrase_query()
self.decoded_token = decoded_token
self._validate_vectorstore_config()
@@ -64,7 +63,6 @@ class ClassicRAG(BaseRetriever):
if not self.vectorstores:
logging.warning("No vectorstores configured for retrieval")
return
invalid_ids = [
vs_id for vs_id in self.vectorstores if not vs_id or not vs_id.strip()
]
@@ -84,12 +82,16 @@ class ClassicRAG(BaseRetriever):
or not self.vectorstores
):
return self.original_question
prompt = f"""Given the following conversation history:
{self.chat_history}
Rephrase the following user question to be a standalone search query
that captures all relevant context from the conversation:
"""
messages = [
@@ -109,7 +111,6 @@ class ClassicRAG(BaseRetriever):
"""Retrieve relevant documents from configured vectorstores"""
if self.chunks == 0 or not self.vectorstores:
return []
all_docs = []
chunks_per_source = max(1, self.chunks // len(self.vectorstores))
@@ -128,7 +129,6 @@ class ClassicRAG(BaseRetriever):
else:
page_content = doc.get("text", doc.get("page_content", ""))
metadata = doc.get("metadata", {})
title = metadata.get(
"title", metadata.get("post_title", page_content)
)
@@ -136,7 +136,6 @@ class ClassicRAG(BaseRetriever):
title = title.split("/")[-1]
else:
title = str(title).split("/")[-1]
all_docs.append(
{
"title": title,
@@ -150,7 +149,6 @@ class ClassicRAG(BaseRetriever):
exc_info=True,
)
continue
return all_docs
def search(self, query: str = ""):