UN-2967 [FIX] - Fix Repeated Embedding Call For Zero Chunk Size and Multiple Prompts (#1682)

* [MISC] - Update Tool Versions

Bumped tool versions:
- Classifier: 0.0.70 → 0.0.71
- Structure: 0.0.90 → 0.0.91
- Text Extractor: 0.0.66 → 0.0.67

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

* Fixed extra embedding calls while chunking is zero

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

---------

Co-authored-by: Claude <[email protected]>
Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>

Author: 3 people

prompt-service/src/unstract/prompt_service/controllers/answer_prompt.py

@@ -149,19 +149,24 @@ def prompt_processor() -> Any:
                 capture_metrics=True,
             )
 
-            embedding = EmbeddingCompat(
-                adapter_instance_id=output[PSKeys.EMBEDDING],
-                tool=util,
-                kwargs={
-                    **usage_kwargs,
-                },
-            )
+            # Only create embedding and vector_db if chunk_size > 0
+            # When chunk_size is 0, we read the complete file without embeddings
+            embedding = None
+            vector_db = None
+            if chunk_size > 0:
+                embedding = EmbeddingCompat(
+                    adapter_instance_id=output[PSKeys.EMBEDDING],
+                    tool=util,
+                    kwargs={
+                        **usage_kwargs,
+                    },
+                )
 
-            vector_db = VectorDB(
-                tool=util,
-                adapter_instance_id=output[PSKeys.VECTOR_DB],
-                embedding=embedding,
-            )
+                vector_db = VectorDB(
+                    tool=util,
+                    adapter_instance_id=output[PSKeys.VECTOR_DB],
+                    embedding=embedding,
+                )
         except SdkError as e:
             msg = f"Couldn't fetch adapter. {e}"
             app.logger.error(msg)
@@ -384,7 +389,7 @@ def prompt_processor() -> Any:
                     output=output,
                     doc_id=doc_id,
                     llm=llm,
-                    vector_db=vector_db,
+                    vector_db=vector_db,  # This will be None when chunk_size is 0
                     retrieval_type=retrieval_strategy,
                     metadata=metadata,
                     chunk_size=chunk_size,
@@ -657,7 +662,9 @@ def prompt_processor() -> Any:
                     **challenge_metrics,
                 }
             )
-            vector_db.close()
+            # Only close vector_db if it was created (chunk_size > 0)
+            if vector_db:
+                vector_db.close()
     publish_log(
         log_events_id,
         {"tool_id": tool_id, "doc_name": doc_name},

prompt-service/src/unstract/prompt_service/services/indexing.py

@@ -51,6 +51,13 @@ def index(
                 tool=util,
                 fs=fs_instance,
             )
+
+            # Skip embedding creation and indexing when chunk_size is 0
+            # When chunk_size is 0, we don't need vector operations
+            if chunking_config.chunk_size == 0:
+                logger.info(f"Skipping indexing for chunk_size=0. Doc ID: {doc_id}")
+                return doc_id
+
             embedding = EmbeddingCompat(
                 adapter_instance_id=instance_identifiers.embedding_instance_id,
                 tool=util,