fix: Fix pipeline with join node

haystack/nodes/file_converter/image.py

@@ -119,7 +119,7 @@ def convert(
 
         file_path = Path(file_path)
         image = Image.open(file_path)
-        pages = self._image_to_text(image)
+        pages = self._image_to_text(image)  # type: ignore
         if remove_numeric_tables is None:
             remove_numeric_tables = self.remove_numeric_tables
         if valid_languages is None:

haystack/nodes/other/join_docs.py

@@ -1,7 +1,7 @@
 import logging
 from collections import defaultdict
 from math import inf
-from typing import List, Optional
+from typing import List, Optional, Dict, Tuple
 
 from haystack.nodes.other.join import JoinNode
 from haystack.schema import Document
@@ -58,8 +58,13 @@ def __init__(
         self.top_k_join = top_k_join
         self.sort_by_score = sort_by_score
 
-    def run_accumulated(self, inputs: List[dict], top_k_join: Optional[int] = None):  # type: ignore
+    def run_accumulated(self, inputs: List[Dict], top_k_join: Optional[int] = None) -> Tuple[Dict, str]:
         results = [inp["documents"] for inp in inputs]
+
+        # Check if all results are non-empty
+        if all(not res for res in results):
+            return {"documents": [], "labels": inputs[0].get("labels", None)}, "output_1"
+
         document_map = {doc.id: doc for result in results for doc in result}
 
         if self.join_mode == "concatenate":
@@ -98,7 +103,7 @@ def run_accumulated(self, inputs: List[dict], top_k_join: Optional[int] = None):
 
         return output, "output_1"
 
-    def run_batch_accumulated(self, inputs: List[dict], top_k_join: Optional[int] = None):  # type: ignore
+    def run_batch_accumulated(self, inputs: List[dict], top_k_join: Optional[int] = None) -> Tuple[Dict, str]:
         # Join single document lists
         if isinstance(inputs[0]["documents"][0], Document):
             return self.run(inputs=inputs, top_k_join=top_k_join)
@@ -117,13 +122,13 @@ def run_batch_accumulated(self, inputs: List[dict], top_k_join: Optional[int] =
 
             return output, "output_1"
 
-    def _concatenate_results(self, results, document_map):
+    def _concatenate_results(self, results: List[List[Document]], document_map: Dict) -> Dict[str, float]:
         """
         Concatenates multiple document result lists.
         Return the documents with the higher score.
         """
         list_id = list(document_map.keys())
-        scores_map = {}
+        scores_map: Dict[str, float] = {}
         for idx in list_id:
             tmp = []
             for result in results:
@@ -134,11 +139,11 @@ def _concatenate_results(self, results, document_map):
             scores_map.update({idx: item_best_score.score})
         return scores_map
 
-    def _calculate_comb_sum(self, results):
+    def _calculate_comb_sum(self, results: List[List[Document]]) -> Dict[str, float]:
         """
         Calculates a combination sum by multiplying each score by its weight.
         """
-        scores_map = defaultdict(int)
+        scores_map: Dict[str, float] = defaultdict(float)
         weights = self.weights if self.weights else [1 / len(results)] * len(results)
 
         for result, weight in zip(results, weights):
@@ -147,14 +152,14 @@ def _calculate_comb_sum(self, results):
 
         return scores_map
 
-    def _calculate_rrf(self, results):
+    def _calculate_rrf(self, results: List[List[Document]]) -> Dict[str, float]:
         """
         Calculates the reciprocal rank fusion. The constant K is set to 61 (60 was suggested by the original paper,
         plus 1 as python lists are 0-based and the paper used 1-based ranking).
         """
         K = 61
 
-        scores_map = defaultdict(int)
+        scores_map: Dict[str, float] = defaultdict(float)
         weights = self.weights if self.weights else [1 / len(results)] * len(results)
 
         # Calculate weighted reciprocal rank fusion score

haystack/nodes/other/shaper.py

@@ -745,7 +745,11 @@ def run(  # type: ignore
         meta: Optional[dict] = None,
         invocation_context: Optional[Dict[str, Any]] = None,
     ) -> Tuple[Dict, str]:
-        invocation_context = invocation_context or {}
+        if invocation_context is None:
+            invocation_context = {}
+        else:
+            invocation_context = invocation_context.copy()
+
         if query and "query" not in invocation_context.keys():
             invocation_context["query"] = query
 
@@ -755,7 +759,7 @@ def run(  # type: ignore
         if labels and "labels" not in invocation_context.keys():
             invocation_context["labels"] = labels
 
-        if documents != None and "documents" not in invocation_context.keys():
+        if documents is not None and "documents" not in invocation_context.keys():
             invocation_context["documents"] = documents
 
         if meta and "meta" not in invocation_context.keys():

haystack/nodes/prompt/prompt_node.py

@@ -247,7 +247,10 @@ def _prepare(  # type: ignore
         """
         Prepare prompt invocation.
         """
-        invocation_context = invocation_context or {}
+        if invocation_context is None:
+            invocation_context = {}
+        else:
+            invocation_context = invocation_context.copy()
 
         if query and "query" not in invocation_context:
             invocation_context["query"] = query

haystack/pipelines/base.py

@@ -596,19 +596,27 @@ def run(  # type: ignore
                                         **existing_input.get("_debug", {}),
                                         **node_output.get("_debug", {}),
                                     }
-                                if query:
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **updated_input}
+                                if query and "query" not in updated_input:
                                     updated_input["query"] = query
-                                if file_paths:
+                                if file_paths and "file_paths" not in updated_input:
                                     updated_input["file_paths"] = file_paths
-                                if labels:
+                                if labels and "labels" not in updated_input:
                                     updated_input["labels"] = labels
-                                if documents:
+                                if documents and "documents" not in updated_input:
                                     updated_input["documents"] = documents
-                                if meta:
+                                if meta and "meta" not in updated_input:
                                     updated_input["meta"] = meta
                             else:
                                 existing_input["inputs"].append(node_output)
-                                updated_input = existing_input
+                                if "_debug" in node_output.keys():
+                                    existing_input["_debug"] = {
+                                        **existing_input.get("_debug", {}),
+                                        **node_output.get("_debug", {}),
+                                    }
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **existing_input}
                             queue[n] = updated_input
                         else:
                             queue[n] = node_output
@@ -618,6 +626,22 @@ def run(  # type: ignore
 
         return node_output
 
+    def _combine_node_outputs(self, existing_input: Dict[str, Any], node_output: Dict[str, Any]) -> Dict[str, Any]:
+        """
+        Combines the outputs of two nodes into a single input for a downstream node.
+        For matching keys first node's (existing_input) value is kept. This is used for join nodes.
+
+        :param existing_input: The output of the first node.
+        :param node_output: The output of the second node.
+        """
+        additional_input = {}
+        combined = {**node_output, **existing_input}
+        for key in combined:
+            # Don't overwrite these keys since they are set in Pipeline.run
+            if key not in ["inputs", "params", "_debug"]:
+                additional_input[key] = combined[key]
+        return additional_input
+
     async def _arun(  # noqa: C901,PLR0912 type: ignore
         self,
         query: Optional[str] = None,
@@ -734,19 +758,27 @@ async def _arun(  # noqa: C901,PLR0912 type: ignore
                                         **existing_input.get("_debug", {}),
                                         **node_output.get("_debug", {}),
                                     }
-                                if query:
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **updated_input}
+                                if query and "query" not in updated_input:
                                     updated_input["query"] = query
-                                if file_paths:
+                                if file_paths and "file_paths" not in updated_input:
                                     updated_input["file_paths"] = file_paths
-                                if labels:
+                                if labels and "labels" not in updated_input:
                                     updated_input["labels"] = labels
-                                if documents:
+                                if documents and "documents" not in updated_input:
                                     updated_input["documents"] = documents
-                                if meta:
+                                if meta and "meta" not in updated_input:
                                     updated_input["meta"] = meta
                             else:
                                 existing_input["inputs"].append(node_output)
-                                updated_input = existing_input
+                                if "_debug" in node_output.keys():
+                                    existing_input["_debug"] = {
+                                        **existing_input.get("_debug", {}),
+                                        **node_output.get("_debug", {}),
+                                    }
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **existing_input}
                             queue[n] = updated_input
                         else:
                             queue[n] = node_output
@@ -756,6 +788,7 @@ async def _arun(  # noqa: C901,PLR0912 type: ignore
 
         return node_output
 
+    # pylint: disable=too-many-branches
     def run_batch(  # noqa: C901,PLR0912 type: ignore
         self,
         queries: Optional[List[str]] = None,
@@ -896,19 +929,32 @@ def run_batch(  # noqa: C901,PLR0912 type: ignore
                             existing_input = queue[n]
                             if "inputs" not in existing_input.keys():
                                 updated_input: Dict = {"inputs": [existing_input, node_output], "params": params}
-                                if queries:
+                                if "_debug" in existing_input.keys() or "_debug" in node_output.keys():
+                                    updated_input["_debug"] = {
+                                        **existing_input.get("_debug", {}),
+                                        **node_output.get("_debug", {}),
+                                    }
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **updated_input}
+                                if queries and "queries" not in updated_input:
                                     updated_input["queries"] = queries
-                                if file_paths:
+                                if file_paths and "file_paths" not in updated_input:
                                     updated_input["file_paths"] = file_paths
-                                if labels:
+                                if labels and "labels" not in updated_input:
                                     updated_input["labels"] = labels
-                                if documents:
+                                if documents and "documents" not in updated_input:
                                     updated_input["documents"] = documents
-                                if meta:
+                                if meta and "meta" not in updated_input:
                                     updated_input["meta"] = meta
                             else:
                                 existing_input["inputs"].append(node_output)
-                                updated_input = existing_input
+                                if "_debug" in node_output.keys():
+                                    existing_input["_debug"] = {
+                                        **existing_input.get("_debug", {}),
+                                        **node_output.get("_debug", {}),
+                                    }
+                                additional_input = self._combine_node_outputs(existing_input, node_output)
+                                updated_input = {**additional_input, **existing_input}
                             queue[n] = updated_input
                         else:
                             queue[n] = node_output

releasenotes/notes/fix-pipeline-with-join-node-5f23a426cd4d88d9.yaml

@@ -0,0 +1,69 @@
+---
+fixes:
+  - |
+    When using a `Pipeline` with a `JoinNode` (e.g. `JoinDocuments`) all information from the previous nodes was lost
+    other than a few select fields (e.g. `documents`). This was due to the `JoinNode` not properly passing on
+    the information from the previous nodes. This has been fixed and now all information from the previous nodes is
+    passed on to the next node in the pipeline.
+
+    For example, this is a pipeline that rewrites the `query` during pipeline execution combined with a hybrid retrieval
+    setup that requires a `JoinDocuments` node. Specifically the first prompt node rewrites the `query` to fix all
+    spelling errors, and this new `query` is used for retrieval. And now the `JoinDocuments` node will now pass on the
+    rewritten `query` so it can be used by the `QAPromptNode` node whereas before it would pass on the original query.
+    ```python
+    from haystack import Pipeline
+    from haystack.nodes import BM25Retriever, EmbeddingRetriever, PromptNode, Shaper, JoinDocuments, PromptTemplate
+    from haystack.document_stores import InMemoryDocumentStore
+
+    document_store = InMemoryDocumentStore(use_bm25=True)
+    dicts = [{"content": "The capital of Germany is Berlin."}, {"content": "The capital of France is Paris."}]
+    document_store.write_documents(dicts)
+
+    query_prompt_node = PromptNode(
+        model_name_or_path="gpt-3.5-turbo",
+        api_key="",
+        default_prompt_template=PromptTemplate("You are a spell checker. Given a user query return the same query with all spelling errors fixed.\nUser Query: {query}\nSpell Checked Query:")
+    )
+    shaper = Shaper(
+        func="join_strings",
+        inputs={"strings": "results"},
+        outputs=["query"],
+    )
+    qa_prompt_node = PromptNode(
+        model_name_or_path="gpt-3.5-turbo",
+        api_key="",
+        default_prompt_template=PromptTemplate("Answer the user query. Query: {query}")
+    )
+    sparse_retriever = BM25Retriever(
+        document_store=document_store,
+        top_k=2
+    )
+    dense_retriever = EmbeddingRetriever(
+        document_store=document_store,
+        embedding_model="intfloat/e5-base-v2",
+        model_format="sentence_transformers",
+        top_k=2
+    )
+    document_store.update_embeddings(dense_retriever)
+
+    pipeline = Pipeline()
+    pipeline.add_node(component=query_prompt_node, name="QueryPromptNode", inputs=["Query"])
+    pipeline.add_node(component=shaper, name="ListToString", inputs=["QueryPromptNode"])
+    pipeline.add_node(component=sparse_retriever, name="BM25", inputs=["ListToString"])
+    pipeline.add_node(component=dense_retriever, name="Embedding", inputs=["ListToString"])
+    pipeline.add_node(
+        component=JoinDocuments(join_mode="concatenate"), name="Join", inputs=["BM25", "Embedding"]
+    )
+    pipeline.add_node(component=qa_prompt_node, name="QAPromptNode", inputs=["Join"])
+
+    out = pipeline.run(query="What is the captial of Grmny?", debug=True)
+    print(out["invocation_context"])
+    # Before Fix
+    # {'query': 'What is the captial of Grmny?',  <-- Original Query!!
+    #   'results': ['The capital of Germany is Berlin.'],
+    #   'prompts': ['Answer the user query. Query: What is the captial of Grmny?'],  <-- Original Query!!
+    # After Fix
+    # {'query': 'What is the capital of Germany?',  <-- Rewritten Query!!
+    #   'results': ['The capital of Germany is Berlin.'],
+    #   'prompts': ['Answer the user query. Query: What is the capital of Germany?'],  <-- Rewritten Query!!
+    ```

test/nodes/test_join_documents.py

@@ -1,7 +1,7 @@
 import pytest
 
 
-from haystack import Document
+from haystack import Document, Pipeline
 from haystack.nodes.other.join_docs import JoinDocuments
 from copy import deepcopy
 
@@ -149,3 +149,25 @@ def test_joindocuments_rrf_weights():
     assert result_none["documents"] == result_even["documents"]
     assert result_uneven["documents"] != result_none["documents"]
     assert result_uneven["documents"][0].score > result_none["documents"][0].score
+
+
+@pytest.mark.unit
+def test_join_node_empty_documents():
+    pipe = Pipeline()
+    join_node = JoinDocuments(join_mode="concatenate")
+    pipe.add_node(component=join_node, name="Join", inputs=["Query"])
+
+    # Test single document lists
+    output = pipe.run(query="test", documents=[])
+    assert len(output["documents"]) == 0
+
+
+@pytest.mark.unit
+def test_join_node_none_documents():
+    pipe = Pipeline()
+    join_node = JoinDocuments(join_mode="concatenate")
+    pipe.add_node(component=join_node, name="Join", inputs=["Query"])
+
+    # Test single document lists
+    output = pipe.run(query="test", documents=None)
+    assert len(output["documents"]) == 0