text: Title: ValueError: Input question not found in component chat_prompt_builder.
  Body: ```python
  
  #!/usr/bin/env python
  # coding: utf-8
  
  # In[51]:
  
  
  from haystack.components.writers import DocumentWriter
  from haystack.components.converters import MarkdownToDocument, PyPDFToDocument, TextFileToDocument
  from haystack.components.preprocessors import DocumentSplitter, DocumentCleaner
  from haystack.components.routers import FileTypeRouter
  from haystack.components.joiners import DocumentJoiner
  from haystack.components.embedders import SentenceTransformersDocumentEmbedder
  from haystack import Pipeline
  from haystack.document_stores.in_memory import InMemoryDocumentStore
  from pathlib import Path
  
  
  document_store = InMemoryDocumentStore()
  file_type_router = FileTypeRouter(mime_types=["application/pdf"])
  pdf_converter = PyPDFToDocument()
  document_joiner = DocumentJoiner()
  
  
  # In[ ]:
  
  
  
  
  
  # In[52]:
  
  
  mpath = "/Users/apapoo/Desktop/Github_Hub/AutoHealthRAG/input/model/bge-large-zh-v1.5/"
  
  document_cleaner = DocumentCleaner()
  document_splitter = DocumentSplitter(split_by="word", split_length=150, split_overlap=50)
  document_embedder = SentenceTransformersDocumentEmbedder(model=mpath)
  document_writer = DocumentWriter(document_store)
  
  
  # In[53]:
  
  
  preprocessing_pipeline = Pipeline()
  preprocessing_pipeline.add_component(instance=file_type_router, name="file_type_router")
  preprocessing_pipeline.add_component(instance=pdf_converter, name="pypdf_converter")
  preprocessing_pipeline.add_component(instance=document_joiner, name="document_joiner")
  preprocessing_pipeline.add_component(instance=document_cleaner, name="document_cleaner")
  preprocessing_pipeline.add_component(instance=document_splitter, name="document_splitter")
  preprocessing_pipeline.add_component(instance=document_embedder, name="document_embedder")
  preprocessing_pipeline.add_component(instance=document_writer, name="document_writer")
  
  
  # In[54]:
  
  
  preprocessing_pipeline.connect("file_type_router.application/pdf", "pypdf_converter.sources")
  preprocessing_pipeline.connect("pypdf_converter", "document_joiner")
  preprocessing_pipeline.connect("document_joiner", "document_cleaner")
  preprocessing_pipeline.connect("document_cleaner", "document_splitter")
  preprocessing_pipeline.connect("document_splitter", "document_embedder")
  preprocessing_pipeline.connect("document_embedder", "document_writer")
  
  
  # In[55]:
  
  
  output_dir = "../input/debug_txt"
  preprocessing_pipeline.run({"file_type_router": {"sources": list(Path(output_dir).glob("**/*"))}})
  
  
  # In[50]:
  
  
  from haystack.components.embedders import SentenceTransformersTextEmbedder
  from haystack.components.retrievers.in_memory import InMemoryEmbeddingRetriever
  from haystack.components.builders import ChatPromptBuilder
  from haystack.dataclasses import ChatMessage
  from haystack.components.generators.chat import HuggingFaceAPIChatGenerator
  from haystack.components.generators.chat import OpenAIChatGenerator
  from haystack.utils import Secret
  from getpass import getpass
  import os
  
  
  
  template = [
      ChatMessage.from_user(
        """
      根据此文本的内容：
      {% for document in documents %}
      {{document.content}}
      {% endfor %}
      回答给定的问题：{{query}}
      答案：
        """
      )]
  pipe = Pipeline()
  mpath = "/Users/apapoo/Desktop/Github_Hub/AutoHealthRAG/input/model/bge-large-zh-v1.5/"
  pipe.add_component("embedder", SentenceTransformersTextEmbedder(model=mpath))
  pipe.add_component("retriever", InMemoryEmbeddingRetriever(document_store=document_store))
  pipe.add_component("chat_prompt_builder", ChatPromptBuilder(template=template))
  
  if "TOGETHER_AI_API_KEY" not in os.environ:
      os.environ["TOGETHER_AI_API_KEY"] = getpass("Enter TogetherAI API key:")
  
  pipe.add_component(
      "llm",
      OpenAIChatGenerator(model="deepseek-ai/DeepSeek-R1",
          api_key=Secret.from_env_var("TOGETHER_AI_API_KEY"),
          api_base_url="https://api.together.xyz/v1",
          streaming_callback=lambda chunk: print(chunk.content, end="", flush=True))
  )
  
  # pipe.add_component(
  #     "llm",
  #     HuggingFaceAPIChatGenerator(
  #         api_type="serverless_inference_api", api_params={"model": "HuggingFaceH4/zephyr-7b-beta"}
  #     ),
  # )
  pipe.connect("embedder.embedding", "retriever.query_embedding")
  pipe.connect("retriever", "chat_prompt_builder.documents")
  pipe.connect("abc", "llm.messages")
  
  
  # In[ ]:
  
  
  # pipe.draw(path="./show_pip.png")
  
  
  # In[48]:
  
  
  question = (
      "2024年福建省男生的肺活量是多少"
  )
  
  pipe.run({"embedder": {"text": question}, "abc": {"question": question}})
  ```
  
  
  =============>This is my code, and the following error occurred, Can you tell me the solution?
  ---------------------------------------------------------------------------
  File ~/anaconda3/envs/py311/lib/python3.11/site-packages/haystack/core/pipeline/pipeline.py:195, in Pipeline.run(self, data, include_outputs_from)
      192 data = self._prepare_component_input_data(data)
      194 # Raise ValueError if input is malformed in some way
  --> 195 self._validate_input(data)
      197 if include_outputs_from is None:
      198     include_outputs_from = set()
  
  File ~/anaconda3/envs/py311/lib/python3.11/site-packages/haystack/core/pipeline/base.py:789, in PipelineBase._validate_input(self, data)
      787     for input_name in component_inputs.keys():
      788         if input_name not in instance.__haystack_input__._sockets_dict:
  --> 789             raise ValueError(f"Input {input_name} not found in component {component_name}.")
      791 for component_name in self.graph.nodes:
      792     instance = self.graph.nodes[component_name]["instance"]
  
  ValueError: Input question not found in component chat_prompt_builder.
  
  
  
  