fix stuff count (#1083)

docs/modules/chains/combine_docs_examples/chat_vector_db.ipynb

@@ -214,6 +214,78 @@
     "result['answer']"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "908c00e2",
+   "metadata": {},
+   "source": [
+    "## Chat Vector DB with `map_reduce`\n",
+    "We can also use different types of combine document chains with the Chat Vector DB chain."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "06d91167",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "from langchain.chains import LLMChain\n",
+    "from langchain.chains.question_answering import load_qa_chain\n",
+    "from langchain.chains.chat_vector_db.prompts import CONDENSE_QUESTION_PROMPT"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 9,
+   "id": "1711d3b4",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "llm = OpenAI(temperature=0)\n",
+    "question_generator = LLMChain(llm=llm, prompt=CONDENSE_QUESTION_PROMPT)\n",
+    "doc_chain = load_qa_chain(llm, chain_type=\"map_reduce\")\n",
+    "\n",
+    "chain = ChatVectorDBChain(\n",
+    "    vectorstore=vectorstore,\n",
+    "    question_generator=question_generator,\n",
+    "    combine_docs_chain=doc_chain,\n",
+    ")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 10,
+   "id": "375b33ef",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "chat_history = []\n",
+    "query = \"What did the president say about Ketanji Brown Jackson\"\n",
+    "result = chain({\"question\": query, \"chat_history\": chat_history})"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "ca48ff74",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "\" The president said that Ketanji Brown Jackson is one of the nation's top legal minds, a former top litigator in private practice, a former federal public defender, from a family of public school educators and police officers, a consensus builder, and has received a broad range of support from the Fraternal Order of Police to former judges appointed by Democrats and Republicans.\""
+      ]
+     },
+     "execution_count": 11,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "result['answer']"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "2324cdc6-98bf-4708-b8cd-02a98b1e5b67",
@@ -293,14 +365,6 @@
     "query = \"Did he mention who she suceeded\"\n",
     "result = qa({\"question\": query, \"chat_history\": chat_history})"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a7ea93ff-1899-4171-9c24-85df20ae1a3d",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
@@ -319,7 +383,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.9"
+   "version": "3.9.1"
   }
  },
  "nbformat": 4,

langchain/chains/combine_documents/stuff.py

@@ -68,7 +68,11 @@ class StuffDocumentsChain(BaseCombineDocumentsChain, BaseModel):
         # Format each document according to the prompt
         doc_strings = [self.document_prompt.format(**doc) for doc in doc_dicts]
         # Join the documents together to put them in the prompt.
-        inputs = kwargs.copy()
+        inputs = {
+            k: v
+            for k, v in kwargs.items()
+            if k in self.llm_chain.prompt.input_variables
+        }
         inputs[self.document_variable_name] = "\n\n".join(doc_strings)
         return inputs