langchain/templates/stepback-qa-prompting/stepback_qa_prompting/chain.py

from langchain.utilities import DuckDuckGoSearchAPIWrapper
from langchain_community.chat_models import ChatOpenAI
from langchain_core.output_parsers import StrOutputParser
from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
from langchain_core.runnables import RunnableLambda

search = DuckDuckGoSearchAPIWrapper(max_results=4)


def retriever(query):
    return search.run(query)


# Few Shot Examples
examples = [
    {
        "input": "Could the members of The Police perform lawful arrests?",
        "output": "what can the members of The Police do?",
    },
    {
        "input": "Jan Sindel’s was born in what country?",
        "output": "what is Jan Sindel’s personal history?",
    },
]
# We now transform these to example messages
example_prompt = ChatPromptTemplate.from_messages(
    [
        ("human", "{input}"),
        ("ai", "{output}"),
    ]
)
few_shot_prompt = FewShotChatMessagePromptTemplate(
    example_prompt=example_prompt,
    examples=examples,
)

prompt = ChatPromptTemplate.from_messages(
    [
        (
            "system",
            "You are an expert at world knowledge. Your task is to step back "
            "and paraphrase a question to a more generic step-back question, which "
            "is easier to answer. Here are a few examples:",
        ),
        # Few shot examples
        few_shot_prompt,
        # New question
        ("user", "{question}"),
    ]
)

question_gen = prompt | ChatOpenAI(temperature=0) | StrOutputParser()

response_prompt_template = """You are an expert of world knowledge. I am going to ask you a question. Your response should be comprehensive and not contradicted with the following context if they are relevant. Otherwise, ignore them if they are not relevant.

{normal_context}
{step_back_context}

Original Question: {question}
Answer:"""  # noqa: E501
response_prompt = ChatPromptTemplate.from_template(response_prompt_template)

chain = (
    {
        # Retrieve context using the normal question
        "normal_context": RunnableLambda(lambda x: x["question"]) | retriever,
        # Retrieve context using the step-back question
        "step_back_context": question_gen | retriever,
        # Pass on the question
        "question": lambda x: x["question"],
    }
    | response_prompt
    | ChatOpenAI(temperature=0)
    | StrOutputParser()
)
-												templates: fix deps (#15439)


											
										
										
											9 months ago
+								from langchain.utilities import DuckDuckGoSearchAPIWrapper
-												docs, community[patch], experimental[patch], langchain[patch], cli[pa… (#15412)

…tch]: import models from community

ran
```bash
git grep -l 'from langchain\.chat_models' | xargs -L 1 sed -i '' "s/from\ langchain\.chat_models/from\ langchain_community.chat_models/g"
git grep -l 'from langchain\.llms' | xargs -L 1 sed -i '' "s/from\ langchain\.llms/from\ langchain_community.llms/g"
git grep -l 'from langchain\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.embeddings/from\ langchain_community.embeddings/g"
git checkout master libs/langchain/tests/unit_tests/llms
git checkout master libs/langchain/tests/unit_tests/chat_models
git checkout master libs/langchain/tests/unit_tests/embeddings/test_imports.py
make format
cd libs/langchain; make format
cd ../experimental; make format
cd ../core; make format
```
											
										
										
											9 months ago
+								from langchain_community.chat_models import ChatOpenAI
-												docs[patch], templates[patch]: Import from core (#14575)

Update imports to use core for the low-hanging fruit changes. Ran
following

```bash
git grep -l 'langchain.schema.runnable' {docs,templates,cookbook}  | xargs sed -i '' 's/langchain\.schema\.runnable/langchain_core.runnables/g'
git grep -l 'langchain.schema.output_parser' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.output_parser/langchain_core.output_parsers/g'
git grep -l 'langchain.schema.messages' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.messages/langchain_core.messages/g'
git grep -l 'langchain.schema.chat_histry' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.chat_history/langchain_core.chat_history/g'
git grep -l 'langchain.schema.prompt_template' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.prompt_template/langchain_core.prompts/g'
git grep -l 'from langchain.pydantic_v1' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.pydantic_v1/from langchain_core.pydantic_v1/g'
git grep -l 'from langchain.tools.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.tools\.base/from langchain_core.tools/g'
git grep -l 'from langchain.chat_models.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.chat_models.base/from langchain_core.language_models.chat_models/g'
git grep -l 'from langchain.llms.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.llms\.base\ /from langchain_core.language_models.llms\ /g'
git grep -l 'from langchain.embeddings.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.embeddings\.base/from langchain_core.embeddings/g'
git grep -l 'from langchain.vectorstores.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.vectorstores\.base/from langchain_core.vectorstores/g'
git grep -l 'from langchain.agents.tools' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.agents\.tools/from langchain_core.tools/g'
git grep -l 'from langchain.schema.output' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.output\ /from langchain_core.outputs\ /g'
git grep -l 'from langchain.schema.embeddings' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.embeddings/from langchain_core.embeddings/g'
git grep -l 'from langchain.schema.document' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.document/from langchain_core.documents/g'
git grep -l 'from langchain.schema.agent' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.agent/from langchain_core.agents/g'
git grep -l 'from langchain.schema.prompt ' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.prompt\ /from langchain_core.prompt_values /g'
git grep -l 'from langchain.schema.language_model' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.language_model/from langchain_core.language_models/g'


```
											
										
										
											9 months ago
+								from langchain_core.output_parsers import StrOutputParser
-												templates: fix deps (#15439)


											
										
										
											9 months ago
+								from langchain_core.prompts import ChatPromptTemplate, FewShotChatMessagePromptTemplate
-												docs[patch], templates[patch]: Import from core (#14575)

Update imports to use core for the low-hanging fruit changes. Ran
following

```bash
git grep -l 'langchain.schema.runnable' {docs,templates,cookbook}  | xargs sed -i '' 's/langchain\.schema\.runnable/langchain_core.runnables/g'
git grep -l 'langchain.schema.output_parser' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.output_parser/langchain_core.output_parsers/g'
git grep -l 'langchain.schema.messages' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.messages/langchain_core.messages/g'
git grep -l 'langchain.schema.chat_histry' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.chat_history/langchain_core.chat_history/g'
git grep -l 'langchain.schema.prompt_template' {docs,templates,cookbook} | xargs sed -i '' 's/langchain\.schema\.prompt_template/langchain_core.prompts/g'
git grep -l 'from langchain.pydantic_v1' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.pydantic_v1/from langchain_core.pydantic_v1/g'
git grep -l 'from langchain.tools.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.tools\.base/from langchain_core.tools/g'
git grep -l 'from langchain.chat_models.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.chat_models.base/from langchain_core.language_models.chat_models/g'
git grep -l 'from langchain.llms.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.llms\.base\ /from langchain_core.language_models.llms\ /g'
git grep -l 'from langchain.embeddings.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.embeddings\.base/from langchain_core.embeddings/g'
git grep -l 'from langchain.vectorstores.base' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.vectorstores\.base/from langchain_core.vectorstores/g'
git grep -l 'from langchain.agents.tools' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.agents\.tools/from langchain_core.tools/g'
git grep -l 'from langchain.schema.output' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.output\ /from langchain_core.outputs\ /g'
git grep -l 'from langchain.schema.embeddings' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.embeddings/from langchain_core.embeddings/g'
git grep -l 'from langchain.schema.document' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.document/from langchain_core.documents/g'
git grep -l 'from langchain.schema.agent' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.agent/from langchain_core.agents/g'
git grep -l 'from langchain.schema.prompt ' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.prompt\ /from langchain_core.prompt_values /g'
git grep -l 'from langchain.schema.language_model' {docs,templates,cookbook} | xargs sed -i '' 's/from langchain\.schema\.language_model/from langchain_core.language_models/g'


```
											
										
										
											9 months ago
+								from langchain_core.runnables import RunnableLambda
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
 								search = DuckDuckGoSearchAPIWrapper(max_results=4)
-												Format Templates (#12396)


											
										
										
											11 months ago
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
+								def retriever(query):
 								    return search.run(query)
 								# Few Shot Examples
 								examples = [
 								    {
 								        "input": "Could the members of The Police perform lawful arrests?",
-												Format Templates (#12396)


											
										
										
											11 months ago
+								        "output": "what can the members of The Police do?",
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
+								    },
 								    {
-												Format Templates (#12396)


											
										
										
											11 months ago
+								        "input": "Jan Sindel’s was born in what country?",
 								        "output": "what is Jan Sindel’s personal history?",
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
+								    },
 								]
 								# We now transform these to example messages
 								example_prompt = ChatPromptTemplate.from_messages(
 								    [
 								        ("human", "{input}"),
 								        ("ai", "{output}"),
 								    ]
 								)
 								few_shot_prompt = FewShotChatMessagePromptTemplate(
 								    example_prompt=example_prompt,
 								    examples=examples,
 								)
-												Format Templates (#12396)


											
										
										
											11 months ago
+								prompt = ChatPromptTemplate.from_messages(
 								    [
 								        (
 								            "system",
 								            "You are an expert at world knowledge. Your task is to step back "
 								            "and paraphrase a question to a more generic step-back question, which "
 								            "is easier to answer. Here are a few examples:",
 								        ),
 								        # Few shot examples
 								        few_shot_prompt,
 								        # New question
 								        ("user", "{question}"),
 								    ]
 								)
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
 								question_gen = prompt | ChatOpenAI(temperature=0) | StrOutputParser()
 								response_prompt_template = """You are an expert of world knowledge. I am going to ask you a question. Your response should be comprehensive and not contradicted with the following context if they are relevant. Otherwise, ignore them if they are not relevant.
 								{normal_context}
 								{step_back_context}
 								Original Question: {question}
-												Format Templates (#12396)


											
										
										
											11 months ago
+								Answer:"""  # noqa: E501
-												Templates (#12294)

Co-authored-by: Harrison Chase <hw.chase.17@gmail.com>
Co-authored-by: Lance Martin <lance@langchain.dev>
Co-authored-by: Jacob Lee <jacoblee93@gmail.com>
											
										
										
											11 months ago
+								response_prompt = ChatPromptTemplate.from_template(response_prompt_template)
-												Format Templates (#12396)


											
										
										
											11 months ago
+								chain = (
 								    {
 								        # Retrieve context using the normal question
 								        "normal_context": RunnableLambda(lambda x: x["question"]) | retriever,
 								        # Retrieve context using the step-back question
 								        "step_back_context": question_gen | retriever,
 								        # Pass on the question
 								        "question": lambda x: x["question"],
 								    }
 								    | response_prompt
 								    | ChatOpenAI(temperature=0)
 								    | StrOutputParser()
 								)