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langchain/templates/rag-redis/rag_redis/chain.py

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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 ```
2024-01-02 20:32:16 +00:00
from langchain_community.chat_models import ChatOpenAI
from langchain_community.embeddings import HuggingFaceEmbeddings
docs, experimental[patch], langchain[patch], community[patch]: update storage imports (#15429) ran ```bash g grep -l "langchain.vectorstores" | xargs -L 1 sed -i '' "s/langchain\.vectorstores/langchain_community.vectorstores/g" g grep -l "langchain.document_loaders" | xargs -L 1 sed -i '' "s/langchain\.document_loaders/langchain_community.document_loaders/g" g grep -l "langchain.chat_loaders" | xargs -L 1 sed -i '' "s/langchain\.chat_loaders/langchain_community.chat_loaders/g" g grep -l "langchain.document_transformers" | xargs -L 1 sed -i '' "s/langchain\.document_transformers/langchain_community.document_transformers/g" g grep -l "langchain\.graphs" | xargs -L 1 sed -i '' "s/langchain\.graphs/langchain_community.graphs/g" g grep -l "langchain\.memory\.chat_message_histories" | xargs -L 1 sed -i '' "s/langchain\.memory\.chat_message_histories/langchain_community.chat_message_histories/g" gco master libs/langchain/tests/unit_tests/*/test_imports.py gco master libs/langchain/tests/unit_tests/**/test_public_api.py ```
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from langchain_community.vectorstores import Redis
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' ```
2023-12-12 00:49:10 +00:00
from langchain_core.output_parsers import StrOutputParser
templates: fix deps (#15439)
2024-01-03 21:28:05 +00:00
from langchain_core.prompts import ChatPromptTemplate
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' ```
2023-12-12 00:49:10 +00:00
from langchain_core.pydantic_v1 import BaseModel
from langchain_core.runnables import RunnableParallel, RunnablePassthrough
Redis langserve template (#12443) Add Redis langserve template! Eventually will add semantic caching to this too. But I was struggling to get that to work for some reason with the LCEL implementation here. - **Description:** Introduces the Redis LangServe template. A simple RAG based app built on top of Redis that allows you to chat with company's public financial data (Edgar 10k filings) - **Issue:** None - **Dependencies:** The template contains the poetry project requirements to run this template - **Tag maintainer:** @baskaryan @Spartee - **Twitter handle:** @tchutch94 **Note**: this requires the commit here that deletes the `_aget_relevant_documents()` method from the Redis retriever class that wasn't implemented. That was breaking the langserve app. --------- Co-authored-by: Sam Partee <sam.partee@redis.com>
2023-10-28 15:31:12 +00:00
from rag_redis.config import (
EMBED_MODEL,
INDEX_NAME,
INDEX_SCHEMA,
REDIS_URL,
)
# Make this look better in the docs.
class Question(BaseModel):
__root__: str
# Init Embeddings
embedder = HuggingFaceEmbeddings(model_name=EMBED_MODEL)
# Connect to pre-loaded vectorstore
# run the ingest.py script to populate this
vectorstore = Redis.from_existing_index(
notebook fmt (#12498)
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embedding=embedder, index_name=INDEX_NAME, schema=INDEX_SCHEMA, redis_url=REDIS_URL
Redis langserve template (#12443) Add Redis langserve template! Eventually will add semantic caching to this too. But I was struggling to get that to work for some reason with the LCEL implementation here. - **Description:** Introduces the Redis LangServe template. A simple RAG based app built on top of Redis that allows you to chat with company's public financial data (Edgar 10k filings) - **Issue:** None - **Dependencies:** The template contains the poetry project requirements to run this template - **Tag maintainer:** @baskaryan @Spartee - **Twitter handle:** @tchutch94 **Note**: this requires the commit here that deletes the `_aget_relevant_documents()` method from the Redis retriever class that wasn't implemented. That was breaking the langserve app. --------- Co-authored-by: Sam Partee <sam.partee@redis.com>
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)
# TODO allow user to change parameters
retriever = vectorstore.as_retriever(search_type="mmr")
# Define our prompt
template = """
Use the following pieces of context from Nike's financial 10k filings
dataset to answer the question. Do not make up an answer if there is no
context provided to help answer it. Include the 'source' and 'start_index'
from the metadata included in the context you used to answer the question
Context:
---------
{context}
---------
Question: {question}
---------
Answer:
"""
prompt = ChatPromptTemplate.from_template(template)
# RAG Chain
model = ChatOpenAI(model_name="gpt-3.5-turbo-16k")
chain = (
notebook fmt (#12498)
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RunnableParallel({"context": retriever, "question": RunnablePassthrough()})
Redis langserve template (#12443) Add Redis langserve template! Eventually will add semantic caching to this too. But I was struggling to get that to work for some reason with the LCEL implementation here. - **Description:** Introduces the Redis LangServe template. A simple RAG based app built on top of Redis that allows you to chat with company's public financial data (Edgar 10k filings) - **Issue:** None - **Dependencies:** The template contains the poetry project requirements to run this template - **Tag maintainer:** @baskaryan @Spartee - **Twitter handle:** @tchutch94 **Note**: this requires the commit here that deletes the `_aget_relevant_documents()` method from the Redis retriever class that wasn't implemented. That was breaking the langserve app. --------- Co-authored-by: Sam Partee <sam.partee@redis.com>
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| prompt
| model
| StrOutputParser()
).with_types(input_type=Question)
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