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langchain/templates/sql-research-assistant/sql_research_assistant/writer.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
langchain[patch], experimental[patch]: replace langchain.schema imports (#15410) Import from core instead. Ran: ```bash git grep -l 'from langchain.schema\.output_parser' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.output_parser/from\ langchain_core.output_parsers/g" git grep -l 'from langchain.schema\.messages' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.messages/from\ langchain_core.messages/g" git grep -l 'from langchain.schema\.document' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.document/from\ langchain_core.documents/g" git grep -l 'from langchain.schema\.runnable' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.runnable/from\ langchain_core.runnables/g" git grep -l 'from langchain.schema\.vectorstore' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.vectorstore/from\ langchain_core.vectorstores/g" git grep -l 'from langchain.schema\.language_model' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.language_model/from\ langchain_core.language_models/g" git grep -l 'from langchain.schema\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.embeddings/from\ langchain_core.embeddings/g" git grep -l 'from langchain.schema\.storage' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.storage/from\ langchain_core.stores/g" git checkout master libs/langchain/tests/unit_tests/schema/ make format cd libs/experimental make format cd ../langchain make format ```
2024-01-02 20:09:45 +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
langchain[patch], experimental[patch]: replace langchain.schema imports (#15410) Import from core instead. Ran: ```bash git grep -l 'from langchain.schema\.output_parser' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.output_parser/from\ langchain_core.output_parsers/g" git grep -l 'from langchain.schema\.messages' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.messages/from\ langchain_core.messages/g" git grep -l 'from langchain.schema\.document' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.document/from\ langchain_core.documents/g" git grep -l 'from langchain.schema\.runnable' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.runnable/from\ langchain_core.runnables/g" git grep -l 'from langchain.schema\.vectorstore' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.vectorstore/from\ langchain_core.vectorstores/g" git grep -l 'from langchain.schema\.language_model' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.language_model/from\ langchain_core.language_models/g" git grep -l 'from langchain.schema\.embeddings' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.embeddings/from\ langchain_core.embeddings/g" git grep -l 'from langchain.schema\.storage' | xargs -L 1 sed -i '' "s/from\ langchain\.schema\.storage/from\ langchain_core.stores/g" git checkout master libs/langchain/tests/unit_tests/schema/ make format cd libs/experimental make format cd ../langchain make format ```
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from langchain_core.runnables import ConfigurableField
WIP: sql research assistant (#14240)
2023-12-18 22:00:18 +00:00
WRITER_SYSTEM_PROMPT = "You are an AI critical thinker research assistant. Your sole purpose is to write well written, critically acclaimed, objective and structured reports on given text." # noqa: E501
# Report prompts from https://github.com/assafelovic/gpt-researcher/blob/master/gpt_researcher/master/prompts.py
RESEARCH_REPORT_TEMPLATE = """Information:
--------
{research_summary}
--------
Using the above information, answer the following question or topic: "{question}" in a detailed report -- \
The report should focus on the answer to the question, should be well structured, informative, \
in depth, with facts and numbers if available and a minimum of 1,200 words.
You should strive to write the report as long as you can using all relevant and necessary information provided.
You must write the report with markdown syntax.
You MUST determine your own concrete and valid opinion based on the given information. Do NOT deter to general and meaningless conclusions.
Write all used source urls at the end of the report, and make sure to not add duplicated sources, but only one reference for each.
You must write the report in apa format.
Please do your best, this is very important to my career.""" # noqa: E501
RESOURCE_REPORT_TEMPLATE = """Information:
--------
{research_summary}
--------
Based on the above information, generate a bibliography recommendation report for the following question or topic: "{question}". \
The report should provide a detailed analysis of each recommended resource, explaining how each source can contribute to finding answers to the research question. \
Focus on the relevance, reliability, and significance of each source. \
Ensure that the report is well-structured, informative, in-depth, and follows Markdown syntax. \
Include relevant facts, figures, and numbers whenever available. \
The report should have a minimum length of 1,200 words.
Please do your best, this is very important to my career.""" # noqa: E501
OUTLINE_REPORT_TEMPLATE = """Information:
--------
{research_summary}
--------
Using the above information, generate an outline for a research report in Markdown syntax for the following question or topic: "{question}". \
The outline should provide a well-structured framework for the research report, including the main sections, subsections, and key points to be covered. \
The research report should be detailed, informative, in-depth, and a minimum of 1,200 words. \
Use appropriate Markdown syntax to format the outline and ensure readability.
Please do your best, this is very important to my career.""" # noqa: E501
model = ChatOpenAI(temperature=0)
prompt = ChatPromptTemplate.from_messages(
[
("system", WRITER_SYSTEM_PROMPT),
("user", RESEARCH_REPORT_TEMPLATE),
]
).configurable_alternatives(
ConfigurableField("report_type"),
default_key="research_report",
resource_report=ChatPromptTemplate.from_messages(
[
("system", WRITER_SYSTEM_PROMPT),
("user", RESOURCE_REPORT_TEMPLATE),
]
),
outline_report=ChatPromptTemplate.from_messages(
[
("system", WRITER_SYSTEM_PROMPT),
("user", OUTLINE_REPORT_TEMPLATE),
]
),
)
chain = prompt | model | StrOutputParser()
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