From 8844dba5a7b9a0e92ad5cfa8b1fa5ecb4032086b Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 12 Sep 2023 10:37:17 +0300 Subject: [PATCH 01/26] added boilerplate for permchain example --- actions/web_scrape.py | 9 +- permchain_example/README.md | 2 + permchain_example/output/AAPL.md | 50 +++++++++++ permchain_example/output/AAPL.pdf | Bin 0 -> 144942 bytes permchain_example/researcher.py | 35 ++++++++ .../search_actors/gpt_researcher.py | 85 ++++++++++++++++++ permchain_example/search_actors/search_api.py | 13 +++ permchain_example/test.py | 31 +++++++ permchain_example/writer_actors/openai.py | 34 +++++++ requirements.txt | 2 + 10 files changed, 258 insertions(+), 3 deletions(-) create mode 100644 permchain_example/README.md create mode 100644 permchain_example/output/AAPL.md create mode 100644 permchain_example/output/AAPL.pdf create mode 100644 permchain_example/researcher.py create mode 100644 permchain_example/search_actors/gpt_researcher.py create mode 100644 permchain_example/search_actors/search_api.py create mode 100644 permchain_example/test.py create mode 100644 permchain_example/writer_actors/openai.py diff --git a/actions/web_scrape.py b/actions/web_scrape.py index 3939bfb31..a8cafed47 100644 --- a/actions/web_scrape.py +++ b/actions/web_scrape.py @@ -19,7 +19,7 @@ from selenium.webdriver.support import expected_conditions as EC from selenium.webdriver.support.wait import WebDriverWait from fastapi import WebSocket -import chromedriver_autoinstaller +#import chromedriver_autoinstaller import processing.text as summary @@ -32,7 +32,7 @@ FILE_DIR = Path(__file__).parent.parent CFG = Config() -chromedriver_autoinstaller.install() #Installs the latest compat version of chromedriver +#chromedriver_autoinstaller.install() async def async_browse(url: str, question: str, websocket: WebSocket) -> str: @@ -137,7 +137,10 @@ def scrape_text_with_selenium(url: str) -> tuple[WebDriver, str]: options.add_experimental_option( "prefs", {"download_restrictions": 3} ) - driver = webdriver.Chrome(options=options) + service = Service(executable_path=ChromeDriverManager().install()) + driver = webdriver.Chrome(service=service, options=options) + + print(f"scraping url {url}...") driver.get(url) WebDriverWait(driver, 10).until( diff --git a/permchain_example/README.md b/permchain_example/README.md new file mode 100644 index 000000000..d68dd3762 --- /dev/null +++ b/permchain_example/README.md @@ -0,0 +1,2 @@ +# permchain_researcher +Sample use of permchain within GPT Researcher diff --git a/permchain_example/output/AAPL.md b/permchain_example/output/AAPL.md new file mode 100644 index 000000000..447aa64cc --- /dev/null +++ b/permchain_example/output/AAPL.md @@ -0,0 +1,50 @@ +# Title: Apple Inc. (AAPL): A Detailed Analysis + +## Introduction + +This report provides an in-depth analysis of Apple Inc. (AAPL), focusing on the company's upcoming product launches, financial performance, and recent news. Apple Inc. is an American multinational technology company that is widely recognized as one of the Big Five American information technology companies. The report aims to provide a comprehensive understanding of AAPL, considering various sources and relevant data. + +## Product Launches + +Apple is known for its innovative and cutting-edge product launches. The upcoming launch event on September 12 has generated significant attention and speculation. According to an article on Business Insider[^1^], this event is considered a litmus test for Apple's supremacy in the smart products realm. The article also indicates that the author is neutral on AAPL stock, suggesting a cautious stance. + +While one of the sources mentioned an invalid URL[^2^], the Google Finance page for AAPL provides valuable information about the company[^3^]. It states that Apple is the world's largest technology company by revenue and the fourth-largest personal computer vendor by unit sales. Additionally, it highlights that Apple is the second-largest mobile phone manufacturer globally. + +## Financial Performance + +To understand AAPL's financial performance, we can refer to the Wall Street Journal's financials for the company[^4^]. The data reveals the following key figures: + +- Earnings Per Share: +6.11 +- Sales: 24.15 +- Tangible Book Value: 3.18 +- Operating Profit: 7.32 +- Working Capital: -1.17 +- Long Term Liabilities: 9.29 +- Capital Expenditure: 0.66 +- Capital Expenditure TTM: 0.77 + +These figures provide insights into AAPL's financial strength and profitability. The positive earnings per share and operating profit indicate a healthy financial position. However, the negative working capital and long-term liabilities suggest areas that require attention. + +## Recent News + +Recent news articles shed light on Apple's current developments and market influence. One article on Yahoo Finance discusses the surge in Apple TV+ sign-ups due to Lionel Messi's MLS debut[^5^]. This highlights the impact of live sports events on streaming service subscriptions. Another article on Yahoo Finance focuses on the European Union's Digital Markets Act and its implications for Big Tech companies like Apple[^5^]. This demonstrates the regulatory challenges faced by AAPL and its peers. + +## Conclusion + +In conclusion, Apple Inc. (AAPL) is a technology giant that continues to dominate the market with its innovative products. The upcoming product launches are eagerly anticipated, and they serve as a litmus test for Apple's position in the industry. The financial performance of AAPL remains strong, with positive earnings per share and operating profit. However, areas such as working capital and long-term liabilities require attention. + +Recent news articles highlight Apple's market influence and regulatory challenges. The surge in Apple TV+ sign-ups due to live sports events and the European Union's Digital Markets Act exemplify the company's impact and the external factors it faces. + +Overall, Apple Inc. (AAPL) demonstrates resilience and innovation in the technology sector. While the report provides a comprehensive analysis based on available information, it is essential to consider additional factors and conduct further research to form a concrete and valid opinion. + +## References + +[^1^]: [Apple's (NASDAQ:AAPL) Upcoming Launch Event: The Ultimate Litmus Test](https://markets.businessinsider.com/news/stocks/apple-s-nasdaq-aapl-upcoming-launch-event-the-ultimate-litmus-test-1032603665?op=1) +[^2^]: [What's Apple (AAPL) Releasing in 2022?](https://www.bloomberg.com/news/newsletters/2022-01-02/what-s-apple-aapl-releasing-in-2022-iphone-14-airpods-pro-2-imac-pro-ipads-kxxmcej5) +[^3^]: [Apple Inc. (AAPL) - Google Finance](https://www.google.com/finance/quote/AAPL:NASDAQ) +[^4^]: [Apple Inc. (AAPL) Financials - Wall Street Journal](https://www.wsj.com/market-data/quotes/AAPL/financials) +[^5^]: [Latest News about AAPL - Yahoo Finance](https://finance.yahoo.com/quote/AAPL/news/) + +--- + +Please note that the URLs provided in the report are not clickable as per the APA format. \ No newline at end of file diff --git a/permchain_example/output/AAPL.pdf b/permchain_example/output/AAPL.pdf new file mode 100644 index 0000000000000000000000000000000000000000..b09b812f8ea1eb2075d31b4d366a2bb4ce1fc49d GIT binary patch literal 144942 zcma&MLy$0R%%^8*SySjbZp-H4sYrW25wT9wxQu0Q3TwEG_ zGfA4rMF%t9;03YYms>IRcchji<%K}deDL_&(KUL7*;QsvZ%;z`O>=hiy`Flf(rSj* z`KGL{3?{J@QC8|lAr0jjJGCbLCTx7IH<#Y=lIhypJ8gFTbf!5yS82f>ccwITb$dPG zs$8UtsLVTE3!f`Bnd{8gqw}#3dv^Z$38`gIJo$f3p=^apVY5CfGqIC{^FvapHKnHa zzT#IgIV**9E{JK7ok1=2s>eH(nt+EE!1!(BpI~y@7`kS`U3v5_sV~9=gS^+UNAP|p z9#Tt+S6w5MJK?g0OiPZ-dx}}l0J^Kd&u}jek;PP9SyeD5^RBJgVtX~7=zNqmIFlht z%O8Ol4^YKuok}EQjeEPm-t`A# 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self.search_actor_instance = search_actor + self.writer_actor_instance = writer_actor + + def run(self, query): + # The research inbox + research_inbox = Topic("research") + search_actor = ( + Topic.IN.subscribe() + | { + "query": lambda x: x, + "results": self.search_actor_instance.runnable + } + | research_inbox.publish() + ) + + write_actor = ( + research_inbox.subscribe() + | self.writer_actor_instance.runnable + | Topic.OUT.publish() + ) + + researcher = PubSub( + processes=(search_actor, write_actor), + connection=InMemoryPubSubConnection(), + ) + + res = researcher.invoke(query) + return res[0]['answer'] diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py new file mode 100644 index 000000000..319594f4a --- /dev/null +++ b/permchain_example/search_actors/gpt_researcher.py @@ -0,0 +1,85 @@ +from processing.text import split_text +from actions.web_scrape import scrape_text_with_selenium +from actions.web_search import web_search + +from langchain.chat_models import ChatOpenAI, ChatAnthropic +from langchain.prompts import SystemMessagePromptTemplate, ChatPromptTemplate +from langchain.schema.output_parser import StrOutputParser +from langchain.schema.runnable import RunnableMap +import json +from langchain.schema.messages import SystemMessage +from agent.prompts import auto_agent_instructions +from datetime import date + +summary_message = ( + '"""{chunk}""" Using the above text, answer the following' + ' question: "{question}" -- if the question cannot be answered using the text,' + " simply summarize the text in depth. " + "Include all factual information, numbers, stats etc if available." +) +SUMMARY_PROMPT = ChatPromptTemplate.from_messages([ + ("user", summary_message) +]) +search_message = ( + f'The current date is: {date.today()}. ' + 'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ + f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' +) + +SEARCH_PROMPT = ChatPromptTemplate.from_messages([ + ("system", "{agent_prompt}"), + ("user", search_message) +]) + +AUTO_AGENT_INSTRUCTIONS = auto_agent_instructions() +CHOOSE_AGENT_PROMPT = ChatPromptTemplate.from_messages([ + SystemMessage(content=AUTO_AGENT_INSTRUCTIONS), +("user", "task: {task}") +]) + + +summary_chain = SUMMARY_PROMPT | ChatOpenAI() | StrOutputParser() +chunk_and_combine = (lambda x: [{ + "question": x["question"], + "chunk": chunk +} for chunk in split_text(x["text"])]) | summary_chain.map() | (lambda x: "\n".join(x)) + +recursive_summary_chain = { + "question": lambda x: x["question"], + "chunk": chunk_and_combine +} | summary_chain + +scrape_and_summarize = { + "question": lambda x: x["question"], + "text": lambda x: scrape_text_with_selenium(x['url'])[1], + "url": lambda x: x['url'] +} | RunnableMap({ + "summary": recursive_summary_chain, + "url": lambda x: x['url'] +}) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") + +multi_search = (lambda x: [ + {"url": url.get("href"), "question": x["question"]} + for url in json.loads(web_search(x["question"])) +]) | scrape_and_summarize.map() | (lambda x: "\n".join(x)) + +search_query = SEARCH_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads +choose_agent = CHOOSE_AGENT_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads + +get_search_queries = { + "question": lambda x: x, + "agent_prompt": {"task": lambda x: x} | choose_agent | (lambda x: x["agent_role_prompt"]) +} | search_query + + +class GPTResearcherActor: + + @property + def runnable(self): + return ( + get_search_queries + | (lambda x: [{"question": q} for q in x]) + | multi_search.map() + | (lambda x: "\n\n".join(x)) + ) + diff --git a/permchain_example/search_actors/search_api.py b/permchain_example/search_actors/search_api.py new file mode 100644 index 000000000..04b13c9f6 --- /dev/null +++ b/permchain_example/search_actors/search_api.py @@ -0,0 +1,13 @@ +from tavily import Client +import os +from langchain.schema.runnable import RunnableLambda + + +class TavilySearchActor: + def __init__(self): + self.api_key = os.environ["TAVILY_API_KEY"] + + @property + def runnable(self): + client = Client(self.api_key) + return RunnableLambda(client.advanced_search) | {"results": lambda x: x["results"]} diff --git a/permchain_example/test.py b/permchain_example/test.py new file mode 100644 index 000000000..e5a6b8b00 --- /dev/null +++ b/permchain_example/test.py @@ -0,0 +1,31 @@ +# main +import os, sys +sys.path.insert(0, os.path.abspath(os.path.join(os.path.dirname(__file__), '..'))) + +from permchain_example.researcher import Researcher +from permchain_example.search_actors.search_api import TavilySearchActor +from permchain_example.search_actors.gpt_researcher import GPTResearcherActor +from permchain_example.writer_actors.openai import OpenAIWriterActor +from processing.text import md_to_pdf + + + +if __name__ == '__main__': + output_path = "./permchain_example/output" + if not os.path.exists(output_path): + # If the directory does not exist, create it + os.makedirs(output_path) + + def md2pdf(md_file, pdf_file): + md_to_pdf(md_file, pdf_file) + + stocks = ["MSFT"] + + for stock in stocks[:1]: + researcher = Researcher(TavilySearchActor(), OpenAIWriterActor()) + research = researcher.run(stock) + with open(f"{output_path}/{stock}.md", "w") as f: + f.write(research) + md2pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") + + diff --git a/permchain_example/writer_actors/openai.py b/permchain_example/writer_actors/openai.py new file mode 100644 index 000000000..d5f82c27d --- /dev/null +++ b/permchain_example/writer_actors/openai.py @@ -0,0 +1,34 @@ +from langchain.prompts import ChatPromptTemplate +from langchain.chat_models import ChatOpenAI, ChatAnthropic +from langchain.schema.output_parser import StrOutputParser +from datetime import date +from config import Config + +CFG = Config() + +class OpenAIWriterActor: + def __init__(self): + self.model = ChatOpenAI(model=CFG.fast_llm_model) + self.prompt = ChatPromptTemplate.from_messages([ + ("system", + "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." + ), + ("user", + '"""{results}""" Using the above information, answer the following' + ' question or topic: "{query}" 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, a minimum of 1,200 words and with markdown syntax and apa format. " + "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 in apa format" + ) + ]) + + @property + def runnable(self): + return { + "answer": { + "query": lambda x: x["query"], + "results": lambda x: "\n\n".join(x["results"]) + } + | self.prompt | self.model | StrOutputParser() + } diff --git a/requirements.txt b/requirements.txt index c30785495..9c5296bca 100644 --- a/requirements.txt +++ b/requirements.txt @@ -18,3 +18,5 @@ python-multipart markdown langchain==0.0.275 chromedriver-autoinstaller +tavily-python +permchain \ No newline at end of file From 0feba9b183734dc4e43a1e3177f45c9cda8010ae Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 12 Sep 2023 10:38:14 +0300 Subject: [PATCH 02/26] removed date from search prompt --- permchain_example/search_actors/gpt_researcher.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index 319594f4a..8e46f6ae6 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -21,9 +21,8 @@ ("user", summary_message) ]) search_message = ( - f'The current date is: {date.today()}. ' 'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ - f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' + 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' ) SEARCH_PROMPT = ChatPromptTemplate.from_messages([ From 71a49decbe93a21b447361bb341e1317a097e0d8 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 12 Sep 2023 10:39:22 +0300 Subject: [PATCH 03/26] modified --- permchain_example/search_actors/gpt_researcher.py | 1 - 1 file changed, 1 deletion(-) diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index 8e46f6ae6..7b82ef86d 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -9,7 +9,6 @@ import json from langchain.schema.messages import SystemMessage from agent.prompts import auto_agent_instructions -from datetime import date summary_message = ( '"""{chunk}""" Using the above text, answer the following' From ea1ec5c5c22eecfd039b21ea73ea196f668afff6 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 12 Sep 2023 14:04:47 +0300 Subject: [PATCH 04/26] fixed issue with scraper --- actions/web_scrape.py | 3 +-- permchain_example/test.py | 2 +- processing/text.py | 6 +++--- 3 files changed, 5 insertions(+), 6 deletions(-) diff --git a/actions/web_scrape.py b/actions/web_scrape.py index a8cafed47..076ef2b91 100644 --- a/actions/web_scrape.py +++ b/actions/web_scrape.py @@ -137,8 +137,7 @@ def scrape_text_with_selenium(url: str) -> tuple[WebDriver, str]: options.add_experimental_option( "prefs", {"download_restrictions": 3} ) - service = Service(executable_path=ChromeDriverManager().install()) - driver = webdriver.Chrome(service=service, options=options) + driver = webdriver.Chrome(options=options) print(f"scraping url {url}...") driver.get(url) diff --git a/permchain_example/test.py b/permchain_example/test.py index e5a6b8b00..0e8fafef0 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -22,7 +22,7 @@ def md2pdf(md_file, pdf_file): stocks = ["MSFT"] for stock in stocks[:1]: - researcher = Researcher(TavilySearchActor(), OpenAIWriterActor()) + researcher = Researcher(GPTResearcherActor(), OpenAIWriterActor()) research = researcher.run(stock) with open(f"{output_path}/{stock}.md", "w") as f: f.write(research) diff --git a/processing/text.py b/processing/text.py index e3881d0f0..928bb0b23 100644 --- a/processing/text.py +++ b/processing/text.py @@ -61,14 +61,14 @@ def summarize_text( return "Error: No text to summarize" summaries = [] - chunks = list(split_text(text)) + chunks = list(split_text(text, 3500)) scroll_ratio = 1 / len(chunks) for i, chunk in enumerate(chunks): if driver: scroll_to_percentage(driver, scroll_ratio * i) - memory_to_add = f"Source: {url}\n" f"Raw content part#{i + 1}: {chunk}" + #memory_to_add = f"Source: {url}\n" f"Raw content part#{i + 1}: {chunk}" #MEMORY.add_documents([Document(page_content=memory_to_add)]) @@ -79,7 +79,7 @@ def summarize_text( messages=messages, ) summaries.append(summary) - memory_to_add = f"Source: {url}\n" f"Content summary part#{i + 1}: {summary}" + #memory_to_add = f"Source: {url}\n" f"Content summary part#{i + 1}: {summary}" #MEMORY.add_documents([Document(page_content=memory_to_add)]) From c050832bba6258cd8ce9a858005cf74cc46e84bd Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 12 Sep 2023 22:27:00 +0300 Subject: [PATCH 05/26] added logs and used more source code for one source of truth --- .../search_actors/gpt_researcher.py | 38 ++++--------------- permchain_example/test.py | 2 +- processing/text.py | 16 +++++--- 3 files changed, 20 insertions(+), 36 deletions(-) diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index 7b82ef86d..b65b60e51 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -1,4 +1,4 @@ -from processing.text import split_text +from processing.text import split_text, summarize_text from actions.web_scrape import scrape_text_with_selenium from actions.web_search import web_search @@ -10,20 +10,10 @@ from langchain.schema.messages import SystemMessage from agent.prompts import auto_agent_instructions -summary_message = ( - '"""{chunk}""" Using the above text, answer the following' - ' question: "{question}" -- if the question cannot be answered using the text,' - " simply summarize the text in depth. " - "Include all factual information, numbers, stats etc if available." -) -SUMMARY_PROMPT = ChatPromptTemplate.from_messages([ - ("user", summary_message) -]) search_message = ( - 'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ - 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' + 'Write 3 google search queries to search online that form an objective opinion from the following: "{question}"'\ + 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3"]' ) - SEARCH_PROMPT = ChatPromptTemplate.from_messages([ ("system", "{agent_prompt}"), ("user", search_message) @@ -32,33 +22,21 @@ AUTO_AGENT_INSTRUCTIONS = auto_agent_instructions() CHOOSE_AGENT_PROMPT = ChatPromptTemplate.from_messages([ SystemMessage(content=AUTO_AGENT_INSTRUCTIONS), -("user", "task: {task}") + ("user", "task: {task}") ]) - -summary_chain = SUMMARY_PROMPT | ChatOpenAI() | StrOutputParser() -chunk_and_combine = (lambda x: [{ - "question": x["question"], - "chunk": chunk -} for chunk in split_text(x["text"])]) | summary_chain.map() | (lambda x: "\n".join(x)) - -recursive_summary_chain = { - "question": lambda x: x["question"], - "chunk": chunk_and_combine -} | summary_chain - scrape_and_summarize = { "question": lambda x: x["question"], "text": lambda x: scrape_text_with_selenium(x['url'])[1], "url": lambda x: x['url'] } | RunnableMap({ - "summary": recursive_summary_chain, - "url": lambda x: x['url'] -}) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") + "summary": lambda x: summarize_text(text=x["text"], question=x["question"], url=x["url"]), + "url": lambda x: x['url'] +}) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") multi_search = (lambda x: [ {"url": url.get("href"), "question": x["question"]} - for url in json.loads(web_search(x["question"])) + for url in json.loads(web_search(query=x["question"], num_results=2)) ]) | scrape_and_summarize.map() | (lambda x: "\n".join(x)) search_query = SEARCH_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads diff --git a/permchain_example/test.py b/permchain_example/test.py index 0e8fafef0..2d8147e79 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -23,7 +23,7 @@ def md2pdf(md_file, pdf_file): for stock in stocks[:1]: researcher = Researcher(GPTResearcherActor(), OpenAIWriterActor()) - research = researcher.run(stock) + research = researcher.run(f"is the stock {stock} a good buy?") with open(f"{output_path}/{stock}.md", "w") as f: f.write(research) md2pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") diff --git a/processing/text.py b/processing/text.py index 928bb0b23..48032d181 100644 --- a/processing/text.py +++ b/processing/text.py @@ -46,6 +46,7 @@ def split_text(text: str, max_length: int = 8192) -> Generator[str, None, None]: def summarize_text( url: str, text: str, question: str, driver: Optional[WebDriver] = None ) -> str: + print(question) """Summarize text using the OpenAI API Args: @@ -61,9 +62,10 @@ def summarize_text( return "Error: No text to summarize" summaries = [] - chunks = list(split_text(text, 3500)) + chunks = list(split_text(text)) scroll_ratio = 1 / len(chunks) + print(f"Summarizing url: {url} with total chunks: {len(chunks)}") for i, chunk in enumerate(chunks): if driver: scroll_to_percentage(driver, scroll_ratio * i) @@ -83,14 +85,17 @@ def summarize_text( #MEMORY.add_documents([Document(page_content=memory_to_add)]) - combined_summary = "\n".join(summaries) messages = [create_message(combined_summary, question)] - return create_chat_completion( + final_summary = create_chat_completion( model=CFG.fast_llm_model, messages=messages, ) + print("Final summary length: ", len(combined_summary)) + print(final_summary) + + return final_summary def scroll_to_percentage(driver: WebDriver, ratio: float) -> None: @@ -120,9 +125,10 @@ def create_message(chunk: str, question: str) -> Dict[str, str]: """ return { "role": "user", - "content": f'"""{chunk}""" Using the above text, answer the following' + "content": f'"""{chunk}""" Using the above text, the following' f' question: "{question}" -- if the question cannot be answered using the text,' - " simply summarize the text in depth. " + " simply summarize the text. " + "You should NOT answer in more than 300 words. " "Include all factual information, numbers, stats etc if available.", } From 01b3c2e398748e1c5c1636b1200e225944350af7 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Wed, 13 Sep 2023 09:23:29 +0300 Subject: [PATCH 06/26] added validation for visited urls --- config/config.py | 1 + .../search_actors/gpt_researcher.py | 16 ++++++++++------ permchain_example/test.py | 2 +- permchain_example/writer_actors/openai.py | 4 ++-- processing/text.py | 5 +++-- 5 files changed, 17 insertions(+), 11 deletions(-) diff --git a/config/config.py b/config/config.py index 865b91396..1a902bcab 100644 --- a/config/config.py +++ b/config/config.py @@ -27,6 +27,7 @@ def __init__(self) -> None: self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000)) self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000)) self.browse_chunk_max_length = int(os.getenv("BROWSE_CHUNK_MAX_LENGTH", 8192)) + self.summary_token_limit = int(os.getenv("SUMMARY_TOKEN_LIMIT", 700)) self.openai_api_key = os.getenv("OPENAI_API_KEY") self.temperature = float(os.getenv("TEMPERATURE", "1")) diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index b65b60e51..5dfadbd65 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -11,8 +11,8 @@ from agent.prompts import auto_agent_instructions search_message = ( - 'Write 3 google search queries to search online that form an objective opinion from the following: "{question}"'\ - 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3"]' + 'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ + 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' ) SEARCH_PROMPT = ChatPromptTemplate.from_messages([ ("system", "{agent_prompt}"), @@ -34,10 +34,14 @@ "url": lambda x: x['url'] }) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") -multi_search = (lambda x: [ - {"url": url.get("href"), "question": x["question"]} - for url in json.loads(web_search(query=x["question"], num_results=2)) -]) | scrape_and_summarize.map() | (lambda x: "\n".join(x)) +seen_urls = set() +multi_search = ( + lambda x: [ + {"url": url.get("href"), "question": x["question"]} + for url in json.loads(web_search(query=x["question"], num_results=3)) + if not (url.get("href") in seen_urls or seen_urls.add(url.get("href"))) + ] +) | scrape_and_summarize.map() | (lambda x: "\n".join(x)) search_query = SEARCH_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads choose_agent = CHOOSE_AGENT_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads diff --git a/permchain_example/test.py b/permchain_example/test.py index 2d8147e79..c00487fa2 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -19,7 +19,7 @@ def md2pdf(md_file, pdf_file): md_to_pdf(md_file, pdf_file) - stocks = ["MSFT"] + stocks = ["AAPL"] for stock in stocks[:1]: researcher = Researcher(GPTResearcherActor(), OpenAIWriterActor()) diff --git a/permchain_example/writer_actors/openai.py b/permchain_example/writer_actors/openai.py index d5f82c27d..9b942cfc0 100644 --- a/permchain_example/writer_actors/openai.py +++ b/permchain_example/writer_actors/openai.py @@ -8,7 +8,7 @@ class OpenAIWriterActor: def __init__(self): - self.model = ChatOpenAI(model=CFG.fast_llm_model) + self.model = ChatOpenAI(model=CFG.smart_llm_model) self.prompt = ChatPromptTemplate.from_messages([ ("system", "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." @@ -17,7 +17,7 @@ def __init__(self): '"""{results}""" Using the above information, answer the following' ' question or topic: "{query}" 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, a minimum of 1,200 words and with markdown syntax and apa format. " + " in depth, with facts and numbers if available, a minimum of 1,200 words and with markdown syntax (including titles) and apa format. " "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 in apa format" ) diff --git a/processing/text.py b/processing/text.py index 48032d181..277e7809f 100644 --- a/processing/text.py +++ b/processing/text.py @@ -79,6 +79,7 @@ def summarize_text( summary = create_chat_completion( model=CFG.fast_llm_model, messages=messages, + max_tokens=CFG.summary_token_limit ) summaries.append(summary) #memory_to_add = f"Source: {url}\n" f"Content summary part#{i + 1}: {summary}" @@ -91,6 +92,7 @@ def summarize_text( final_summary = create_chat_completion( model=CFG.fast_llm_model, messages=messages, + max_tokens=CFG.summary_token_limit ) print("Final summary length: ", len(combined_summary)) print(final_summary) @@ -125,10 +127,9 @@ def create_message(chunk: str, question: str) -> Dict[str, str]: """ return { "role": "user", - "content": f'"""{chunk}""" Using the above text, the following' + "content": f'"""{chunk}""" Using the above text, answer in short the following' f' question: "{question}" -- if the question cannot be answered using the text,' " simply summarize the text. " - "You should NOT answer in more than 300 words. " "Include all factual information, numbers, stats etc if available.", } From 8bccd34c2c0157a298b9c4f3d98be827d60e61f9 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 15:50:51 +0300 Subject: [PATCH 07/26] removed redundant method --- permchain_example/output/AAPL.md | 50 ------------------------------ permchain_example/output/AAPL.pdf | Bin 144942 -> 0 bytes permchain_example/test.py | 5 +-- 3 files changed, 1 insertion(+), 54 deletions(-) delete mode 100644 permchain_example/output/AAPL.md delete mode 100644 permchain_example/output/AAPL.pdf diff --git a/permchain_example/output/AAPL.md b/permchain_example/output/AAPL.md deleted file mode 100644 index 447aa64cc..000000000 --- a/permchain_example/output/AAPL.md +++ /dev/null @@ -1,50 +0,0 @@ -# Title: Apple Inc. (AAPL): A Detailed Analysis - -## Introduction - -This report provides an in-depth analysis of Apple Inc. (AAPL), focusing on the company's upcoming product launches, financial performance, and recent news. Apple Inc. is an American multinational technology company that is widely recognized as one of the Big Five American information technology companies. The report aims to provide a comprehensive understanding of AAPL, considering various sources and relevant data. - -## Product Launches - -Apple is known for its innovative and cutting-edge product launches. The upcoming launch event on September 12 has generated significant attention and speculation. According to an article on Business Insider[^1^], this event is considered a litmus test for Apple's supremacy in the smart products realm. The article also indicates that the author is neutral on AAPL stock, suggesting a cautious stance. - -While one of the sources mentioned an invalid URL[^2^], the Google Finance page for AAPL provides valuable information about the company[^3^]. It states that Apple is the world's largest technology company by revenue and the fourth-largest personal computer vendor by unit sales. Additionally, it highlights that Apple is the second-largest mobile phone manufacturer globally. - -## Financial Performance - -To understand AAPL's financial performance, we can refer to the Wall Street Journal's financials for the company[^4^]. The data reveals the following key figures: - -- Earnings Per Share: +6.11 -- Sales: 24.15 -- Tangible Book Value: 3.18 -- Operating Profit: 7.32 -- Working Capital: -1.17 -- Long Term Liabilities: 9.29 -- Capital Expenditure: 0.66 -- Capital Expenditure TTM: 0.77 - -These figures provide insights into AAPL's financial strength and profitability. The positive earnings per share and operating profit indicate a healthy financial position. However, the negative working capital and long-term liabilities suggest areas that require attention. - -## Recent News - -Recent news articles shed light on Apple's current developments and market influence. One article on Yahoo Finance discusses the surge in Apple TV+ sign-ups due to Lionel Messi's MLS debut[^5^]. This highlights the impact of live sports events on streaming service subscriptions. Another article on Yahoo Finance focuses on the European Union's Digital Markets Act and its implications for Big Tech companies like Apple[^5^]. This demonstrates the regulatory challenges faced by AAPL and its peers. - -## Conclusion - -In conclusion, Apple Inc. (AAPL) is a technology giant that continues to dominate the market with its innovative products. The upcoming product launches are eagerly anticipated, and they serve as a litmus test for Apple's position in the industry. The financial performance of AAPL remains strong, with positive earnings per share and operating profit. However, areas such as working capital and long-term liabilities require attention. - -Recent news articles highlight Apple's market influence and regulatory challenges. The surge in Apple TV+ sign-ups due to live sports events and the European Union's Digital Markets Act exemplify the company's impact and the external factors it faces. - -Overall, Apple Inc. (AAPL) demonstrates resilience and innovation in the technology sector. While the report provides a comprehensive analysis based on available information, it is essential to consider additional factors and conduct further research to form a concrete and valid opinion. - -## References - -[^1^]: [Apple's (NASDAQ:AAPL) Upcoming Launch Event: The Ultimate Litmus Test](https://markets.businessinsider.com/news/stocks/apple-s-nasdaq-aapl-upcoming-launch-event-the-ultimate-litmus-test-1032603665?op=1) -[^2^]: [What's Apple (AAPL) Releasing in 2022?](https://www.bloomberg.com/news/newsletters/2022-01-02/what-s-apple-aapl-releasing-in-2022-iphone-14-airpods-pro-2-imac-pro-ipads-kxxmcej5) -[^3^]: [Apple Inc. (AAPL) - Google Finance](https://www.google.com/finance/quote/AAPL:NASDAQ) -[^4^]: [Apple Inc. (AAPL) Financials - Wall Street Journal](https://www.wsj.com/market-data/quotes/AAPL/financials) -[^5^]: [Latest News about AAPL - Yahoo Finance](https://finance.yahoo.com/quote/AAPL/news/) - ---- - -Please note that the URLs provided in the report are not clickable as per the APA format. \ No newline at end of file diff --git a/permchain_example/output/AAPL.pdf b/permchain_example/output/AAPL.pdf deleted file mode 100644 index b09b812f8ea1eb2075d31b4d366a2bb4ce1fc49d..0000000000000000000000000000000000000000 GIT binary patch literal 0 HcmV?d00001 literal 144942 zcma&MLy$0R%%^8*SySjbZp-H4sYrW25wT9wxQu0Q3TwEG_ zGfA4rMF%t9;03YYms>IRcchji<%K}deDL_&(KUL7*;QsvZ%;z`O>=hiy`Flf(rSj* z`KGL{3?{J@QC8|lAr0jjJGCbLCTx7IH<#Y=lIhypJ8gFTbf!5yS82f>ccwITb$dPG zs$8UtsLVTE3!f`Bnd{8gqw}#3dv^Z$38`gIJo$f3p=^apVY5CfGqIC{^FvapHKnHa zzT#IgIV**9E{JK7ok1=2s>eH(nt+EE!1!(BpI~y@7`kS`U3v5_sV~9=gS^+UNAP|p z9#Tt+S6w5MJK?g0OiPZ-dx}}l0J^Kd&u}jek;PP9SyeD5^RBJgVtX~7=zNqmIFlht z%O8Ol4^YKuok}EQjeEPm-t`A# 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the stock {stock} a good buy?") with open(f"{output_path}/{stock}.md", "w") as f: f.write(research) - md2pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") + md_to_pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") From 7893e00d9ff24481e98398c616f52e33850db39b Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:21:03 +0300 Subject: [PATCH 08/26] added new actors and formed a research team --- .../editor_actors/editor-runnable.py | 53 +++++++++++++ permchain_example/editor_actors/editor.py | 55 ++++++++++++++ permchain_example/research_team.py | 74 +++++++++++++++++++ permchain_example/reviser_actors/reviser.py | 25 +++++++ .../search_actors/gpt_researcher.py | 4 +- permchain_example/test.py | 19 +++-- .../writer_actors/{openai.py => writer.py} | 2 +- 7 files changed, 221 insertions(+), 11 deletions(-) create mode 100644 permchain_example/editor_actors/editor-runnable.py create mode 100644 permchain_example/editor_actors/editor.py create mode 100644 permchain_example/research_team.py create mode 100644 permchain_example/reviser_actors/reviser.py rename permchain_example/writer_actors/{openai.py => writer.py} (98%) diff --git a/permchain_example/editor_actors/editor-runnable.py b/permchain_example/editor_actors/editor-runnable.py new file mode 100644 index 000000000..e0695c835 --- /dev/null +++ b/permchain_example/editor_actors/editor-runnable.py @@ -0,0 +1,53 @@ +from langchain.prompts import ChatPromptTemplate +from langchain.chat_models import ChatOpenAI, ChatAnthropic +from langchain.schema.output_parser import StrOutputParser +from langchain.prompts import SystemMessagePromptTemplate +from datetime import date +from config import Config + +CFG = Config() + +EDIT_TEMPLATE = """You are an editor. \ +You have been tasked with editing the following draft, which was written by a non-expert. \ +Please accept the draft if it is good enough to publish, or send it for revision, along with your notes to guide the revision. \ +Things you should be checking for: + +- This draft MUST fully answer the original question +- This draft MUST be written in spanish + +If not all of the above criteria are met, you should send appropriate revision notes. +""" + +class EditorActor: + def __init__(self): + self.model = ChatOpenAI(model=CFG.smart_llm_model) + self.prompt = SystemMessagePromptTemplate.from_template(EDIT_TEMPLATE) + "Draft:\n\n{draft}" + self.functions = [ + { + "name": "revise", + "description": "Sends the draft for revision", + "parameters": { + "type": "object", + "properties": { + "notes": { + "type": "string", + "description": "The editor's notes to guide the revision.", + }, + }, + }, + }, + { + "name": "accept", + "description": "Accepts the draft", + "parameters": { + "type": "object", + "properties": {"ready": {"const": True}}, + }, + }, + ] + + @property + def runnable(self): + return { + "answer": self.prompt | self.model.bind(functions=self.functions) + } diff --git a/permchain_example/editor_actors/editor.py b/permchain_example/editor_actors/editor.py new file mode 100644 index 000000000..dd55aa068 --- /dev/null +++ b/permchain_example/editor_actors/editor.py @@ -0,0 +1,55 @@ +from langchain.chat_models import ChatOpenAI +from langchain.prompts import SystemMessagePromptTemplate +from config import Config + +CFG = Config() + +EDIT_TEMPLATE = """You are an editor. \ +You have been tasked with editing the following draft, which was written by a non-expert. \ +Please accept the draft if it is good enough to publish, or send it for revision, along with your notes to guide the revision. \ +Things you should be checking for: + +- This draft MUST fully answer the original question +- This draft MUST be apa format + +If not all of the above criteria are met, you should send appropriate revision notes. +""" + +critique_prompt = ( + SystemMessagePromptTemplate.from_template(EDIT_TEMPLATE) + + "Draft:\n\n{draft}" +) +critique_llm = ChatOpenAI(model=CFG.smart_llm_model) +functions = [ + { + "name": "revise", + "description": "Sends the draft for revision", + "parameters": { + "type": "object", + "properties": { + "notes": { + "type": "string", + "description": "The editor's notes to guide the revision.", + }, + }, + }, + }, + { + "name": "accept", + "description": "Accepts the draft", + "parameters": { + "type": "object", + "properties": {"ready": {"const": True}}, + }, + }, +] + +#EditorActor = critique_prompt | critique_llm.bind(functions=functions) + + +class EditorActor: + @property + def runnable(self): + return ( + critique_prompt | critique_llm.bind(functions=functions) + ) \ No newline at end of file diff --git a/permchain_example/research_team.py b/permchain_example/research_team.py new file mode 100644 index 000000000..d38b1901e --- /dev/null +++ b/permchain_example/research_team.py @@ -0,0 +1,74 @@ +from operator import itemgetter +from langchain.runnables.openai_functions import OpenAIFunctionsRouter + +from permchain.connection_inmemory import InMemoryPubSubConnection +from permchain.pubsub import PubSub +from permchain.topic import Topic + +''' + This is the research team. + It is a group of autonomous agents that work together to answer a given question + using a comprehensive research process that includes: + - Searching for relevant information across multiple sources + - Extracting relevant information + - Writing a well structured report + - Revising the report + - Editing the report + - Repeat until the report is satisfactory +''' +class ResearchTeam: + def __init__(self, research_actor, editor_actor, reviser_actor): + self.research_actor_instance = research_actor + self.editor_actor_instance = editor_actor + self.revise_actor_instance = reviser_actor + + def run(self, query): + # create topics + editor_inbox = Topic("editor_inbox") + reviser_inbox = Topic("reviser_inbox") + draft_chain = ( + # Listed in inputs + Topic.IN.subscribe() + | {"draft": lambda x: self.research_actor_instance.run(x["question"])} + # The draft always goes to the critique inbox + | editor_inbox.publish() + ) + + editor_chain = ( + # Listen for events in the editor_inbox + editor_inbox.subscribe() + | self.editor_actor_instance.runnable + # Depending on the output, different things should happen + | OpenAIFunctionsRouter( + { + # If revise is chosen, we send a push to the critique_inbox + "revise": ( + { + "notes": itemgetter("notes"), + "draft": editor_inbox.current() | itemgetter("draft"), + "question": Topic.IN.current() | itemgetter("question"), + } + | reviser_inbox.publish() + ), + # If accepted, then we return + "accept": editor_inbox.current() | Topic.OUT.publish(), + }, + ) + ) + + reviser_chain = ( + # Listen for events in the reviser's inbox + reviser_inbox.subscribe() + | {"draft": self.revise_actor_instance.runnable} + # Publish to the critique inbox + | editor_inbox.publish() + ) + + web_researcher = PubSub( + processes=(draft_chain, editor_chain, reviser_chain), + connection=InMemoryPubSubConnection(), + ) + + res = web_researcher.invoke({"question": query}) + print(res) + return res[0]["draft"]["answer"] diff --git a/permchain_example/reviser_actors/reviser.py b/permchain_example/reviser_actors/reviser.py new file mode 100644 index 000000000..b8b7d3569 --- /dev/null +++ b/permchain_example/reviser_actors/reviser.py @@ -0,0 +1,25 @@ +from langchain.chat_models import ChatOpenAI, ChatAnthropic +from langchain.schema.output_parser import StrOutputParser +from langchain.prompts import SystemMessagePromptTemplate +from config import Config + +CFG = Config() + +class ReviserActor: + def __init__(self): + self.model = ChatOpenAI(model=CFG.smart_llm_model) + self.prompt = SystemMessagePromptTemplate.from_template( + "You are an expert writer. " + "You have been tasked by your editor with revising the following draft, which was written by a non-expert. " + "You may follow the editor's notes or not, as you see fit." + ) + "Draft:\n\n{draft}" + "Editor's notes:\n\n{notes}" + + @property + def runnable(self): + return { + "answer": { + "draft": lambda x: x["draft"], + "notes": lambda x: x["notes"], + } + | self.prompt | self.model | StrOutputParser() + } diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index 5dfadbd65..37aafbcea 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -11,8 +11,8 @@ from agent.prompts import auto_agent_instructions search_message = ( - 'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ - 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' + 'Write 3 google search queries to search online that form an objective opinion from the following: "{question}"'\ + 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3"]' ) SEARCH_PROMPT = ChatPromptTemplate.from_messages([ ("system", "{agent_prompt}"), diff --git a/permchain_example/test.py b/permchain_example/test.py index 55b852ee4..eef274cb1 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -4,14 +4,17 @@ from permchain_example.researcher import Researcher from permchain_example.search_actors.search_api import TavilySearchActor +from permchain_example.editor_actors.editor import EditorActor +from permchain_example.reviser_actors.reviser import ReviserActor from permchain_example.search_actors.gpt_researcher import GPTResearcherActor -from permchain_example.writer_actors.openai import OpenAIWriterActor +from permchain_example.writer_actors.writer import WriterActor +from permchain_example.research_team import ResearchTeam from processing.text import md_to_pdf if __name__ == '__main__': - output_path = "./permchain_example/output" + output_path = "./output" if not os.path.exists(output_path): # If the directory does not exist, create it os.makedirs(output_path) @@ -19,10 +22,10 @@ stocks = ["AAPL"] for stock in stocks[:1]: - researcher = Researcher(GPTResearcherActor(), OpenAIWriterActor()) - research = researcher.run(f"is the stock {stock} a good buy?") - with open(f"{output_path}/{stock}.md", "w") as f: - f.write(research) - md_to_pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") - + researcher = Researcher(GPTResearcherActor(), WriterActor()) + research_team = ResearchTeam(researcher, EditorActor(), ReviserActor()) + draft = research_team.run(f"is the stock {stock} a good buy?") + with open(f"{output_path}/{stock}.md", "w") as f: + f.write(draft) + md_to_pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") \ No newline at end of file diff --git a/permchain_example/writer_actors/openai.py b/permchain_example/writer_actors/writer.py similarity index 98% rename from permchain_example/writer_actors/openai.py rename to permchain_example/writer_actors/writer.py index 9b942cfc0..ff14072a8 100644 --- a/permchain_example/writer_actors/openai.py +++ b/permchain_example/writer_actors/writer.py @@ -6,7 +6,7 @@ CFG = Config() -class OpenAIWriterActor: +class WriterActor: def __init__(self): self.model = ChatOpenAI(model=CFG.smart_llm_model) self.prompt = ChatPromptTemplate.from_messages([ From 7931884bb3d312ed38b132d51d0c956665a6c91f Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:31:19 +0300 Subject: [PATCH 09/26] wrapped editor in object --- .../editor_actors/editor-runnable.py | 53 ---------------- permchain_example/editor_actors/editor.py | 62 +++++++++---------- permchain_example/test.py | 2 +- 3 files changed, 30 insertions(+), 87 deletions(-) delete mode 100644 permchain_example/editor_actors/editor-runnable.py diff --git a/permchain_example/editor_actors/editor-runnable.py b/permchain_example/editor_actors/editor-runnable.py deleted file mode 100644 index e0695c835..000000000 --- a/permchain_example/editor_actors/editor-runnable.py +++ /dev/null @@ -1,53 +0,0 @@ -from langchain.prompts import ChatPromptTemplate -from langchain.chat_models import ChatOpenAI, ChatAnthropic -from langchain.schema.output_parser import StrOutputParser -from langchain.prompts import SystemMessagePromptTemplate -from datetime import date -from config import Config - -CFG = Config() - -EDIT_TEMPLATE = """You are an editor. \ -You have been tasked with editing the following draft, which was written by a non-expert. \ -Please accept the draft if it is good enough to publish, or send it for revision, along with your notes to guide the revision. \ -Things you should be checking for: - -- This draft MUST fully answer the original question -- This draft MUST be written in spanish - -If not all of the above criteria are met, you should send appropriate revision notes. -""" - -class EditorActor: - def __init__(self): - self.model = ChatOpenAI(model=CFG.smart_llm_model) - self.prompt = SystemMessagePromptTemplate.from_template(EDIT_TEMPLATE) + "Draft:\n\n{draft}" - self.functions = [ - { - "name": "revise", - "description": "Sends the draft for revision", - "parameters": { - "type": "object", - "properties": { - "notes": { - "type": "string", - "description": "The editor's notes to guide the revision.", - }, - }, - }, - }, - { - "name": "accept", - "description": "Accepts the draft", - "parameters": { - "type": "object", - "properties": {"ready": {"const": True}}, - }, - }, - ] - - @property - def runnable(self): - return { - "answer": self.prompt | self.model.bind(functions=self.functions) - } diff --git a/permchain_example/editor_actors/editor.py b/permchain_example/editor_actors/editor.py index dd55aa068..1c62f4fc5 100644 --- a/permchain_example/editor_actors/editor.py +++ b/permchain_example/editor_actors/editor.py @@ -10,46 +10,42 @@ Things you should be checking for: - This draft MUST fully answer the original question -- This draft MUST be apa format +- This draft MUST be written in apa format If not all of the above criteria are met, you should send appropriate revision notes. """ -critique_prompt = ( - SystemMessagePromptTemplate.from_template(EDIT_TEMPLATE) - + "Draft:\n\n{draft}" -) -critique_llm = ChatOpenAI(model=CFG.smart_llm_model) -functions = [ - { - "name": "revise", - "description": "Sends the draft for revision", - "parameters": { - "type": "object", - "properties": { - "notes": { - "type": "string", - "description": "The editor's notes to guide the revision.", + +class EditorActor: + def __init__(self): + self.model = ChatOpenAI(model=CFG.smart_llm_model) + self.prompt = SystemMessagePromptTemplate.from_template(EDIT_TEMPLATE) + "Draft:\n\n{draft}" + self.functions = [ + { + "name": "revise", + "description": "Sends the draft for revision", + "parameters": { + "type": "object", + "properties": { + "notes": { + "type": "string", + "description": "The editor's notes to guide the revision.", + }, + }, }, }, - }, - }, - { - "name": "accept", - "description": "Accepts the draft", - "parameters": { - "type": "object", - "properties": {"ready": {"const": True}}, - }, - }, -] - -#EditorActor = critique_prompt | critique_llm.bind(functions=functions) - + { + "name": "accept", + "description": "Accepts the draft", + "parameters": { + "type": "object", + "properties": {"ready": {"const": True}}, + }, + }, + ] -class EditorActor: @property def runnable(self): return ( - critique_prompt | critique_llm.bind(functions=functions) - ) \ No newline at end of file + self.prompt | self.model.bind(functions=self.functions) + ) diff --git a/permchain_example/test.py b/permchain_example/test.py index eef274cb1..ab68d7e4f 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -19,7 +19,7 @@ # If the directory does not exist, create it os.makedirs(output_path) - stocks = ["AAPL"] + stocks = ["WIX"] for stock in stocks[:1]: researcher = Researcher(GPTResearcherActor(), WriterActor()) From 50caade878dcdd4e98a91d6a0945beef0d77c7a5 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:33:01 +0300 Subject: [PATCH 10/26] cleaned code --- permchain_example/reviser_actors/reviser.py | 3 +-- permchain_example/writer_actors/writer.py | 3 +-- 2 files changed, 2 insertions(+), 4 deletions(-) diff --git a/permchain_example/reviser_actors/reviser.py b/permchain_example/reviser_actors/reviser.py index b8b7d3569..dd15a6492 100644 --- a/permchain_example/reviser_actors/reviser.py +++ b/permchain_example/reviser_actors/reviser.py @@ -20,6 +20,5 @@ def runnable(self): "answer": { "draft": lambda x: x["draft"], "notes": lambda x: x["notes"], - } - | self.prompt | self.model | StrOutputParser() + } | self.prompt | self.model | StrOutputParser() } diff --git a/permchain_example/writer_actors/writer.py b/permchain_example/writer_actors/writer.py index ff14072a8..3026dc9f8 100644 --- a/permchain_example/writer_actors/writer.py +++ b/permchain_example/writer_actors/writer.py @@ -29,6 +29,5 @@ def runnable(self): "answer": { "query": lambda x: x["query"], "results": lambda x: "\n\n".join(x["results"]) - } - | self.prompt | self.model | StrOutputParser() + } | self.prompt | self.model | StrOutputParser() } From 62fcb368564524c5ff58f8287216bfb468ba8414 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:47:09 +0300 Subject: [PATCH 11/26] fixed wrong output --- permchain_example/research_team.py | 6 +++--- permchain_example/reviser_actors/reviser.py | 2 +- 2 files changed, 4 insertions(+), 4 deletions(-) diff --git a/permchain_example/research_team.py b/permchain_example/research_team.py index d38b1901e..17e841591 100644 --- a/permchain_example/research_team.py +++ b/permchain_example/research_team.py @@ -26,7 +26,7 @@ def run(self, query): # create topics editor_inbox = Topic("editor_inbox") reviser_inbox = Topic("reviser_inbox") - draft_chain = ( + research_chain = ( # Listed in inputs Topic.IN.subscribe() | {"draft": lambda x: self.research_actor_instance.run(x["question"])} @@ -65,10 +65,10 @@ def run(self, query): ) web_researcher = PubSub( - processes=(draft_chain, editor_chain, reviser_chain), + processes=(research_chain, editor_chain, reviser_chain), connection=InMemoryPubSubConnection(), ) res = web_researcher.invoke({"question": query}) print(res) - return res[0]["draft"]["answer"] + return res[0]["draft"] diff --git a/permchain_example/reviser_actors/reviser.py b/permchain_example/reviser_actors/reviser.py index dd15a6492..fc26134fb 100644 --- a/permchain_example/reviser_actors/reviser.py +++ b/permchain_example/reviser_actors/reviser.py @@ -17,7 +17,7 @@ def __init__(self): @property def runnable(self): return { - "answer": { + "draft": { "draft": lambda x: x["draft"], "notes": lambda x: x["notes"], } | self.prompt | self.model | StrOutputParser() From c2ebe172dbb432ed50a161d2282676f65637340b Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:50:03 +0300 Subject: [PATCH 12/26] cleaned indents --- permchain_example/research_team.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/permchain_example/research_team.py b/permchain_example/research_team.py index 17e841591..10891f311 100644 --- a/permchain_example/research_team.py +++ b/permchain_example/research_team.py @@ -27,7 +27,7 @@ def run(self, query): editor_inbox = Topic("editor_inbox") reviser_inbox = Topic("reviser_inbox") research_chain = ( - # Listed in inputs + # Listed in inputs Topic.IN.subscribe() | {"draft": lambda x: self.research_actor_instance.run(x["question"])} # The draft always goes to the critique inbox @@ -35,7 +35,7 @@ def run(self, query): ) editor_chain = ( - # Listen for events in the editor_inbox + # Listen for events in the editor_inbox editor_inbox.subscribe() | self.editor_actor_instance.runnable # Depending on the output, different things should happen From b0dce20ff5fa9c6c0c352f71ec14bbe755f349cb Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:52:40 +0300 Subject: [PATCH 13/26] d --- permchain_example/writer_actors/writer.py | 3 +-- 1 file changed, 1 insertion(+), 2 deletions(-) diff --git a/permchain_example/writer_actors/writer.py b/permchain_example/writer_actors/writer.py index 3026dc9f8..cbfacaf65 100644 --- a/permchain_example/writer_actors/writer.py +++ b/permchain_example/writer_actors/writer.py @@ -1,7 +1,6 @@ from langchain.prompts import ChatPromptTemplate -from langchain.chat_models import ChatOpenAI, ChatAnthropic +from langchain.chat_models import ChatOpenAI from langchain.schema.output_parser import StrOutputParser -from datetime import date from config import Config CFG = Config() From fc5d37f003e8b881bc0fe62fd5c990b1855bbe31 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 20:54:16 +0300 Subject: [PATCH 14/26] cleaned code --- permchain_example/writer_actors/writer.py | 15 +++++++++------ 1 file changed, 9 insertions(+), 6 deletions(-) diff --git a/permchain_example/writer_actors/writer.py b/permchain_example/writer_actors/writer.py index cbfacaf65..3ffe4a917 100644 --- a/permchain_example/writer_actors/writer.py +++ b/permchain_example/writer_actors/writer.py @@ -10,15 +10,18 @@ def __init__(self): self.model = ChatOpenAI(model=CFG.smart_llm_model) self.prompt = ChatPromptTemplate.from_messages([ ("system", - "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." + "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." ), ("user", '"""{results}""" Using the above information, answer the following' - ' question or topic: "{query}" 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, a minimum of 1,200 words and with markdown syntax (including titles) and apa format. " - "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 in apa format" + ' question or topic: "{query}" 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, " + "a minimum of 1,200 words and with markdown syntax (including titles) and apa format. " + "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 in apa format" ) ]) From 335b22bff250d0acb1cc9c894823ae1fe2d48b19 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 16 Sep 2023 21:09:49 +0300 Subject: [PATCH 15/26] refactored code --- permchain_example/research_team.py | 35 +++++++++++++++--------------- 1 file changed, 17 insertions(+), 18 deletions(-) diff --git a/permchain_example/research_team.py b/permchain_example/research_team.py index 10891f311..26264d209 100644 --- a/permchain_example/research_team.py +++ b/permchain_example/research_team.py @@ -12,8 +12,8 @@ - Searching for relevant information across multiple sources - Extracting relevant information - Writing a well structured report + - Validating the report - Revising the report - - Editing the report - Repeat until the report is satisfactory ''' class ResearchTeam: @@ -26,21 +26,21 @@ def run(self, query): # create topics editor_inbox = Topic("editor_inbox") reviser_inbox = Topic("reviser_inbox") + research_chain = ( - # Listed in inputs - Topic.IN.subscribe() - | {"draft": lambda x: self.research_actor_instance.run(x["question"])} - # The draft always goes to the critique inbox - | editor_inbox.publish() + # Listed in inputs + Topic.IN.subscribe() + | {"draft": lambda x: self.research_actor_instance.run(x["question"])} + # The draft always goes to the editor inbox + | editor_inbox.publish() ) editor_chain = ( - # Listen for events in the editor_inbox - editor_inbox.subscribe() - | self.editor_actor_instance.runnable - # Depending on the output, different things should happen - | OpenAIFunctionsRouter( - { + # Listen for events in the editor_inbox + editor_inbox.subscribe() + | self.editor_actor_instance.runnable + # Depending on the output, different things should happen + | OpenAIFunctionsRouter({ # If revise is chosen, we send a push to the critique_inbox "revise": ( { @@ -52,16 +52,15 @@ def run(self, query): ), # If accepted, then we return "accept": editor_inbox.current() | Topic.OUT.publish(), - }, - ) + }) ) reviser_chain = ( # Listen for events in the reviser's inbox - reviser_inbox.subscribe() - | {"draft": self.revise_actor_instance.runnable} - # Publish to the critique inbox - | editor_inbox.publish() + reviser_inbox.subscribe() + | self.revise_actor_instance.runnable + # Publish to the editor inbox + | editor_inbox.publish() ) web_researcher = PubSub( From 4b241739711f18ad1f5f765e6615ab4f07b606b0 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sun, 17 Sep 2023 14:38:07 +0300 Subject: [PATCH 16/26] refactored gpt researcher to allow for both streaming and non streaming calls --- agent/research_agent.py | 51 ++++++++++++++++++++++------------------- processing/text.py | 4 ++-- 2 files changed, 29 insertions(+), 26 deletions(-) diff --git a/agent/research_agent.py b/agent/research_agent.py index 9c0d95f16..17de24d0b 100644 --- a/agent/research_agent.py +++ b/agent/research_agent.py @@ -3,7 +3,7 @@ # libraries import asyncio import json -import uuid +import hashlib from actions.web_search import web_search from actions.web_scrape import async_browse @@ -23,7 +23,7 @@ class ResearchAgent: - def __init__(self, question, agent, agent_role_prompt, websocket): + def __init__(self, question, agent, agent_role_prompt, websocket=None): """ Initializes the research assistant with the given question. Args: question (str): The question to research Returns: None @@ -34,10 +34,14 @@ def __init__(self, question, agent, agent_role_prompt, websocket): self.agent_role_prompt = agent_role_prompt if agent_role_prompt else prompts.generate_agent_role_prompt(agent) self.visited_urls = set() self.research_summary = "" - self.directory_name = uuid.uuid4() - self.dir_path = os.path.dirname(f"./outputs/{self.directory_name}/") + self.dir_path = f"./outputs/{hashlib.sha1(question.encode()).hexdigest()}" self.websocket = websocket + async def stream_output(self, output): + if not self.websocket: + return print(output) + await self.websocket.send_json({"type": "logs", "output": output}) + async def summarize(self, text, topic): """ Summarizes the given text for the given topic. @@ -47,7 +51,7 @@ async def summarize(self, text, topic): """ messages = [create_message(text, topic)] - await self.websocket.send_json({"type": "logs", "output": f"📝 Summarizing text for query: {text}"}) + await self.stream_output(f"📝 Summarizing text for query: {text}") return create_chat_completion( model=CFG.fast_llm_model, @@ -63,7 +67,8 @@ async def get_new_urls(self, url_set_input): new_urls = [] for url in url_set_input: if url not in self.visited_urls: - await self.websocket.send_json({"type": "logs", "output": f"✅ Adding source url to research: {url}\n"}) + await self.stream_output(f"✅ Adding source url to research: {url}\n") + self.visited_urls.add(url) new_urls.append(url) @@ -91,8 +96,7 @@ async def create_search_queries(self): Returns: list[str]: The search queries for the given question """ result = await self.call_agent(prompts.generate_search_queries_prompt(self.question)) - print(result) - await self.websocket.send_json({"type": "logs", "output": f"🧠 I will conduct my research based on the following queries: {result}..."}) + await self.stream_output(f"🧠 I will conduct my research based on the following queries: {result}...") return json.loads(result) async def async_search(self, query): @@ -103,8 +107,7 @@ async def async_search(self, query): search_results = json.loads(web_search(query)) new_search_urls = self.get_new_urls([url.get("href") for url in search_results]) - await self.websocket.send_json( - {"type": "logs", "output": f"🌐 Browsing the following sites for relevant information: {new_search_urls}..."}) + await self.stream_output(f"🌐 Browsing the following sites for relevant information: {new_search_urls}...") # Create a list to hold the coroutine objects tasks = [async_browse(url, query, self.websocket) for url in await new_search_urls] @@ -120,13 +123,13 @@ async def run_search_summary(self, query): Returns: str: The search summary for the given query """ - await self.websocket.send_json({"type": "logs", "output": f"🔎 Running research for '{query}'..."}) + await self.stream_output(f"🔎 Running research for '{query}'...") responses = await self.async_search(query) result = "\n".join(responses) - os.makedirs(os.path.dirname(f"./outputs/{self.directory_name}/research-{query}.txt"), exist_ok=True) - write_to_file(f"./outputs/{self.directory_name}/research-{query}.txt", result) + os.makedirs(os.path.dirname(f"{self.dir_path}/research-{query}.txt"), exist_ok=True) + write_to_file(f"{self.dir_path}/research-{query}.txt", result) return result async def conduct_research(self): @@ -134,7 +137,6 @@ async def conduct_research(self): Args: None Returns: str: The research for the given question """ - self.research_summary = read_txt_files(self.dir_path) if os.path.isdir(self.dir_path) else "" if not self.research_summary: @@ -143,8 +145,7 @@ async def conduct_research(self): research_result = await self.run_search_summary(query) self.research_summary += f"{research_result}\n\n" - await self.websocket.send_json( - {"type": "logs", "output": f"Total research words: {len(self.research_summary.split(' '))}"}) + await self.stream_output(f"Total research words: {len(self.research_summary.split(' '))}") return self.research_summary @@ -156,21 +157,23 @@ async def create_concepts(self): """ result = self.call_agent(prompts.generate_concepts_prompt(self.question, self.research_summary)) - await self.websocket.send_json({"type": "logs", "output": f"I will research based on the following concepts: {result}\n"}) + await self.stream_output(f"I will research based on the following concepts: {result}\n") return json.loads(result) - async def write_report(self, report_type, websocket): + async def write_report(self, report_type, websocket=None): """ Writes the report for the given question. Args: None Returns: str: The report for the given question """ report_type_func = prompts.get_report_by_type(report_type) - await websocket.send_json( - {"type": "logs", "output": f"✍️ Writing {report_type} for research task: {self.question}..."}) - answer = await self.call_agent(report_type_func(self.question, self.research_summary), stream=True, - websocket=websocket) + await self.stream_output(f"✍️ Writing {report_type} for research task: {self.question}...") + + answer = await self.call_agent(report_type_func(self.question, self.research_summary), + stream=websocket is not None, websocket=websocket) + # if websocket is True than we are streaming gpt response, so we need to wait for the final response + final_report = await answer if websocket else answer - path = await write_md_to_pdf(report_type, self.directory_name, await answer) + path = await write_md_to_pdf(report_type, self.dir_path, final_report) return answer, path @@ -182,4 +185,4 @@ async def write_lessons(self): concepts = await self.create_concepts() for concept in concepts: answer = await self.call_agent(prompts.generate_lesson_prompt(concept), stream=True) - write_md_to_pdf("Lesson", self.directory_name, answer) + await write_md_to_pdf("Lesson", self.dir_path, answer) diff --git a/processing/text.py b/processing/text.py index 277e7809f..cf591aa06 100644 --- a/processing/text.py +++ b/processing/text.py @@ -143,8 +143,8 @@ def write_to_file(filename: str, text: str) -> None: with open(filename, "w") as file: file.write(text) -async def write_md_to_pdf(task: str, directory_name: str, text: str) -> None: - file_path = f"./outputs/{directory_name}/{task}" +async def write_md_to_pdf(task: str, path: str, text: str) -> None: + file_path = f"{path}/{task}" write_to_file(f"{file_path}.md", text) md_to_pdf(f"{file_path}.md", f"{file_path}.pdf") print(f"{task} written to {file_path}.pdf") From 0d74cab88642a07f06902cfa5578952e8fab1742 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sun, 17 Sep 2023 15:47:51 +0300 Subject: [PATCH 17/26] fixed issue with wrong type output --- agent/llm_utils.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/agent/llm_utils.py b/agent/llm_utils.py index e36a2535a..ed432ebee 100644 --- a/agent/llm_utils.py +++ b/agent/llm_utils.py @@ -98,7 +98,7 @@ async def stream_response(model, messages, temperature, max_tokens, websocket): return response -def choose_agent(task: str) -> str: +def choose_agent(task: str) -> dict: """Determines what agent should be used Args: task (str): The research question the user asked From 6bb12781909aa0a64788c614f9709ad67b010ab2 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sun, 17 Sep 2023 17:31:06 +0300 Subject: [PATCH 18/26] refactored to use existing code instead of duplicates --- agent/prompts.py | 4 +-- .../search_actors/gpt_researcher.py | 34 +++++++++---------- permchain_example/writer_actors/writer.py | 17 ++-------- 3 files changed, 22 insertions(+), 33 deletions(-) diff --git a/agent/prompts.py b/agent/prompts.py index 3913fd1ba..9576ad719 100644 --- a/agent/prompts.py +++ b/agent/prompts.py @@ -35,8 +35,8 @@ def generate_search_queries_prompt(question): Returns: str: The search queries prompt for the given question """ - return f'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ - f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' + return f'Write 2 google search queries to search online that form an objective opinion from the following: "{question}"'\ + f'You must respond with a list of strings in the following format: ["query 1", "query 2"]' def generate_resource_report_prompt(question, research_summary): diff --git a/permchain_example/search_actors/gpt_researcher.py b/permchain_example/search_actors/gpt_researcher.py index 37aafbcea..899ec25fb 100644 --- a/permchain_example/search_actors/gpt_researcher.py +++ b/permchain_example/search_actors/gpt_researcher.py @@ -1,19 +1,19 @@ -from processing.text import split_text, summarize_text +import json +from processing.text import summarize_text from actions.web_scrape import scrape_text_with_selenium from actions.web_search import web_search -from langchain.chat_models import ChatOpenAI, ChatAnthropic -from langchain.prompts import SystemMessagePromptTemplate, ChatPromptTemplate +from langchain.chat_models import ChatOpenAI +from langchain.prompts import ChatPromptTemplate from langchain.schema.output_parser import StrOutputParser -from langchain.schema.runnable import RunnableMap -import json +from langchain.schema.runnable import RunnableMap, RunnableLambda from langchain.schema.messages import SystemMessage -from agent.prompts import auto_agent_instructions +from agent.prompts import auto_agent_instructions, generate_search_queries_prompt +from config import Config + +CFG = Config() -search_message = ( - 'Write 3 google search queries to search online that form an objective opinion from the following: "{question}"'\ - 'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3"]' -) +search_message = (generate_search_queries_prompt("{question}")) SEARCH_PROMPT = ChatPromptTemplate.from_messages([ ("system", "{agent_prompt}"), ("user", search_message) @@ -32,7 +32,7 @@ } | RunnableMap({ "summary": lambda x: summarize_text(text=x["text"], question=x["question"], url=x["url"]), "url": lambda x: x['url'] -}) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") +}) | (lambda x: f"Source Url: {x['url']}\nSummary: {x['summary']}") seen_urls = set() multi_search = ( @@ -43,8 +43,8 @@ ] ) | scrape_and_summarize.map() | (lambda x: "\n".join(x)) -search_query = SEARCH_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads -choose_agent = CHOOSE_AGENT_PROMPT | ChatOpenAI() | StrOutputParser() | json.loads +search_query = SEARCH_PROMPT | ChatOpenAI(model=CFG.smart_llm_model) | StrOutputParser() | json.loads +choose_agent = CHOOSE_AGENT_PROMPT | ChatOpenAI(model=CFG.smart_llm_model) | StrOutputParser() | json.loads get_search_queries = { "question": lambda x: x, @@ -57,9 +57,9 @@ class GPTResearcherActor: @property def runnable(self): return ( - get_search_queries - | (lambda x: [{"question": q} for q in x]) - | multi_search.map() - | (lambda x: "\n\n".join(x)) + get_search_queries + | (lambda x: [{"question": q} for q in x]) + | multi_search.map() + | (lambda x: "\n\n".join(x)) ) diff --git a/permchain_example/writer_actors/writer.py b/permchain_example/writer_actors/writer.py index 3ffe4a917..e65421b20 100644 --- a/permchain_example/writer_actors/writer.py +++ b/permchain_example/writer_actors/writer.py @@ -1,6 +1,7 @@ from langchain.prompts import ChatPromptTemplate from langchain.chat_models import ChatOpenAI from langchain.schema.output_parser import StrOutputParser +from agent.prompts import generate_report_prompt, generate_agent_role_prompt from config import Config CFG = Config() @@ -9,20 +10,8 @@ class WriterActor: def __init__(self): self.model = ChatOpenAI(model=CFG.smart_llm_model) self.prompt = ChatPromptTemplate.from_messages([ - ("system", - "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." - ), - ("user", - '"""{results}""" Using the above information, answer the following' - ' question or topic: "{query}" 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, " - "a minimum of 1,200 words and with markdown syntax (including titles) and apa format. " - "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 in apa format" - ) + ("system", generate_agent_role_prompt(agent="Default Agent")), + ("user", generate_report_prompt(question="{query}", research_summary="{results}")) ]) @property From 5ce1a5aa31b38b75677a2bff667eeb13d0ff109b Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sun, 17 Sep 2023 17:32:14 +0300 Subject: [PATCH 19/26] modified prompts --- agent/prompts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/agent/prompts.py b/agent/prompts.py index 9576ad719..3913fd1ba 100644 --- a/agent/prompts.py +++ b/agent/prompts.py @@ -35,8 +35,8 @@ def generate_search_queries_prompt(question): Returns: str: The search queries prompt for the given question """ - return f'Write 2 google search queries to search online that form an objective opinion from the following: "{question}"'\ - f'You must respond with a list of strings in the following format: ["query 1", "query 2"]' + return f'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ + f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' def generate_resource_report_prompt(question, research_summary): From 92cae429a12a994c97f9505f6393ffce866a0760 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 30 Sep 2023 11:00:23 +0300 Subject: [PATCH 20/26] added readme explanation --- permchain_example/README.md | 22 ++++++++++++++++-- permchain_example/output/AAPL.md | 25 ++++++++++++++++++++ permchain_example/output/AAPL.pdf | Bin 0 -> 54863 bytes permchain_example/output/AMZN.md | 12 ++++++++++ permchain_example/output/AMZN.pdf | Bin 0 -> 48722 bytes permchain_example/output/NVDA.md | 37 ++++++++++++++++++++++++++++++ permchain_example/output/NVDA.pdf | Bin 0 -> 62373 bytes permchain_example/output/WIX.md | 30 ++++++++++++++++++++++++ permchain_example/output/WIX.pdf | Bin 0 -> 61110 bytes 9 files changed, 124 insertions(+), 2 deletions(-) create mode 100644 permchain_example/output/AAPL.md create mode 100644 permchain_example/output/AAPL.pdf create mode 100644 permchain_example/output/AMZN.md create mode 100644 permchain_example/output/AMZN.pdf create mode 100644 permchain_example/output/NVDA.md create mode 100644 permchain_example/output/NVDA.pdf create mode 100644 permchain_example/output/WIX.md create mode 100644 permchain_example/output/WIX.pdf diff --git a/permchain_example/README.md b/permchain_example/README.md index d68dd3762..d690da8eb 100644 --- a/permchain_example/README.md +++ b/permchain_example/README.md @@ -1,2 +1,20 @@ -# permchain_researcher -Sample use of permchain within GPT Researcher +# Permchain x Researcher +Sample use of Langchain's Autonomous agent framework Permchain with GPT Researcher. + +## Use case +Permchain is a framework for building autonomous agents that can be used to automate tasks and communication between agents to complete complex tasks. This example uses Permchain to automate the process of finding and summarizing research reports on any given topic. + +## The Agent Team +The research team is made up of 3 agents: +- Researcher agent (gpt-researcher) - This agent is in charge of finding and summarizing relevant research papers. +- Editor agent - This agent is in charge of validating the correctness of the report given a set of criteria. +- Reviser agent - This agent is in charge of revising the report until it is satisfactory. + +## How it works +The research agent (gpt-researcher) is in charge of finding and summarizing relevant research papers. It does this by using the following process: +- Search for relevant research papers using a search engine +- Extract the relevant information from the research papers +- Summarize the information into a report +- Send the report to the editor agent for validation +- Send the report to the reviser agent for revision +- Repeat until the report is satisfactory \ No newline at end of file diff --git a/permchain_example/output/AAPL.md b/permchain_example/output/AAPL.md new file mode 100644 index 000000000..2e8fe7803 --- /dev/null +++ b/permchain_example/output/AAPL.md @@ -0,0 +1,25 @@ +Revised Draft: + +# Is Apple Inc. (AAPL) a Good Investment? + +## Abstract + +This article aims to evaluate the investment potential of Apple Inc. (AAPL), a leading multinational technology company. The analysis uses financial data from various sources to assess the company's performance, valuation, dividend payments, and recent stock splits. The findings suggest that AAPL stock exhibits promising signs of growth and profitability, making it a potential investment opportunity in the current financial market. + +## Financial Performance + +Apple Inc.'s financial performance has shown consistent growth over recent years. According to StockAnalysis.com, the company reported a revenue of $394.33 billion in 2022, a 7.79% increase from the prior year (StockAnalysis.com, 2022). Additionally, earnings rose by 5.41% to $99.80 billion, further demonstrating the company's financial stability. These figures, coupled with a "Buy" rating from 35 surveyed analysts and a forecasted 13.69% increase in the 12-month stock price, underscore the potential profitability of AAPL stock (StockAnalysis.com, 2022). + +## Valuation Analysis + +StockAnalysis.com's valuation analysis reveals that Apple's market capitalization stands at $2.74 trillion, and its enterprise value is $2.68 trillion (StockAnalysis.com, 2022). The company's trailing and forward P/E ratios are 29.41 and 26.66, respectively. These figures indicate a high market valuation, suggesting investor confidence in Apple's future growth. Furthermore, a ROIC of 38.90% and a WACC of 11.2% indicate that Apple effectively uses its capital to generate profits (StockAnalysis.com, 2022). + +## Dividends and Stock Split + +Apple pays an annual dividend of $0.96 per share, yielding 0.55% (StockAnalysis.com, 2022). This yield, albeit lower than some competitors, signifies Apple's commitment to shareholder returns. + +As for stock splits, Apple's last split occurred in 2020, when it divided each share into four (StockAnalysis.com, 2022). Stock splits can make shares more accessible to individual investors, increasing demand and potentially driving up the stock price. + +## References + +StockAnalysis.com. (2022). Apple Inc. (AAPL) Stock Analysis. 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000000000..9a5aa00c0 --- /dev/null +++ b/permchain_example/output/AMZN.md @@ -0,0 +1,12 @@ +Revised Draft: + +# Amazon Stock: A Quick Investment Analysis + +Amazon Inc. (NASDAQ: AMZN) is a significant player in e-commerce, cloud computing, and artificial intelligence. Its success is mirrored in its strong stock market performance. This brief analysis considers the potential of AMZN stock as an investment. + +Currently, Amazon's stock price is at a new 52-week high (Yahoo Finance, 2021). Analysts predict a 214% earnings increase to $2.23 per share by 2023 (Yahoo Finance, 2021). This could further boost the stock price. In the last 60 days, Amazon's FY23 and FY24 earnings per share estimates rose by 42% and 35% respectively (Yahoo Finance, 2021), indicating positive market sentiment. The Zacks Price Target predicts an 18% stock upside (Yahoo Finance, 2021), suggesting more growth potential. + +Considering its strong performance, promising earnings prospects, and potential upside, AMZN stock appears to be a worthwhile investment. Nonetheless, it's crucial to note the inherent risks of the stock market and the importance of thorough research before investing. + +References +- Yahoo Finance. (2021). Amazon's (AMZN) Stock Keeps Rising. 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This report aims to provide a comprehensive evaluation of NVDA (Nvidia Corporation) as a potential investment, based on the limited information available from the given sources. + +## Overview of NVDA + +NVDA is a multinational technology corporation based in the United States, known primarily for its developments in artificial intelligence and graphics processing units (GPUs). NVDA's innovative technology and dominance in the market have made its stock a subject of interest for many investors. + +## Performance Analysis + +Unfortunately, the URLs provided from Morningstar, Stockanalysis, and the Wall Street Journal do not offer specific data on NVDA's performance in 2021. As such, detailed performance analysis, including aspects such as earnings per share, price-to-earnings ratio, and dividend yield, cannot be provided. + +## Expert Opinions and Future Growth Prospects + +According to information from Investorplace, expert opinions on NVDA's future growth prospects are divided. Critics point to potential challenges related to the company's generative artificial intelligence growth catalyst, including high competition and geopolitical tensions, which could potentially impact demand, margins, and profitability. However, the article argues that Nvidia's premium valuation is justified due to strong demand for AI chips and the company's prospects for high earnings growth in the coming years. It also emphasizes Nvidia's competitive advantage as a provider of AI software and services, suggesting it has a deep moat. + +The website Marketbeat, however, only provides factual information about NVDA's recent earnings results, quarterly dividend, stock split, and third-quarter earnings guidance. The Motley Fool URL does not contain any specific information about expert opinions on NVDA's future growth prospects. + +## Conclusion + +Based on the limited information available, it's difficult to confidently conclude whether NVDA stock is a good buy. The company's strong position in the AI and GPU markets, along with its potential for high earnings growth, suggests that NVDA could be a solid investment. However, potential investors must also consider potential headwinds, such as high competition and geopolitical tensions. + +To make a more informed decision, investors should consider conducting a thorough analysis using comprehensive and up-to-date data, including financial statements and relevant macroeconomic indicators. They should also consider their own investment goals, risk tolerance, and financial situation. + +## References + +Morningstar. (n.d.). NVDA Stock | NVIDIA Stock Price Today | Markets Insider. Retrieved from https://www.morningstar.com/stocks/xnas/nvda/performance + +Stockanalysis. (n.d.). NVDA Stock Price and Chart — NASDAQ:NVDA — TradingView. Retrieved from https://stockanalysis.com/stocks/nvda/ + +The Wall Street Journal. (n.d.). NVDA Stock Price | NVIDIA Corp. Stock Quote (U.S.: Nasdaq) | MarketWatch. Retrieved from https://www.wsj.com/market-data/quotes/NVDA/research-ratings + +Investorplace. (n.d.). Ignore Nvidia Skeptics: Here’s Why NVDA Stock Will Remain a Winner. Retrieved from https://investorplace.com/market360/2023/09/ignore-nvidia-skeptics-heres-why-nvda-stock-will-remain-a-winner/ + +Marketbeat. (n.d.). NVIDIA (NASDAQ:NVDA) Stock Quotes & Market Cap. Retrieved from https://www.marketbeat.com/stocks/NASDAQ/NVDA/ + +The Motley Fool. (n.d.). Where Will Nvidia Be in 5 Years? | The Motley Fool. 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zkN+VP5*5LC`45?>gg7Q(|B#`fNc@LA5fKQQ6o2Xoga1<|a=se;p$7p$!2iY!0f~vB zN%t>3@&D)-y~YXu+bhK@PF!w zf<@4=`Y$~R(7)}8qBmIo#*CJU{2L$I%cAJK_J=*ROzhunAs|uAM&=Ja2pByf{~;5V z_{|>D!wS7U^Eh8G^&I?R82(`rrY-`31fFyIg14%!b_n2k_?@q|o=7VXV0sSsQNdN!< literal 0 HcmV?d00001 diff --git a/permchain_example/output/WIX.md b/permchain_example/output/WIX.md new file mode 100644 index 000000000..293bda06f --- /dev/null +++ b/permchain_example/output/WIX.md @@ -0,0 +1,30 @@ +# Is WIX a Good Buy? +The evaluation of the viability of a stock as an investment is typically dependent on a multitude of factors including the company's financial health, its place within the competitive market, future prospects, and the current and projected state of the market. This report seeks to assess whether WIX stock is a good buy based on the available information. + +## Analysis of WIX's Financial Health +Wix.com Ltd. (WIX) is a cloud-based web development platform that allows users to create HTML5 websites and mobile sites through the use of online drag and drop tools. The company's revenue generation is primarily from the freemium business model, offering users free website design and hosting, with additional premium features available for purchase. + +According to the information obtained from MarketBeat, the company has a negative earnings per share (EPS) of -$1.10. This indicates that the company is not currently profitable. Furthermore, the company has reported a net loss of -$424,860,000, which further emphasizes the company's current lack of profitability. WIX's negative P/E ratio of -86.65 is a reflection of these negative earnings. + +That being said, the company's market capitalization stands at $5.41 billion, with revenues amounting to $1.39 billion. These figures reveal that despite its current lack of profitability, the company is generating substantial revenues and holds a significant place within the market. Moreover, WIX's global workforce of 4,742 employees indicates a large scale operation. + +## Analyst Opinions and Stock Forecasts +According to the information obtained from StockAnalysis.com, the average analyst rating for WIX stock is a "Buy." This suggests a positive sentiment towards the stock amongst market analysts. + +Furthermore, the 12-month stock price forecast for WIX stands at $113.07, indicating an 18.62% increase from the current price. This forecasted increase in stock price suggests a potential for capital gains if the stock were purchased at the current price and sold at the forecasted future price. + +However, it's crucial to note that stock price forecasts are not guaranteed to be accurate. They are often based on financial modeling techniques that incorporate a range of assumptions about the company's future performance and the state of the market. Unforeseen circumstances, such as drastic changes in market conditions or the company's performance, can result in the actual stock price deviating significantly from the forecasted price. + +## Conclusion +Based on the available information, WIX's financial health appears compromised due to its current lack of profitability. However, substantial revenues and significant market capitalization, along with a positive analyst rating and a forecasted increase in stock price, suggest potential for growth and recovery. + +Purchasing WIX stock would therefore involve a degree of risk, particularly due to the company's negative earnings. Investors must weigh this risk against the potential rewards, as suggested by the positive analyst ratings and the forecasted stock price increase. + +This decision should be made in consideration of the investor's individual financial situation, risk tolerance, and investment goals. It's always advisable to conduct further research or consult with a financial advisor before making investment decisions. + +### References +- StockAnalysis.com. WIX. Retrieved from https://stockanalysis.com/stocks/wix/ +- Yahoo Finance. WIX Analysis. Retrieved from https://finance.yahoo.com/quote/WIX/analysis +- MarketBeat. WIX. Retrieved from https://www.marketbeat.com/stocks/NASDAQ/WIX/ +- Yahoo Finance. WIX. Retrieved from https://finance.yahoo.com/quote/WIX +- CNN Money. WIX. 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3c213b7e9aaafe3518397baa4257caa3664a069e Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 30 Sep 2023 11:05:19 +0300 Subject: [PATCH 21/26] modified config params for improved performance --- agent/prompts.py | 8 +++++--- config/config.py | 4 ++-- permchain_example/README.md | 12 +++++++++++- 3 files changed, 18 insertions(+), 6 deletions(-) diff --git a/agent/prompts.py b/agent/prompts.py index 3913fd1ba..98a476b01 100644 --- a/agent/prompts.py +++ b/agent/prompts.py @@ -1,3 +1,4 @@ +from datetime import datetime def generate_agent_role_prompt(agent): """ Generates the agent role prompt. Args: agent (str): The type of the agent. @@ -25,9 +26,10 @@ def generate_report_prompt(question, research_summary): return f'"""{research_summary}""" Using the above information, answer the following'\ f' 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, a minimum of 1,200 words and with markdown syntax and apa format. "\ - "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 in apa format" + " in depth, with facts and numbers if available, a minimum of 1,200 words and with markdown syntax and apa format.\n "\ + "You MUST determine your own concrete and valid opinion based on the given information. Do NOT deter to general and meaningless conclusions.\n" \ + f"Write all used source urls at the end of the report in apa format.\n " \ + f"Assume that the current date is {datetime.now().strftime('%B %d, %Y')}" def generate_search_queries_prompt(question): """ Generates the search queries prompt for the given question. diff --git a/config/config.py b/config/config.py index 1a902bcab..a302d6e61 100644 --- a/config/config.py +++ b/config/config.py @@ -24,8 +24,8 @@ def __init__(self) -> None: self.llm_provider = os.getenv("LLM_PROVIDER", "ChatOpenAI") self.fast_llm_model = os.getenv("FAST_LLM_MODEL", "gpt-3.5-turbo-16k") self.smart_llm_model = os.getenv("SMART_LLM_MODEL", "gpt-4") - self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 4000)) - self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 8000)) + self.fast_token_limit = int(os.getenv("FAST_TOKEN_LIMIT", 2000)) + self.smart_token_limit = int(os.getenv("SMART_TOKEN_LIMIT", 4000)) self.browse_chunk_max_length = int(os.getenv("BROWSE_CHUNK_MAX_LENGTH", 8192)) self.summary_token_limit = int(os.getenv("SUMMARY_TOKEN_LIMIT", 700)) diff --git a/permchain_example/README.md b/permchain_example/README.md index d690da8eb..ab5b71c20 100644 --- a/permchain_example/README.md +++ b/permchain_example/README.md @@ -17,4 +17,14 @@ The research agent (gpt-researcher) is in charge of finding and summarizing rele - Summarize the information into a report - Send the report to the editor agent for validation - Send the report to the reviser agent for revision -- Repeat until the report is satisfactory \ No newline at end of file +- Repeat until the report is satisfactory + +## How to run +1. Install required packages: + ```bash + pip install -r requirements.txt + ``` +2. Run the application: + ```bash + python test.py + ``` \ No newline at end of file From dee3c345848bd654eaf982ce39eb55f81643a986 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 30 Sep 2023 11:07:00 +0300 Subject: [PATCH 22/26] modified stock example --- permchain_example/test.py | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/permchain_example/test.py b/permchain_example/test.py index ab68d7e4f..369ff7797 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -19,7 +19,7 @@ # If the directory does not exist, create it os.makedirs(output_path) - stocks = ["WIX"] + stocks = ["NVDA"] for stock in stocks[:1]: researcher = Researcher(GPTResearcherActor(), WriterActor()) From 8c1c654d31b614683a154e83e9a659fb2218936c Mon Sep 17 00:00:00 2001 From: assafelovic Date: Sat, 30 Sep 2023 11:08:47 +0300 Subject: [PATCH 23/26] modified readme --- permchain_example/README.md | 5 ++++- permchain_example/test.py | 3 ++- 2 files changed, 6 insertions(+), 2 deletions(-) diff --git a/permchain_example/README.md b/permchain_example/README.md index ab5b71c20..f8368ce03 100644 --- a/permchain_example/README.md +++ b/permchain_example/README.md @@ -27,4 +27,7 @@ The research agent (gpt-researcher) is in charge of finding and summarizing rele 2. Run the application: ```bash python test.py - ``` \ No newline at end of file + ``` + +## Usage +To change the research topic, edit the `query` variable in `test.py` to the desired topic. \ No newline at end of file diff --git a/permchain_example/test.py b/permchain_example/test.py index 369ff7797..736a0fd2a 100644 --- a/permchain_example/test.py +++ b/permchain_example/test.py @@ -22,10 +22,11 @@ stocks = ["NVDA"] for stock in stocks[:1]: + query = f"is the stock {stock} a good buy?" researcher = Researcher(GPTResearcherActor(), WriterActor()) research_team = ResearchTeam(researcher, EditorActor(), ReviserActor()) - draft = research_team.run(f"is the stock {stock} a good buy?") + draft = research_team.run(query) with open(f"{output_path}/{stock}.md", "w") as f: f.write(draft) md_to_pdf(f"{output_path}/{stock}.md", f"{output_path}/{stock}.pdf") \ No newline at end of file From b04c57bcf94a68564e7f287deead8259038611b0 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 3 Oct 2023 13:30:30 +0300 Subject: [PATCH 24/26] removed one search query to increase context limit --- agent/prompts.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/agent/prompts.py b/agent/prompts.py index 98a476b01..c8405ced6 100644 --- a/agent/prompts.py +++ b/agent/prompts.py @@ -37,8 +37,8 @@ def generate_search_queries_prompt(question): Returns: str: The search queries prompt for the given question """ - return f'Write 4 google search queries to search online that form an objective opinion from the following: "{question}"'\ - f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3", "query 4"]' + return f'Write 3 google search queries to search online that form an objective opinion from the following: "{question}"'\ + f'You must respond with a list of strings in the following format: ["query 1", "query 2", "query 3"]' def generate_resource_report_prompt(question, research_summary): From c5fb5581f0965e3937bf5f6023eeb15561154237 Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 3 Oct 2023 14:19:48 +0300 Subject: [PATCH 25/26] modified --- processing/text.py | 1 - 1 file changed, 1 deletion(-) diff --git a/processing/text.py b/processing/text.py index cf591aa06..23edef4f1 100644 --- a/processing/text.py +++ b/processing/text.py @@ -46,7 +46,6 @@ def split_text(text: str, max_length: int = 8192) -> Generator[str, None, None]: def summarize_text( url: str, text: str, question: str, driver: Optional[WebDriver] = None ) -> str: - print(question) """Summarize text using the OpenAI API Args: From 03199211931e9d4e05c915ecc1c3220cdeefb43a Mon Sep 17 00:00:00 2001 From: assafelovic Date: Tue, 3 Oct 2023 14:21:01 +0300 Subject: [PATCH 26/26] removed outputs --- permchain_example/output/AAPL.md | 25 -------------------- permchain_example/output/AAPL.pdf | Bin 54863 -> 0 bytes permchain_example/output/AMZN.md | 12 ---------- permchain_example/output/AMZN.pdf | Bin 48722 -> 0 bytes permchain_example/output/NVDA.md | 37 ------------------------------ permchain_example/output/NVDA.pdf | Bin 62373 -> 0 bytes permchain_example/output/WIX.md | 30 ------------------------ permchain_example/output/WIX.pdf | Bin 61110 -> 0 bytes 8 files changed, 104 deletions(-) delete mode 100644 permchain_example/output/AAPL.md delete mode 100644 permchain_example/output/AAPL.pdf delete mode 100644 permchain_example/output/AMZN.md delete mode 100644 permchain_example/output/AMZN.pdf delete mode 100644 permchain_example/output/NVDA.md delete mode 100644 permchain_example/output/NVDA.pdf delete mode 100644 permchain_example/output/WIX.md delete mode 100644 permchain_example/output/WIX.pdf diff --git a/permchain_example/output/AAPL.md b/permchain_example/output/AAPL.md deleted file mode 100644 index 2e8fe7803..000000000 --- a/permchain_example/output/AAPL.md +++ /dev/null @@ -1,25 +0,0 @@ -Revised Draft: - -# Is Apple Inc. (AAPL) a Good Investment? - -## Abstract - -This article aims to evaluate the investment potential of Apple Inc. (AAPL), a leading multinational technology company. The analysis uses financial data from various sources to assess the company's performance, valuation, dividend payments, and recent stock splits. The findings suggest that AAPL stock exhibits promising signs of growth and profitability, making it a potential investment opportunity in the current financial market. - -## Financial Performance - -Apple Inc.'s financial performance has shown consistent growth over recent years. According to StockAnalysis.com, the company reported a revenue of $394.33 billion in 2022, a 7.79% increase from the prior year (StockAnalysis.com, 2022). Additionally, earnings rose by 5.41% to $99.80 billion, further demonstrating the company's financial stability. These figures, coupled with a "Buy" rating from 35 surveyed analysts and a forecasted 13.69% increase in the 12-month stock price, underscore the potential profitability of AAPL stock (StockAnalysis.com, 2022). - -## Valuation Analysis - -StockAnalysis.com's valuation analysis reveals that Apple's market capitalization stands at $2.74 trillion, and its enterprise value is $2.68 trillion (StockAnalysis.com, 2022). The company's trailing and forward P/E ratios are 29.41 and 26.66, respectively. These figures indicate a high market valuation, suggesting investor confidence in Apple's future growth. Furthermore, a ROIC of 38.90% and a WACC of 11.2% indicate that Apple effectively uses its capital to generate profits (StockAnalysis.com, 2022). - -## Dividends and Stock Split - -Apple pays an annual dividend of $0.96 per share, yielding 0.55% (StockAnalysis.com, 2022). This yield, albeit lower than some competitors, signifies Apple's commitment to shareholder returns. - -As for stock splits, Apple's last split occurred in 2020, when it divided each share into four (StockAnalysis.com, 2022). Stock splits can make shares more accessible to individual investors, increasing demand and potentially driving up the stock price. - -## References - -StockAnalysis.com. (2022). Apple Inc. (AAPL) Stock Analysis. 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9a5aa00c0..000000000 --- a/permchain_example/output/AMZN.md +++ /dev/null @@ -1,12 +0,0 @@ -Revised Draft: - -# Amazon Stock: A Quick Investment Analysis - -Amazon Inc. (NASDAQ: AMZN) is a significant player in e-commerce, cloud computing, and artificial intelligence. Its success is mirrored in its strong stock market performance. This brief analysis considers the potential of AMZN stock as an investment. - -Currently, Amazon's stock price is at a new 52-week high (Yahoo Finance, 2021). Analysts predict a 214% earnings increase to $2.23 per share by 2023 (Yahoo Finance, 2021). This could further boost the stock price. In the last 60 days, Amazon's FY23 and FY24 earnings per share estimates rose by 42% and 35% respectively (Yahoo Finance, 2021), indicating positive market sentiment. The Zacks Price Target predicts an 18% stock upside (Yahoo Finance, 2021), suggesting more growth potential. - -Considering its strong performance, promising earnings prospects, and potential upside, AMZN stock appears to be a worthwhile investment. Nonetheless, it's crucial to note the inherent risks of the stock market and the importance of thorough research before investing. - -References -- Yahoo Finance. (2021). Amazon's (AMZN) Stock Keeps Rising. 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@@ -# Is the Stock NVDA a Good Buy? - -The stock market is a complex environment, and making investment decisions requires careful analysis of various factors. This report aims to provide a comprehensive evaluation of NVDA (Nvidia Corporation) as a potential investment, based on the limited information available from the given sources. - -## Overview of NVDA - -NVDA is a multinational technology corporation based in the United States, known primarily for its developments in artificial intelligence and graphics processing units (GPUs). NVDA's innovative technology and dominance in the market have made its stock a subject of interest for many investors. - -## Performance Analysis - -Unfortunately, the URLs provided from Morningstar, Stockanalysis, and the Wall Street Journal do not offer specific data on NVDA's performance in 2021. As such, detailed performance analysis, including aspects such as earnings per share, price-to-earnings ratio, and dividend yield, cannot be provided. - -## Expert Opinions and Future Growth Prospects - -According to information from Investorplace, expert opinions on NVDA's future growth prospects are divided. Critics point to potential challenges related to the company's generative artificial intelligence growth catalyst, including high competition and geopolitical tensions, which could potentially impact demand, margins, and profitability. However, the article argues that Nvidia's premium valuation is justified due to strong demand for AI chips and the company's prospects for high earnings growth in the coming years. It also emphasizes Nvidia's competitive advantage as a provider of AI software and services, suggesting it has a deep moat. - -The website Marketbeat, however, only provides factual information about NVDA's recent earnings results, quarterly dividend, stock split, and third-quarter earnings guidance. The Motley Fool URL does not contain any specific information about expert opinions on NVDA's future growth prospects. - -## Conclusion - -Based on the limited information available, it's difficult to confidently conclude whether NVDA stock is a good buy. The company's strong position in the AI and GPU markets, along with its potential for high earnings growth, suggests that NVDA could be a solid investment. However, potential investors must also consider potential headwinds, such as high competition and geopolitical tensions. - -To make a more informed decision, investors should consider conducting a thorough analysis using comprehensive and up-to-date data, including financial statements and relevant macroeconomic indicators. They should also consider their own investment goals, risk tolerance, and financial situation. - -## References - -Morningstar. (n.d.). NVDA Stock | NVIDIA Stock Price Today | Markets Insider. Retrieved from https://www.morningstar.com/stocks/xnas/nvda/performance - -Stockanalysis. (n.d.). NVDA Stock Price and Chart — NASDAQ:NVDA — TradingView. Retrieved from https://stockanalysis.com/stocks/nvda/ - -The Wall Street Journal. (n.d.). NVDA Stock Price | NVIDIA Corp. Stock Quote (U.S.: Nasdaq) | MarketWatch. Retrieved from https://www.wsj.com/market-data/quotes/NVDA/research-ratings - -Investorplace. (n.d.). Ignore Nvidia Skeptics: Here’s Why NVDA Stock Will Remain a Winner. Retrieved from https://investorplace.com/market360/2023/09/ignore-nvidia-skeptics-heres-why-nvda-stock-will-remain-a-winner/ - -Marketbeat. (n.d.). NVIDIA (NASDAQ:NVDA) Stock Quotes & Market Cap. Retrieved from https://www.marketbeat.com/stocks/NASDAQ/NVDA/ - -The Motley Fool. (n.d.). Where Will Nvidia Be in 5 Years? | The Motley Fool. 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zkN+VP5*5LC`45?>gg7Q(|B#`fNc@LA5fKQQ6o2Xoga1<|a=se;p$7p$!2iY!0f~vB zN%t>3@&D)-y~YXu+bhK@PF!w zf<@4=`Y$~R(7)}8qBmIo#*CJU{2L$I%cAJK_J=*ROzhunAs|uAM&=Ja2pByf{~;5V z_{|>D!wS7U^Eh8G^&I?R82(`rrY-`31fFyIg14%!b_n2k_?@q|o=7VXV0sSsQNdN!< diff --git a/permchain_example/output/WIX.md b/permchain_example/output/WIX.md deleted file mode 100644 index 293bda06f..000000000 --- a/permchain_example/output/WIX.md +++ /dev/null @@ -1,30 +0,0 @@ -# Is WIX a Good Buy? -The evaluation of the viability of a stock as an investment is typically dependent on a multitude of factors including the company's financial health, its place within the competitive market, future prospects, and the current and projected state of the market. This report seeks to assess whether WIX stock is a good buy based on the available information. - -## Analysis of WIX's Financial Health -Wix.com Ltd. (WIX) is a cloud-based web development platform that allows users to create HTML5 websites and mobile sites through the use of online drag and drop tools. The company's revenue generation is primarily from the freemium business model, offering users free website design and hosting, with additional premium features available for purchase. - -According to the information obtained from MarketBeat, the company has a negative earnings per share (EPS) of -$1.10. This indicates that the company is not currently profitable. Furthermore, the company has reported a net loss of -$424,860,000, which further emphasizes the company's current lack of profitability. WIX's negative P/E ratio of -86.65 is a reflection of these negative earnings. - -That being said, the company's market capitalization stands at $5.41 billion, with revenues amounting to $1.39 billion. These figures reveal that despite its current lack of profitability, the company is generating substantial revenues and holds a significant place within the market. Moreover, WIX's global workforce of 4,742 employees indicates a large scale operation. - -## Analyst Opinions and Stock Forecasts -According to the information obtained from StockAnalysis.com, the average analyst rating for WIX stock is a "Buy." This suggests a positive sentiment towards the stock amongst market analysts. - -Furthermore, the 12-month stock price forecast for WIX stands at $113.07, indicating an 18.62% increase from the current price. This forecasted increase in stock price suggests a potential for capital gains if the stock were purchased at the current price and sold at the forecasted future price. - -However, it's crucial to note that stock price forecasts are not guaranteed to be accurate. They are often based on financial modeling techniques that incorporate a range of assumptions about the company's future performance and the state of the market. Unforeseen circumstances, such as drastic changes in market conditions or the company's performance, can result in the actual stock price deviating significantly from the forecasted price. - -## Conclusion -Based on the available information, WIX's financial health appears compromised due to its current lack of profitability. However, substantial revenues and significant market capitalization, along with a positive analyst rating and a forecasted increase in stock price, suggest potential for growth and recovery. - -Purchasing WIX stock would therefore involve a degree of risk, particularly due to the company's negative earnings. Investors must weigh this risk against the potential rewards, as suggested by the positive analyst ratings and the forecasted stock price increase. - -This decision should be made in consideration of the investor's individual financial situation, risk tolerance, and investment goals. It's always advisable to conduct further research or consult with a financial advisor before making investment decisions. - -### References -- StockAnalysis.com. WIX. Retrieved from https://stockanalysis.com/stocks/wix/ -- Yahoo Finance. WIX Analysis. Retrieved from https://finance.yahoo.com/quote/WIX/analysis -- MarketBeat. WIX. Retrieved from https://www.marketbeat.com/stocks/NASDAQ/WIX/ -- Yahoo Finance. WIX. Retrieved from https://finance.yahoo.com/quote/WIX -- CNN Money. WIX. 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