Autogen Agents with RAG - Upgrading Agents with a Knowledge Base
Summary
TLDR视频介绍了如何使用自动生成框架Autogen进行知识检索,以提高工作流程的效率。通过向GPT模型提供特定上下文,可以生成更个性化和针对性的内容。以向QI团队发送电子邮件为例,展示了在提供公司背景信息后,GPT能够生成更具体和相关的邮件内容。视频还提到了使用Chrome扩展和AI代码助手来提高编程效率,以及如何通过Autogen框架进行自动化服务的推广。
Takeaways
- 📚 使用Autogen框架进行知识检索是提升工作流程的关键更新。
- 🔍 知识驱动(RAG)通过在提示中添加更多数据或上下文,帮助利用新知识或特定知识完成任务。
- 📧 在写给特定公司的电子邮件中,提供公司相关信息可以避免内容过于通用。
- 🤖 GPT-4由于知识截止日期的限制,可能无法准确了解新出现的公司或平台。
- 📈 通过Autogen的检索代理,可以从QI的GitHub仓库中提取数据,以改善生成的电子邮件内容。
- 🔗 利用Autogen的Gab仓库中的笔记本和示例,可以启发不同的用例。
- 🛠️ 使用Chrome扩展和AI代码助手可以提高代码理解和问题解答的效率。
- 📝 在自动化服务的电子邮件中,个性化和展示对项目的理解是关键。
- 🔄 通过对比使用和不使用RAG的电子邮件,可以看出知识检索对内容质量的影响。
- 📊 知识检索(RAG)可以显著提高AI框架在特定任务中的性能。
- 📌 通过优化提示和系统消息,可以进一步提升自动化框架在创建个性化内容方面的潜力。
Q & A
什么是RAG(Retrieval-Augmented Generation)?
-RAG是一种结合了检索和生成的技术,它通过在生成过程中引入外部知识源(如数据库或网页)来增强模型的知识库和生成质量。
在脚本中,如何使用RAG来改进GPT-4的输出?
-通过在提示中添加关于特定公司或主题的额外内容,RAG可以帮助GPT-4生成更具体、更准确的信息,而不是仅仅基于其内部知识库生成通用内容。
脚本中提到的Autogen是什么?
-Autogen是一个框架,用于构建和部署基于GPT-3的应用程序。它提供了一套工具和库,使得开发者能够更容易地利用GPT-3的能力。
脚本中提到的QI是什么?
-QI是一个平台,旨在通过利用AI来提高销售和客户服务团队的生产力。它通过自动化数据录入和分析等任务,帮助团队更专注于与客户互动和完成交易。
脚本中提到的GPT-4在没有额外上下文的情况下对QI的了解如何?
-GPT-4在没有额外上下文的情况下,对QI的了解非常有限,可能会基于其内部知识库生成一些基于猜测的内容。
脚本中提到的Chrome扩展是什么?
-脚本中提到的Chrome扩展是一个名为“继续”(Continue)的AI代码助手,它可以帮助用户在编写代码时提供智能建议和帮助。
脚本中提到的自动化服务是什么?
-自动化服务指的是使用技术(如AI和RPA工具)来简化和自动化业务流程,以提高效率和生产力。
脚本中提到的个性化电子邮件的目的是什么?
-个性化电子邮件的目的是向收件人展示发件人对他们的了解和关注,从而提高回应率和建立更好的客户关系。
脚本中提到的CMO在团队中的角色是什么?
-CMO(首席营销官)在团队中负责市场营销策略的制定和执行,专注于市场定位、品牌建设和推广活动。
脚本中提到的自动化服务如何与QI团队的工作集成?
-自动化服务可以与QI团队的工作集成,通过提供先进的自动化解决方案,帮助他们优化开发和生产流程,提高AI代理的工作效率。
Outlines
🔍 知识检索与自动生成的结合
介绍了在特定工作流中使用自动生成(Autogen)框架的重要性。通过向提示中添加更多数据或上下文,可以利用新知识或特定知识来完成特定任务。例如,向GPT模型提供关于新公司的额外信息,以便生成针对性的电子邮件。视频展示了如何使用知识检索在Autogen中,以及如何通过提供更多上下文来改善GPT模型的输出。
📝 代码实现与应用
讨论了如何通过代码实现知识检索,以及如何将检索到的信息应用于自动化工作流。提到了一个名为“继续”的Chrome扩展,它是一个AI代码助手,可以帮助理解和测试代码。视频还展示了如何使用Autogen框架来构建一个销售和营销用例,以及如何通过提供GitHub仓库的URL来让检索代理获取信息。
📧 自动化服务的电子邮件撰写
展示了如何使用代理框架来撰写一封针对QI团队的自动化服务推销电子邮件。邮件的撰写过程包括了多个角色,如老板、助理、高级撰稿人和首席营销官,他们各自有不同的任务和目标。视频还比较了使用和不使用知识检索(RAG)时的电子邮件撰写效果,以及如何通过提供正确的提示和指导来改善输出。
📩 电子邮件内容的比较与分析
分析了在没有使用知识检索(RAG)的情况下,GPT模型生成的电子邮件内容。指出了邮件内容的不足之处,如缺乏个性化和对QI项目的了解。然后,展示了在提供QI项目上下文后,GPT模型如何生成更准确和个性化的电子邮件。视频还提到了如何通过比较QI与其他代理框架来增强邮件的说服力。
🚀 利用RAG提升自动化服务
强调了在自动化服务中利用知识检索(RAG)的重要性。通过实际案例,展示了如何通过RAG来提升电子邮件的个性化程度和效果。视频还提到了如何通过更好的提示和系统消息来优化代理框架,以及如何通过这种方式来实现大规模的个性化。
📢 订阅频道与持续自动化
视频最后,鼓励观众订阅频道以获取更多关于自动化和代理框架的视频。同时,提出了对视频内容的反馈和建议,以及如何通过观众的反馈来优化和改进视频内容。
Mindmap
Keywords
💡知识检索
💡Autogen
💡上下文
💡GPT
💡自动化服务
💡个性化
💡角色扮演
💡开源开发
💡AI代理
💡工作流程自动化
Highlights
知识检索与自动生成(Autogen)是任何工作流程中的关键且可行的更新或升级。
RAG(Retrieval-Augmented Generation)或知识驱动,基本上是将更多数据或上下文引入提示中,以便利用新知识或特定知识完成特定任务。
例如,如果你想给一个新公司写电子邮件,而这个公司在C GPT中找不到,你可以在提示中添加关于公司的内容。
如果不提供关于Qi的更多上下文,生成的电子邮件将会非常通用。
视频展示了如何在Autogen中使用知识检索。
GPT-4由于知识截止日期在Qi推出之前,所以不知道Qi是什么,可能会基于上下文写出一些不准确的内容。
通过Autogen的检索代理从Qi的GitHub仓库中拉取数据,可以生成更好的电子邮件,因为它能够理解上下文。
Autogen gab仓库提供了许多不同用例的笔记本,这些笔记本包含了许多示例。
展示了如何使用Autogen中的检索代理来拉取Qi GitHub仓库的数据。
代码示例展示了如何构建一个团队,包括老板、检索代理、文案和高级文案,以及CMO(首席营销官)。
目标是向Qi团队发送一封个性化的冷邮件,展示对他们所做工作的了解。
在没有RAG的情况下,团队可能会生成一个通用的电子邮件。
使用RAG时,电子邮件会更加个性化,因为它包含了从Qi GitHub仓库中检索到的上下文。
展示了如何使用Autogen框架来创建个性化的电子邮件,而不是使用RPA(Robotic Process Automation)工具。
强调测试代理框架的潜力,而不使用RPA工具,以查看仅使用代理框架的潜力。
展示了如何使用Autogen框架来创建个性化的电子邮件,而不是使用RPA工具。
讨论了如何通过更好的提示和系统消息来优化代理框架。
视频最后邀请观众订阅频道,以便获取有关自动化和代理的更多视频。
Transcripts
knowledge retrieval with autogen this is
a crucial and viable update or upgrade
for any of your workflows when you're
using a gentic Frameworks specifically
autogen for those of you who don't know
what is rag or knowledge drival is
basically pulling more data or more
context into the prompt allowing you to
leverage mostly a new knowledge or
specific specific knowledge for the
specific tasks so for example let's say
I would like to
write an
email to a specific company and this
company um is a new company that you
can't find in C GPT so what you can do
you can add content about the company in
the
prompt and let's say you write provide
to me a c email for to the company cre a
I so you provide it in the prompt and
then CH GPT will write the specific C
email to this company in this instance
Qi but if you didn't provide more
context about
Qi the email would be pretty generic so
in this video I'm going to show you how
I'm using knowledge knowledge retrieval
in autogen wow I feel Rusty I didn't
upload a video a few days ago when my
speaking kind of sucks but bear with me
because this is a very interesting use
case so let's just
cover a few things so before we dive in
I want to show you that CH GPT doesn't
know at the moment what is Q AI can you
write for me an email
about crew
AI do you know what is clue AI so it
will probably just write
BS so Qi let's see Qi is a platform
designed to enhance sales and customer
service teams productivity by leveraging
AI it assists in automating various
tasks such as data entry and Analysis
enabling teams to focus more on engaging
with customers and closing deals Qi
typically
integrates with existing crm's
communication tools to provide
actionable insights Coach sales rep
Etc so you can see um the llm in this
specific case GPT
4 since its knowledge cut off was before
the launching of Qi it doesn't know what
Q is it does H write some BS based on
its understanding from the context
because he sees okay a name which is Qi
so it thinks okay it's Pro it's possibly
a platform leveraging artificial
intelligence which is correct in this
case but it's not good enough so let's
say I want to write an email to the quii
team I have to feed CH GPT or anting an
agentic framework that I'm leveraging I
have to feed it with the
knowledge of what is Qi so basically
what I did and I'll show with I'll show
you the code in a moment I used the
retrieval agent in autogen to pull data
from the QI GitHub repository and then
see
if the email that I generated was better
because it was able to understand the
context by the way the whole idea is a
spin-off from the
autogen gab repository and they have
here over here they have many notebooks
and these notebooks contain many
examples of different use
cases obviously I'm not just copying and
pasting this and I'm using these
examples as in inspiration to what I'm
trying to build and this use case is
focused is more like a sales SL
marketing use case now let's dive into
the
code uh one more quick update by the way
I told you a few weeks ago I I showed
you to those of you who are
following the channel I showed you this
Chrome extension which is called
continue not a Chrome extension it's a
visual
code extension which is basically an AI
code assistant I plugged into it dolphin
mistal which is a model that is
supported by orama and it has been
working pretty well so far so I'm using
it to ask it many questions about the
repository about the code just testing
it around to see exactly what go what's
what it's understanding what doesn't
understand you can check out the video
specifically that I did about this uh
visual code extension a few days ago but
it's pretty cool so far so good I'm
pretty happy about
it now let's uh take a look into the
code I won't cover the installation you
know my Moto this channel isn't about
installations it's about applications
and
implementations but in general we
have a crew that consists of a boss the
boss assistant which is a retrieval
agent an assistant who has extra cont
content retrieval power for solving
difficult
problems and we are providing him with
the URL in this case the
URL the knowledge base is the the GitHub
repository of Qi let me show you the the
content you can see over here you guys
are probably familiar with it if you've
been following the agent space so you
probably know about Qi so they have
information over here Qi is a Cutting
Edge framework for all Orest rating role
playing autonomous a autonomous AI by
fostering coll collaborative
intelligence Qi empowers agents to work
together seamlessly tackling complex
tasks and they have a ton of information
about y AI why is it better than Chad
Dev which I don't know nobody's talking
about I mean based on my observation
nobody's talking that much about Chad
Dev lately but I need to if you guys
seen anything else so let me know but I
I'll definitely check out the repository
afterwards and see if I'm correct or not
and this is a comparison to autogen
never mind so basically this code is
going to pull the
content of this page so let's go back to
visual studio code so we have the boss
we have the boss assistant which is a
retrieval agent and as you can see it is
pulling let's see if I can make this
larger
let's close this
guy yes
and so we have the retrieval agent we
have the
copywriter and I gave it the system
message you are a witty and bold
copywriter specializing in writing short
and perspective called
emails we have the senior
copywriter and the system messages you
are a senior copywriter you specialize
in providing constructive feedback to to
copy of copy maybe and we have the CMO
you are a CMO specializing in marketing
copyrighting and understanding the
prospect mindset and the whole goal over
in this instance
is to send a Cod email to the QI team
show them that we know what they are
doing so personalizing the Reach
Out
you can see over here so the
problem basically the prompt for the
group is write a short called email to
the QI team pitching Automation Services
so I'm providing Automation Services and
let's assume that I want to pitch the QI
team start with a hook then make sure to
show them your knowledge of the project
and then add a CTA suggesting suggest
thing a quick call also write two
follow-ups in case they don't answer the
third follow-up should be a standalone
email that will be sent to the founder
of the project offering him to come to
be a podcast a guest on on the
podcast now the reason the reason why I
wanted to build this workflow which we
using
rag because in the past if you guys have
been following me and by the way this
may be a
good um opportunity to tell you that I
invite you to subscribe to the channel
if you enjoy videos about Automation and
agent and you haven't subscribed yet
please make sure to
subscribe I usually drop this H plug or
this request to subscribe at the end of
the video but my wife told me I should
do it at the beginning this is not the
beginning it's like halfway through or
maybe even more but next time I'll
probably remember to do it um at the
beginning anyway
so the whole idea here
in opposing to other videos in which I
automated a
workflow of personalizing a DM in
Facebook or LinkedIn based on what I
scraped
from the prospects profile which is also
a viable um
Modi like you can do that H what I
wanted to do to see here if I can use
only the agentic framework in opposing
to what I did in the past
which was basically using an RPA tool
Microsoft power automate to scrape the
data and then fit it as
context to
gp4 and in the prompt it had the context
about the prospect so this is slightly
different workflow and the main reasons
for doing this is first of all
I'm I want to create videos and
tutorials that are not using necessary
RPA tools and like doing the whole
workflow from a to zed using Python and
the second reason is I want to stress
test um the agentic Frameworks because I
want to see I'm pretty pretty
straightforward I want to see the
potential of using agentic Frameworks
without using RPA
tools which yeah they do they do allow
us more control but at end of day the
whole goal of using an AIC framework and
my vision and hopefully other people
Vision in the space is using agents to
streamline the whole process and
automate more parts of the process
instead of using an RPA tool which
basically we create and control the
workflow and just use the ating
framework or the GPT in only certain
instances well I've been talking a lot
let me take a sip of water
Okay cool
so I showed you the The Prompt for the
team we've
created and the boss the boss assistant
the copywriter the senior copywriter and
the
CMO now we have two um different
instances
one is an instance with no rag we will
just send the prompt and these are the
agents and there is another chat another
instance in which we also share um the
context so as you can see over here we
have the boss Aid which is the retrieval
agent the CMO the copywriter and the
senior
copywriter
and there is a distinction between both
chats because one we have print line
message rag chat and the other one
contains the no rag tag so I already run
this code let me go up to show you the
results
okay let's do this again
it will be better let's see if I I can
also let me just adjust the prompt to
make it more
interesting
um
special let's see what we can
adjust also WR two follow-ups in this
case write a short call email to quii
team pitching Automation Services start
with a to start with a hook then make
sure to show them your knowledge of the
project try to
comp lement them on
their
unique
this compare
them to a
competitor okay comparing them to a
competitor and this is something that
only if if you take a look in this
page you will know the difference
between Qi and the other agentic
Frameworks so when we are not going to
use the rag there is no
way that uh the output is going to be
correct now let's run this code and see
what happen in in both instances again
one instance we have no
rag the chat team has no idea what is Qi
they're probably going to BS and the
other team does know what is Qi because
we have the retrieval agent and he's
pulling
data okay so as you can see over
here write a short Cod email to the quii
team pitching Automation Services start
with a hook then make sure to show them
your knowledge of the project try to
complement them on their
uniqueness comp compare them to the
competitor and then add a c ta
suggesting suggesting wow a quick
call
okay this is the first one email One
initial called email to the qu AI team
transforming the future of work with CI
hey CI team hope this finds you well
I've been closely following your journey
and I'm genuinely impressed by how
you're redefining productivity tools in
the workspace okay you can see it's it's
incorrect but still it is somewhat
compelling and can be relevant no
probably not relevant but it is pretty
generic but not so far off so it's clear
you're not just another player in the
game you're setting new standards much
like how Tesla reimagined the electric
car okay nice analogy your unique
approach to integrating AI into everyday
work tool is nothing short of
revolutionary it's evident that Qi is on
the path on becoming an indispensable
asset for business aiming to stay ahead
of the curve okay that's good that said
I believe there's an untapped potential
in further automating your processes
enhancing efficiencies and scaling your
impact our team specializes in B spoke
automation solutions that could
seamlessly integrate with your existing
Frameworks propelling kui to new heights
how about a quick call next week to
explore how we can collaborate sorry
about that how we can collaborate to
make work even smarter
I'm confident we can add significant
value to your already impressive Suite
of
tools looking forward now follow up if
no response in three or four days let's
make magic happen at Qi hey Qi team just
floating to the top of your inbox in
case my previous email got buried Buried
buried I'm still super excited about the
possibility of bringing our automation
expertise to complement kui Innovative
platform
can we find 15 minutes this week for a
chat I have a few ideas that I believe
could really amplify your
impact second followup quick ping hey qu
team I understand you you're swamped
with making a work the workspace a
better place so I'll keep this brief
steing on blah blah blah let's move
on this is the Standalone email to the
founder dear Founder's name I've been an
admirer of Qi and your Visionary
leadership in transforming how we
approach prod activity tools your
journey is a beacon of for Innovation
much like how pioneers reshape
Industries this is correct I host a
podcast that spotlights thought leaders
and disruptors who are making
significant waves in their sectors
okay now um so this was the no rag chat
obviously not not obviously but as you
can see over here and first of all the
pumpt for the cold email wasn't good
enough so I didn't Pro
provide
um enough examples perhaps and also good
enough guidance to the
copywriter and so it was too long but in
general I do like this is way too long
but in general I like the I somewhat
like the content but so this is one
thing that obviously needs to be
improved like the specific promp prompt
and as you can see over here the group
chat basically doesn't exist so only the
copywriter
answered now let's move on to the
rug so as you can see over here in
opping to the
first um process that has no rug over
here
automatically autogen is
creating the knowledge base so it is
fetch fetching the data from the URL
that we provided which is the GitHub
repository of
crei and now it it created a few
documents and now you can see the boss
assistant to the chat manager so you
retrieve augmented coding assistant your
answers blah blah blah this is a a bit
of
um
information now the user question is
write a short IM to the qu I team
pitching Automation Services start with
the hook then make sure to show your
knowledge try to complement them you
know this
already now he is adding and this is the
rag the context is and it is basically
scraped the page from Qi let's open
it
scraped the context roles of agents in a
crew this just looks like a lot of text
to you guys but as you can see over here
let's see what
happened okay elevate your AI crew with
tailor Automation Services this is the
message tailor to the QI team that
already is supposed to know the context
let's see what is the
difference I hope this message finds you
well I've been closely following your
journey in orchestrating role playing
autonomous AI agents and I must say your
framework is nothing short of
revolutionary the way Qi empowers agents
to collaborate and Tackle complex task
is a game changer setting you apart from
competitors like autogen and ched Dev
yes baby this is exactly what we wanted
so you can see took this
context
and he it also took this how I compar it
name dropped the
correct competitors now let's see
because we are using GPT 4 let's see
just making sure to see if it knows what
our autogen and ched Dev so do you know
do you know the
names of the
QI of qu
eyes
competitors Ki operates in the r of AI
power la la la so it
is offering stuff that I don't even know
but it's obviously incorrect great now
let's move back to the email I hope this
message find you well we covered that
already while your approach offers
unparalleled flexibility and ad an
adaptability I believe our Automation
Services can further enhance your
project efficiency and scalability our
expertise in integrating Advanced
automations solutions could streamline
your development and production
workflows ensuring your AI crew Crews
operate as their Peak
potential I'm particularly impressed
with your commitment to open source
development and the community-driven
enhancement that have prop propelled Qi
forward it's clear that your project is
not just about technology
not just about technology it's about
building a future where AI can work
alongside humans
seamlessly would you be open to a brief
chat okay call to action let's move on
to the next email quick followup hi I
just wanted to quickly follow up on my
previous email I understand you're
incredibly busy but I truly believe
thato let's see if there is anything
specific to
Qi nothing specific okay but because I
didn't um guide the second followup the
first followup to be specific to
kui now another email last try can we
help KU I saw I
realize also over here nothing
specific now let's see the message to
the
founder I've been deeply inspired by
your work with Quan the groundbreaking
strides you're making in the realm of
autonomous AI agents your vision for a
future where Ai and humans collaborate
seamlessly is not only Innovative but
essential I host a podcast blah blah
blah and that is pretty much
it
so let's go back to the wide screen
because it just looks
better I let's go back here as
background Qi although it's it's kind of
funny because I've used
autogen in the whole video and the video
was about approaching the QI a team or
founder but it was just a a simple a
simple example of how we can leverage
rag in h an ating framework in this
specific case it was
autogen I very happy about the results I
believe that with slightly better
prompts and better system messages for
each one of the agents this could be
very valuable because it basically um
will allow us to create
personalization at
scale obviously there are many other use
cases and instances in which you can
leverage uh retrieval Rags or knowledge
bases but this is what just a a simple
example of how we can leverage it for
creating
personalization um I guess that's it for
today guys if you enjoy the video like
always please leave a comment below I'm
happy to hear any feedback any
suggestions for more videos any
suggestions how these videos can become
more interesting more impactful please
let me know in the comment section
always happy to learn and optimize and
improve um regardless again if you
haven't subscribed yet please do and I
guess that's it until next time keep on
automating
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