georgesh
2 months ago
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|||||||
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# Framework Configuration
|
||||||
WORKSPACE_DIR="agent_workspace"
|
WORKSPACE_DIR="agent_workspace"
|
||||||
|
SWARMS_VERBOSE_GLOBAL="False"
|
||||||
SWARMS_API_KEY=""
|
SWARMS_API_KEY=""
|
||||||
USE_TELEMETRY=True
|
|
||||||
OPENAI_API_KEY="sk-"
|
# Model Provider API Keys
|
||||||
GOOGLE_API_KEY=""
|
## OpenAI
|
||||||
AI21_API_KEY="your_api_key_here"
|
OPENAI_API_KEY=""
|
||||||
COHERE_API_KEY="your_api_key_here"
|
|
||||||
ALEPHALPHA_API_KEY="your_api_key_here"
|
## Anthropic
|
||||||
HUGGINFACEHUB_API_KEY="your_api_key_here"
|
ANTHROPIC_API_KEY=""
|
||||||
EVAL_PORT=8000
|
|
||||||
MODEL_NAME="gpt-4"
|
## Google
|
||||||
USE_GPU=True
|
GEMINI_API_KEY=""
|
||||||
PLAYGROUND_DIR="examples"
|
|
||||||
LOG_LEVEL="INFO"
|
## Hugging Face
|
||||||
BOT_NAME="Orca"
|
HUGGINGFACE_TOKEN=""
|
||||||
HF_API_KEY="your_huggingface_api_key_here"
|
|
||||||
|
## Perplexity AI
|
||||||
|
PPLX_API_KEY=""
|
||||||
|
|
||||||
|
## AI21
|
||||||
|
AI21_API_KEY=""
|
||||||
|
|
||||||
|
# Tool Provider API Keys
|
||||||
|
## Search Tools
|
||||||
|
BING_BROWSER_API=""
|
||||||
|
BRAVESEARCH_API_KEY=""
|
||||||
|
TAVILY_API_KEY=""
|
||||||
|
YOU_API_KEY=""
|
||||||
|
|
||||||
|
## Analytics & Monitoring
|
||||||
AGENTOPS_API_KEY=""
|
AGENTOPS_API_KEY=""
|
||||||
ANTHROPIC_API_KEY="your_anthropic_api_key"
|
EXA_API_KEY=""
|
||||||
AZURE_OPENAI_ENDPOINT="your_azure_openai_endpoint"
|
|
||||||
AZURE_OPENAI_DEPLOYMENT="your_azure_openai_deployment"
|
## Browser Automation
|
||||||
OPENAI_API_VERSION="your_openai_api_version"
|
MULTION_API_KEY=""
|
||||||
AZURE_OPENAI_API_KEY="your_azure_openai_api_key"
|
|
||||||
AZURE_OPENAI_AD_TOKEN="your_azure_openai_ad_token"
|
## Other Tools
|
||||||
|
HCP_APP_ID=""
|
||||||
|
|
||||||
|
# Cloud Provider Configuration
|
||||||
|
## Azure OpenAI
|
||||||
|
AZURE_OPENAI_ENDPOINT=""
|
||||||
|
AZURE_OPENAI_DEPLOYMENT=""
|
||||||
|
OPENAI_API_VERSION=""
|
||||||
|
AZURE_OPENAI_API_KEY=""
|
||||||
|
AZURE_OPENAI_AD_TOKEN=""
|
||||||
|
|||||||
@ -1,661 +1,201 @@
|
|||||||
GNU AFFERO GENERAL PUBLIC LICENSE
|
Apache License
|
||||||
Version 3, 19 November 2007
|
Version 2.0, January 2004
|
||||||
|
http://www.apache.org/licenses/
|
||||||
Copyright (C) 2007 Free Software Foundation, Inc. <https://fsf.org/>
|
|
||||||
Everyone is permitted to copy and distribute verbatim copies
|
TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
|
||||||
of this license document, but changing it is not allowed.
|
|
||||||
|
1. Definitions.
|
||||||
Preamble
|
|
||||||
|
"License" shall mean the terms and conditions for use, reproduction,
|
||||||
The GNU Affero General Public License is a free, copyleft license for
|
and distribution as defined by Sections 1 through 9 of this document.
|
||||||
software and other kinds of works, specifically designed to ensure
|
|
||||||
cooperation with the community in the case of network server software.
|
"Licensor" shall mean the copyright owner or entity authorized by
|
||||||
|
the copyright owner that is granting the License.
|
||||||
The licenses for most software and other practical works are designed
|
|
||||||
to take away your freedom to share and change the works. By contrast,
|
"Legal Entity" shall mean the union of the acting entity and all
|
||||||
our General Public Licenses are intended to guarantee your freedom to
|
other entities that control, are controlled by, or are under common
|
||||||
share and change all versions of a program--to make sure it remains free
|
control with that entity. For the purposes of this definition,
|
||||||
software for all its users.
|
"control" means (i) the power, direct or indirect, to cause the
|
||||||
|
direction or management of such entity, whether by contract or
|
||||||
When we speak of free software, we are referring to freedom, not
|
otherwise, or (ii) ownership of fifty percent (50%) or more of the
|
||||||
price. Our General Public Licenses are designed to make sure that you
|
outstanding shares, or (iii) beneficial ownership of such entity.
|
||||||
have the freedom to distribute copies of free software (and charge for
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|
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them if you wish), that you receive source code or can get it if you
|
"You" (or "Your") shall mean an individual or Legal Entity
|
||||||
want it, that you can change the software or use pieces of it in new
|
exercising permissions granted by this License.
|
||||||
free programs, and that you know you can do these things.
|
|
||||||
|
"Source" form shall mean the preferred form for making modifications,
|
||||||
Developers that use our General Public Licenses protect your rights
|
including but not limited to software source code, documentation
|
||||||
with two steps: (1) assert copyright on the software, and (2) offer
|
source, and configuration files.
|
||||||
you this License which gives you legal permission to copy, distribute
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and/or modify the software.
|
"Object" form shall mean any form resulting from mechanical
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transformation or translation of a Source form, including but
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A secondary benefit of defending all users' freedom is that
|
not limited to compiled object code, generated documentation,
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|
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receive widespread use, become available for other developers to
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incorporate. Many developers of free software are heartened and
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"Work" shall mean the work of authorship, whether in Source or
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encouraged by the resulting cooperation. However, in the case of
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Object form, made available under the License, as indicated by a
|
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software used on network servers, this result may fail to come about.
|
copyright notice that is included in or attached to the work
|
||||||
The GNU General Public License permits making a modified version and
|
(an example is provided in the Appendix below).
|
||||||
letting the public access it on a server without ever releasing its
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|
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source code to the public.
|
"Derivative Works" shall mean any work, whether in Source or Object
|
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form, that is based on (or derived from) the Work and for which the
|
||||||
The GNU Affero General Public License is designed specifically to
|
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|
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ensure that, in such cases, the modified source code becomes available
|
represent, as a whole, an original work of authorship. For the purposes
|
||||||
to the community. It requires the operator of a network server to
|
of this License, Derivative Works shall not include works that remain
|
||||||
provide the source code of the modified version running there to the
|
separable from, or merely link (or bind by name) to the interfaces of,
|
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users of that server. Therefore, public use of a modified version, on
|
the Work and Derivative Works thereof.
|
||||||
a publicly accessible server, gives the public access to the source
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|
||||||
code of the modified version.
|
"Contribution" shall mean any work of authorship, including
|
||||||
|
the original version of the Work and any modifications or additions
|
||||||
An older license, called the Affero General Public License and
|
to that Work or Derivative Works thereof, that is intentionally
|
||||||
published by Affero, was designed to accomplish similar goals. This is
|
submitted to Licensor for inclusion in the Work by the copyright owner
|
||||||
a different license, not a version of the Affero GPL, but Affero has
|
or by an individual or Legal Entity authorized to submit on behalf of
|
||||||
released a new version of the Affero GPL which permits relicensing under
|
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|
||||||
this license.
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means any form of electronic, verbal, or written communication sent
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|
to the Licensor or its representatives, including but not limited to
|
||||||
The precise terms and conditions for copying, distribution and
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communication on electronic mailing lists, source code control systems,
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and issue tracking systems that are managed by, or on behalf of, the
|
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|
Licensor for the purpose of discussing and improving the Work, but
|
||||||
TERMS AND CONDITIONS
|
excluding communication that is conspicuously marked or otherwise
|
||||||
|
designated in writing by the copyright owner as "Not a Contribution."
|
||||||
0. Definitions.
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|
||||||
|
"Contributor" shall mean Licensor and any individual or Legal Entity
|
||||||
"This License" refers to version 3 of the GNU Affero General Public License.
|
on behalf of whom a Contribution has been received by Licensor and
|
||||||
|
subsequently incorporated within the Work.
|
||||||
"Copyright" also means copyright-like laws that apply to other kinds of
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|
||||||
works, such as semiconductor masks.
|
2. Grant of Copyright License. Subject to the terms and conditions of
|
||||||
|
this License, each Contributor hereby grants to You a perpetual,
|
||||||
"The Program" refers to any copyrightable work licensed under this
|
worldwide, non-exclusive, no-charge, royalty-free, irrevocable
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License. Each licensee is addressed as "you". "Licensees" and
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copyright license to reproduce, prepare Derivative Works of,
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"recipients" may be individuals or organizations.
|
publicly display, publicly perform, sublicense, and distribute the
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|
Work and such Derivative Works in Source or Object form.
|
||||||
To "modify" a work means to copy from or adapt all or part of the work
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|
||||||
in a fashion requiring copyright permission, other than the making of an
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3. Grant of Patent License. Subject to the terms and conditions of
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exact copy. The resulting work is called a "modified version" of the
|
this License, each Contributor hereby grants to You a perpetual,
|
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earlier work or a work "based on" the earlier work.
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worldwide, non-exclusive, no-charge, royalty-free, irrevocable
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||||||
|
(except as stated in this section) patent license to make, have made,
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||||||
A "covered work" means either the unmodified Program or a work based
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use, offer to sell, sell, import, and otherwise transfer the Work,
|
||||||
on the Program.
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where such license applies only to those patent claims licensable
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by such Contributor that are necessarily infringed by their
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To "propagate" a work means to do anything with it that, without
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Contribution(s) alone or by combination of their Contribution(s)
|
||||||
permission, would make you directly or secondarily liable for
|
with the Work to which such Contribution(s) was submitted. If You
|
||||||
infringement under applicable copyright law, except executing it on a
|
institute patent litigation against any entity (including a
|
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computer or modifying a private copy. Propagation includes copying,
|
cross-claim or counterclaim in a lawsuit) alleging that the Work
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distribution (with or without modification), making available to the
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or a Contribution incorporated within the Work constitutes direct
|
||||||
public, and in some countries other activities as well.
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or contributory patent infringement, then any patent licenses
|
||||||
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granted to You under this License for that Work shall terminate
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||||||
To "convey" a work means any kind of propagation that enables other
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as of the date such litigation is filed.
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||||||
parties to make or receive copies. Mere interaction with a user through
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a computer network, with no transfer of a copy, is not conveying.
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4. Redistribution. You may reproduce and distribute copies of the
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Work or Derivative Works thereof in any medium, with or without
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An interactive user interface displays "Appropriate Legal Notices"
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modifications, and in Source or Object form, provided that You
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to the extent that it includes a convenient and prominently visible
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meet the following conditions:
|
||||||
feature that (1) displays an appropriate copyright notice, and (2)
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tells the user that there is no warranty for the work (except to the
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(a) You must give any other recipients of the Work or
|
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extent that warranties are provided), that licensees may convey the
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Derivative Works a copy of this License; and
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work under this License, and how to view a copy of this License. If
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the interface presents a list of user commands or options, such as a
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(b) You must cause any modified files to carry prominent notices
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menu, a prominent item in the list meets this criterion.
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stating that You changed the files; and
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1. Source Code.
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(c) You must retain, in the Source form of any Derivative Works
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that You distribute, all copyright, patent, trademark, and
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The "source code" for a work means the preferred form of the work
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attribution notices from the Source form of the Work,
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for making modifications to it. "Object code" means any non-source
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excluding those notices that do not pertain to any part of
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form of a work.
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the Derivative Works; and
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A "Standard Interface" means an interface that either is an official
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(d) If the Work includes a "NOTICE" text file as part of its
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standard defined by a recognized standards body, or, in the case of
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distribution, then any Derivative Works that You distribute must
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interfaces specified for a particular programming language, one that
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include a readable copy of the attribution notices contained
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is widely used among developers working in that language.
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within such NOTICE file, excluding those notices that do not
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pertain to any part of the Derivative Works, in at least one
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The "System Libraries" of an executable work include anything, other
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as part of the Derivative Works; within the Source form or
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packaging a Major Component, but which is not part of that Major
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documentation, if provided along with the Derivative Works; or,
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Component, and (b) serves only to enable use of the work with that
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within a display generated by the Derivative Works, if and
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Major Component, or to implement a Standard Interface for which an
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wherever such third-party notices normally appear. The contents
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implementation is available to the public in source code form. A
|
of the NOTICE file are for informational purposes only and
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"Major Component", in this context, means a major essential component
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do not modify the License. You may add Your own attribution
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(kernel, window system, and so on) of the specific operating system
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notices within Derivative Works that You distribute, alongside
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(if any) on which the executable work runs, or a compiler used to
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or as an addendum to the NOTICE text from the Work, provided
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produce the work, or an object code interpreter used to run it.
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that such additional attribution notices cannot be construed
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as modifying the License.
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The "Corresponding Source" for a work in object code form means all
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the source code needed to generate, install, and (for an executable
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You may add Your own copyright statement to Your modifications and
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work) run the object code and to modify the work, including scripts to
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may provide additional or different license terms and conditions
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control those activities. However, it does not include the work's
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for use, reproduction, or distribution of Your modifications, or
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System Libraries, or general-purpose tools or generally available free
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for any such Derivative Works as a whole, provided Your use,
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programs which are used unmodified in performing those activities but
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reproduction, and distribution of the Work otherwise complies with
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includes interface definition files associated with source files for
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by You to the Licensor shall be under the terms and conditions of
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Notwithstanding the above, nothing herein shall supersede or modify
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The Corresponding Source need not include anything that users
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the terms of any separate license agreement you may have executed
|
||||||
can regenerate automatically from other parts of the Corresponding
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with Licensor regarding such Contributions.
|
||||||
Source.
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|
||||||
|
6. Trademarks. This License does not grant permission to use the trade
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The Corresponding Source for a work in source code form is that
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names, trademarks, service marks, or product names of the Licensor,
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same work.
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except as required for reasonable and customary use in describing the
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origin of the Work and reproducing the content of the NOTICE file.
|
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2. Basic Permissions.
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7. Disclaimer of Warranty. Unless required by applicable law or
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All rights granted under this License are granted for the term of
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Contributor provides its Contributions) on an "AS IS" BASIS,
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WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
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covered work is covered by this License only if the output, given its
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Conveying under any other circumstances is permitted solely under
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No covered work shall be deemed part of an effective technological
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When you convey a covered work, you waive any legal power to forbid
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technological measures.
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||||||
4. Conveying Verbatim Copies.
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|
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You may convey verbatim copies of the Program's source code as you
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|
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receive it, in any medium, provided that you conspicuously and
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appropriately publish on each copy an appropriate copyright notice;
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keep intact all notices stating that this License and any
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non-permissive terms added in accord with section 7 apply to the code;
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keep intact all notices of the absence of any warranty; and give all
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You may charge any price or no price for each copy that you convey,
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and you may offer support or warranty protection for a fee.
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|
||||||
5. Conveying Modified Source Versions.
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|
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|
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You may convey a work based on the Program, or the modifications to
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|
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|
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|
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a) The work must carry prominent notices stating that you modified
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|
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|
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b) The work must carry prominent notices stating that it is
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|
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|
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7. This requirement modifies the requirement in section 4 to
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|
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|
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|
||||||
c) You must license the entire work, as a whole, under this
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|
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License to anyone who comes into possession of a copy. This
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|
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License will therefore apply, along with any applicable section 7
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|
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additional terms, to the whole of the work, and all its parts,
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|
||||||
regardless of how they are packaged. This License gives no
|
|
||||||
permission to license the work in any other way, but it does not
|
|
||||||
invalidate such permission if you have separately received it.
|
|
||||||
|
|
||||||
d) If the work has interactive user interfaces, each must display
|
|
||||||
Appropriate Legal Notices; however, if the Program has interactive
|
|
||||||
interfaces that do not display Appropriate Legal Notices, your
|
|
||||||
work need not make them do so.
|
|
||||||
|
|
||||||
A compilation of a covered work with other separate and independent
|
|
||||||
works, which are not by their nature extensions of the covered work,
|
|
||||||
and which are not combined with it such as to form a larger program,
|
|
||||||
in or on a volume of a storage or distribution medium, is called an
|
|
||||||
"aggregate" if the compilation and its resulting copyright are not
|
|
||||||
used to limit the access or legal rights of the compilation's users
|
|
||||||
beyond what the individual works permit. Inclusion of a covered work
|
|
||||||
in an aggregate does not cause this License to apply to the other
|
|
||||||
parts of the aggregate.
|
|
||||||
|
|
||||||
6. Conveying Non-Source Forms.
|
|
||||||
|
|
||||||
You may convey a covered work in object code form under the terms
|
|
||||||
of sections 4 and 5, provided that you also convey the
|
|
||||||
machine-readable Corresponding Source under the terms of this License,
|
|
||||||
in one of these ways:
|
|
||||||
|
|
||||||
a) Convey the object code in, or embodied in, a physical product
|
|
||||||
(including a physical distribution medium), accompanied by the
|
|
||||||
Corresponding Source fixed on a durable physical medium
|
|
||||||
customarily used for software interchange.
|
|
||||||
|
|
||||||
b) Convey the object code in, or embodied in, a physical product
|
|
||||||
(including a physical distribution medium), accompanied by a
|
|
||||||
written offer, valid for at least three years and valid for as
|
|
||||||
long as you offer spare parts or customer support for that product
|
|
||||||
model, to give anyone who possesses the object code either (1) a
|
|
||||||
copy of the Corresponding Source for all the software in the
|
|
||||||
product that is covered by this License, on a durable physical
|
|
||||||
medium customarily used for software interchange, for a price no
|
|
||||||
more than your reasonable cost of physically performing this
|
|
||||||
conveying of source, or (2) access to copy the
|
|
||||||
Corresponding Source from a network server at no charge.
|
|
||||||
|
|
||||||
c) Convey individual copies of the object code with a copy of the
|
|
||||||
written offer to provide the Corresponding Source. This
|
|
||||||
alternative is allowed only occasionally and noncommercially, and
|
|
||||||
only if you received the object code with such an offer, in accord
|
|
||||||
with subsection 6b.
|
|
||||||
|
|
||||||
d) Convey the object code by offering access from a designated
|
|
||||||
place (gratis or for a charge), and offer equivalent access to the
|
|
||||||
Corresponding Source in the same way through the same place at no
|
|
||||||
further charge. You need not require recipients to copy the
|
|
||||||
Corresponding Source along with the object code. If the place to
|
|
||||||
copy the object code is a network server, the Corresponding Source
|
|
||||||
may be on a different server (operated by you or a third party)
|
|
||||||
that supports equivalent copying facilities, provided you maintain
|
|
||||||
clear directions next to the object code saying where to find the
|
|
||||||
Corresponding Source. Regardless of what server hosts the
|
|
||||||
Corresponding Source, you remain obligated to ensure that it is
|
|
||||||
available for as long as needed to satisfy these requirements.
|
|
||||||
|
|
||||||
e) Convey the object code using peer-to-peer transmission, provided
|
|
||||||
you inform other peers where the object code and Corresponding
|
|
||||||
Source of the work are being offered to the general public at no
|
|
||||||
charge under subsection 6d.
|
|
||||||
|
|
||||||
A separable portion of the object code, whose source code is excluded
|
|
||||||
from the Corresponding Source as a System Library, need not be
|
|
||||||
included in conveying the object code work.
|
|
||||||
|
|
||||||
A "User Product" is either (1) a "consumer product", which means any
|
|
||||||
tangible personal property which is normally used for personal, family,
|
|
||||||
or household purposes, or (2) anything designed or sold for incorporation
|
|
||||||
into a dwelling. In determining whether a product is a consumer product,
|
|
||||||
doubtful cases shall be resolved in favor of coverage. For a particular
|
|
||||||
product received by a particular user, "normally used" refers to a
|
|
||||||
typical or common use of that class of product, regardless of the status
|
|
||||||
of the particular user or of the way in which the particular user
|
|
||||||
actually uses, or expects or is expected to use, the product. A product
|
|
||||||
is a consumer product regardless of whether the product has substantial
|
|
||||||
commercial, industrial or non-consumer uses, unless such uses represent
|
|
||||||
the only significant mode of use of the product.
|
|
||||||
|
|
||||||
"Installation Information" for a User Product means any methods,
|
|
||||||
procedures, authorization keys, or other information required to install
|
|
||||||
and execute modified versions of a covered work in that User Product from
|
|
||||||
a modified version of its Corresponding Source. The information must
|
|
||||||
suffice to ensure that the continued functioning of the modified object
|
|
||||||
code is in no case prevented or interfered with solely because
|
|
||||||
modification has been made.
|
|
||||||
|
|
||||||
If you convey an object code work under this section in, or with, or
|
|
||||||
specifically for use in, a User Product, and the conveying occurs as
|
|
||||||
part of a transaction in which the right of possession and use of the
|
|
||||||
User Product is transferred to the recipient in perpetuity or for a
|
|
||||||
fixed term (regardless of how the transaction is characterized), the
|
|
||||||
Corresponding Source conveyed under this section must be accompanied
|
|
||||||
by the Installation Information. But this requirement does not apply
|
|
||||||
if neither you nor any third party retains the ability to install
|
|
||||||
modified object code on the User Product (for example, the work has
|
|
||||||
been installed in ROM).
|
|
||||||
|
|
||||||
The requirement to provide Installation Information does not include a
|
|
||||||
requirement to continue to provide support service, warranty, or updates
|
|
||||||
for a work that has been modified or installed by the recipient, or for
|
|
||||||
the User Product in which it has been modified or installed. Access to a
|
|
||||||
network may be denied when the modification itself materially and
|
|
||||||
adversely affects the operation of the network or violates the rules and
|
|
||||||
protocols for communication across the network.
|
|
||||||
|
|
||||||
Corresponding Source conveyed, and Installation Information provided,
|
|
||||||
in accord with this section must be in a format that is publicly
|
|
||||||
documented (and with an implementation available to the public in
|
|
||||||
source code form), and must require no special password or key for
|
|
||||||
unpacking, reading or copying.
|
|
||||||
|
|
||||||
7. Additional Terms.
|
|
||||||
|
|
||||||
"Additional permissions" are terms that supplement the terms of this
|
|
||||||
License by making exceptions from one or more of its conditions.
|
|
||||||
Additional permissions that are applicable to the entire Program shall
|
|
||||||
be treated as though they were included in this License, to the extent
|
|
||||||
that they are valid under applicable law. If additional permissions
|
|
||||||
apply only to part of the Program, that part may be used separately
|
|
||||||
under those permissions, but the entire Program remains governed by
|
|
||||||
this License without regard to the additional permissions.
|
|
||||||
|
|
||||||
When you convey a copy of a covered work, you may at your option
|
|
||||||
remove any additional permissions from that copy, or from any part of
|
|
||||||
it. (Additional permissions may be written to require their own
|
|
||||||
removal in certain cases when you modify the work.) You may place
|
|
||||||
additional permissions on material, added by you to a covered work,
|
|
||||||
for which you have or can give appropriate copyright permission.
|
|
||||||
|
|
||||||
Notwithstanding any other provision of this License, for material you
|
|
||||||
add to a covered work, you may (if authorized by the copyright holders of
|
|
||||||
that material) supplement the terms of this License with terms:
|
|
||||||
|
|
||||||
a) Disclaiming warranty or limiting liability differently from the
|
|
||||||
terms of sections 15 and 16 of this License; or
|
|
||||||
|
|
||||||
b) Requiring preservation of specified reasonable legal notices or
|
|
||||||
author attributions in that material or in the Appropriate Legal
|
|
||||||
Notices displayed by works containing it; or
|
|
||||||
|
|
||||||
c) Prohibiting misrepresentation of the origin of that material, or
|
|
||||||
requiring that modified versions of such material be marked in
|
|
||||||
reasonable ways as different from the original version; or
|
|
||||||
|
|
||||||
d) Limiting the use for publicity purposes of names of licensors or
|
|
||||||
authors of the material; or
|
|
||||||
|
|
||||||
e) Declining to grant rights under trademark law for use of some
|
|
||||||
trade names, trademarks, or service marks; or
|
|
||||||
|
|
||||||
f) Requiring indemnification of licensors and authors of that
|
|
||||||
material by anyone who conveys the material (or modified versions of
|
|
||||||
it) with contractual assumptions of liability to the recipient, for
|
|
||||||
any liability that these contractual assumptions directly impose on
|
|
||||||
those licensors and authors.
|
|
||||||
|
|
||||||
All other non-permissive additional terms are considered "further
|
|
||||||
restrictions" within the meaning of section 10. If the Program as you
|
|
||||||
received it, or any part of it, contains a notice stating that it is
|
|
||||||
governed by this License along with a term that is a further
|
|
||||||
restriction, you may remove that term. If a license document contains
|
|
||||||
a further restriction but permits relicensing or conveying under this
|
|
||||||
License, you may add to a covered work material governed by the terms
|
|
||||||
of that license document, provided that the further restriction does
|
|
||||||
not survive such relicensing or conveying.
|
|
||||||
|
|
||||||
If you add terms to a covered work in accord with this section, you
|
|
||||||
must place, in the relevant source files, a statement of the
|
|
||||||
additional terms that apply to those files, or a notice indicating
|
|
||||||
where to find the applicable terms.
|
|
||||||
|
|
||||||
Additional terms, permissive or non-permissive, may be stated in the
|
|
||||||
form of a separately written license, or stated as exceptions;
|
|
||||||
the above requirements apply either way.
|
|
||||||
|
|
||||||
8. Termination.
|
|
||||||
|
|
||||||
You may not propagate or modify a covered work except as expressly
|
|
||||||
provided under this License. Any attempt otherwise to propagate or
|
|
||||||
modify it is void, and will automatically terminate your rights under
|
|
||||||
this License (including any patent licenses granted under the third
|
|
||||||
paragraph of section 11).
|
|
||||||
|
|
||||||
However, if you cease all violation of this License, then your
|
|
||||||
license from a particular copyright holder is reinstated (a)
|
|
||||||
provisionally, unless and until the copyright holder explicitly and
|
|
||||||
finally terminates your license, and (b) permanently, if the copyright
|
|
||||||
holder fails to notify you of the violation by some reasonable means
|
|
||||||
prior to 60 days after the cessation.
|
|
||||||
|
|
||||||
Moreover, your license from a particular copyright holder is
|
|
||||||
reinstated permanently if the copyright holder notifies you of the
|
|
||||||
violation by some reasonable means, this is the first time you have
|
|
||||||
received notice of violation of this License (for any work) from that
|
|
||||||
copyright holder, and you cure the violation prior to 30 days after
|
|
||||||
your receipt of the notice.
|
|
||||||
|
|
||||||
Termination of your rights under this section does not terminate the
|
|
||||||
licenses of parties who have received copies or rights from you under
|
|
||||||
this License. If your rights have been terminated and not permanently
|
|
||||||
reinstated, you do not qualify to receive new licenses for the same
|
|
||||||
material under section 10.
|
|
||||||
|
|
||||||
9. Acceptance Not Required for Having Copies.
|
|
||||||
|
|
||||||
You are not required to accept this License in order to receive or
|
|
||||||
run a copy of the Program. Ancillary propagation of a covered work
|
|
||||||
occurring solely as a consequence of using peer-to-peer transmission
|
|
||||||
to receive a copy likewise does not require acceptance. However,
|
|
||||||
nothing other than this License grants you permission to propagate or
|
|
||||||
modify any covered work. These actions infringe copyright if you do
|
|
||||||
not accept this License. Therefore, by modifying or propagating a
|
|
||||||
covered work, you indicate your acceptance of this License to do so.
|
|
||||||
|
|
||||||
10. Automatic Licensing of Downstream Recipients.
|
|
||||||
|
|
||||||
Each time you convey a covered work, the recipient automatically
|
|
||||||
receives a license from the original licensors, to run, modify and
|
|
||||||
propagate that work, subject to this License. You are not responsible
|
|
||||||
for enforcing compliance by third parties with this License.
|
|
||||||
|
|
||||||
An "entity transaction" is a transaction transferring control of an
|
|
||||||
organization, or substantially all assets of one, or subdividing an
|
|
||||||
organization, or merging organizations. If propagation of a covered
|
|
||||||
work results from an entity transaction, each party to that
|
|
||||||
transaction who receives a copy of the work also receives whatever
|
|
||||||
licenses to the work the party's predecessor in interest had or could
|
|
||||||
give under the previous paragraph, plus a right to possession of the
|
|
||||||
Corresponding Source of the work from the predecessor in interest, if
|
|
||||||
the predecessor has it or can get it with reasonable efforts.
|
|
||||||
|
|
||||||
You may not impose any further restrictions on the exercise of the
|
|
||||||
rights granted or affirmed under this License. For example, you may
|
|
||||||
not impose a license fee, royalty, or other charge for exercise of
|
|
||||||
rights granted under this License, and you may not initiate litigation
|
|
||||||
(including a cross-claim or counterclaim in a lawsuit) alleging that
|
|
||||||
any patent claim is infringed by making, using, selling, offering for
|
|
||||||
sale, or importing the Program or any portion of it.
|
|
||||||
|
|
||||||
11. Patents.
|
|
||||||
|
|
||||||
A "contributor" is a copyright holder who authorizes use under this
|
|
||||||
License of the Program or a work on which the Program is based. The
|
|
||||||
work thus licensed is called the contributor's "contributor version".
|
|
||||||
|
|
||||||
A contributor's "essential patent claims" are all patent claims
|
|
||||||
owned or controlled by the contributor, whether already acquired or
|
|
||||||
hereafter acquired, that would be infringed by some manner, permitted
|
|
||||||
by this License, of making, using, or selling its contributor version,
|
|
||||||
but do not include claims that would be infringed only as a
|
|
||||||
consequence of further modification of the contributor version. For
|
|
||||||
purposes of this definition, "control" includes the right to grant
|
|
||||||
patent sublicenses in a manner consistent with the requirements of
|
|
||||||
this License.
|
|
||||||
|
|
||||||
Each contributor grants you a non-exclusive, worldwide, royalty-free
|
|
||||||
patent license under the contributor's essential patent claims, to
|
|
||||||
make, use, sell, offer for sale, import and otherwise run, modify and
|
|
||||||
propagate the contents of its contributor version.
|
|
||||||
|
|
||||||
In the following three paragraphs, a "patent license" is any express
|
|
||||||
agreement or commitment, however denominated, not to enforce a patent
|
|
||||||
(such as an express permission to practice a patent or covenant not to
|
|
||||||
sue for patent infringement). To "grant" such a patent license to a
|
|
||||||
party means to make such an agreement or commitment not to enforce a
|
|
||||||
patent against the party.
|
|
||||||
|
|
||||||
If you convey a covered work, knowingly relying on a patent license,
|
|
||||||
and the Corresponding Source of the work is not available for anyone
|
|
||||||
to copy, free of charge and under the terms of this License, through a
|
|
||||||
publicly available network server or other readily accessible means,
|
|
||||||
then you must either (1) cause the Corresponding Source to be so
|
|
||||||
available, or (2) arrange to deprive yourself of the benefit of the
|
|
||||||
patent license for this particular work, or (3) arrange, in a manner
|
|
||||||
consistent with the requirements of this License, to extend the patent
|
|
||||||
license to downstream recipients. "Knowingly relying" means you have
|
|
||||||
actual knowledge that, but for the patent license, your conveying the
|
|
||||||
covered work in a country, or your recipient's use of the covered work
|
|
||||||
in a country, would infringe one or more identifiable patents in that
|
|
||||||
country that you have reason to believe are valid.
|
|
||||||
|
|
||||||
If, pursuant to or in connection with a single transaction or
|
|
||||||
arrangement, you convey, or propagate by procuring conveyance of, a
|
|
||||||
covered work, and grant a patent license to some of the parties
|
|
||||||
receiving the covered work authorizing them to use, propagate, modify
|
|
||||||
or convey a specific copy of the covered work, then the patent license
|
|
||||||
you grant is automatically extended to all recipients of the covered
|
|
||||||
work and works based on it.
|
|
||||||
|
|
||||||
A patent license is "discriminatory" if it does not include within
|
|
||||||
the scope of its coverage, prohibits the exercise of, or is
|
|
||||||
conditioned on the non-exercise of one or more of the rights that are
|
|
||||||
specifically granted under this License. You may not convey a covered
|
|
||||||
work if you are a party to an arrangement with a third party that is
|
|
||||||
in the business of distributing software, under which you make payment
|
|
||||||
to the third party based on the extent of your activity of conveying
|
|
||||||
the work, and under which the third party grants, to any of the
|
|
||||||
parties who would receive the covered work from you, a discriminatory
|
|
||||||
patent license (a) in connection with copies of the covered work
|
|
||||||
conveyed by you (or copies made from those copies), or (b) primarily
|
|
||||||
for and in connection with specific products or compilations that
|
|
||||||
contain the covered work, unless you entered into that arrangement,
|
|
||||||
or that patent license was granted, prior to 28 March 2007.
|
|
||||||
|
|
||||||
Nothing in this License shall be construed as excluding or limiting
|
|
||||||
any implied license or other defenses to infringement that may
|
|
||||||
otherwise be available to you under applicable patent law.
|
|
||||||
|
|
||||||
12. No Surrender of Others' Freedom.
|
|
||||||
|
|
||||||
If conditions are imposed on you (whether by court order, agreement or
|
|
||||||
otherwise) that contradict the conditions of this License, they do not
|
|
||||||
excuse you from the conditions of this License. If you cannot convey a
|
|
||||||
covered work so as to satisfy simultaneously your obligations under this
|
|
||||||
License and any other pertinent obligations, then as a consequence you may
|
|
||||||
not convey it at all. For example, if you agree to terms that obligate you
|
|
||||||
to collect a royalty for further conveying from those to whom you convey
|
|
||||||
the Program, the only way you could satisfy both those terms and this
|
|
||||||
License would be to refrain entirely from conveying the Program.
|
|
||||||
|
|
||||||
13. Remote Network Interaction; Use with the GNU General Public License.
|
|
||||||
|
|
||||||
Notwithstanding any other provision of this License, if you modify the
|
|
||||||
Program, your modified version must prominently offer all users
|
|
||||||
interacting with it remotely through a computer network (if your version
|
|
||||||
supports such interaction) an opportunity to receive the Corresponding
|
|
||||||
Source of your version by providing access to the Corresponding Source
|
|
||||||
from a network server at no charge, through some standard or customary
|
|
||||||
means of facilitating copying of software. This Corresponding Source
|
|
||||||
shall include the Corresponding Source for any work covered by version 3
|
|
||||||
of the GNU General Public License that is incorporated pursuant to the
|
|
||||||
following paragraph.
|
|
||||||
|
|
||||||
Notwithstanding any other provision of this License, you have
|
|
||||||
permission to link or combine any covered work with a work licensed
|
|
||||||
under version 3 of the GNU General Public License into a single
|
|
||||||
combined work, and to convey the resulting work. The terms of this
|
|
||||||
License will continue to apply to the part which is the covered work,
|
|
||||||
but the work with which it is combined will remain governed by version
|
|
||||||
3 of the GNU General Public License.
|
|
||||||
|
|
||||||
14. Revised Versions of this License.
|
|
||||||
|
|
||||||
The Free Software Foundation may publish revised and/or new versions of
|
|
||||||
the GNU Affero General Public License from time to time. Such new versions
|
|
||||||
will be similar in spirit to the present version, but may differ in detail to
|
|
||||||
address new problems or concerns.
|
|
||||||
|
|
||||||
Each version is given a distinguishing version number. If the
|
|
||||||
Program specifies that a certain numbered version of the GNU Affero General
|
|
||||||
Public License "or any later version" applies to it, you have the
|
|
||||||
option of following the terms and conditions either of that numbered
|
|
||||||
version or of any later version published by the Free Software
|
|
||||||
Foundation. If the Program does not specify a version number of the
|
|
||||||
GNU Affero General Public License, you may choose any version ever published
|
|
||||||
by the Free Software Foundation.
|
|
||||||
|
|
||||||
If the Program specifies that a proxy can decide which future
|
|
||||||
versions of the GNU Affero General Public License can be used, that proxy's
|
|
||||||
public statement of acceptance of a version permanently authorizes you
|
|
||||||
to choose that version for the Program.
|
|
||||||
|
|
||||||
Later license versions may give you additional or different
|
|
||||||
permissions. However, no additional obligations are imposed on any
|
|
||||||
author or copyright holder as a result of your choosing to follow a
|
|
||||||
later version.
|
|
||||||
|
|
||||||
15. Disclaimer of Warranty.
|
|
||||||
|
|
||||||
THERE IS NO WARRANTY FOR THE PROGRAM, TO THE EXTENT PERMITTED BY
|
|
||||||
APPLICABLE LAW. EXCEPT WHEN OTHERWISE STATED IN WRITING THE COPYRIGHT
|
|
||||||
HOLDERS AND/OR OTHER PARTIES PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
|
|
||||||
OF ANY KIND, EITHER EXPRESSED OR IMPLIED, INCLUDING, BUT NOT LIMITED TO,
|
|
||||||
THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
|
|
||||||
PURPOSE. THE ENTIRE RISK AS TO THE QUALITY AND PERFORMANCE OF THE PROGRAM
|
|
||||||
IS WITH YOU. SHOULD THE PROGRAM PROVE DEFECTIVE, YOU ASSUME THE COST OF
|
|
||||||
ALL NECESSARY SERVICING, REPAIR OR CORRECTION.
|
|
||||||
|
|
||||||
16. Limitation of Liability.
|
|
||||||
|
|
||||||
IN NO EVENT UNLESS REQUIRED BY APPLICABLE LAW OR AGREED TO IN WRITING
|
|
||||||
WILL ANY COPYRIGHT HOLDER, OR ANY OTHER PARTY WHO MODIFIES AND/OR CONVEYS
|
|
||||||
THE PROGRAM AS PERMITTED ABOVE, BE LIABLE TO YOU FOR DAMAGES, INCLUDING ANY
|
|
||||||
GENERAL, SPECIAL, INCIDENTAL OR CONSEQUENTIAL DAMAGES ARISING OUT OF THE
|
|
||||||
USE OR INABILITY TO USE THE PROGRAM (INCLUDING BUT NOT LIMITED TO LOSS OF
|
|
||||||
DATA OR DATA BEING RENDERED INACCURATE OR LOSSES SUSTAINED BY YOU OR THIRD
|
|
||||||
PARTIES OR A FAILURE OF THE PROGRAM TO OPERATE WITH ANY OTHER PROGRAMS),
|
|
||||||
EVEN IF SUCH HOLDER OR OTHER PARTY HAS BEEN ADVISED OF THE POSSIBILITY OF
|
|
||||||
SUCH DAMAGES.
|
|
||||||
|
|
||||||
17. Interpretation of Sections 15 and 16.
|
|
||||||
|
|
||||||
If the disclaimer of warranty and limitation of liability provided
|
|
||||||
above cannot be given local legal effect according to their terms,
|
|
||||||
reviewing courts shall apply local law that most closely approximates
|
|
||||||
an absolute waiver of all civil liability in connection with the
|
|
||||||
Program, unless a warranty or assumption of liability accompanies a
|
|
||||||
copy of the Program in return for a fee.
|
|
||||||
|
|
||||||
END OF TERMS AND CONDITIONS
|
END OF TERMS AND CONDITIONS
|
||||||
|
|
||||||
How to Apply These Terms to Your New Programs
|
APPENDIX: How to apply the Apache License to your work.
|
||||||
|
|
||||||
If you develop a new program, and you want it to be of the greatest
|
To apply the Apache License to your work, attach the following
|
||||||
possible use to the public, the best way to achieve this is to make it
|
boilerplate notice, with the fields enclosed by brackets "[]"
|
||||||
free software which everyone can redistribute and change under these terms.
|
replaced with your own identifying information. (Don't include
|
||||||
|
the brackets!) The text should be enclosed in the appropriate
|
||||||
|
comment syntax for the file format. We also recommend that a
|
||||||
|
file or class name and description of purpose be included on the
|
||||||
|
same "printed page" as the copyright notice for easier
|
||||||
|
identification within third-party archives.
|
||||||
|
|
||||||
To do so, attach the following notices to the program. It is safest
|
Copyright [2025] [The Galactic Swarm Corporation]
|
||||||
to attach them to the start of each source file to most effectively
|
|
||||||
state the exclusion of warranty; and each file should have at least
|
|
||||||
the "copyright" line and a pointer to where the full notice is found.
|
|
||||||
|
|
||||||
Swarms provides multi-agent orchestration mechanisms to enable llm agents to collaborate and work together
|
Licensed under the Apache License, Version 2.0 (the "License");
|
||||||
Copyright (C) <2025> <Kye Gomez Chairman of TGSC>
|
you may not use this file except in compliance with the License.
|
||||||
|
You may obtain a copy of the License at
|
||||||
|
|
||||||
This program is free software: you can redistribute it and/or modify
|
http://www.apache.org/licenses/LICENSE-2.0
|
||||||
it under the terms of the GNU Affero General Public License as published
|
|
||||||
by the Free Software Foundation, either version 3 of the License, or
|
|
||||||
(at your option) any later version.
|
|
||||||
|
|
||||||
This program is distributed in the hope that it will be useful,
|
Unless required by applicable law or agreed to in writing, software
|
||||||
but WITHOUT ANY WARRANTY; without even the implied warranty of
|
distributed under the License is distributed on an "AS IS" BASIS,
|
||||||
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
||||||
GNU Affero General Public License for more details.
|
See the License for the specific language governing permissions and
|
||||||
|
limitations under the License.
|
||||||
You should have received a copy of the GNU Affero General Public License
|
|
||||||
along with this program. If not, see <https://www.gnu.org/licenses/>.
|
|
||||||
|
|
||||||
Also add information on how to contact you by electronic and paper mail.
|
|
||||||
|
|
||||||
If your software can interact with users remotely through a computer
|
|
||||||
network, you should also make sure that it provides a way for users to
|
|
||||||
get its source. For example, if your program is a web application, its
|
|
||||||
interface could display a "Source" link that leads users to an archive
|
|
||||||
of the code. There are many ways you could offer source, and different
|
|
||||||
solutions will be better for different programs; see section 13 for the
|
|
||||||
specific requirements.
|
|
||||||
|
|
||||||
You should also get your employer (if you work as a programmer) or school,
|
|
||||||
if any, to sign a "copyright disclaimer" for the program, if necessary.
|
|
||||||
For more information on this, and how to apply and follow the GNU AGPL, see
|
|
||||||
<https://www.gnu.org/licenses/>.
|
|
||||||
File diff suppressed because it is too large
Load Diff
@ -0,0 +1,383 @@
|
|||||||
|
# $swarms Token Integration Guide
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
This guide covers the integration of $swarms token (74SBV4zDXxTRgv1pEMoECskKBkZHc2yGPnc7GYVepump) payments into your platform using Solana and Phantom wallet. The $swarms token offers numerous benefits on the Solana blockchain, including high transaction per second (TPS) capabilities, low transaction fees, and more.
|
||||||
|
|
||||||
|
## Table of Contents
|
||||||
|
- [Prerequisites](#prerequisites)
|
||||||
|
- [Installation](#installation)
|
||||||
|
- [Architecture Overview](#architecture-overview)
|
||||||
|
- [Setup Guide](#setup-guide)
|
||||||
|
- [Integration Examples](#integration-examples)
|
||||||
|
- [One-Click Payment Implementation](#one-click-payment-implementation)
|
||||||
|
- [Security Considerations](#security-considerations)
|
||||||
|
- [Troubleshooting](#troubleshooting)
|
||||||
|
|
||||||
|
## Prerequisites
|
||||||
|
- Node.js v16.x or higher
|
||||||
|
- TypeScript 4.x or higher
|
||||||
|
- Phantom Wallet browser extension
|
||||||
|
- Solana development environment
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
|
||||||
|
```bash
|
||||||
|
npm install @solana/web3.js @solana/spl-token @project-serum/anchor @solana/wallet-adapter-react @solana/wallet-adapter-phantom
|
||||||
|
```
|
||||||
|
|
||||||
|
## Architecture Overview
|
||||||
|
|
||||||
|
```mermaid
|
||||||
|
flowchart TB
|
||||||
|
A[User Interface] -->|Trigger Payment| B[Payment Handler]
|
||||||
|
B --> C{Phantom Wallet}
|
||||||
|
C -->|Sign Transaction| D[Solana Network]
|
||||||
|
D -->|Execute Transfer| E[$swarms Token Contract]
|
||||||
|
E -->|Confirm Transaction| F[Payment Confirmation]
|
||||||
|
F -->|Update UI| A
|
||||||
|
```
|
||||||
|
|
||||||
|
## Setup Guide
|
||||||
|
|
||||||
|
### 1. Initialize Solana Connection
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
import { Connection, clusterApiUrl } from '@solana/web3.js';
|
||||||
|
import { PhantomWalletAdapter } from '@solana/wallet-adapter-phantom';
|
||||||
|
|
||||||
|
const connection = new Connection(clusterApiUrl('mainnet-beta'));
|
||||||
|
const wallet = new PhantomWalletAdapter();
|
||||||
|
|
||||||
|
// Initialize wallet connection
|
||||||
|
await wallet.connect();
|
||||||
|
```
|
||||||
|
|
||||||
|
### 2. Configure Token Parameters
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
const SWARMS_TOKEN_ADDRESS = '74SBV4zDXxTRgv1pEMoECskKBkZHc2yGPnc7GYVepump';
|
||||||
|
|
||||||
|
interface TokenConfig {
|
||||||
|
mint: PublicKey;
|
||||||
|
decimals: number;
|
||||||
|
}
|
||||||
|
|
||||||
|
const swarmTokenConfig: TokenConfig = {
|
||||||
|
mint: new PublicKey(SWARMS_TOKEN_ADDRESS),
|
||||||
|
decimals: 9
|
||||||
|
};
|
||||||
|
```
|
||||||
|
|
||||||
|
### 3. Create Payment Handler
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
export class SwarmPaymentHandler {
|
||||||
|
private connection: Connection;
|
||||||
|
private wallet: PhantomWalletAdapter;
|
||||||
|
|
||||||
|
constructor(connection: Connection, wallet: PhantomWalletAdapter) {
|
||||||
|
this.connection = connection;
|
||||||
|
this.wallet = wallet;
|
||||||
|
}
|
||||||
|
|
||||||
|
async createTransferTransaction(
|
||||||
|
amount: number,
|
||||||
|
recipientAddress: string
|
||||||
|
): Promise<Transaction> {
|
||||||
|
const transaction = new Transaction();
|
||||||
|
|
||||||
|
const transferInstruction = createTransferInstruction(
|
||||||
|
await getAssociatedTokenAddress(swarmTokenConfig.mint, this.wallet.publicKey),
|
||||||
|
await getAssociatedTokenAddress(swarmTokenConfig.mint, new PublicKey(recipientAddress)),
|
||||||
|
this.wallet.publicKey,
|
||||||
|
amount * Math.pow(10, swarmTokenConfig.decimals)
|
||||||
|
);
|
||||||
|
|
||||||
|
transaction.add(transferInstruction);
|
||||||
|
return transaction;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## One-Click Payment Implementation
|
||||||
|
|
||||||
|
### React Component Example
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
import React, { useState } from 'react';
|
||||||
|
import { useWallet } from '@solana/wallet-adapter-react';
|
||||||
|
|
||||||
|
const SwarmPaymentButton: React.FC<{
|
||||||
|
amount: number;
|
||||||
|
recipientAddress: string;
|
||||||
|
}> = ({ amount, recipientAddress }) => {
|
||||||
|
const [loading, setLoading] = useState(false);
|
||||||
|
const wallet = useWallet();
|
||||||
|
const paymentHandler = new SwarmPaymentHandler(connection, wallet);
|
||||||
|
|
||||||
|
const handlePayment = async () => {
|
||||||
|
try {
|
||||||
|
setLoading(true);
|
||||||
|
|
||||||
|
const transaction = await paymentHandler.createTransferTransaction(
|
||||||
|
amount,
|
||||||
|
recipientAddress
|
||||||
|
);
|
||||||
|
|
||||||
|
const signature = await wallet.sendTransaction(transaction, connection);
|
||||||
|
await connection.confirmTransaction(signature);
|
||||||
|
|
||||||
|
// Handle success
|
||||||
|
console.log('Payment successful:', signature);
|
||||||
|
} catch (error) {
|
||||||
|
console.error('Payment failed:', error);
|
||||||
|
} finally {
|
||||||
|
setLoading(false);
|
||||||
|
}
|
||||||
|
};
|
||||||
|
|
||||||
|
return (
|
||||||
|
<button
|
||||||
|
onClick={handlePayment}
|
||||||
|
disabled={loading || !wallet.connected}
|
||||||
|
className="payment-button"
|
||||||
|
>
|
||||||
|
{loading ? 'Processing...' : `Pay ${amount} $swarms`}
|
||||||
|
</button>
|
||||||
|
);
|
||||||
|
};
|
||||||
|
```
|
||||||
|
|
||||||
|
### Payment Flow Sequence
|
||||||
|
|
||||||
|
```mermaid
|
||||||
|
sequenceDiagram
|
||||||
|
participant User
|
||||||
|
participant UI
|
||||||
|
participant PaymentHandler
|
||||||
|
participant PhantomWallet
|
||||||
|
participant Solana
|
||||||
|
|
||||||
|
User->>UI: Click Pay Button
|
||||||
|
UI->>PaymentHandler: Create Transaction
|
||||||
|
PaymentHandler->>PhantomWallet: Request Signature
|
||||||
|
PhantomWallet->>User: Prompt for Approval
|
||||||
|
User->>PhantomWallet: Approve Transaction
|
||||||
|
PhantomWallet->>Solana: Submit Transaction
|
||||||
|
Solana->>PaymentHandler: Confirm Transaction
|
||||||
|
PaymentHandler->>UI: Update Status
|
||||||
|
UI->>User: Show Confirmation
|
||||||
|
```
|
||||||
|
|
||||||
|
## Security Considerations
|
||||||
|
|
||||||
|
### Transaction Validation
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
function validateTransaction(
|
||||||
|
transaction: Transaction,
|
||||||
|
expectedAmount: number,
|
||||||
|
expectedRecipient: PublicKey
|
||||||
|
): boolean {
|
||||||
|
try {
|
||||||
|
const instruction = transaction.instructions[0];
|
||||||
|
const decodedData = TOKEN_PROGRAM_ID.decode(instruction.data);
|
||||||
|
|
||||||
|
return (
|
||||||
|
decodedData.amount === expectedAmount &&
|
||||||
|
instruction.keys[1].pubkey.equals(expectedRecipient)
|
||||||
|
);
|
||||||
|
} catch (error) {
|
||||||
|
console.error('Transaction validation failed:', error);
|
||||||
|
return false;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
### Error Handling
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
class PaymentError extends Error {
|
||||||
|
constructor(
|
||||||
|
message: string,
|
||||||
|
public code: string,
|
||||||
|
public transaction?: string
|
||||||
|
) {
|
||||||
|
super(message);
|
||||||
|
this.name = 'PaymentError';
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
async function handlePaymentError(error: any): Promise<void> {
|
||||||
|
if (error instanceof WalletError) {
|
||||||
|
// Handle wallet-specific errors
|
||||||
|
throw new PaymentError(
|
||||||
|
'Wallet error occurred',
|
||||||
|
'WALLET_ERROR',
|
||||||
|
error.message
|
||||||
|
);
|
||||||
|
} else if (error.code === 'TransactionError') {
|
||||||
|
// Handle Solana transaction errors
|
||||||
|
throw new PaymentError(
|
||||||
|
'Transaction failed',
|
||||||
|
'TRANSACTION_ERROR',
|
||||||
|
error.txid
|
||||||
|
);
|
||||||
|
}
|
||||||
|
// Handle other errors...
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Testing
|
||||||
|
|
||||||
|
### Unit Test Example
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
import { expect } from 'chai';
|
||||||
|
import { SwarmPaymentHandler } from './payment-handler';
|
||||||
|
|
||||||
|
describe('SwarmPaymentHandler', () => {
|
||||||
|
let paymentHandler: SwarmPaymentHandler;
|
||||||
|
|
||||||
|
beforeEach(() => {
|
||||||
|
// Setup test environment
|
||||||
|
});
|
||||||
|
|
||||||
|
it('should create valid transfer transaction', async () => {
|
||||||
|
const amount = 100;
|
||||||
|
const recipientAddress = 'recipient_address';
|
||||||
|
|
||||||
|
const transaction = await paymentHandler.createTransferTransaction(
|
||||||
|
amount,
|
||||||
|
recipientAddress
|
||||||
|
);
|
||||||
|
|
||||||
|
expect(transaction.instructions).to.have.lengthOf(1);
|
||||||
|
// Add more assertions...
|
||||||
|
});
|
||||||
|
});
|
||||||
|
```
|
||||||
|
|
||||||
|
## Troubleshooting
|
||||||
|
|
||||||
|
### Common Issues and Solutions
|
||||||
|
|
||||||
|
1. **Insufficient Balance**
|
||||||
|
```typescript
|
||||||
|
async function checkBalance(
|
||||||
|
connection: Connection,
|
||||||
|
walletAddress: PublicKey
|
||||||
|
): Promise<boolean> {
|
||||||
|
const balance = await connection.getTokenAccountBalance(
|
||||||
|
await getAssociatedTokenAddress(swarmTokenConfig.mint, walletAddress)
|
||||||
|
);
|
||||||
|
|
||||||
|
return parseInt(balance.value.amount) > 0;
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
2. **Transaction Timeout**
|
||||||
|
```typescript
|
||||||
|
async function submitWithRetry(
|
||||||
|
transaction: Transaction,
|
||||||
|
maxRetries = 3
|
||||||
|
): Promise<string> {
|
||||||
|
let attempt = 0;
|
||||||
|
|
||||||
|
while (attempt < maxRetries) {
|
||||||
|
try {
|
||||||
|
const signature = await wallet.sendTransaction(transaction, connection);
|
||||||
|
const confirmation = await connection.confirmTransaction(signature);
|
||||||
|
|
||||||
|
if (confirmation.value.err) {
|
||||||
|
throw new Error('Transaction failed');
|
||||||
|
}
|
||||||
|
|
||||||
|
return signature;
|
||||||
|
} catch (error) {
|
||||||
|
attempt++;
|
||||||
|
if (attempt === maxRetries) throw error;
|
||||||
|
await new Promise(resolve => setTimeout(resolve, 1000 * attempt));
|
||||||
|
}
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Monitoring and Analytics
|
||||||
|
|
||||||
|
### Transaction Monitoring
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
interface TransactionMetrics {
|
||||||
|
timestamp: number;
|
||||||
|
amount: number;
|
||||||
|
success: boolean;
|
||||||
|
duration: number;
|
||||||
|
}
|
||||||
|
|
||||||
|
class TransactionMonitor {
|
||||||
|
private metrics: TransactionMetrics[] = [];
|
||||||
|
|
||||||
|
logTransaction(metric: TransactionMetrics): void {
|
||||||
|
this.metrics.push(metric);
|
||||||
|
// Add your analytics implementation
|
||||||
|
}
|
||||||
|
|
||||||
|
getAverageSuccessRate(): number {
|
||||||
|
return (
|
||||||
|
this.metrics.filter(m => m.success).length / this.metrics.length * 100
|
||||||
|
);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Advanced Features
|
||||||
|
|
||||||
|
### Batch Payments
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
async function createBatchPayment(
|
||||||
|
recipients: Array<{ address: string; amount: number }>
|
||||||
|
): Promise<Transaction> {
|
||||||
|
const transaction = new Transaction();
|
||||||
|
|
||||||
|
for (const recipient of recipients) {
|
||||||
|
const transferInstruction = createTransferInstruction(/* ... */);
|
||||||
|
transaction.add(transferInstruction);
|
||||||
|
}
|
||||||
|
|
||||||
|
return transaction;
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
### Subscription Payments
|
||||||
|
|
||||||
|
```typescript
|
||||||
|
class SubscriptionManager {
|
||||||
|
async createSubscription(
|
||||||
|
amount: number,
|
||||||
|
interval: number,
|
||||||
|
recipientAddress: string
|
||||||
|
): Promise<string> {
|
||||||
|
// Implementation for recurring payments
|
||||||
|
}
|
||||||
|
|
||||||
|
async cancelSubscription(subscriptionId: string): Promise<void> {
|
||||||
|
// Implementation for cancellation
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
## Support and Resources
|
||||||
|
|
||||||
|
For additional support:
|
||||||
|
- Solana Documentation: https://docs.solana.com
|
||||||
|
- Phantom Wallet Docs: https://docs.phantom.app
|
||||||
|
- $swarms Token Contract: 74SBV4zDXxTRgv1pEMoECskKBkZHc2yGPnc7GYVepump
|
||||||
|
|
||||||
|
## Version History
|
||||||
|
|
||||||
|
- v1.0.0 - Initial release
|
||||||
|
- v1.0.1 - Added batch payment support
|
||||||
|
- v1.0.2 - Enhanced error handling
|
||||||
|
- v1.0.3 - Added subscription payment feature
|
||||||
@ -0,0 +1,63 @@
|
|||||||
|
# Lumo Example
|
||||||
|
Introducing Lumo-70B-Instruct - the largest and most advanced AI model ever created for the Solana ecosystem. Built on Meta's groundbreaking LLaMa 3.3 70B Instruct foundation, this revolutionary model represents a quantum leap in blockchain-specific artificial intelligence. With an unprecedented 70 billion parameters and trained on the most comprehensive Solana documentation dataset ever assembled, Lumo-70B-Instruct sets a new standard for developer assistance in the blockchain space.
|
||||||
|
|
||||||
|
|
||||||
|
- [Docs](https://huggingface.co/lumolabs-ai/Lumo-70B-Instruct)
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from transformers import LlamaForCausalLM, AutoTokenizer
|
||||||
|
import torch
|
||||||
|
from transformers import BitsAndBytesConfig
|
||||||
|
|
||||||
|
class Lumo:
|
||||||
|
"""
|
||||||
|
A class for generating text using the Lumo model with 4-bit quantization.
|
||||||
|
"""
|
||||||
|
def __init__(self):
|
||||||
|
"""
|
||||||
|
Initializes the Lumo model with 4-bit quantization and a tokenizer.
|
||||||
|
"""
|
||||||
|
# Configure 4-bit quantization
|
||||||
|
bnb_config = BitsAndBytesConfig(
|
||||||
|
load_in_4bit=True,
|
||||||
|
bnb_4bit_quant_type="nf4",
|
||||||
|
bnb_4bit_compute_dtype=torch.float16,
|
||||||
|
llm_int8_enable_fp32_cpu_offload=True
|
||||||
|
)
|
||||||
|
|
||||||
|
self.model = LlamaForCausalLM.from_pretrained(
|
||||||
|
"lumolabs-ai/Lumo-70B-Instruct",
|
||||||
|
device_map="auto",
|
||||||
|
quantization_config=bnb_config,
|
||||||
|
use_cache=False,
|
||||||
|
attn_implementation="sdpa"
|
||||||
|
)
|
||||||
|
self.tokenizer = AutoTokenizer.from_pretrained("lumolabs-ai/Lumo-70B-Instruct")
|
||||||
|
|
||||||
|
def run(self, task: str) -> str:
|
||||||
|
"""
|
||||||
|
Generates text based on the given prompt using the Lumo model.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
prompt (str): The input prompt for the model.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: The generated text.
|
||||||
|
"""
|
||||||
|
inputs = self.tokenizer(task, return_tensors="pt").to(self.model.device)
|
||||||
|
outputs = self.model.generate(**inputs, max_new_tokens=100)
|
||||||
|
return self.tokenizer.decode(outputs[0], skip_special_tokens=True)
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
Agent(
|
||||||
|
agent_name="Solana-Analysis-Agent",
|
||||||
|
llm=Lumo(),
|
||||||
|
max_loops="auto",
|
||||||
|
interactive=True,
|
||||||
|
streaming_on=True,
|
||||||
|
).run("How do i create a smart contract in solana?")
|
||||||
|
|
||||||
|
```
|
||||||
@ -0,0 +1,28 @@
|
|||||||
|
# Meme Agent Builder
|
||||||
|
|
||||||
|
- `pip3 install -U swarms`
|
||||||
|
- Add your OpenAI API key to the `.env` file with `OPENAI_API_KEY=your_api_key`
|
||||||
|
- Run the script
|
||||||
|
- Multiple agents will be created and saved to the `meme_agents` folder
|
||||||
|
- A swarm architecture will be selected autonomously and executed
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms.structs.meme_agent_persona_generator import (
|
||||||
|
MemeAgentGenerator,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
example = MemeAgentGenerator(
|
||||||
|
name="Meme-Swarm",
|
||||||
|
description="A swarm of specialized AI agents collaborating on generating and sharing memes around cool media from 2001s",
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
print(
|
||||||
|
example.run(
|
||||||
|
"Generate funny meme agents around cool media from 2001s"
|
||||||
|
)
|
||||||
|
)
|
||||||
|
|
||||||
|
```
|
||||||
@ -0,0 +1,129 @@
|
|||||||
|
# Quant Crypto Agent
|
||||||
|
|
||||||
|
- This is a simple example of a crypto agent that uses the `Agent` class from the `swarms` library.
|
||||||
|
- It uses the `fetch_htx_data` and `coin_gecko_coin_api` tools to fetch data from the `htx` and `CoinGecko` APIs.
|
||||||
|
- It uses the `Agent` class to create an agent that can analyze the current state of a crypto asset.
|
||||||
|
|
||||||
|
## Steps
|
||||||
|
|
||||||
|
1. Install the `swarms` library.
|
||||||
|
2. Install the `swarms_tools` library.
|
||||||
|
3. Setup your `.env` file with the `OPENAI_API_KEY` environment variables.
|
||||||
|
4. Run the code.
|
||||||
|
|
||||||
|
## Installation:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip install swarms swarms-tools python-dotenv
|
||||||
|
```
|
||||||
|
|
||||||
|
## Code:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
from swarms_tools import fetch_htx_data, coin_gecko_coin_api
|
||||||
|
|
||||||
|
load_dotenv()
|
||||||
|
|
||||||
|
CRYPTO_ANALYST_SYSTEM_PROMPT = """
|
||||||
|
You are an expert cryptocurrency financial analyst with deep expertise in:
|
||||||
|
1. Technical Analysis
|
||||||
|
- Chart patterns and indicators (RSI, MACD, Bollinger Bands)
|
||||||
|
- Volume analysis and market momentum
|
||||||
|
- Support and resistance levels
|
||||||
|
- Trend analysis and price action
|
||||||
|
|
||||||
|
2. Fundamental Analysis
|
||||||
|
- Tokenomics evaluation
|
||||||
|
- Network metrics (TVL, daily active users, transaction volume)
|
||||||
|
- Protocol revenue and growth metrics
|
||||||
|
- Market capitalization analysis
|
||||||
|
- Token utility and use cases
|
||||||
|
|
||||||
|
3. Market Analysis
|
||||||
|
- Market sentiment analysis
|
||||||
|
- Correlation with broader crypto market
|
||||||
|
- Impact of macro events
|
||||||
|
- Institutional adoption metrics
|
||||||
|
- DeFi and NFT market analysis
|
||||||
|
|
||||||
|
4. Risk Assessment
|
||||||
|
- Volatility metrics
|
||||||
|
- Liquidity analysis
|
||||||
|
- Smart contract risks
|
||||||
|
- Regulatory considerations
|
||||||
|
- Exchange exposure risks
|
||||||
|
|
||||||
|
5. Data Analysis Methods
|
||||||
|
- On-chain metrics analysis
|
||||||
|
- Whale wallet tracking
|
||||||
|
- Exchange inflow/outflow
|
||||||
|
- Mining/Staking statistics
|
||||||
|
- Network health indicators
|
||||||
|
|
||||||
|
When analyzing crypto assets, always:
|
||||||
|
1. Start with a comprehensive market overview
|
||||||
|
2. Examine both on-chain and off-chain metrics
|
||||||
|
3. Consider multiple timeframes (short, medium, long-term)
|
||||||
|
4. Evaluate risk-reward ratios
|
||||||
|
5. Assess market sentiment and momentum
|
||||||
|
6. Consider regulatory and security factors
|
||||||
|
7. Analyze correlations with BTC, ETH, and traditional markets
|
||||||
|
8. Examine liquidity and volume profiles
|
||||||
|
9. Review recent protocol developments and updates
|
||||||
|
10. Consider macro economic factors
|
||||||
|
|
||||||
|
Format your analysis with:
|
||||||
|
- Clear section headings
|
||||||
|
- Relevant metrics and data points
|
||||||
|
- Risk warnings and disclaimers
|
||||||
|
- Price action analysis
|
||||||
|
- Market sentiment summary
|
||||||
|
- Technical indicators
|
||||||
|
- Fundamental factors
|
||||||
|
- Clear recommendations with rationale
|
||||||
|
|
||||||
|
Remember to:
|
||||||
|
- Always provide data-driven insights
|
||||||
|
- Include both bullish and bearish scenarios
|
||||||
|
- Highlight key risk factors
|
||||||
|
- Consider market cycles and seasonality
|
||||||
|
- Maintain objectivity in analysis
|
||||||
|
- Cite sources for data and claims
|
||||||
|
- Update analysis based on new market conditions
|
||||||
|
"""
|
||||||
|
|
||||||
|
# Initialize the crypto analysis agent
|
||||||
|
agent = Agent(
|
||||||
|
agent_name="Crypto-Analysis-Expert",
|
||||||
|
agent_description="Expert cryptocurrency financial analyst and market researcher",
|
||||||
|
system_prompt=CRYPTO_ANALYST_SYSTEM_PROMPT,
|
||||||
|
max_loops="auto",
|
||||||
|
model_name="gpt-4o",
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
user_name="crypto_analyst",
|
||||||
|
output_type="str",
|
||||||
|
interactive=True,
|
||||||
|
)
|
||||||
|
|
||||||
|
print(fetch_htx_data("sol"))
|
||||||
|
print(coin_gecko_coin_api("solana"))
|
||||||
|
|
||||||
|
# Example usage
|
||||||
|
agent.run(
|
||||||
|
f"""
|
||||||
|
Analyze the current state of Solana (SOL), including:
|
||||||
|
1. Technical analysis of price action
|
||||||
|
2. On-chain metrics and network health
|
||||||
|
3. Recent protocol developments
|
||||||
|
4. Market sentiment
|
||||||
|
5. Risk factors
|
||||||
|
Please provide a comprehensive analysis with data-driven insights.
|
||||||
|
|
||||||
|
# Solana CoinGecko Data
|
||||||
|
Real-tim data from Solana CoinGecko: \n {coin_gecko_coin_api("solana")}
|
||||||
|
|
||||||
|
"""
|
||||||
|
)
|
||||||
|
```
|
||||||
@ -0,0 +1,37 @@
|
|||||||
|
# Swarms Tools Example with HTX + CoinGecko
|
||||||
|
|
||||||
|
- `pip3 install swarms swarms-tools`
|
||||||
|
- Add `OPENAI_API_KEY` to your `.env` file
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from swarms.prompts.finance_agent_sys_prompt import (
|
||||||
|
FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
)
|
||||||
|
from swarms_tools import (
|
||||||
|
coin_gecko_coin_api,
|
||||||
|
fetch_htx_data,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
# Initialize the agent
|
||||||
|
agent = Agent(
|
||||||
|
agent_name="Financial-Analysis-Agent",
|
||||||
|
agent_description="Personal finance advisor agent",
|
||||||
|
system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
max_loops=1,
|
||||||
|
model_name="gpt-4o",
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
user_name="swarms_corp",
|
||||||
|
return_step_meta=False,
|
||||||
|
output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
|
||||||
|
auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
|
||||||
|
max_tokens=4000, # max output tokens
|
||||||
|
saved_state_path="agent_00.json",
|
||||||
|
interactive=False,
|
||||||
|
)
|
||||||
|
|
||||||
|
agent.run(
|
||||||
|
f"Analyze the $swarms token on HTX with data: {fetch_htx_data('swarms')}. Additionally, consider the following CoinGecko data: {coin_gecko_coin_api('swarms')}"
|
||||||
|
)
|
||||||
|
```
|
||||||
@ -0,0 +1,43 @@
|
|||||||
|
# Swarms Tools Example with HTX + CoinGecko
|
||||||
|
|
||||||
|
- `pip3 install swarms swarms-tools`
|
||||||
|
- Add `OPENAI_API_KEY` to your `.env` file
|
||||||
|
- Run `swarms_tools_htx_gecko.py`
|
||||||
|
- Agent will make a function call to the desired tool
|
||||||
|
- The tool will be executed and the result will be returned to the agent
|
||||||
|
- The agent will then analyze the result and return the final output
|
||||||
|
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from swarms.prompts.finance_agent_sys_prompt import (
|
||||||
|
FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
)
|
||||||
|
from swarms_tools import (
|
||||||
|
fetch_stock_news,
|
||||||
|
coin_gecko_coin_api,
|
||||||
|
fetch_htx_data,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Initialize the agent
|
||||||
|
agent = Agent(
|
||||||
|
agent_name="Financial-Analysis-Agent",
|
||||||
|
agent_description="Personal finance advisor agent",
|
||||||
|
system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
max_loops=1,
|
||||||
|
model_name="gpt-4o",
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
user_name="swarms_corp",
|
||||||
|
retry_attempts=3,
|
||||||
|
context_length=8192,
|
||||||
|
return_step_meta=False,
|
||||||
|
output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
|
||||||
|
auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
|
||||||
|
max_tokens=4000, # max output tokens
|
||||||
|
saved_state_path="agent_00.json",
|
||||||
|
interactive=False,
|
||||||
|
tools=[fetch_stock_news, coin_gecko_coin_api, fetch_htx_data],
|
||||||
|
)
|
||||||
|
|
||||||
|
agent.run("Analyze the $swarms token on htx")
|
||||||
|
```
|
||||||
@ -0,0 +1,42 @@
|
|||||||
|
# Swarms Tools Example with Yahoo Finance
|
||||||
|
|
||||||
|
- `pip3 install swarms swarms-tools`
|
||||||
|
- Add `OPENAI_API_KEY` to your `.env` file
|
||||||
|
- Run `yahoo_finance_agent.py`
|
||||||
|
- Agent will make a function call to the desired tool
|
||||||
|
- The tool will be executed and the result will be returned to the agent
|
||||||
|
- The agent will then analyze the result and return the final output
|
||||||
|
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from swarms.prompts.finance_agent_sys_prompt import (
|
||||||
|
FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
)
|
||||||
|
from swarms_tools import (
|
||||||
|
yahoo_finance_api,
|
||||||
|
)
|
||||||
|
|
||||||
|
# Initialize the agent
|
||||||
|
agent = Agent(
|
||||||
|
agent_name="Financial-Analysis-Agent",
|
||||||
|
agent_description="Personal finance advisor agent",
|
||||||
|
system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
max_loops=1,
|
||||||
|
model_name="gpt-4o",
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
user_name="swarms_corp",
|
||||||
|
retry_attempts=3,
|
||||||
|
context_length=8192,
|
||||||
|
return_step_meta=False,
|
||||||
|
output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
|
||||||
|
auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
|
||||||
|
max_tokens=4000, # max output tokens
|
||||||
|
saved_state_path="agent_00.json",
|
||||||
|
interactive=False,
|
||||||
|
tools=[yahoo_finance_api],
|
||||||
|
)
|
||||||
|
|
||||||
|
agent.run("Analyze the latest metrics for nvidia")
|
||||||
|
# Less than 30 lines of code....
|
||||||
|
```
|
||||||
@ -0,0 +1,187 @@
|
|||||||
|
# Environment Variable Management & Security
|
||||||
|
|
||||||
|
This guide provides comprehensive documentation for managing environment variables and API keys securely in the Swarms framework.
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
Swarms uses environment variables for configuration management and secure credential storage. This approach keeps sensitive information like API keys out of your code and allows for easy configuration changes across different environments.
|
||||||
|
|
||||||
|
## Core Environment Variables
|
||||||
|
|
||||||
|
### Framework Configuration
|
||||||
|
|
||||||
|
- `SWARMS_VERBOSE_GLOBAL`: Controls global logging verbosity
|
||||||
|
```bash
|
||||||
|
SWARMS_VERBOSE_GLOBAL="True" # Enable verbose logging
|
||||||
|
SWARMS_VERBOSE_GLOBAL="False" # Disable verbose logging
|
||||||
|
```
|
||||||
|
|
||||||
|
- `WORKSPACE_DIR`: Defines the workspace directory for agent operations
|
||||||
|
```bash
|
||||||
|
WORKSPACE_DIR="agent_workspace"
|
||||||
|
```
|
||||||
|
|
||||||
|
### API Keys
|
||||||
|
|
||||||
|
#### Model Provider Keys
|
||||||
|
|
||||||
|
1. **OpenAI**
|
||||||
|
- `OPENAI_API_KEY`: Authentication for GPT models
|
||||||
|
```bash
|
||||||
|
OPENAI_API_KEY="your-openai-key"
|
||||||
|
```
|
||||||
|
|
||||||
|
2. **Anthropic**
|
||||||
|
- `ANTHROPIC_API_KEY`: Authentication for Claude models
|
||||||
|
```bash
|
||||||
|
ANTHROPIC_API_KEY="your-anthropic-key"
|
||||||
|
```
|
||||||
|
|
||||||
|
3. **Google**
|
||||||
|
- `GEMINI_API_KEY`: Authentication for Gemini models
|
||||||
|
|
||||||
|
4. **Hugging Face**
|
||||||
|
- `HUGGINGFACE_TOKEN`: Access to Hugging Face models
|
||||||
|
|
||||||
|
5. **Perplexity AI**
|
||||||
|
- `PPLX_API_KEY`: Access to Perplexity models
|
||||||
|
|
||||||
|
6. **AI21**
|
||||||
|
- `AI21_API_KEY`: Access to AI21 models
|
||||||
|
|
||||||
|
#### Tool Provider Keys
|
||||||
|
|
||||||
|
1. **Search Tools**
|
||||||
|
- `BING_BROWSER_API`: Bing search capabilities
|
||||||
|
- `BRAVESEARCH_API_KEY`: Brave search integration
|
||||||
|
- `TAVILY_API_KEY`: Tavily search services
|
||||||
|
- `YOU_API_KEY`: You.com search integration
|
||||||
|
|
||||||
|
2. **Analytics & Monitoring**
|
||||||
|
- `AGENTOPS_API_KEY`: AgentOps monitoring
|
||||||
|
- `EXA_API_KEY`: Exa.ai services
|
||||||
|
|
||||||
|
3. **Browser Automation**
|
||||||
|
- `MULTION_API_KEY`: Multi-browser automation
|
||||||
|
|
||||||
|
|
||||||
|
## Security Best Practices
|
||||||
|
|
||||||
|
### 1. Environment File Management
|
||||||
|
|
||||||
|
- Create a `.env` file in your project root
|
||||||
|
- Never commit `.env` files to version control
|
||||||
|
- Add `.env` to your `.gitignore`:
|
||||||
|
```bash
|
||||||
|
echo ".env" >> .gitignore
|
||||||
|
```
|
||||||
|
|
||||||
|
### 2. API Key Security
|
||||||
|
|
||||||
|
- Rotate API keys regularly
|
||||||
|
- Use different API keys for development and production
|
||||||
|
- Never hardcode API keys in your code
|
||||||
|
- Limit API key permissions to only what's necessary
|
||||||
|
- Monitor API key usage for unusual patterns
|
||||||
|
|
||||||
|
### 3. Template Configuration
|
||||||
|
|
||||||
|
Create a `.env.example` template without actual values:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Required Configuration
|
||||||
|
OPENAI_API_KEY=""
|
||||||
|
ANTHROPIC_API_KEY=""
|
||||||
|
WORKSPACE_DIR="agent_workspace"
|
||||||
|
|
||||||
|
# Optional Configuration
|
||||||
|
SWARMS_VERBOSE_GLOBAL="False"
|
||||||
|
```
|
||||||
|
|
||||||
|
### 4. Loading Environment Variables
|
||||||
|
|
||||||
|
```python
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
import os
|
||||||
|
|
||||||
|
# Load environment variables
|
||||||
|
load_dotenv()
|
||||||
|
|
||||||
|
# Access variables
|
||||||
|
workspace_dir = os.getenv("WORKSPACE_DIR")
|
||||||
|
openai_key = os.getenv("OPENAI_API_KEY")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Environment Setup Guide
|
||||||
|
|
||||||
|
1. **Install Dependencies**:
|
||||||
|
```bash
|
||||||
|
pip install python-dotenv
|
||||||
|
```
|
||||||
|
|
||||||
|
2. **Create Environment File**:
|
||||||
|
```bash
|
||||||
|
cp .env.example .env
|
||||||
|
```
|
||||||
|
|
||||||
|
3. **Configure Variables**:
|
||||||
|
- Open `.env` in your text editor
|
||||||
|
- Add your API keys and configuration
|
||||||
|
- Save the file
|
||||||
|
|
||||||
|
4. **Verify Setup**:
|
||||||
|
```python
|
||||||
|
import os
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
|
||||||
|
load_dotenv()
|
||||||
|
assert os.getenv("OPENAI_API_KEY") is not None, "OpenAI API key not found"
|
||||||
|
```
|
||||||
|
|
||||||
|
## Environment-Specific Configuration
|
||||||
|
|
||||||
|
### Development
|
||||||
|
|
||||||
|
```bash
|
||||||
|
WORKSPACE_DIR="agent_workspace"
|
||||||
|
SWARMS_VERBOSE_GLOBAL="True"
|
||||||
|
```
|
||||||
|
|
||||||
|
### Production
|
||||||
|
|
||||||
|
```bash
|
||||||
|
WORKSPACE_DIR="/var/swarms/workspace"
|
||||||
|
SWARMS_VERBOSE_GLOBAL="False"
|
||||||
|
```
|
||||||
|
|
||||||
|
### Testing
|
||||||
|
|
||||||
|
```bash
|
||||||
|
WORKSPACE_DIR="test_workspace"
|
||||||
|
SWARMS_VERBOSE_GLOBAL="True"
|
||||||
|
```
|
||||||
|
|
||||||
|
## Troubleshooting
|
||||||
|
|
||||||
|
### Common Issues
|
||||||
|
|
||||||
|
1. **Environment Variables Not Loading**
|
||||||
|
- Verify `.env` file exists in project root
|
||||||
|
- Confirm `load_dotenv()` is called before accessing variables
|
||||||
|
- Check file permissions
|
||||||
|
|
||||||
|
2. **API Key Issues**
|
||||||
|
- Verify key format is correct
|
||||||
|
- Ensure key has not expired
|
||||||
|
- Check for leading/trailing whitespace
|
||||||
|
|
||||||
|
3. **Workspace Directory Problems**
|
||||||
|
- Confirm directory exists
|
||||||
|
- Verify write permissions
|
||||||
|
- Check path is absolute when required
|
||||||
|
|
||||||
|
## Additional Resources
|
||||||
|
|
||||||
|
- [Swarms Documentation](https://docs.swarms.world)
|
||||||
|
- [Security Best Practices](https://swarms.world/security)
|
||||||
|
- [API Documentation](https://swarms.world/docs/api)
|
||||||
@ -0,0 +1,247 @@
|
|||||||
|
# MatrixSwarm
|
||||||
|
|
||||||
|
The `MatrixSwarm` class provides a framework for managing and operating on matrices of AI agents, enabling matrix-like operations similar to linear algebra. This allows for complex agent interactions and parallel processing capabilities.
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
`MatrixSwarm` treats AI agents as elements in a matrix, allowing for operations like addition, multiplication, and transposition. This approach enables sophisticated agent orchestration and parallel processing patterns.
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms
|
||||||
|
```
|
||||||
|
|
||||||
|
## Basic Usage
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from swarms.matrix import MatrixSwarm
|
||||||
|
|
||||||
|
# Create a 2x2 matrix of agents
|
||||||
|
agents = [
|
||||||
|
[Agent(agent_name="Agent-0-0"), Agent(agent_name="Agent-0-1")],
|
||||||
|
[Agent(agent_name="Agent-1-0"), Agent(agent_name="Agent-1-1")]
|
||||||
|
]
|
||||||
|
|
||||||
|
# Initialize the matrix
|
||||||
|
matrix = MatrixSwarm(agents)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Class Constructor
|
||||||
|
|
||||||
|
```python
|
||||||
|
def __init__(self, agents: List[List[Agent]])
|
||||||
|
```
|
||||||
|
|
||||||
|
### Parameters
|
||||||
|
- `agents` (`List[List[Agent]]`): A 2D list of Agent instances representing the matrix.
|
||||||
|
|
||||||
|
### Raises
|
||||||
|
- `ValueError`: If the input is not a valid 2D list of Agent instances.
|
||||||
|
|
||||||
|
## Methods
|
||||||
|
|
||||||
|
### transpose()
|
||||||
|
|
||||||
|
Transposes the matrix of agents by swapping rows and columns.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def transpose(self) -> MatrixSwarm
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `MatrixSwarm`: A new MatrixSwarm instance with transposed dimensions.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### add(other)
|
||||||
|
|
||||||
|
Performs element-wise addition of two agent matrices.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def add(self, other: MatrixSwarm) -> MatrixSwarm
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `other` (`MatrixSwarm`): Another MatrixSwarm instance to add.
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `MatrixSwarm`: A new MatrixSwarm resulting from the addition.
|
||||||
|
|
||||||
|
#### Raises
|
||||||
|
- `ValueError`: If matrix dimensions are incompatible.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### scalar_multiply(scalar)
|
||||||
|
|
||||||
|
Scales the matrix by duplicating agents along rows.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def scalar_multiply(self, scalar: int) -> MatrixSwarm
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `scalar` (`int`): The multiplication factor.
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `MatrixSwarm`: A new MatrixSwarm with scaled dimensions.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### multiply(other, inputs)
|
||||||
|
|
||||||
|
Performs matrix multiplication (dot product) between two agent matrices.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def multiply(self, other: MatrixSwarm, inputs: List[str]) -> List[List[AgentOutput]]
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `other` (`MatrixSwarm`): The second MatrixSwarm for multiplication.
|
||||||
|
- `inputs` (`List[str]`): Input queries for the agents.
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `List[List[AgentOutput]]`: Matrix of operation results.
|
||||||
|
|
||||||
|
#### Raises
|
||||||
|
- `ValueError`: If matrix dimensions are incompatible for multiplication.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### subtract(other)
|
||||||
|
|
||||||
|
Performs element-wise subtraction of two agent matrices.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def subtract(self, other: MatrixSwarm) -> MatrixSwarm
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `other` (`MatrixSwarm`): Another MatrixSwarm to subtract.
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `MatrixSwarm`: A new MatrixSwarm resulting from the subtraction.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### identity(size)
|
||||||
|
|
||||||
|
Creates an identity matrix of agents.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def identity(self, size: int) -> MatrixSwarm
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `size` (`int`): Size of the identity matrix (NxN).
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `MatrixSwarm`: An identity MatrixSwarm.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### determinant()
|
||||||
|
|
||||||
|
Computes the determinant of a square agent matrix.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def determinant(self) -> Any
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Returns
|
||||||
|
- `Any`: The determinant result.
|
||||||
|
|
||||||
|
#### Raises
|
||||||
|
- `ValueError`: If the matrix is not square.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
### save_to_file(path)
|
||||||
|
|
||||||
|
Saves the matrix structure and metadata to a JSON file.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def save_to_file(self, path: str) -> None
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Parameters
|
||||||
|
- `path` (`str`): File path for saving the matrix data.
|
||||||
|
|
||||||
|
## Extended Example
|
||||||
|
|
||||||
|
Here's a comprehensive example demonstrating various MatrixSwarm operations:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import Agent
|
||||||
|
from swarms.matrix import MatrixSwarm
|
||||||
|
|
||||||
|
# Create agents with specific configurations
|
||||||
|
agents = [
|
||||||
|
[
|
||||||
|
Agent(
|
||||||
|
agent_name=f"Agent-{i}-{j}",
|
||||||
|
system_prompt="Your system prompt here",
|
||||||
|
model_name="gpt-4",
|
||||||
|
max_loops=1,
|
||||||
|
verbose=True
|
||||||
|
) for j in range(2)
|
||||||
|
] for i in range(2)
|
||||||
|
]
|
||||||
|
|
||||||
|
# Initialize matrix
|
||||||
|
matrix = MatrixSwarm(agents)
|
||||||
|
|
||||||
|
# Example operations
|
||||||
|
transposed = matrix.transpose()
|
||||||
|
scaled = matrix.scalar_multiply(2)
|
||||||
|
|
||||||
|
# Run operations with inputs
|
||||||
|
inputs = ["Query 1", "Query 2"]
|
||||||
|
results = matrix.multiply(transposed, inputs)
|
||||||
|
|
||||||
|
# Save results
|
||||||
|
matrix.save_to_file("matrix_results.json")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Output Schema
|
||||||
|
|
||||||
|
The `AgentOutput` class defines the structure for operation results:
|
||||||
|
|
||||||
|
```python
|
||||||
|
class AgentOutput(BaseModel):
|
||||||
|
agent_name: str
|
||||||
|
input_query: str
|
||||||
|
output_result: Any
|
||||||
|
metadata: dict
|
||||||
|
```
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
|
||||||
|
1. **Initialization**
|
||||||
|
- Ensure all agents in the matrix are properly configured before initialization
|
||||||
|
- Validate matrix dimensions for your use case
|
||||||
|
|
||||||
|
2. **Operation Performance**
|
||||||
|
- Consider computational costs for large matrices
|
||||||
|
- Use appropriate batch sizes for inputs
|
||||||
|
|
||||||
|
3. **Error Handling**
|
||||||
|
- Implement proper error handling for agent operations
|
||||||
|
- Validate inputs before matrix operations
|
||||||
|
|
||||||
|
4. **Resource Management**
|
||||||
|
- Monitor agent resource usage in large matrices
|
||||||
|
- Implement proper cleanup procedures
|
||||||
|
|
||||||
|
## Limitations
|
||||||
|
|
||||||
|
- Matrix operations are constrained by the underlying agent capabilities
|
||||||
|
- Performance may vary based on agent configuration and complexity
|
||||||
|
- Resource usage scales with matrix dimensions
|
||||||
|
|
||||||
|
## See Also
|
||||||
|
|
||||||
|
- [Swarms Documentation](https://github.com/kyegomez/swarms)
|
||||||
|
- [Agent Class Reference](https://github.com/kyegomez/swarms/tree/main/swarms)
|
||||||
@ -0,0 +1,361 @@
|
|||||||
|
# ModelRouter Docs
|
||||||
|
|
||||||
|
The ModelRouter is an intelligent routing system that automatically selects and executes AI models based on task requirements. It leverages a function-calling architecture to analyze tasks and recommend the optimal model and provider combination for each specific use case.
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
### Key Features
|
||||||
|
|
||||||
|
- Dynamic model selection based on task complexity and requirements
|
||||||
|
- Multi-provider support (OpenAI, Anthropic, Google, etc.)
|
||||||
|
- Concurrent and asynchronous execution capabilities
|
||||||
|
- Batch processing with memory
|
||||||
|
- Automatic error handling and retries
|
||||||
|
- Provider-aware routing
|
||||||
|
- Cost optimization
|
||||||
|
|
||||||
|
### Constructor Arguments
|
||||||
|
|
||||||
|
| Parameter | Type | Default | Description |
|
||||||
|
|-----------|------|---------|-------------|
|
||||||
|
| system_prompt | str | model_router_system_prompt | Custom prompt for guiding model selection behavior |
|
||||||
|
| max_tokens | int | 4000 | Maximum token limit for model outputs |
|
||||||
|
| temperature | float | 0.5 | Control parameter for response randomness (0.0-1.0) |
|
||||||
|
| max_workers | int/str | 10 | Maximum concurrent workers ("auto" for CPU count) |
|
||||||
|
| api_key | str | None | API key for model access |
|
||||||
|
| max_loops | int | 1 | Maximum number of refinement iterations |
|
||||||
|
| *args | Any | None | Additional positional arguments |
|
||||||
|
| **kwargs | Any | None | Additional keyword arguments |
|
||||||
|
|
||||||
|
### Core Methods
|
||||||
|
|
||||||
|
#### run(task: str) -> str
|
||||||
|
|
||||||
|
Executes a single task through the model router with memory and refinement capabilities.
|
||||||
|
|
||||||
|
# Installation
|
||||||
|
|
||||||
|
1. Install the latest version of swarms using pip:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms
|
||||||
|
```
|
||||||
|
|
||||||
|
2. Setup your API Keys in your .env file with the following:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
OPENAI_API_KEY=your_openai_api_key
|
||||||
|
ANTHROPIC_API_KEY=your_anthropic_api_key
|
||||||
|
GOOGLE_API_KEY=your_google_api_key
|
||||||
|
# Add more API keys as needed following litellm format
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import ModelRouter
|
||||||
|
|
||||||
|
router = ModelRouter()
|
||||||
|
|
||||||
|
# Simple text analysis
|
||||||
|
result = router.run("Analyze the sentiment and key themes in this customer feedback")
|
||||||
|
|
||||||
|
# Complex reasoning task
|
||||||
|
complex_result = router.run("""
|
||||||
|
Evaluate the following business proposal:
|
||||||
|
- Initial investment: $500,000
|
||||||
|
- Projected ROI: 25% annually
|
||||||
|
- Market size: $2B
|
||||||
|
- Competition: 3 major players
|
||||||
|
Provide detailed analysis and recommendations.
|
||||||
|
""")
|
||||||
|
```
|
||||||
|
|
||||||
|
#### batch_run(tasks: list) -> list
|
||||||
|
Executes multiple tasks sequentially with result aggregation.
|
||||||
|
|
||||||
|
```python
|
||||||
|
# Multiple analysis tasks
|
||||||
|
tasks = [
|
||||||
|
"Analyze Q1 financial performance",
|
||||||
|
"Predict Q2 market trends",
|
||||||
|
"Evaluate competitor strategies",
|
||||||
|
"Generate growth recommendations"
|
||||||
|
]
|
||||||
|
|
||||||
|
results = router.batch_run(tasks)
|
||||||
|
|
||||||
|
# Process results
|
||||||
|
for task, result in zip(tasks, results):
|
||||||
|
print(f"Task: {task}\nResult: {result}\n")
|
||||||
|
```
|
||||||
|
|
||||||
|
#### concurrent_run(tasks: list) -> list
|
||||||
|
Parallel execution of multiple tasks using thread pooling.
|
||||||
|
|
||||||
|
```python
|
||||||
|
import asyncio
|
||||||
|
from typing import List
|
||||||
|
|
||||||
|
# Define multiple concurrent tasks
|
||||||
|
analysis_tasks = [
|
||||||
|
"Perform technical analysis of AAPL stock",
|
||||||
|
"Analyze market sentiment from social media",
|
||||||
|
"Generate trading signals",
|
||||||
|
"Calculate risk metrics"
|
||||||
|
]
|
||||||
|
|
||||||
|
# Execute tasks concurrently
|
||||||
|
results = router.concurrent_run(analysis_tasks)
|
||||||
|
|
||||||
|
# Process results with error handling
|
||||||
|
for task, result in zip(analysis_tasks, results):
|
||||||
|
try:
|
||||||
|
processed_result = process_analysis(result)
|
||||||
|
save_to_database(processed_result)
|
||||||
|
except Exception as e:
|
||||||
|
log_error(f"Error processing {task}: {str(e)}")
|
||||||
|
```
|
||||||
|
|
||||||
|
#### async_run(task: str) -> asyncio.Task
|
||||||
|
Asynchronous task execution with coroutine support.
|
||||||
|
|
||||||
|
```python
|
||||||
|
async def process_data_stream():
|
||||||
|
tasks = []
|
||||||
|
async for data in data_stream:
|
||||||
|
task = await router.async_run(f"Process data: {data}")
|
||||||
|
tasks.append(task)
|
||||||
|
|
||||||
|
results = await asyncio.gather(*tasks)
|
||||||
|
return results
|
||||||
|
|
||||||
|
# Usage in async context
|
||||||
|
async def main():
|
||||||
|
router = ModelRouter()
|
||||||
|
results = await process_data_stream()
|
||||||
|
```
|
||||||
|
|
||||||
|
### Advanced Usage Examples
|
||||||
|
|
||||||
|
#### Financial Analysis System
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import ModelRouter
|
||||||
|
from typing import Dict, List
|
||||||
|
import pandas as pd
|
||||||
|
|
||||||
|
class FinancialAnalysisSystem:
|
||||||
|
def __init__(self):
|
||||||
|
self.router = ModelRouter(
|
||||||
|
temperature=0.3, # Lower temperature for more deterministic outputs
|
||||||
|
max_tokens=8000, # Higher token limit for detailed analysis
|
||||||
|
max_loops=2 # Allow for refinement iteration
|
||||||
|
)
|
||||||
|
|
||||||
|
def analyze_company_financials(self, financial_data: Dict) -> Dict:
|
||||||
|
analysis_task = f"""
|
||||||
|
Perform comprehensive financial analysis:
|
||||||
|
|
||||||
|
Financial Metrics:
|
||||||
|
- Revenue: ${financial_data['revenue']}M
|
||||||
|
- EBITDA: ${financial_data['ebitda']}M
|
||||||
|
- Debt/Equity: {financial_data['debt_equity']}
|
||||||
|
- Working Capital: ${financial_data['working_capital']}M
|
||||||
|
|
||||||
|
Required Analysis:
|
||||||
|
1. Profitability assessment
|
||||||
|
2. Liquidity analysis
|
||||||
|
3. Growth projections
|
||||||
|
4. Risk evaluation
|
||||||
|
5. Investment recommendations
|
||||||
|
|
||||||
|
Provide detailed insights and actionable recommendations.
|
||||||
|
"""
|
||||||
|
|
||||||
|
result = self.router.run(analysis_task)
|
||||||
|
return self._parse_analysis_result(result)
|
||||||
|
|
||||||
|
def _parse_analysis_result(self, result: str) -> Dict:
|
||||||
|
# Implementation of result parsing
|
||||||
|
pass
|
||||||
|
|
||||||
|
# Usage
|
||||||
|
analyzer = FinancialAnalysisSystem()
|
||||||
|
company_data = {
|
||||||
|
'revenue': 150,
|
||||||
|
'ebitda': 45,
|
||||||
|
'debt_equity': 0.8,
|
||||||
|
'working_capital': 25
|
||||||
|
}
|
||||||
|
|
||||||
|
analysis = analyzer.analyze_company_financials(company_data)
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Healthcare Data Processing Pipeline
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import ModelRouter
|
||||||
|
import pandas as pd
|
||||||
|
from typing import List, Dict
|
||||||
|
|
||||||
|
class MedicalDataProcessor:
|
||||||
|
def __init__(self):
|
||||||
|
self.router = ModelRouter(
|
||||||
|
max_workers="auto", # Automatic worker scaling
|
||||||
|
temperature=0.2, # Conservative temperature for medical analysis
|
||||||
|
system_prompt="""You are a specialized medical data analyzer focused on:
|
||||||
|
1. Clinical terminology interpretation
|
||||||
|
2. Patient data analysis
|
||||||
|
3. Treatment recommendation review
|
||||||
|
4. Medical research synthesis"""
|
||||||
|
)
|
||||||
|
|
||||||
|
async def process_patient_records(self, records: List[Dict]) -> List[Dict]:
|
||||||
|
analysis_tasks = []
|
||||||
|
|
||||||
|
for record in records:
|
||||||
|
task = f"""
|
||||||
|
Analyze patient record:
|
||||||
|
- Age: {record['age']}
|
||||||
|
- Symptoms: {', '.join(record['symptoms'])}
|
||||||
|
- Vital Signs: {record['vitals']}
|
||||||
|
- Medications: {', '.join(record['medications'])}
|
||||||
|
- Lab Results: {record['lab_results']}
|
||||||
|
|
||||||
|
Provide:
|
||||||
|
1. Symptom analysis
|
||||||
|
2. Medication interaction check
|
||||||
|
3. Lab results interpretation
|
||||||
|
4. Treatment recommendations
|
||||||
|
"""
|
||||||
|
analysis_tasks.append(task)
|
||||||
|
|
||||||
|
results = await asyncio.gather(*[
|
||||||
|
self.router.async_run(task) for task in analysis_tasks
|
||||||
|
])
|
||||||
|
|
||||||
|
return [self._parse_medical_analysis(r) for r in results]
|
||||||
|
|
||||||
|
def _parse_medical_analysis(self, analysis: str) -> Dict:
|
||||||
|
# Implementation of medical analysis parsing
|
||||||
|
pass
|
||||||
|
|
||||||
|
# Usage
|
||||||
|
async def main():
|
||||||
|
processor = MedicalDataProcessor()
|
||||||
|
patient_records = [
|
||||||
|
{
|
||||||
|
'age': 45,
|
||||||
|
'symptoms': ['fever', 'cough', 'fatigue'],
|
||||||
|
'vitals': {'bp': '120/80', 'temp': '38.5C'},
|
||||||
|
'medications': ['lisinopril', 'metformin'],
|
||||||
|
'lab_results': 'WBC: 11,000, CRP: 2.5'
|
||||||
|
}
|
||||||
|
# More records...
|
||||||
|
]
|
||||||
|
|
||||||
|
analyses = await processor.process_patient_records(patient_records)
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Natural Language Processing Pipeline
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms import ModelRouter
|
||||||
|
from typing import List, Dict
|
||||||
|
import asyncio
|
||||||
|
|
||||||
|
class NLPPipeline:
|
||||||
|
def __init__(self):
|
||||||
|
self.router = ModelRouter(
|
||||||
|
temperature=0.4,
|
||||||
|
max_loops=2
|
||||||
|
)
|
||||||
|
|
||||||
|
def process_documents(self, documents: List[str]) -> List[Dict]:
|
||||||
|
tasks = [self._create_nlp_task(doc) for doc in documents]
|
||||||
|
results = self.router.concurrent_run(tasks)
|
||||||
|
return [self._parse_nlp_result(r) for r in results]
|
||||||
|
|
||||||
|
def _create_nlp_task(self, document: str) -> str:
|
||||||
|
return f"""
|
||||||
|
Perform comprehensive NLP analysis:
|
||||||
|
|
||||||
|
Text: {document}
|
||||||
|
|
||||||
|
Required Analysis:
|
||||||
|
1. Entity recognition
|
||||||
|
2. Sentiment analysis
|
||||||
|
3. Topic classification
|
||||||
|
4. Key phrase extraction
|
||||||
|
5. Intent detection
|
||||||
|
|
||||||
|
Provide structured analysis with confidence scores.
|
||||||
|
"""
|
||||||
|
|
||||||
|
def _parse_nlp_result(self, result: str) -> Dict:
|
||||||
|
# Implementation of NLP result parsing
|
||||||
|
pass
|
||||||
|
|
||||||
|
# Usage
|
||||||
|
pipeline = NLPPipeline()
|
||||||
|
documents = [
|
||||||
|
"We're extremely satisfied with the new product features!",
|
||||||
|
"The customer service response time needs improvement.",
|
||||||
|
"Looking to upgrade our subscription plan next month."
|
||||||
|
]
|
||||||
|
|
||||||
|
analyses = pipeline.process_documents(documents)
|
||||||
|
```
|
||||||
|
|
||||||
|
### Available Models and Use Cases
|
||||||
|
|
||||||
|
| Model | Provider | Optimal Use Cases | Characteristics |
|
||||||
|
|-------|----------|-------------------|-----------------|
|
||||||
|
| gpt-4-turbo | OpenAI | Complex reasoning, Code generation, Creative writing | High accuracy, Latest knowledge cutoff |
|
||||||
|
| claude-3-opus | Anthropic | Research analysis, Technical documentation, Long-form content | Strong reasoning, Detailed outputs |
|
||||||
|
| gemini-pro | Google | Multimodal tasks, Code generation, Technical analysis | Fast inference, Strong coding abilities |
|
||||||
|
| mistral-large | Mistral | General tasks, Content generation, Classification | Open source, Good price/performance |
|
||||||
|
| deepseek-reasoner | DeepSeek | Mathematical analysis, Logic problems, Scientific computing | Specialized reasoning capabilities |
|
||||||
|
|
||||||
|
### Provider Capabilities
|
||||||
|
|
||||||
|
| Provider | Strengths | Best For | Integration Notes |
|
||||||
|
|----------|-----------|-----------|------------------|
|
||||||
|
| OpenAI | Consistent performance, Strong reasoning | Production systems, Complex tasks | Requires API key setup |
|
||||||
|
| Anthropic | Safety features, Detailed analysis | Research, Technical writing | Claude-specific formatting |
|
||||||
|
| Google | Technical tasks, Multimodal support | Code generation, Analysis | Vertex AI integration available |
|
||||||
|
| Groq | High-speed inference | Real-time applications | Optimized for specific models |
|
||||||
|
| DeepSeek | Specialized reasoning | Scientific computing | Custom API integration |
|
||||||
|
| Mistral | Open source flexibility | General applications | Self-hosted options available |
|
||||||
|
|
||||||
|
|
||||||
|
### Performance Optimization Tips
|
||||||
|
|
||||||
|
1. Token Management
|
||||||
|
- Set appropriate max_tokens based on task complexity
|
||||||
|
- Monitor token usage for cost optimization
|
||||||
|
- Use streaming for long outputs
|
||||||
|
|
||||||
|
2. Concurrency Settings
|
||||||
|
- Adjust max_workers based on system resources
|
||||||
|
- Use "auto" workers for optimal CPU utilization
|
||||||
|
- Monitor memory usage with large batch sizes
|
||||||
|
|
||||||
|
3. Temperature Tuning
|
||||||
|
- Lower (0.1-0.3) for factual/analytical tasks
|
||||||
|
- Higher (0.7-0.9) for creative tasks
|
||||||
|
- Mid-range (0.4-0.6) for balanced outputs
|
||||||
|
|
||||||
|
4. System Prompts
|
||||||
|
- Customize for specific domains
|
||||||
|
- Include relevant context
|
||||||
|
- Define clear output formats
|
||||||
|
|
||||||
|
### Dependencies
|
||||||
|
|
||||||
|
- asyncio: Asynchronous I/O support
|
||||||
|
- concurrent.futures: Thread pool execution
|
||||||
|
- pydantic: Data validation
|
||||||
|
- litellm: LLM interface standardization
|
||||||
@ -1,124 +0,0 @@
|
|||||||
# MultiProcessWorkflow Documentation
|
|
||||||
|
|
||||||
|
|
||||||
The `MultiProcessWorkflow` class provides a framework for executing tasks concurrently using multiple processes. This class leverages Python's `multiprocessing` module to parallelize task execution, thereby enhancing performance and efficiency. It includes features such as automatic task retry on failure and optional autosaving of results. This documentation details the class, its parameters, attributes, methods, and usage examples.
|
|
||||||
|
|
||||||
## Class Definition
|
|
||||||
|
|
||||||
### `MultiProcessWorkflow`
|
|
||||||
|
|
||||||
|
|
||||||
## Parameters
|
|
||||||
|
|
||||||
| Parameter | Type | Default | Description |
|
|
||||||
|---------------|---------------------|---------|---------------------------------------------------------------|
|
|
||||||
| `max_workers` | `int` | `5` | The maximum number of workers to use for parallel processing. |
|
|
||||||
| `autosave` | `bool` | `True` | Flag indicating whether to automatically save the workflow. |
|
|
||||||
| `agents` | `Sequence[Agent]` | `None` | A list of Agent objects representing the workflow agents. |
|
|
||||||
| `*args` | `tuple` | | Additional positional arguments. |
|
|
||||||
| `**kwargs` | `dict` | | Additional keyword arguments. |
|
|
||||||
|
|
||||||
## Attributes
|
|
||||||
|
|
||||||
| Attribute | Type | Description |
|
|
||||||
|-----------------|---------------------|--------------------------------------------------------------|
|
|
||||||
| `max_workers` | `int` | The maximum number of workers to use for parallel processing.|
|
|
||||||
| `autosave` | `bool` | Flag indicating whether to automatically save the workflow. |
|
|
||||||
| `agents` | `Sequence[Agent]` | A list of Agent objects representing the workflow agents. |
|
|
||||||
|
|
||||||
## Methods
|
|
||||||
|
|
||||||
### `execute_task`
|
|
||||||
|
|
||||||
#### Description
|
|
||||||
|
|
||||||
The `execute_task` method executes a given task and handles any exceptions that may occur during execution. If agents are defined, it will execute the task using each agent in sequence.
|
|
||||||
|
|
||||||
#### Usage Example
|
|
||||||
|
|
||||||
```python
|
|
||||||
# Define a task
|
|
||||||
task = Task()
|
|
||||||
|
|
||||||
# Execute the task
|
|
||||||
workflow = MultiProcessWorkflow()
|
|
||||||
result = workflow.execute_task(task)
|
|
||||||
print(result)
|
|
||||||
```
|
|
||||||
|
|
||||||
### `run`
|
|
||||||
|
|
||||||
#### Description
|
|
||||||
|
|
||||||
The `run` method executes the workflow by running the given task using multiple processes. It manages the task execution using a process pool and collects the results.
|
|
||||||
|
|
||||||
#### Usage Example
|
|
||||||
|
|
||||||
```python
|
|
||||||
from swarms.structs.multi_process_workflow import MultiProcessingWorkflow
|
|
||||||
from swarms.structs.task import Task
|
|
||||||
from datetime import datetime
|
|
||||||
from time import sleep
|
|
||||||
|
|
||||||
# Define a simple task
|
|
||||||
def simple_task():
|
|
||||||
sleep(1)
|
|
||||||
return datetime.now()
|
|
||||||
|
|
||||||
# Create a task object
|
|
||||||
task = Task(
|
|
||||||
name="Simple Task",
|
|
||||||
execute=simple_task,
|
|
||||||
priority=1,
|
|
||||||
)
|
|
||||||
|
|
||||||
# Create a workflow with the task
|
|
||||||
workflow = MultiProcessWorkflow(max_workers=3, autosave=True, agents=[agent1, agent2])
|
|
||||||
|
|
||||||
# Run the workflow
|
|
||||||
results = workflow.run(task)
|
|
||||||
|
|
||||||
# Print the results
|
|
||||||
print(results)
|
|
||||||
```
|
|
||||||
|
|
||||||
## Detailed Functionality and Usage
|
|
||||||
|
|
||||||
### Initialization
|
|
||||||
|
|
||||||
When an instance of `MultiProcessWorkflow` is created, it initializes the following:
|
|
||||||
|
|
||||||
- **max_workers**: Sets the maximum number of processes that can run concurrently.
|
|
||||||
- **autosave**: Determines if the workflow results should be saved automatically.
|
|
||||||
- **agents**: Accepts a list of agents that will perform the tasks.
|
|
||||||
|
|
||||||
### Running Tasks
|
|
||||||
|
|
||||||
The `run` method performs the following steps:
|
|
||||||
|
|
||||||
1. **Initialize Results and Manager**: Creates a list to store results and a `Manager` to manage shared state between processes.
|
|
||||||
2. **Initialize Process Pool**: Creates a pool of worker processes.
|
|
||||||
3. **Submit Tasks**: Iterates over the agents, submitting tasks to the pool for execution and collecting the results.
|
|
||||||
4. **Wait for Completion**: Waits for all tasks to complete and collects the results.
|
|
||||||
5. **Return Results**: Returns the list of results from all executed tasks.
|
|
||||||
|
|
||||||
### Autosave Task Result
|
|
||||||
|
|
||||||
Although the autosave functionality is mentioned in the parameters, it is not explicitly defined in the given code. The implementation for autosaving should be added based on the specific requirements of the application.
|
|
||||||
|
|
||||||
## Additional Information and Tips
|
|
||||||
|
|
||||||
- **Process Safety**: The use of `Manager` ensures that the list of results is managed safely across multiple processes.
|
|
||||||
- **Logging**: The class uses the `logger` module to log information about task execution, retries, and failures.
|
|
||||||
- **Error Handling**: The retry mechanism in the `execute_task` method helps in handling transient errors by attempting to re-execute failed tasks.
|
|
||||||
|
|
||||||
## References and Resources
|
|
||||||
|
|
||||||
For more information on multiprocessing in Python, refer to the following resources:
|
|
||||||
|
|
||||||
- [Python Multiprocessing Documentation](https://docs.python.org/3/library/multiprocessing.html)
|
|
||||||
- [Python Logging Documentation](https://docs.python.org/3/library/logging.html)
|
|
||||||
|
|
||||||
---
|
|
||||||
|
|
||||||
By following this detailed documentation, users can effectively understand and utilize the `MultiProcessWorkflow` class to execute tasks concurrently with multiple processes. The examples provided help in demonstrating the practical usage of the class.
|
|
||||||
@ -1,204 +0,0 @@
|
|||||||
# MultiProcessWorkflow Documentation
|
|
||||||
|
|
||||||
The `MultiProcessWorkflow` class extends the `BaseWorkflow` to support parallel processing using multiple workers. This class is designed to efficiently execute tasks concurrently, leveraging the power of multi-processing to enhance performance and scalability.
|
|
||||||
|
|
||||||
### Key Concepts
|
|
||||||
|
|
||||||
- **Parallel Processing**: Utilizing multiple workers to execute tasks concurrently.
|
|
||||||
- **Workflow Management**: Handling the execution of tasks in a structured workflow.
|
|
||||||
- **Agents**: Entities responsible for executing tasks.
|
|
||||||
|
|
||||||
## Attributes
|
|
||||||
|
|
||||||
### Arguments
|
|
||||||
|
|
||||||
| Argument | Type | Default | Description |
|
|
||||||
|--------------|---------------------|---------|-------------|
|
|
||||||
| `max_workers`| `int` | `5` | The maximum number of workers to use for parallel processing. |
|
|
||||||
| `autosave` | `bool` | `True` | Flag indicating whether to automatically save the workflow. |
|
|
||||||
| `agents` | `Sequence[Agent]` | `None` | A list of agents participating in the workflow. |
|
|
||||||
| `*args` | | | Additional positional arguments. |
|
|
||||||
| `**kwargs` | | | Additional keyword arguments. |
|
|
||||||
|
|
||||||
### Attributes
|
|
||||||
|
|
||||||
| Attribute | Type | Description |
|
|
||||||
|--------------|---------------------|-------------|
|
|
||||||
| `max_workers`| `int` | The maximum number of workers to use for parallel processing. |
|
|
||||||
| `autosave` | `bool` | Flag indicating whether to automatically save the workflow. |
|
|
||||||
| `agents` | `Sequence[Agent]` | A list of agents participating in the workflow. |
|
|
||||||
|
|
||||||
## Methods
|
|
||||||
|
|
||||||
### __init__
|
|
||||||
|
|
||||||
Initializes the `MultiProcessWorkflow` with the given parameters.
|
|
||||||
|
|
||||||
**Examples:**
|
|
||||||
|
|
||||||
```python
|
|
||||||
from swarms.structs.agent import Agent
|
|
||||||
from swarms.structs.task import Task
|
|
||||||
from swarms.structs.multi_process_workflow import MultiProcessWorkflow
|
|
||||||
|
|
||||||
agents = [Agent(name="Agent 1"), Agent(name="Agent 2")]
|
|
||||||
tasks = [Task(name="Task 1", execute=lambda: "result1"), Task(name="Task 2", execute=lambda: "result2")]
|
|
||||||
|
|
||||||
workflow = MultiProcessWorkflow(max_workers=3, agents=agents, tasks=tasks)
|
|
||||||
```
|
|
||||||
|
|
||||||
### execute_task
|
|
||||||
|
|
||||||
Executes a task and handles exceptions.
|
|
||||||
|
|
||||||
**Arguments:**
|
|
||||||
|
|
||||||
| Parameter | Type | Description |
|
|
||||||
|-----------|------|-------------|
|
|
||||||
| `task` | `str` | The task to execute. |
|
|
||||||
| `*args` | | Additional positional arguments for the task execution. |
|
|
||||||
| `**kwargs`| | Additional keyword arguments for the task execution. |
|
|
||||||
|
|
||||||
**Returns:**
|
|
||||||
|
|
||||||
| Return Type | Description |
|
|
||||||
|-------------|-------------|
|
|
||||||
| `Any` | The result of the task execution. |
|
|
||||||
|
|
||||||
**Examples:**
|
|
||||||
|
|
||||||
```python
|
|
||||||
result = workflow.execute_task(task="Sample Task")
|
|
||||||
print(result)
|
|
||||||
```
|
|
||||||
|
|
||||||
### run
|
|
||||||
|
|
||||||
Runs the workflow.
|
|
||||||
|
|
||||||
**Arguments:**
|
|
||||||
|
|
||||||
| Parameter | Type | Description |
|
|
||||||
|-----------|------|-------------|
|
|
||||||
| `task` | `str` | The task to run. |
|
|
||||||
| `*args` | | Additional positional arguments for the task execution. |
|
|
||||||
| `**kwargs`| | Additional keyword arguments for the task execution. |
|
|
||||||
|
|
||||||
**Returns:**
|
|
||||||
|
|
||||||
| Return Type | Description |
|
|
||||||
|-------------|-------------|
|
|
||||||
| `List[Any]` | The results of all executed tasks. |
|
|
||||||
|
|
||||||
**Examples:**
|
|
||||||
|
|
||||||
```python
|
|
||||||
results = workflow.run(task="Sample Task")
|
|
||||||
print(results)
|
|
||||||
```
|
|
||||||
|
|
||||||
### Additional Examples
|
|
||||||
|
|
||||||
#### Example 1: Simple Task Execution
|
|
||||||
|
|
||||||
```python
|
|
||||||
from swarms import Agent, Task, MultiProcessWorkflow, OpenAIChat
|
|
||||||
from datetime import datetime
|
|
||||||
from time import sleep
|
|
||||||
|
|
||||||
import os
|
|
||||||
from dotenv import load_dotenv
|
|
||||||
|
|
||||||
# Load the environment variables
|
|
||||||
load_dotenv()
|
|
||||||
|
|
||||||
|
|
||||||
# Define a function to be used as the action
|
|
||||||
def my_action():
|
|
||||||
print("Action executed")
|
|
||||||
|
|
||||||
|
|
||||||
# Define a function to be used as the condition
|
|
||||||
def my_condition():
|
|
||||||
print("Condition checked")
|
|
||||||
return True
|
|
||||||
|
|
||||||
|
|
||||||
# Create an agent
|
|
||||||
agent = Agent(
|
|
||||||
llm=OpenAIChat(openai_api_key=os.environ["OPENAI_API_KEY"]),
|
|
||||||
max_loops=1,
|
|
||||||
dashboard=False,
|
|
||||||
)
|
|
||||||
|
|
||||||
# Create a task
|
|
||||||
task = Task(
|
|
||||||
description=(
|
|
||||||
"Generate a report on the top 3 biggest expenses for small"
|
|
||||||
" businesses and how businesses can save 20%"
|
|
||||||
),
|
|
||||||
agent=agent,
|
|
||||||
)
|
|
||||||
|
|
||||||
# Create a workflow with the task
|
|
||||||
workflow = MultiProcessWorkflow(tasks=[task])
|
|
||||||
|
|
||||||
# Run the workflow
|
|
||||||
results = workflow.run(task)
|
|
||||||
print(results)
|
|
||||||
```
|
|
||||||
|
|
||||||
#### Example 2: Workflow with Multiple Agents
|
|
||||||
|
|
||||||
```python
|
|
||||||
from swarms import Agent, Task, MultiProcessWorkflow
|
|
||||||
|
|
||||||
# Define tasks
|
|
||||||
def task1():
|
|
||||||
return "Task 1 result"
|
|
||||||
|
|
||||||
def task2():
|
|
||||||
return "Task 2 result"
|
|
||||||
|
|
||||||
# Create agents
|
|
||||||
agent1 = Agent(name="Agent 1", llm=OpenAIChat())
|
|
||||||
agent2 = Agent(name="Agent 2", llm=OpenAIChat())
|
|
||||||
|
|
||||||
# Create tasks
|
|
||||||
task_1 = Task(name="Task 1", execute=task1)
|
|
||||||
task_2 = Task(name="Task 2", execute=task2)
|
|
||||||
|
|
||||||
# Create a workflow
|
|
||||||
workflow = MultiProcessWorkflow(agents=[agent1, agent2], tasks=[task_1, task_2])
|
|
||||||
|
|
||||||
# Run the workflow
|
|
||||||
results = workflow.run(task="Example Task")
|
|
||||||
print(results)
|
|
||||||
```
|
|
||||||
|
|
||||||
#### Example 3: Customizing Max Workers
|
|
||||||
|
|
||||||
```python
|
|
||||||
from swarms import Agent, Task, MultiProcessWorkflow, OpenAIChat
|
|
||||||
|
|
||||||
# Define a task
|
|
||||||
def example_task():
|
|
||||||
return "Task result"
|
|
||||||
|
|
||||||
# Create an agent
|
|
||||||
agent = Agent(name="Agent 1", llm=OpenAIChat())
|
|
||||||
|
|
||||||
# Create a task
|
|
||||||
task = Task(name="Example Task", execute=example_task)
|
|
||||||
|
|
||||||
# Create a workflow with custom max workers
|
|
||||||
workflow = MultiProcessWorkflow(max_workers=10, agents=[agent], tasks=[task])
|
|
||||||
|
|
||||||
# Run the workflow
|
|
||||||
results = workflow.run(task="Example Task")
|
|
||||||
print(results)
|
|
||||||
```
|
|
||||||
|
|
||||||
## Summary
|
|
||||||
|
|
||||||
The `MultiProcessWorkflow` class provides a powerful framework for managing and executing tasks using multiple workers. With support for parallel processing, customizable workflows, and detailed logging, it is an ideal tool for complex task execution scenarios. This class enhances performance and scalability, making it suitable for a wide range of applications that require efficient task management.
|
|
||||||
@ -0,0 +1,204 @@
|
|||||||
|
# CreateNow API Documentation
|
||||||
|
|
||||||
|
Welcome to the CreateNow API documentation! This API enables developers to generate AI-powered content, including images, music, videos, and speech, using natural language prompts. Use the endpoints below to start generating content.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## **1. Claim Your API Key**
|
||||||
|
To use the API, you must first claim your API key. Visit the following link to create an account and get your API key:
|
||||||
|
|
||||||
|
### **Claim Your Key**
|
||||||
|
```
|
||||||
|
https://createnow.xyz/account
|
||||||
|
```
|
||||||
|
|
||||||
|
After signing up, your API key will be available in your account dashboard. Keep it secure and include it in your API requests as a Bearer token.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## **2. Generation Endpoint**
|
||||||
|
The generation endpoint allows you to create AI-generated content using natural language prompts.
|
||||||
|
|
||||||
|
### **Endpoint**
|
||||||
|
```
|
||||||
|
POST https://createnow.xyz/api/v1/generate
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Authentication**
|
||||||
|
Include a Bearer token in the `Authorization` header for all requests:
|
||||||
|
```
|
||||||
|
Authorization: Bearer YOUR_API_KEY
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Basic Usage**
|
||||||
|
The simplest way to use the API is to send a prompt. The system will automatically detect the appropriate media type.
|
||||||
|
|
||||||
|
#### **Example Request (Basic)**
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"prompt": "a beautiful sunset over the ocean"
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Advanced Options**
|
||||||
|
You can specify additional parameters for finer control over the output.
|
||||||
|
|
||||||
|
#### **Parameters**
|
||||||
|
| Parameter | Type | Description | Default |
|
||||||
|
|----------------|-----------|---------------------------------------------------------------------------------------------------|--------------|
|
||||||
|
| `prompt` | `string` | The natural language description of the content to generate. | Required |
|
||||||
|
| `type` | `string` | The type of content to generate (`image`, `music`, `video`, `speech`). | Auto-detect |
|
||||||
|
| `count` | `integer` | The number of outputs to generate (1-4). | 1 |
|
||||||
|
| `duration` | `integer` | Duration of audio or video content in seconds (applicable to `music` and `speech`). | N/A |
|
||||||
|
|
||||||
|
#### **Example Request (Advanced)**
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"prompt": "create an upbeat jazz melody",
|
||||||
|
"type": "music",
|
||||||
|
"count": 2,
|
||||||
|
"duration": 30
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Response Format**
|
||||||
|
|
||||||
|
#### **Success Response**
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"success": true,
|
||||||
|
"outputs": [
|
||||||
|
{
|
||||||
|
"url": "https://createnow.xyz/storage/image1.png",
|
||||||
|
"creation_id": "12345",
|
||||||
|
"share_url": "https://createnow.xyz/share/12345"
|
||||||
|
}
|
||||||
|
],
|
||||||
|
"mediaType": "image",
|
||||||
|
"confidence": 0.95,
|
||||||
|
"detected": true
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
#### **Error Response**
|
||||||
|
```json
|
||||||
|
{
|
||||||
|
"error": "Invalid API Key",
|
||||||
|
"status": 401
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## **3. Examples in Multiple Languages**
|
||||||
|
|
||||||
|
### **Python**
|
||||||
|
```python
|
||||||
|
import requests
|
||||||
|
|
||||||
|
url = "https://createnow.xyz/api/v1/generate"
|
||||||
|
headers = {
|
||||||
|
"Authorization": "Bearer YOUR_API_KEY",
|
||||||
|
"Content-Type": "application/json"
|
||||||
|
}
|
||||||
|
|
||||||
|
payload = {
|
||||||
|
"prompt": "a futuristic cityscape at night",
|
||||||
|
"type": "image",
|
||||||
|
"count": 2
|
||||||
|
}
|
||||||
|
|
||||||
|
response = requests.post(url, json=payload, headers=headers)
|
||||||
|
print(response.json())
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Node.js**
|
||||||
|
```javascript
|
||||||
|
const axios = require('axios');
|
||||||
|
|
||||||
|
const url = "https://createnow.xyz/api/v1/generate";
|
||||||
|
const headers = {
|
||||||
|
Authorization: "Bearer YOUR_API_KEY",
|
||||||
|
"Content-Type": "application/json"
|
||||||
|
};
|
||||||
|
|
||||||
|
const payload = {
|
||||||
|
prompt: "a futuristic cityscape at night",
|
||||||
|
type: "image",
|
||||||
|
count: 2
|
||||||
|
};
|
||||||
|
|
||||||
|
axios.post(url, payload, { headers })
|
||||||
|
.then(response => {
|
||||||
|
console.log(response.data);
|
||||||
|
})
|
||||||
|
.catch(error => {
|
||||||
|
console.error(error.response.data);
|
||||||
|
});
|
||||||
|
```
|
||||||
|
|
||||||
|
### **cURL**
|
||||||
|
```bash
|
||||||
|
curl -X POST https://createnow.xyz/api/v1/generate \
|
||||||
|
-H "Authorization: Bearer YOUR_API_KEY" \
|
||||||
|
-H "Content-Type: application/json" \
|
||||||
|
-d '{
|
||||||
|
"prompt": "a futuristic cityscape at night",
|
||||||
|
"type": "image",
|
||||||
|
"count": 2
|
||||||
|
}'
|
||||||
|
```
|
||||||
|
|
||||||
|
### **Java**
|
||||||
|
```java
|
||||||
|
import java.net.HttpURLConnection;
|
||||||
|
import java.net.URL;
|
||||||
|
import java.io.OutputStream;
|
||||||
|
|
||||||
|
public class CreateNowAPI {
|
||||||
|
public static void main(String[] args) throws Exception {
|
||||||
|
URL url = new URL("https://createnow.xyz/api/v1/generate");
|
||||||
|
HttpURLConnection conn = (HttpURLConnection) url.openConnection();
|
||||||
|
conn.setRequestMethod("POST");
|
||||||
|
conn.setRequestProperty("Authorization", "Bearer YOUR_API_KEY");
|
||||||
|
conn.setRequestProperty("Content-Type", "application/json");
|
||||||
|
conn.setDoOutput(true);
|
||||||
|
|
||||||
|
String jsonPayload = "{" +
|
||||||
|
"\"prompt\": \"a futuristic cityscape at night\", " +
|
||||||
|
"\"type\": \"image\", " +
|
||||||
|
"\"count\": 2}";
|
||||||
|
|
||||||
|
OutputStream os = conn.getOutputStream();
|
||||||
|
os.write(jsonPayload.getBytes());
|
||||||
|
os.flush();
|
||||||
|
|
||||||
|
int responseCode = conn.getResponseCode();
|
||||||
|
System.out.println("Response Code: " + responseCode);
|
||||||
|
}
|
||||||
|
}
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## **4. Error Codes**
|
||||||
|
| Status Code | Meaning | Possible Causes |
|
||||||
|
|-------------|----------------------------------|----------------------------------------|
|
||||||
|
| 400 | Bad Request | Invalid parameters or payload. |
|
||||||
|
| 401 | Unauthorized | Invalid or missing API key. |
|
||||||
|
| 402 | Payment Required | Insufficient credits for the request. |
|
||||||
|
| 500 | Internal Server Error | Issue on the server side. |
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## **5. Notes and Limitations**
|
||||||
|
- **Maximum Prompt Length:** 1000 characters.
|
||||||
|
- **Maximum Outputs per Request:** 4.
|
||||||
|
- **Supported Media Types:** `image`, `music`, `video`, `speech`.
|
||||||
|
- **Content Shareability:** Every output includes a unique creation ID and shareable URL.
|
||||||
|
- **Auto-Detection:** Uses advanced natural language processing to determine the most appropriate media type.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
For further support or questions, please contact our support team at [support@createnow.xyz](mailto:support@createnow.xyz).
|
||||||
|
|
||||||
@ -0,0 +1,369 @@
|
|||||||
|
# Swarms Cloud API Client Documentation
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
The Swarms Cloud API Client is a production-grade Python library for interacting with the Swarms Cloud Agent API. It provides a comprehensive interface for managing, executing, and monitoring cloud-based agents.
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
```bash
|
||||||
|
pip install swarms-cloud
|
||||||
|
```
|
||||||
|
|
||||||
|
## Quick Start
|
||||||
|
```python
|
||||||
|
from swarms_cloud import SwarmCloudAPI, AgentCreate
|
||||||
|
|
||||||
|
# Initialize the client
|
||||||
|
client = SwarmCloudAPI(
|
||||||
|
base_url="https://swarmcloud-285321057562.us-central1.run.app",
|
||||||
|
api_key="your_api_key_here"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Create an agent
|
||||||
|
agent_data = AgentCreate(
|
||||||
|
name="TranslateAgent",
|
||||||
|
description="Translates text between languages",
|
||||||
|
code="""
|
||||||
|
def main(request, store):
|
||||||
|
text = request.payload.get('text', '')
|
||||||
|
return f'Translated: {text}'
|
||||||
|
""",
|
||||||
|
requirements="requests==2.25.1",
|
||||||
|
envs="DEBUG=True"
|
||||||
|
)
|
||||||
|
|
||||||
|
new_agent = client.create_agent(agent_data)
|
||||||
|
print(f"Created agent with ID: {new_agent.id}")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Client Configuration
|
||||||
|
|
||||||
|
### Constructor Parameters
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Default | Description |
|
||||||
|
|-----------|------|----------|----------|-------------|
|
||||||
|
| base_url | str | No | https://swarmcloud-285321057562.us-central1.run.app | The base URL of the SwarmCloud API |
|
||||||
|
| api_key | str | Yes | None | Your SwarmCloud API key |
|
||||||
|
| timeout | float | No | 10.0 | Request timeout in seconds |
|
||||||
|
|
||||||
|
## Data Models
|
||||||
|
|
||||||
|
### AgentCreate
|
||||||
|
Model for creating new agents.
|
||||||
|
|
||||||
|
| Field | Type | Required | Default | Description |
|
||||||
|
|-------|------|----------|----------|-------------|
|
||||||
|
| name | str | Yes | - | Name of the agent |
|
||||||
|
| description | str | No | None | Description of the agent's purpose |
|
||||||
|
| code | str | Yes | - | Python code that defines the agent's behavior |
|
||||||
|
| requirements | str | No | None | Python package requirements (pip format) |
|
||||||
|
| envs | str | No | None | Environment variables for the agent |
|
||||||
|
| autoscaling | bool | No | False | Enable/disable concurrent execution scaling |
|
||||||
|
|
||||||
|
### AgentUpdate
|
||||||
|
Model for updating existing agents.
|
||||||
|
|
||||||
|
| Field | Type | Required | Default | Description |
|
||||||
|
|-------|------|----------|----------|-------------|
|
||||||
|
| name | str | No | None | Updated name of the agent |
|
||||||
|
| description | str | No | None | Updated description |
|
||||||
|
| code | str | No | None | Updated Python code |
|
||||||
|
| requirements | str | No | None | Updated package requirements |
|
||||||
|
| autoscaling | bool | No | None | Updated autoscaling setting |
|
||||||
|
|
||||||
|
## API Methods
|
||||||
|
|
||||||
|
### List Agents
|
||||||
|
Retrieve all available agents.
|
||||||
|
|
||||||
|
```python
|
||||||
|
agents = client.list_agents()
|
||||||
|
for agent in agents:
|
||||||
|
print(f"Agent: {agent.name} (ID: {agent.id})")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Returns**: List[AgentOut]
|
||||||
|
|
||||||
|
### Create Agent
|
||||||
|
Create a new agent with the specified configuration.
|
||||||
|
|
||||||
|
```python
|
||||||
|
agent_data = AgentCreate(
|
||||||
|
name="DataProcessor",
|
||||||
|
description="Processes incoming data streams",
|
||||||
|
code="""
|
||||||
|
def main(request, store):
|
||||||
|
data = request.payload.get('data', [])
|
||||||
|
return {'processed': len(data)}
|
||||||
|
""",
|
||||||
|
requirements="pandas==1.4.0\nnumpy==1.21.0",
|
||||||
|
envs="PROCESSING_MODE=fast",
|
||||||
|
autoscaling=True
|
||||||
|
)
|
||||||
|
|
||||||
|
new_agent = client.create_agent(agent_data)
|
||||||
|
```
|
||||||
|
|
||||||
|
**Returns**: AgentOut
|
||||||
|
|
||||||
|
### Get Agent
|
||||||
|
Retrieve details of a specific agent.
|
||||||
|
|
||||||
|
```python
|
||||||
|
agent = client.get_agent("agent_id_here")
|
||||||
|
print(f"Agent details: {agent}")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Parameters**:
|
||||||
|
- agent_id (str): The unique identifier of the agent
|
||||||
|
|
||||||
|
**Returns**: AgentOut
|
||||||
|
|
||||||
|
### Update Agent
|
||||||
|
Update an existing agent's configuration.
|
||||||
|
|
||||||
|
```python
|
||||||
|
update_data = AgentUpdate(
|
||||||
|
name="UpdatedProcessor",
|
||||||
|
description="Enhanced data processing capabilities",
|
||||||
|
code="def main(request, store):\n return {'status': 'updated'}"
|
||||||
|
)
|
||||||
|
|
||||||
|
updated_agent = client.update_agent("agent_id_here", update_data)
|
||||||
|
```
|
||||||
|
|
||||||
|
**Parameters**:
|
||||||
|
- agent_id (str): The unique identifier of the agent
|
||||||
|
- update (AgentUpdate): The update data
|
||||||
|
|
||||||
|
**Returns**: AgentOut
|
||||||
|
|
||||||
|
### Execute Agent
|
||||||
|
Manually execute an agent with optional payload data.
|
||||||
|
|
||||||
|
```python
|
||||||
|
# Execute with payload
|
||||||
|
result = client.execute_agent(
|
||||||
|
"agent_id_here",
|
||||||
|
payload={"text": "Hello, World!"}
|
||||||
|
)
|
||||||
|
|
||||||
|
# Execute without payload
|
||||||
|
result = client.execute_agent("agent_id_here")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Parameters**:
|
||||||
|
- agent_id (str): The unique identifier of the agent
|
||||||
|
- payload (Optional[Dict[str, Any]]): Execution payload data
|
||||||
|
|
||||||
|
**Returns**: Dict[str, Any]
|
||||||
|
|
||||||
|
### Get Agent History
|
||||||
|
Retrieve the execution history and logs for an agent.
|
||||||
|
|
||||||
|
```python
|
||||||
|
history = client.get_agent_history("agent_id_here")
|
||||||
|
for execution in history.executions:
|
||||||
|
print(f"[{execution.timestamp}] {execution.log}")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Parameters**:
|
||||||
|
- agent_id (str): The unique identifier of the agent
|
||||||
|
|
||||||
|
**Returns**: AgentExecutionHistory
|
||||||
|
|
||||||
|
### Batch Execute Agents
|
||||||
|
Execute multiple agents simultaneously with the same payload.
|
||||||
|
|
||||||
|
```python
|
||||||
|
# Get list of agents
|
||||||
|
agents = client.list_agents()
|
||||||
|
|
||||||
|
# Execute batch with payload
|
||||||
|
results = client.batch_execute_agents(
|
||||||
|
agents=agents[:3], # Execute first three agents
|
||||||
|
payload={"data": "test"}
|
||||||
|
)
|
||||||
|
|
||||||
|
print(f"Batch execution results: {results}")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Parameters**:
|
||||||
|
- agents (List[AgentOut]): List of agents to execute
|
||||||
|
- payload (Optional[Dict[str, Any]]): Shared execution payload
|
||||||
|
|
||||||
|
**Returns**: List[Any]
|
||||||
|
|
||||||
|
### Health Check
|
||||||
|
Check the API's health status.
|
||||||
|
|
||||||
|
```python
|
||||||
|
status = client.health()
|
||||||
|
print(f"API Status: {status}")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Returns**: Dict[str, Any]
|
||||||
|
|
||||||
|
## Error Handling
|
||||||
|
The client uses exception handling to manage various error scenarios:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_cloud import SwarmCloudAPI
|
||||||
|
import httpx
|
||||||
|
|
||||||
|
try:
|
||||||
|
client = SwarmCloudAPI(api_key="your_api_key_here")
|
||||||
|
agents = client.list_agents()
|
||||||
|
except httpx.HTTPError as http_err:
|
||||||
|
print(f"HTTP error occurred: {http_err}")
|
||||||
|
except Exception as err:
|
||||||
|
print(f"An unexpected error occurred: {err}")
|
||||||
|
finally:
|
||||||
|
client.close()
|
||||||
|
```
|
||||||
|
|
||||||
|
## Context Manager Support
|
||||||
|
The client can be used with Python's context manager:
|
||||||
|
|
||||||
|
```python
|
||||||
|
with SwarmCloudAPI(api_key="your_api_key_here") as client:
|
||||||
|
status = client.health()
|
||||||
|
print(f"API Status: {status}")
|
||||||
|
# Client automatically closes after the with block
|
||||||
|
```
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
|
||||||
|
1. Always close the client when finished:
|
||||||
|
```python
|
||||||
|
client = SwarmCloudAPI(api_key="your_api_key_here")
|
||||||
|
try:
|
||||||
|
# Your code here
|
||||||
|
finally:
|
||||||
|
client.close()
|
||||||
|
```
|
||||||
|
|
||||||
|
2. Use context managers for automatic cleanup:
|
||||||
|
```python
|
||||||
|
with SwarmCloudAPI(api_key="your_api_key_here") as client:
|
||||||
|
# Your code here
|
||||||
|
```
|
||||||
|
|
||||||
|
3. Handle errors appropriately:
|
||||||
|
```python
|
||||||
|
try:
|
||||||
|
result = client.execute_agent("agent_id", payload={"data": "test"})
|
||||||
|
except httpx.HTTPError as e:
|
||||||
|
logger.error(f"HTTP error: {e}")
|
||||||
|
# Handle error appropriately
|
||||||
|
```
|
||||||
|
|
||||||
|
4. Set appropriate timeouts for your use case:
|
||||||
|
```python
|
||||||
|
client = SwarmCloudAPI(
|
||||||
|
api_key="your_api_key_here",
|
||||||
|
timeout=30.0 # Longer timeout for complex operations
|
||||||
|
)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Complete Example
|
||||||
|
Here's a complete example showcasing various features of the client:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_cloud import SwarmCloudAPI, AgentCreate, AgentUpdate
|
||||||
|
import httpx
|
||||||
|
|
||||||
|
def main():
|
||||||
|
with SwarmCloudAPI(api_key="your_api_key_here") as client:
|
||||||
|
# Create an agent
|
||||||
|
agent_data = AgentCreate(
|
||||||
|
name="DataAnalyzer",
|
||||||
|
description="Analyzes incoming data streams",
|
||||||
|
code="""
|
||||||
|
def main(request, store):
|
||||||
|
data = request.payload.get('data', [])
|
||||||
|
return {
|
||||||
|
'count': len(data),
|
||||||
|
'summary': 'Data processed successfully'
|
||||||
|
}
|
||||||
|
""",
|
||||||
|
requirements="pandas==1.4.0",
|
||||||
|
autoscaling=True
|
||||||
|
)
|
||||||
|
|
||||||
|
try:
|
||||||
|
# Create the agent
|
||||||
|
new_agent = client.create_agent(agent_data)
|
||||||
|
print(f"Created agent: {new_agent.name} (ID: {new_agent.id})")
|
||||||
|
|
||||||
|
# Execute the agent
|
||||||
|
result = client.execute_agent(
|
||||||
|
new_agent.id,
|
||||||
|
payload={"data": [1, 2, 3, 4, 5]}
|
||||||
|
)
|
||||||
|
print(f"Execution result: {result}")
|
||||||
|
|
||||||
|
# Update the agent
|
||||||
|
update_data = AgentUpdate(
|
||||||
|
description="Enhanced data analysis capabilities"
|
||||||
|
)
|
||||||
|
updated_agent = client.update_agent(new_agent.id, update_data)
|
||||||
|
print(f"Updated agent: {updated_agent.name}")
|
||||||
|
|
||||||
|
# Get execution history
|
||||||
|
history = client.get_agent_history(new_agent.id)
|
||||||
|
print(f"Execution history: {history}")
|
||||||
|
|
||||||
|
except httpx.HTTPError as e:
|
||||||
|
print(f"HTTP error occurred: {e}")
|
||||||
|
except Exception as e:
|
||||||
|
print(f"Unexpected error: {e}")
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
|
```
|
||||||
|
|
||||||
|
## Logging
|
||||||
|
The client uses the `loguru` library for logging. You can configure the logging level and format:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from loguru import logger
|
||||||
|
|
||||||
|
# Configure logging
|
||||||
|
logger.add("swarmcloud.log", rotation="500 MB")
|
||||||
|
|
||||||
|
client = SwarmCloudAPI(api_key="your_api_key_here")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Performance Considerations
|
||||||
|
|
||||||
|
1. **Connection Reuse**: The client reuses HTTP connections by default, improving performance for multiple requests.
|
||||||
|
|
||||||
|
2. **Timeout Configuration**: Set appropriate timeouts based on your use case:
|
||||||
|
```python
|
||||||
|
client = SwarmCloudAPI(
|
||||||
|
api_key="your_api_key_here",
|
||||||
|
timeout=5.0 # Shorter timeout for time-sensitive operations
|
||||||
|
)
|
||||||
|
```
|
||||||
|
|
||||||
|
3. **Batch Operations**: Use batch_execute_agents for multiple agent executions:
|
||||||
|
```python
|
||||||
|
results = client.batch_execute_agents(
|
||||||
|
agents=agents,
|
||||||
|
payload=shared_payload
|
||||||
|
)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Rate Limiting
|
||||||
|
The client respects API rate limits but does not implement retry logic. Implement your own retry mechanism if needed:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from tenacity import retry, stop_after_attempt, wait_exponential
|
||||||
|
|
||||||
|
@retry(stop=stop_after_attempt(3), wait=wait_exponential(multiplier=1, min=4, max=10))
|
||||||
|
def execute_with_retry(client, agent_id, payload):
|
||||||
|
return client.execute_agent(agent_id, payload)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Thread Safety
|
||||||
|
The client is not thread-safe by default. For concurrent usage, create separate client instances for each thread or implement appropriate synchronization mechanisms.
|
||||||
@ -0,0 +1,189 @@
|
|||||||
|
# Swarms Platform Account Management Documentation
|
||||||
|
|
||||||
|
This guide provides comprehensive, production-grade documentation for managing your account on the Swarms Platform. It covers account settings, profile management, billing, payment methods, subscription details, and cryptocurrency wallet management. Use this documentation to navigate the account management interface, understand available options, and perform account-related operations efficiently and securely.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Table of Contents
|
||||||
|
|
||||||
|
1. [Overview](#overview)
|
||||||
|
2. [Accessing the Account Management Page](#accessing-the-account-management-page)
|
||||||
|
3. [Account Settings](#account-settings)
|
||||||
|
- [Theme Mode](#theme-mode)
|
||||||
|
4. [Profile Management](#profile-management)
|
||||||
|
- [Profile Information](#profile-information)
|
||||||
|
- [Password Management](#password-management)
|
||||||
|
5. [Billing and Payment Methods](#billing-and-payment-methods)
|
||||||
|
- [Subscription Status](#subscription-status)
|
||||||
|
- [Payment Methods](#payment-methods)
|
||||||
|
6. [Cryptocurrency Wallet](#cryptocurrency-wallet)
|
||||||
|
- [Wallet Overview](#wallet-overview)
|
||||||
|
- [Exchange and Transaction History](#exchange-and-transaction-history)
|
||||||
|
7. [Additional Resources](#additional-resources)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
The Swarms Platform account management page, available at [https://swarms.world/platform/account](https://swarms.world/platform/account), allows you to configure and update your account settings and preferences. From here, you can manage the appearance of the platform, view and update profile details, manage your billing information and subscriptions, and handle your cryptocurrency wallet operations.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Accessing the Account Management Page
|
||||||
|
|
||||||
|
To access your account management dashboard:
|
||||||
|
1. Log in to your Swarms Platform account.
|
||||||
|
2. Navigate to [https://swarms.world/platform/account](https://swarms.world/platform/account).
|
||||||
|
|
||||||
|
Once on this page, you will see several sections dedicated to different aspects of your account:
|
||||||
|
|
||||||
|
- **Account Settings:** Customize the platform appearance and user interface.
|
||||||
|
- **Profile:** View and manage personal details.
|
||||||
|
- **Billing:** Review credits, invoices, and manage your payment methods.
|
||||||
|
- **Crypto:** Manage your cryptocurrency wallet and transactions.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Account Settings
|
||||||
|
|
||||||
|
This section allows you to modify your personal account preferences, including the visual theme.
|
||||||
|
|
||||||
|
### Theme Mode
|
||||||
|
|
||||||
|
You can choose between different theme options to tailor your user experience:
|
||||||
|
|
||||||
|
- **Single Theme:**
|
||||||
|
A fixed theme, independent of system settings.
|
||||||
|
- **Example:**
|
||||||
|
- **Logo:** Swarms logo
|
||||||
|
- **Terminal Command:**
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms
|
||||||
|
```
|
||||||
|
- **Theme Options:**
|
||||||
|
- **light**
|
||||||
|
- **dark (default)**
|
||||||
|
|
||||||
|
- **Sync with System Theme:**
|
||||||
|
Automatically adjusts the platform theme to match your system's theme settings.
|
||||||
|
|
||||||
|
Select the theme mode that best fits your workflow. Changes are applied immediately across the platform.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Profile Management
|
||||||
|
|
||||||
|
### Profile Information
|
||||||
|
|
||||||
|
The Profile section allows you to view and update your personal details:
|
||||||
|
|
||||||
|
- **View Details:**
|
||||||
|
Your current profile information is displayed, including contact details, username, and any additional settings.
|
||||||
|
|
||||||
|
- **Manage Profile:**
|
||||||
|
Options to update your information, ensuring your account details remain current.
|
||||||
|
|
||||||
|
### Password Management
|
||||||
|
|
||||||
|
For security purposes, it is important to regularly update your password:
|
||||||
|
|
||||||
|
- **Change Password:**
|
||||||
|
Select the **"Change password"** option to update your login credentials.
|
||||||
|
Ensure you choose a strong password and keep it confidential.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Billing and Payment Methods
|
||||||
|
|
||||||
|
The Billing section helps you manage financial aspects of your account, including credits, invoices, and subscriptions.
|
||||||
|
|
||||||
|
### Subscription Status
|
||||||
|
|
||||||
|
Your subscription details are clearly displayed:
|
||||||
|
|
||||||
|
- **Current Plan:**
|
||||||
|
Options include **Free**, **Premium**, or **Enterprise**.
|
||||||
|
|
||||||
|
- **Status:**
|
||||||
|
The active subscription status is indicated (e.g., "Active").
|
||||||
|
|
||||||
|
- **Customer Portal:**
|
||||||
|
An option to open the customer portal for additional billing and subscription management.
|
||||||
|
|
||||||
|
### Payment Methods
|
||||||
|
|
||||||
|
Manage your payment methods and review your billing details:
|
||||||
|
|
||||||
|
- **Manage Cards:**
|
||||||
|
View existing payment methods.
|
||||||
|
**Example Entry:**
|
||||||
|
- **Card Type:** mastercard
|
||||||
|
- **Last 4 Digits:** ending in 9491
|
||||||
|
- **Expiry Date:** 2030/2
|
||||||
|
|
||||||
|
- **Add Card:**
|
||||||
|
Use the **"Add Card"** option to register a new payment method securely.
|
||||||
|
|
||||||
|
### Credit System
|
||||||
|
|
||||||
|
Details of the credits available for your account:
|
||||||
|
|
||||||
|
- **Credits Available:**
|
||||||
|
Displays the current credit balance (e.g., `$20.00`).
|
||||||
|
|
||||||
|
- **Charge:**
|
||||||
|
Option to apply charges against your available credits.
|
||||||
|
|
||||||
|
- **Invoice:**
|
||||||
|
Review or download your invoices.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Cryptocurrency Wallet
|
||||||
|
|
||||||
|
The Crypto section provides management tools for your cryptocurrency wallet and associated transactions.
|
||||||
|
|
||||||
|
### Wallet Overview
|
||||||
|
|
||||||
|
- **Connected Wallet:**
|
||||||
|
Displays your linked wallet information.
|
||||||
|
- **Example:**
|
||||||
|
- **Wallet Identifier:** A truncated wallet ID (e.g., `EmVa...79Vb`)
|
||||||
|
|
||||||
|
- **$swarms Balance and Price:**
|
||||||
|
- **Balance:**
|
||||||
|
Displays your current $swarms balance (e.g., `0.00`).
|
||||||
|
- **Price:**
|
||||||
|
Current market price for $swarms (e.g., `$0.0400`).
|
||||||
|
|
||||||
|
### Exchange and Transaction History
|
||||||
|
|
||||||
|
- **Exchange Functionality:**
|
||||||
|
Option to exchange $swarms tokens for credits directly through the platform.
|
||||||
|
|
||||||
|
- **Transaction History:**
|
||||||
|
View a detailed log of wallet transactions, ensuring full transparency over all exchanges and wallet activity.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Additional Resources
|
||||||
|
|
||||||
|
For further assistance or to learn more about managing your account on the Swarms Platform, refer to the following resources:
|
||||||
|
|
||||||
|
- [Help Center](https://swarms.world/help)
|
||||||
|
- [Customer Support](https://cal.com/swarms)
|
||||||
|
- [API Documentation](https://swarms.world/platform/api-keys) (for developers)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
|
||||||
|
- **Regular Updates:**
|
||||||
|
Periodically review your account settings, profile, and payment methods to ensure they are up-to-date.
|
||||||
|
|
||||||
|
- **Security Measures:**
|
||||||
|
Always use strong, unique passwords and consider enabling two-factor authentication if available.
|
||||||
|
|
||||||
|
- **Monitor Transactions:**
|
||||||
|
Regularly check your billing and wallet transaction history to detect any unauthorized activities promptly.
|
||||||
|
|
||||||
@ -0,0 +1,87 @@
|
|||||||
|
# Swarms Platform API Keys Documentation
|
||||||
|
|
||||||
|
This document provides detailed information on managing API keys within the Swarms Platform. API keys grant programmatic access to your account and should be handled securely. Follow the guidelines below to manage your API keys safely and effectively.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Table of Contents
|
||||||
|
|
||||||
|
1. [Overview](#overview)
|
||||||
|
2. [Viewing Your API Keys](#viewing-your-api-keys)
|
||||||
|
3. [Creating a New API Key](#creating-a-new-api-key)
|
||||||
|
4. [Security Guidelines](#security-guidelines)
|
||||||
|
5. [Frequently Asked Questions](#frequently-asked-questions)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
|
||||||
|
API keys are unique credentials that allow you to interact with the Swarms Platform programmatically. These keys enable you to make authenticated API requests to access or modify your data. **Important:** Once a secret API key is generated, it will not be displayed again. Ensure you store it securely, as it cannot be retrieved from the platform later.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Viewing Your API Keys
|
||||||
|
|
||||||
|
When you navigate to the API Keys page ([https://swarms.world/platform/api-keys](https://swarms.world/platform/api-keys)), you will see a list of your API keys along with the following information:
|
||||||
|
|
||||||
|
### Key Details:
|
||||||
|
|
||||||
|
- **Name:** A label you assign to your API key to help you identify it.
|
||||||
|
- **Key:** The secret API key is only partially visible here for security reasons.
|
||||||
|
- **Created Date:** The date when the API key was generated.
|
||||||
|
- **Actions:** Options available for managing the key (e.g., deleting an API key).
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Creating a New API Key
|
||||||
|
|
||||||
|
To generate a new API key, follow these steps:
|
||||||
|
|
||||||
|
1. **Attach a Credit Card:**
|
||||||
|
Before creating a new API key, ensure that your account has a credit card attached. This is required for authentication and billing purposes.
|
||||||
|
|
||||||
|
2. **Access the API Keys Page:**
|
||||||
|
Navigate to [https://swarms.world/platform/api-keys](https://swarms.world/platform/api-keys).
|
||||||
|
|
||||||
|
3. **Generate a New Key:**
|
||||||
|
Click on the **"Create new API key"** button. The system will generate a new secret API key for your account.
|
||||||
|
|
||||||
|
4. **Store Your API Key Securely:**
|
||||||
|
Once generated, the full API key will be displayed only once. Copy and store it in a secure location, as it will not be displayed again.
|
||||||
|
**Note:** Do not share your API key with anyone or expose it in any client-side code (e.g., browser JavaScript).
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Security Guidelines
|
||||||
|
|
||||||
|
- **Confidentiality:**
|
||||||
|
Your API keys are sensitive credentials. Do not share them with anyone or include them in public repositories or client-side code.
|
||||||
|
|
||||||
|
- **Storage:**
|
||||||
|
Store your API keys in secure, encrypted storage. Avoid saving them in plain text files or unsecured locations.
|
||||||
|
|
||||||
|
- **Rotation:**
|
||||||
|
If you suspect that your API key has been compromised, immediately delete it and create a new one.
|
||||||
|
|
||||||
|
- **Access Control:**
|
||||||
|
Limit access to your API keys to only those systems and personnel who absolutely require it.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Frequently Asked Questions
|
||||||
|
|
||||||
|
### Q1: **Why do I need a credit card attached to my account to create an API key?**
|
||||||
|
**A:** The requirement to attach a credit card helps verify your identity and manage billing, ensuring responsible usage of the API services provided by the Swarms Platform.
|
||||||
|
|
||||||
|
### Q2: **What happens if I lose my API key?**
|
||||||
|
**A:** If you lose your API key, you will need to generate a new one. The platform does not store the full key after its initial generation, so recovery is not possible.
|
||||||
|
|
||||||
|
### Q3: **How can I delete an API key?**
|
||||||
|
**A:** On the API Keys page, locate the key you wish to delete and click the **"Delete"** action next to it. This will revoke the key's access immediately.
|
||||||
|
|
||||||
|
### Q4: **Can I have multiple API keys?**
|
||||||
|
**A:** Yes, you can generate and manage multiple API keys. Use naming conventions to keep track of their usage and purpose.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
For any further questions or issues regarding API key management, please refer to our [Help Center](https://swarms.world/help) or contact our support team.
|
||||||
@ -0,0 +1,324 @@
|
|||||||
|
# Swarms Finance Tools Documentation
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms-tools yfinance requests httpx pandas loguru backoff web3 solana spl-token
|
||||||
|
```
|
||||||
|
|
||||||
|
## Environment Variables
|
||||||
|
|
||||||
|
Create a `.env` file in your project root with the following variables (as needed):
|
||||||
|
|
||||||
|
| Environment Variable | Description | Required For |
|
||||||
|
|---------------------|-------------|--------------|
|
||||||
|
| `COINBASE_API_KEY` | Coinbase API Key | Coinbase Trading |
|
||||||
|
| `COINBASE_API_SECRET` | Coinbase API Secret | Coinbase Trading |
|
||||||
|
| `COINBASE_API_PASSPHRASE` | Coinbase API Passphrase | Coinbase Trading |
|
||||||
|
| `COINMARKETCAP_API_KEY` | CoinMarketCap API Key | CoinMarketCap Data |
|
||||||
|
| `HELIUS_API_KEY` | Helius API Key | Solana Data |
|
||||||
|
| `EODHD_API_KEY` | EODHD API Key | Stock News |
|
||||||
|
| `OKX_API_KEY` | OKX API Key | OKX Trading |
|
||||||
|
| `OKX_API_SECRET` | OKX API Secret | OKX Trading |
|
||||||
|
| `OKX_PASSPHRASE` | OKX Passphrase | OKX Trading |
|
||||||
|
|
||||||
|
## Tools Overview
|
||||||
|
|
||||||
|
| Tool | Description | Requires API Key |
|
||||||
|
|------|-------------|-----------------|
|
||||||
|
| Yahoo Finance | Real-time stock market data | No |
|
||||||
|
| CoinGecko | Cryptocurrency market data | No |
|
||||||
|
| Coinbase | Cryptocurrency trading and data | Yes |
|
||||||
|
| CoinMarketCap | Cryptocurrency market data | Yes |
|
||||||
|
| Helius | Solana blockchain data | Yes |
|
||||||
|
| DexScreener | DEX trading pairs and data | No |
|
||||||
|
| HTX (Huobi) | Cryptocurrency exchange data | No |
|
||||||
|
| OKX | Cryptocurrency exchange data | Yes |
|
||||||
|
| EODHD | Stock market news | Yes |
|
||||||
|
| Jupiter | Solana DEX aggregator | No |
|
||||||
|
| Sector Analysis | GICS sector ETF analysis | No |
|
||||||
|
| Solana Tools | Solana wallet and token tools | Yes |
|
||||||
|
|
||||||
|
## Detailed Documentation
|
||||||
|
|
||||||
|
### Yahoo Finance API
|
||||||
|
|
||||||
|
Fetch real-time and historical stock market data.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import yahoo_finance_api
|
||||||
|
|
||||||
|
# Fetch data for single stock
|
||||||
|
data = yahoo_finance_api(["AAPL"])
|
||||||
|
|
||||||
|
# Fetch data for multiple stocks
|
||||||
|
data = yahoo_finance_api(["AAPL", "GOOG", "MSFT"])
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| stock_symbols | List[str] | List of stock symbols | Yes |
|
||||||
|
|
||||||
|
### CoinGecko API
|
||||||
|
|
||||||
|
Fetch comprehensive cryptocurrency data.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import coin_gecko_coin_api
|
||||||
|
|
||||||
|
# Fetch Bitcoin data
|
||||||
|
data = coin_gecko_coin_api("bitcoin")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| coin | str | Cryptocurrency ID (e.g., 'bitcoin') | Yes |
|
||||||
|
|
||||||
|
### Coinbase Trading
|
||||||
|
|
||||||
|
Execute trades and fetch market data from Coinbase.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import get_coin_data, place_buy_order, place_sell_order
|
||||||
|
|
||||||
|
# Fetch coin data
|
||||||
|
data = get_coin_data("BTC-USD")
|
||||||
|
|
||||||
|
# Place orders
|
||||||
|
buy_order = place_buy_order("BTC-USD", amount=100) # Buy $100 worth of BTC
|
||||||
|
sell_order = place_sell_order("BTC-USD", amount=0.01) # Sell 0.01 BTC
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| symbol | str | Trading pair (e.g., 'BTC-USD') | Yes |
|
||||||
|
| amount | Union[str, float, Decimal] | Trade amount | Yes |
|
||||||
|
| sandbox | bool | Use sandbox environment | No |
|
||||||
|
|
||||||
|
### CoinMarketCap API
|
||||||
|
|
||||||
|
Fetch cryptocurrency market data from CoinMarketCap.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import coinmarketcap_api
|
||||||
|
|
||||||
|
# Fetch single coin data
|
||||||
|
data = coinmarketcap_api(["Bitcoin"])
|
||||||
|
|
||||||
|
# Fetch multiple coins
|
||||||
|
data = coinmarketcap_api(["Bitcoin", "Ethereum", "Tether"])
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| coin_names | Optional[List[str]] | List of coin names | No |
|
||||||
|
|
||||||
|
### Helius API (Solana)
|
||||||
|
|
||||||
|
Fetch Solana blockchain data.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import helius_api_tool
|
||||||
|
|
||||||
|
# Fetch account data
|
||||||
|
account_data = helius_api_tool("account", "account_address")
|
||||||
|
|
||||||
|
# Fetch transaction data
|
||||||
|
tx_data = helius_api_tool("transaction", "tx_signature")
|
||||||
|
|
||||||
|
# Fetch token data
|
||||||
|
token_data = helius_api_tool("token", "token_mint_address")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| action | str | Type of action ('account', 'transaction', 'token') | Yes |
|
||||||
|
| identifier | str | Address/signature to query | Yes |
|
||||||
|
|
||||||
|
### DexScreener API
|
||||||
|
|
||||||
|
Fetch DEX trading pair data.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import (
|
||||||
|
fetch_dex_screener_profiles,
|
||||||
|
fetch_latest_token_boosts,
|
||||||
|
fetch_solana_token_pairs
|
||||||
|
)
|
||||||
|
|
||||||
|
# Fetch latest profiles
|
||||||
|
profiles = fetch_dex_screener_profiles()
|
||||||
|
|
||||||
|
# Fetch token boosts
|
||||||
|
boosts = fetch_latest_token_boosts()
|
||||||
|
|
||||||
|
# Fetch Solana pairs
|
||||||
|
pairs = fetch_solana_token_pairs(["token_address"])
|
||||||
|
```
|
||||||
|
|
||||||
|
### HTX (Huobi) API
|
||||||
|
|
||||||
|
Fetch cryptocurrency data from HTX.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import fetch_htx_data
|
||||||
|
|
||||||
|
# Fetch coin data
|
||||||
|
data = fetch_htx_data("BTC")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| coin_name | str | Cryptocurrency symbol | Yes |
|
||||||
|
|
||||||
|
### OKX API
|
||||||
|
|
||||||
|
Fetch cryptocurrency data from OKX.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import okx_api_tool
|
||||||
|
|
||||||
|
# Fetch single coin
|
||||||
|
data = okx_api_tool(["BTC-USDT"])
|
||||||
|
|
||||||
|
# Fetch multiple coins
|
||||||
|
data = okx_api_tool(["BTC-USDT", "ETH-USDT"])
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| coin_symbols | Optional[List[str]] | List of trading pairs | No |
|
||||||
|
|
||||||
|
### EODHD Stock News
|
||||||
|
|
||||||
|
Fetch stock market news.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import fetch_stock_news
|
||||||
|
|
||||||
|
# Fetch news for a stock
|
||||||
|
news = fetch_stock_news("AAPL")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| stock_name | str | Stock symbol | Yes |
|
||||||
|
|
||||||
|
### Jupiter (Solana DEX)
|
||||||
|
|
||||||
|
Fetch Solana DEX prices.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import get_jupiter_price
|
||||||
|
|
||||||
|
# Fetch price data
|
||||||
|
price = get_jupiter_price(input_mint="input_token", output_mint="output_token")
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| input_mint | str | Input token mint address | Yes |
|
||||||
|
| output_mint | str | Output token mint address | Yes |
|
||||||
|
|
||||||
|
### Sector Analysis
|
||||||
|
|
||||||
|
Analyze GICS sector ETFs.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance.sector_analysis import analyze_index_sectors
|
||||||
|
|
||||||
|
# Run sector analysis
|
||||||
|
analyze_index_sectors()
|
||||||
|
```
|
||||||
|
|
||||||
|
### Solana Tools
|
||||||
|
|
||||||
|
Check Solana wallet balances and manage tokens.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import check_solana_balance, check_multiple_wallets
|
||||||
|
|
||||||
|
# Check single wallet
|
||||||
|
balance = check_solana_balance("wallet_address")
|
||||||
|
|
||||||
|
# Check multiple wallets
|
||||||
|
balances = check_multiple_wallets(["wallet1", "wallet2"])
|
||||||
|
```
|
||||||
|
|
||||||
|
**Arguments:**
|
||||||
|
|
||||||
|
| Parameter | Type | Description | Required |
|
||||||
|
|-----------|------|-------------|----------|
|
||||||
|
| wallet_address | str | Solana wallet address | Yes |
|
||||||
|
| wallet_addresses | List[str] | List of wallet addresses | Yes |
|
||||||
|
|
||||||
|
## Complete Example
|
||||||
|
|
||||||
|
Here's a comprehensive example using multiple tools:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance import (
|
||||||
|
yahoo_finance_api,
|
||||||
|
coin_gecko_coin_api,
|
||||||
|
coinmarketcap_api,
|
||||||
|
fetch_htx_data
|
||||||
|
)
|
||||||
|
|
||||||
|
# Fetch stock data
|
||||||
|
stocks = yahoo_finance_api(["AAPL", "GOOG"])
|
||||||
|
print("Stock Data:", stocks)
|
||||||
|
|
||||||
|
# Fetch crypto data from multiple sources
|
||||||
|
bitcoin_cg = coin_gecko_coin_api("bitcoin")
|
||||||
|
print("Bitcoin Data (CoinGecko):", bitcoin_cg)
|
||||||
|
|
||||||
|
crypto_cmc = coinmarketcap_api(["Bitcoin", "Ethereum"])
|
||||||
|
print("Crypto Data (CoinMarketCap):", crypto_cmc)
|
||||||
|
|
||||||
|
btc_htx = fetch_htx_data("BTC")
|
||||||
|
print("Bitcoin Data (HTX):", btc_htx)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Error Handling
|
||||||
|
|
||||||
|
All tools include proper error handling and logging. Errors are logged using the `loguru` logger. Example error handling:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from loguru import logger
|
||||||
|
|
||||||
|
try:
|
||||||
|
data = yahoo_finance_api(["INVALID"])
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"Error fetching stock data: {e}")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Rate Limits
|
||||||
|
|
||||||
|
Please be aware of rate limits for various APIs:
|
||||||
|
- CoinGecko: 50 calls/minute (free tier)
|
||||||
|
- CoinMarketCap: Varies by subscription
|
||||||
|
- Helius: Varies by subscription
|
||||||
|
- DexScreener: 300 calls/minute for pairs, 60 calls/minute for profiles
|
||||||
|
- Other APIs: Refer to respective documentation
|
||||||
|
|
||||||
|
## Dependencies
|
||||||
|
|
||||||
|
The package automatically handles most dependencies, but you may need to install some manually:
|
||||||
@ -0,0 +1,239 @@
|
|||||||
|
# Swarms Tools
|
||||||
|
|
||||||
|
|
||||||
|
Welcome to **Swarms Tools**, the ultimate package for integrating **cutting-edge APIs** into Python functions with seamless multi-agent system compatibility. Designed for enterprises at the forefront of innovation, **Swarms Tools** is your key to simplifying complexity and unlocking operational excellence.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🚀 Features
|
||||||
|
|
||||||
|
- **Unified API Integration**: Ready-to-use Python functions for financial data, social media, IoT, and more.
|
||||||
|
- **Enterprise-Grade Design**: Comprehensive type hints, structured outputs, and robust documentation.
|
||||||
|
- **Agent-Ready Framework**: Optimized for seamless integration into Swarms' multi-agent orchestration systems.
|
||||||
|
- **Expandable Architecture**: Easily extend functionality with a standardized schema for new tools.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🔧 Installation
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms-tools
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 📂 Directory Structure
|
||||||
|
|
||||||
|
```plaintext
|
||||||
|
swarms-tools/
|
||||||
|
├── swarms_tools/
|
||||||
|
│ ├── finance/
|
||||||
|
│ │ ├── htx_tool.py
|
||||||
|
│ │ ├── eodh_api.py
|
||||||
|
│ │ └── coingecko_tool.py
|
||||||
|
│ ├── social_media/
|
||||||
|
│ │ ├── telegram_tool.py
|
||||||
|
│ ├── utilities/
|
||||||
|
│ │ └── logging.py
|
||||||
|
├── tests/
|
||||||
|
│ ├── test_financial_data.py
|
||||||
|
│ └── test_social_media.py
|
||||||
|
└── README.md
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 💼 Use Cases
|
||||||
|
|
||||||
|
|
||||||
|
|
||||||
|
## Finance
|
||||||
|
|
||||||
|
Explore our diverse range of financial tools, designed to streamline your operations. If you need a tool not listed, feel free to submit an issue or accelerate integration by contributing a pull request with your tool of choice.
|
||||||
|
|
||||||
|
| **Tool Name** | **Function** | **Description** |
|
||||||
|
|---------------------------|--------------------------|---------------------------------------------------------------------------------|
|
||||||
|
| `fetch_stock_news` | `fetch_stock_news` | Fetches the latest stock news and updates. |
|
||||||
|
| `fetch_htx_data` | `fetch_htx_data` | Retrieves financial data from the HTX platform. |
|
||||||
|
| `yahoo_finance_api` | `yahoo_finance_api` | Fetches comprehensive stock data from Yahoo Finance, including prices and trends. |
|
||||||
|
| `coin_gecko_coin_api` | `coin_gecko_coin_api` | Fetches cryptocurrency data from CoinGecko, including market and price information. |
|
||||||
|
| `helius_api_tool` | `helius_api_tool` | Retrieves blockchain account, transaction, or token data using the Helius API. |
|
||||||
|
| `okx_api_tool` | `okx_api_tool` | Fetches detailed cryptocurrency data for coins from the OKX exchange. |
|
||||||
|
|
||||||
|
|
||||||
|
### Financial Data Retrieval
|
||||||
|
Enable precise and actionable financial insights:
|
||||||
|
|
||||||
|
#### Example 1: Fetch Historical Data
|
||||||
|
```python
|
||||||
|
from swarms_tools import fetch_htx_data
|
||||||
|
|
||||||
|
# Fetch historical trading data for "Swarms Corporation"
|
||||||
|
response = fetch_htx_data("swarms")
|
||||||
|
print(response)
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Example 2: Stock News Analysis
|
||||||
|
```python
|
||||||
|
from swarms_tools import fetch_stock_news
|
||||||
|
|
||||||
|
# Retrieve latest stock news for Apple
|
||||||
|
news = fetch_stock_news("AAPL")
|
||||||
|
print(news)
|
||||||
|
```
|
||||||
|
|
||||||
|
#### Example 3: Cryptocurrency Metrics
|
||||||
|
```python
|
||||||
|
from swarms_tools import coin_gecko_coin_api
|
||||||
|
|
||||||
|
# Fetch live data for Bitcoin
|
||||||
|
crypto_data = coin_gecko_coin_api("bitcoin")
|
||||||
|
print(crypto_data)
|
||||||
|
```
|
||||||
|
|
||||||
|
### Social Media Automation
|
||||||
|
Streamline communication and engagement:
|
||||||
|
|
||||||
|
#### Example: Telegram Bot Messaging
|
||||||
|
```python
|
||||||
|
from swarms_tools import telegram_dm_or_tag_api
|
||||||
|
|
||||||
|
def send_alert(response: str):
|
||||||
|
telegram_dm_or_tag_api(response)
|
||||||
|
|
||||||
|
# Send a message to a user or group
|
||||||
|
send_alert("Mission-critical update from Swarms.")
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## Dex Screener
|
||||||
|
|
||||||
|
This is a tool that allows you to fetch data from the Dex Screener API. It supports multiple chains and multiple tokens.
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.finance.dex_screener import (
|
||||||
|
fetch_latest_token_boosts,
|
||||||
|
fetch_dex_screener_profiles,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
fetch_dex_screener_profiles()
|
||||||
|
fetch_latest_token_boosts()
|
||||||
|
|
||||||
|
```
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
|
||||||
|
## Structs
|
||||||
|
The tool chainer enables the execution of multiple tools in a sequence, allowing for the aggregation of their results in either a parallel or sequential manner.
|
||||||
|
|
||||||
|
```python
|
||||||
|
# Example usage
|
||||||
|
from loguru import logger
|
||||||
|
|
||||||
|
from swarms_tools.structs import tool_chainer
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
logger.add("tool_chainer.log", rotation="500 MB", level="INFO")
|
||||||
|
|
||||||
|
# Example tools
|
||||||
|
def tool1():
|
||||||
|
return "Tool1 Result"
|
||||||
|
|
||||||
|
def tool2():
|
||||||
|
return "Tool2 Result"
|
||||||
|
|
||||||
|
# def tool3():
|
||||||
|
# raise ValueError("Simulated error in Tool3")
|
||||||
|
|
||||||
|
tools = [tool1, tool2]
|
||||||
|
|
||||||
|
# Parallel execution
|
||||||
|
parallel_results = tool_chainer(tools, parallel=True)
|
||||||
|
print("Parallel Results:", parallel_results)
|
||||||
|
|
||||||
|
# Sequential execution
|
||||||
|
# sequential_results = tool_chainer(tools, parallel=False)
|
||||||
|
# print("Sequential Results:", sequential_results)
|
||||||
|
|
||||||
|
```
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🧩 Standardized Schema
|
||||||
|
|
||||||
|
Every tool in **Swarms Tools** adheres to a strict schema for maintainability and interoperability:
|
||||||
|
|
||||||
|
### Schema Template
|
||||||
|
|
||||||
|
1. **Functionality**:
|
||||||
|
- Encapsulate API logic into a modular, reusable function.
|
||||||
|
|
||||||
|
2. **Typing**:
|
||||||
|
- Leverage Python type hints for input validation and clarity.
|
||||||
|
|
||||||
|
Example:
|
||||||
|
```python
|
||||||
|
def fetch_data(symbol: str, date_range: str) -> str:
|
||||||
|
"""
|
||||||
|
Fetch financial data for a given symbol and date range.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
symbol (str): Ticker symbol of the asset.
|
||||||
|
date_range (str): Timeframe for the data (e.g., '1d', '1m', '1y').
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
dict: A dictionary containing financial metrics.
|
||||||
|
"""
|
||||||
|
pass
|
||||||
|
```
|
||||||
|
|
||||||
|
3. **Documentation**:
|
||||||
|
- Include detailed docstrings with parameter explanations and usage examples.
|
||||||
|
|
||||||
|
4. **Output Standardization**:
|
||||||
|
- Ensure consistent outputs (e.g., strings) for easy downstream agent integration.
|
||||||
|
|
||||||
|
5. **API-Key Management**:
|
||||||
|
- All API keys must be fetched with `os.getenv("YOUR_KEY")`
|
||||||
|
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 📖 Documentation
|
||||||
|
|
||||||
|
Comprehensive documentation is available to guide developers and enterprises. Visit our [official docs](https://docs.swarms.world) for detailed API references, usage examples, and best practices.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🛠 Contributing
|
||||||
|
|
||||||
|
We welcome contributions from the global developer community. To contribute:
|
||||||
|
|
||||||
|
1. **Fork the Repository**: Start by forking the repository.
|
||||||
|
2. **Create a Feature Branch**: Use a descriptive branch name: `feature/add-new-tool`.
|
||||||
|
3. **Commit Your Changes**: Write meaningful commit messages.
|
||||||
|
4. **Submit a Pull Request**: Open a pull request for review.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🛡️ License
|
||||||
|
|
||||||
|
This project is licensed under the **MIT License**. See the [LICENSE](LICENSE) file for details.
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
## 🌠 Join the Future
|
||||||
|
|
||||||
|
Explore the limitless possibilities of agent-based systems. Together, we can build a smarter, faster, and more interconnected world.
|
||||||
|
|
||||||
|
**Visit us:** [Swarms Corporation](https://swarms.ai)
|
||||||
|
**Follow us:** [Twitter](https://twitter.com/swarms_corp)
|
||||||
|
|
||||||
|
---
|
||||||
|
|
||||||
|
**"The future belongs to those who dare to automate it."**
|
||||||
|
**— The Swarms Corporation**
|
||||||
|
|
||||||
@ -0,0 +1,172 @@
|
|||||||
|
# Search Tools Documentation
|
||||||
|
|
||||||
|
This documentation covers the search tools available in the `swarms-tools` package.
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
|
||||||
|
```bash
|
||||||
|
pip3 install -U swarms-tools
|
||||||
|
```
|
||||||
|
|
||||||
|
## Environment Variables Required
|
||||||
|
|
||||||
|
Create a `.env` file in your project root with the following API keys:
|
||||||
|
|
||||||
|
```bash
|
||||||
|
# Bing Search API
|
||||||
|
BING_API_KEY=your_bing_api_key
|
||||||
|
|
||||||
|
# Google Search API
|
||||||
|
GOOGLE_API_KEY=your_google_api_key
|
||||||
|
GOOGLE_CX=your_google_cx_id
|
||||||
|
GEMINI_API_KEY=your_gemini_api_key
|
||||||
|
|
||||||
|
# Exa AI API
|
||||||
|
EXA_API_KEY=your_exa_api_key
|
||||||
|
```
|
||||||
|
|
||||||
|
## Tools Overview
|
||||||
|
|
||||||
|
### 1. Bing Search Tool
|
||||||
|
|
||||||
|
The Bing Search tool allows you to fetch web articles using the Bing Web Search API.
|
||||||
|
|
||||||
|
#### Function: `fetch_web_articles_bing_api`
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| query | str | Yes | The search query to retrieve articles |
|
||||||
|
|
||||||
|
#### Example Usage:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.search import fetch_web_articles_bing_api
|
||||||
|
|
||||||
|
# Fetch articles about AI
|
||||||
|
results = fetch_web_articles_bing_api("swarms ai github")
|
||||||
|
print(results)
|
||||||
|
```
|
||||||
|
|
||||||
|
### 2. Exa AI Search Tool
|
||||||
|
|
||||||
|
The Exa AI tool is designed for searching research papers and academic content.
|
||||||
|
|
||||||
|
#### Function: `search_exa_ai`
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Default | Description |
|
||||||
|
|-----------|------|----------|---------|-------------|
|
||||||
|
| query | str | Yes | "Latest developments in LLM capabilities" | Search query |
|
||||||
|
| num_results | int | No | 10 | Number of results to return |
|
||||||
|
| auto_prompt | bool | No | True | Whether to use auto-prompting |
|
||||||
|
| include_domains | List[str] | No | ["arxiv.org", "paperswithcode.com"] | Domains to include |
|
||||||
|
| exclude_domains | List[str] | No | [] | Domains to exclude |
|
||||||
|
| category | str | No | "research paper" | Category of search |
|
||||||
|
|
||||||
|
#### Example Usage:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.search import search_exa_ai
|
||||||
|
|
||||||
|
# Search for research papers
|
||||||
|
results = search_exa_ai(
|
||||||
|
query="Latest developments in LLM capabilities",
|
||||||
|
num_results=5,
|
||||||
|
include_domains=["arxiv.org"]
|
||||||
|
)
|
||||||
|
print(results)
|
||||||
|
```
|
||||||
|
|
||||||
|
### 3. Google Search Tool
|
||||||
|
|
||||||
|
A comprehensive search tool that uses Google Custom Search API and includes content extraction and summarization using Gemini.
|
||||||
|
|
||||||
|
#### Class: `WebsiteChecker`
|
||||||
|
|
||||||
|
| Method | Parameters | Description |
|
||||||
|
|--------|------------|-------------|
|
||||||
|
| search | query: str | Main search function that fetches, processes, and summarizes results |
|
||||||
|
|
||||||
|
#### Example Usage:
|
||||||
|
|
||||||
|
```python
|
||||||
|
from swarms_tools.search import WebsiteChecker
|
||||||
|
|
||||||
|
# Initialize with an agent (required for summarization)
|
||||||
|
checker = WebsiteChecker(agent=your_agent_function)
|
||||||
|
|
||||||
|
# Perform search
|
||||||
|
async def search_example():
|
||||||
|
results = await checker.search("who won elections 2024 us")
|
||||||
|
print(results)
|
||||||
|
|
||||||
|
# For synchronous usage
|
||||||
|
from swarms_tools.search import search
|
||||||
|
|
||||||
|
results = search("who won elections 2024 us", agent=your_agent_function)
|
||||||
|
print(results)
|
||||||
|
```
|
||||||
|
|
||||||
|
## Features
|
||||||
|
|
||||||
|
- **Bing Search**: Fetch and parse web articles with structured output
|
||||||
|
- **Exa AI**: Specialized academic and research paper search
|
||||||
|
- **Google Search**:
|
||||||
|
- Custom search with content extraction
|
||||||
|
- Concurrent URL processing
|
||||||
|
- Content summarization using Gemini
|
||||||
|
- Progress tracking
|
||||||
|
- Automatic retry mechanisms
|
||||||
|
- Results saved to JSON
|
||||||
|
|
||||||
|
## Dependencies
|
||||||
|
|
||||||
|
The tools automatically handle dependency installation, but here are the main requirements:
|
||||||
|
|
||||||
|
```python
|
||||||
|
aiohttp
|
||||||
|
asyncio
|
||||||
|
beautifulsoup4
|
||||||
|
google-generativeai
|
||||||
|
html2text
|
||||||
|
playwright
|
||||||
|
python-dotenv
|
||||||
|
rich
|
||||||
|
tenacity
|
||||||
|
```
|
||||||
|
|
||||||
|
## Error Handling
|
||||||
|
|
||||||
|
All tools include robust error handling:
|
||||||
|
- Automatic retries for failed requests
|
||||||
|
- Timeout handling
|
||||||
|
- Rate limiting consideration
|
||||||
|
- Detailed error messages
|
||||||
|
|
||||||
|
## Output Format
|
||||||
|
|
||||||
|
Each tool provides structured output:
|
||||||
|
|
||||||
|
- **Bing Search**: Returns formatted string with article details
|
||||||
|
- **Exa AI**: Returns JSON response with search results
|
||||||
|
- **Google Search**: Returns summarized content with sections:
|
||||||
|
- Key Findings
|
||||||
|
- Important Details
|
||||||
|
- Sources
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
|
||||||
|
1. Always store API keys in environment variables
|
||||||
|
2. Use appropriate error handling
|
||||||
|
3. Consider rate limits of the APIs
|
||||||
|
4. Cache results when appropriate
|
||||||
|
5. Monitor API usage and costs
|
||||||
|
|
||||||
|
## Limitations
|
||||||
|
|
||||||
|
- Bing Search: Limited to 4 articles per query
|
||||||
|
- Exa AI: Focused on academic content
|
||||||
|
- Google Search: Requires Gemini API for summarization
|
||||||
|
|
||||||
|
## Support
|
||||||
|
|
||||||
|
For issues and feature requests, please visit the [GitHub repository](https://github.com/swarms-tools).
|
||||||
@ -0,0 +1,325 @@
|
|||||||
|
# Twitter Tool Documentation
|
||||||
|
|
||||||
|
## Overview
|
||||||
|
The Twitter Tool provides a convenient interface for interacting with Twitter's API through the swarms-tools package. This documentation covers the initialization process and available functions for posting, replying, liking, and quoting tweets, as well as retrieving metrics.
|
||||||
|
|
||||||
|
## Installation
|
||||||
|
```bash
|
||||||
|
pip install swarms-tools
|
||||||
|
```
|
||||||
|
|
||||||
|
## Authentication
|
||||||
|
The Twitter Tool requires Twitter API credentials for authentication. These should be stored as environment variables:
|
||||||
|
|
||||||
|
```python
|
||||||
|
TWITTER_ID=your_twitter_id
|
||||||
|
TWITTER_NAME=your_twitter_name
|
||||||
|
TWITTER_DESCRIPTION=your_twitter_description
|
||||||
|
TWITTER_API_KEY=your_api_key
|
||||||
|
TWITTER_API_SECRET_KEY=your_api_secret_key
|
||||||
|
TWITTER_ACCESS_TOKEN=your_access_token
|
||||||
|
TWITTER_ACCESS_TOKEN_SECRET=your_access_token_secret
|
||||||
|
```
|
||||||
|
|
||||||
|
## Initialization
|
||||||
|
|
||||||
|
### TwitterTool Configuration Options
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| id | str | Yes | Unique identifier for the Twitter tool instance |
|
||||||
|
| name | str | Yes | Name of the Twitter tool instance |
|
||||||
|
| description | str | No | Description of the tool's purpose |
|
||||||
|
| credentials | dict | Yes | Dictionary containing Twitter API credentials |
|
||||||
|
|
||||||
|
### Credentials Dictionary Structure
|
||||||
|
|
||||||
|
| Key | Type | Required | Description |
|
||||||
|
|-----|------|----------|-------------|
|
||||||
|
| apiKey | str | Yes | Twitter API Key |
|
||||||
|
| apiSecretKey | str | Yes | Twitter API Secret Key |
|
||||||
|
| accessToken | str | Yes | Twitter Access Token |
|
||||||
|
| accessTokenSecret | str | Yes | Twitter Access Token Secret |
|
||||||
|
|
||||||
|
## Available Functions
|
||||||
|
|
||||||
|
### initialize_twitter_tool()
|
||||||
|
|
||||||
|
Creates and returns a new instance of the TwitterTool.
|
||||||
|
|
||||||
|
```python
|
||||||
|
def initialize_twitter_tool() -> TwitterTool:
|
||||||
|
```
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
- TwitterTool: Initialized Twitter tool instance
|
||||||
|
|
||||||
|
### post_tweet()
|
||||||
|
|
||||||
|
Posts a new tweet to Twitter.
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| tweet | str | Yes | Text content of the tweet to post |
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
- tweepy.TweepyException: If tweet posting fails
|
||||||
|
|
||||||
|
### reply_tweet()
|
||||||
|
|
||||||
|
Replies to an existing tweet.
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| tweet_id | int | Yes | ID of the tweet to reply to |
|
||||||
|
| reply | str | Yes | Text content of the reply |
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
- tweepy.TweepyException: If reply posting fails
|
||||||
|
|
||||||
|
### like_tweet()
|
||||||
|
|
||||||
|
Likes a specified tweet.
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| tweet_id | int | Yes | ID of the tweet to like |
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
- tweepy.TweepyException: If liking the tweet fails
|
||||||
|
|
||||||
|
### quote_tweet()
|
||||||
|
|
||||||
|
Creates a quote tweet.
|
||||||
|
|
||||||
|
| Parameter | Type | Required | Description |
|
||||||
|
|-----------|------|----------|-------------|
|
||||||
|
| tweet_id | int | Yes | ID of the tweet to quote |
|
||||||
|
| quote | str | Yes | Text content to add to the quoted tweet |
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
- tweepy.TweepyException: If quote tweet creation fails
|
||||||
|
|
||||||
|
### get_metrics()
|
||||||
|
|
||||||
|
Retrieves Twitter metrics.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
- Dict[str, int]: Dictionary containing various Twitter metrics
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
- tweepy.TweepyException: If metrics retrieval fails
|
||||||
|
|
||||||
|
## Usage Examples
|
||||||
|
|
||||||
|
### Basic Tweet Posting
|
||||||
|
```python
|
||||||
|
from swarms_tools.twitter import initialize_twitter_tool, post_tweet
|
||||||
|
|
||||||
|
# Post a simple tweet
|
||||||
|
post_tweet("Hello, Twitter!")
|
||||||
|
```
|
||||||
|
|
||||||
|
### Interacting with Tweets
|
||||||
|
```python
|
||||||
|
# Reply to a tweet
|
||||||
|
reply_tweet(12345, "Great point!")
|
||||||
|
|
||||||
|
# Like a tweet
|
||||||
|
like_tweet(12345)
|
||||||
|
|
||||||
|
# Quote a tweet
|
||||||
|
quote_tweet(12345, "Adding my thoughts on this!")
|
||||||
|
```
|
||||||
|
|
||||||
|
### Retrieving Metrics
|
||||||
|
```python
|
||||||
|
metrics = get_metrics()
|
||||||
|
print(f"Current metrics: {metrics}")
|
||||||
|
```
|
||||||
|
|
||||||
|
## Error Handling
|
||||||
|
All functions include built-in error handling and will print error messages if operations fail. It's recommended to implement additional error handling in production environments:
|
||||||
|
|
||||||
|
```python
|
||||||
|
try:
|
||||||
|
post_tweet("Hello, Twitter!")
|
||||||
|
except Exception as e:
|
||||||
|
logger.error(f"Tweet posting failed: {e}")
|
||||||
|
# Implement appropriate error handling
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
|
## Production Example
|
||||||
|
|
||||||
|
This is an example of how to use the TwitterTool in a production environment using Swarms.
|
||||||
|
|
||||||
|
```python
|
||||||
|
|
||||||
|
import os
|
||||||
|
from time import time
|
||||||
|
|
||||||
|
from swarm_models import OpenAIChat
|
||||||
|
from swarms import Agent
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
|
||||||
|
from swarms_tools.social_media.twitter_tool import TwitterTool
|
||||||
|
|
||||||
|
load_dotenv()
|
||||||
|
|
||||||
|
model_name = "gpt-4o"
|
||||||
|
|
||||||
|
model = OpenAIChat(
|
||||||
|
model_name=model_name,
|
||||||
|
max_tokens=3000,
|
||||||
|
openai_api_key=os.getenv("OPENAI_API_KEY"),
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
medical_coder = Agent(
|
||||||
|
agent_name="Medical Coder",
|
||||||
|
system_prompt="""
|
||||||
|
You are a highly experienced and certified medical coder with extensive knowledge of ICD-10 coding guidelines, clinical documentation standards, and compliance regulations. Your responsibility is to ensure precise, compliant, and well-documented coding for all clinical cases.
|
||||||
|
|
||||||
|
### Primary Responsibilities:
|
||||||
|
1. **Review Clinical Documentation**: Analyze all available clinical records, including specialist inputs, physician notes, lab results, imaging reports, and discharge summaries.
|
||||||
|
2. **Assign Accurate ICD-10 Codes**: Identify and assign appropriate codes for primary diagnoses, secondary conditions, symptoms, and complications.
|
||||||
|
3. **Ensure Coding Compliance**: Follow the latest ICD-10-CM/PCS coding guidelines, payer-specific requirements, and organizational policies.
|
||||||
|
4. **Document Code Justification**: Provide clear, evidence-based rationale for each assigned code.
|
||||||
|
|
||||||
|
### Detailed Coding Process:
|
||||||
|
- **Review Specialist Inputs**: Examine all relevant documentation to capture the full scope of the patient's condition and care provided.
|
||||||
|
- **Identify Diagnoses**: Determine the primary and secondary diagnoses, as well as any symptoms or complications, based on the documentation.
|
||||||
|
- **Assign ICD-10 Codes**: Select the most accurate and specific ICD-10 codes for each identified diagnosis or condition.
|
||||||
|
- **Document Supporting Evidence**: Record the documentation source (e.g., lab report, imaging, or physician note) for each code to justify its assignment.
|
||||||
|
- **Address Queries**: Note and flag any inconsistencies, missing information, or areas requiring clarification from providers.
|
||||||
|
|
||||||
|
### Output Requirements:
|
||||||
|
Your response must be clear, structured, and compliant with professional standards. Use the following format:
|
||||||
|
|
||||||
|
1. **Primary Diagnosis Codes**:
|
||||||
|
- **ICD-10 Code**: [e.g., E11.9]
|
||||||
|
- **Description**: [e.g., Type 2 diabetes mellitus without complications]
|
||||||
|
- **Supporting Documentation**: [e.g., Physician's note dated MM/DD/YYYY]
|
||||||
|
|
||||||
|
2. **Secondary Diagnosis Codes**:
|
||||||
|
- **ICD-10 Code**: [Code]
|
||||||
|
- **Description**: [Description]
|
||||||
|
- **Order of Clinical Significance**: [Rank or priority]
|
||||||
|
|
||||||
|
3. **Symptom Codes**:
|
||||||
|
- **ICD-10 Code**: [Code]
|
||||||
|
- **Description**: [Description]
|
||||||
|
|
||||||
|
4. **Complication Codes**:
|
||||||
|
- **ICD-10 Code**: [Code]
|
||||||
|
- **Description**: [Description]
|
||||||
|
- **Relevant Documentation**: [Source of information]
|
||||||
|
|
||||||
|
5. **Coding Notes**:
|
||||||
|
- Observations, clarifications, or any potential issues requiring provider input.
|
||||||
|
|
||||||
|
### Additional Guidelines:
|
||||||
|
- Always prioritize specificity and compliance when assigning codes.
|
||||||
|
- For ambiguous cases, provide a brief note with reasoning and flag for clarification.
|
||||||
|
- Ensure the output format is clean, consistent, and ready for professional use.
|
||||||
|
""",
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
# Define your options with the necessary credentials
|
||||||
|
options = {
|
||||||
|
"id": "mcsswarm",
|
||||||
|
"name": "mcsswarm",
|
||||||
|
"description": "An example Twitter Plugin for testing.",
|
||||||
|
"credentials": {
|
||||||
|
"apiKey": os.getenv("TWITTER_API_KEY"),
|
||||||
|
"apiSecretKey": os.getenv("TWITTER_API_SECRET_KEY"),
|
||||||
|
"accessToken": os.getenv("TWITTER_ACCESS_TOKEN"),
|
||||||
|
"accessTokenSecret": os.getenv("TWITTER_ACCESS_TOKEN_SECRET"),
|
||||||
|
},
|
||||||
|
}
|
||||||
|
|
||||||
|
# Initialize the TwitterTool with your options
|
||||||
|
twitter_plugin = TwitterTool(options)
|
||||||
|
|
||||||
|
# # Post a tweet
|
||||||
|
# post_tweet_fn = twitter_plugin.get_function('post_tweet')
|
||||||
|
# post_tweet_fn("Hello world!")
|
||||||
|
|
||||||
|
|
||||||
|
# Assuming `twitter_plugin` and `medical_coder` are already initialized
|
||||||
|
post_tweet = twitter_plugin.get_function("post_tweet")
|
||||||
|
|
||||||
|
# Set to track posted tweets and avoid duplicates
|
||||||
|
posted_tweets = set()
|
||||||
|
|
||||||
|
|
||||||
|
def post_unique_tweet():
|
||||||
|
"""
|
||||||
|
Generate and post a unique tweet. Skip duplicates.
|
||||||
|
"""
|
||||||
|
tweet_prompt = (
|
||||||
|
"Share an intriguing, lesser-known fact about a medical disease, and include an innovative, fun, or surprising way to manage or cure it! "
|
||||||
|
"Make the response playful, engaging, and inspiring—something that makes people smile while learning. No markdown, just plain text!"
|
||||||
|
)
|
||||||
|
|
||||||
|
# Generate a new tweet text
|
||||||
|
tweet_text = medical_coder.run(tweet_prompt)
|
||||||
|
|
||||||
|
# Check for duplicates
|
||||||
|
if tweet_text in posted_tweets:
|
||||||
|
print("Duplicate tweet detected. Skipping...")
|
||||||
|
return
|
||||||
|
|
||||||
|
# Post the tweet
|
||||||
|
try:
|
||||||
|
post_tweet(tweet_text)
|
||||||
|
print(f"Posted tweet: {tweet_text}")
|
||||||
|
# Add the tweet to the set of posted tweets
|
||||||
|
posted_tweets.add(tweet_text)
|
||||||
|
except Exception as e:
|
||||||
|
print(f"Error posting tweet: {e}")
|
||||||
|
|
||||||
|
|
||||||
|
# Loop to post tweets every 10 seconds
|
||||||
|
def start_tweet_loop(interval=10):
|
||||||
|
"""
|
||||||
|
Continuously post tweets every `interval` seconds.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
interval (int): Time in seconds between tweets.
|
||||||
|
"""
|
||||||
|
print("Starting tweet loop...")
|
||||||
|
while True:
|
||||||
|
post_unique_tweet()
|
||||||
|
time.sleep(interval)
|
||||||
|
|
||||||
|
|
||||||
|
# Start the loop
|
||||||
|
start_tweet_loop(10)
|
||||||
|
```
|
||||||
|
|
||||||
|
|
||||||
|
## Best Practices
|
||||||
|
1. Always store credentials in environment variables
|
||||||
|
2. Implement rate limiting in production environments
|
||||||
|
3. Add proper logging for all operations
|
||||||
|
4. Handle errors gracefully
|
||||||
|
5. Validate tweet content before posting
|
||||||
|
6. Monitor API usage limits
|
||||||
|
|
||||||
|
## Rate Limits
|
||||||
|
Be aware of Twitter's API rate limits. Implement appropriate delays between requests in production environments to avoid hitting these limits.
|
||||||
|
|
||||||
|
## Dependencies
|
||||||
|
- tweepy
|
||||||
|
- python-dotenv
|
||||||
|
- swarms-tools
|
||||||
|
|
||||||
|
## Version Compatibility
|
||||||
|
- Python 3.7+
|
||||||
|
- Latest version of swarms-tools package
|
||||||
@ -0,0 +1,388 @@
|
|||||||
|
import os
|
||||||
|
from dataclasses import dataclass
|
||||||
|
from typing import Tuple
|
||||||
|
from litellm import completion
|
||||||
|
from loguru import logger
|
||||||
|
from swarms import Agent
|
||||||
|
|
||||||
|
EXTRACTION_PROMPT = """
|
||||||
|
You are a specialized Chart2Table extraction agent that converts visual charts into precise textual descriptions.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Chart Type]
|
||||||
|
Type: {bar|line|pie|scatter|combination}
|
||||||
|
Title: {chart title}
|
||||||
|
X-Axis: {label and scale}
|
||||||
|
Y-Axis: {label and scale}
|
||||||
|
|
||||||
|
[Data Series]
|
||||||
|
Name: {series name}
|
||||||
|
Values: {comma-separated list of values}
|
||||||
|
{repeat for each series}
|
||||||
|
|
||||||
|
[Annotations]
|
||||||
|
- {list any markers, gridlines, legends}
|
||||||
|
- {note any data gaps or anomalies}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Maintain exact numerical precision
|
||||||
|
2. List ALL data points in order
|
||||||
|
3. Note any gaps, outliers or special patterns
|
||||||
|
4. Describe axes scales (linear/log) and units
|
||||||
|
5. Include legends and series names verbatim
|
||||||
|
6. Note any data point annotations or markers
|
||||||
|
7. Describe chart elements spatially (top-left, center, etc)
|
||||||
|
8. Include color and style information if relevant
|
||||||
|
9. Note relationships between multiple series
|
||||||
|
10. Flag any data quality or readability issues"""
|
||||||
|
|
||||||
|
REFORMULATION_PROMPT = """You are an Answer Reformulation specialist that breaks down complex analytical statements into atomic, verifiable claims.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Core Claims]
|
||||||
|
1. {single fact with exact numbers}
|
||||||
|
2. {another atomic fact}
|
||||||
|
{continue for all core claims}
|
||||||
|
|
||||||
|
[Supporting Context]
|
||||||
|
1. {relevant context that supports core claims}
|
||||||
|
2. {additional contextual information}
|
||||||
|
{continue for all context}
|
||||||
|
|
||||||
|
[Assumptions]
|
||||||
|
1. {implicit assumption made}
|
||||||
|
2. {another assumption}
|
||||||
|
{continue for all assumptions}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Each claim must be independently verifiable
|
||||||
|
2. Use exact numbers, never round or approximate
|
||||||
|
3. Split compound statements into atomic facts
|
||||||
|
4. Make implicit comparisons explicit
|
||||||
|
5. Note temporal relationships clearly
|
||||||
|
6. Include units with all measurements
|
||||||
|
7. Flag any uncertainty or approximations
|
||||||
|
8. Note data source limitations
|
||||||
|
9. Preserve calculation steps
|
||||||
|
10. Maintain logical dependencies"""
|
||||||
|
|
||||||
|
CAPTIONING_PROMPT = """You are an Entity Captioning specialist that generates rich contextual descriptions of chart elements.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Data Points]
|
||||||
|
{x,y}: {detailed description of point significance}
|
||||||
|
{continue for key points}
|
||||||
|
|
||||||
|
[Trends]
|
||||||
|
- {description of overall pattern}
|
||||||
|
- {notable sub-patterns}
|
||||||
|
{continue for all trends}
|
||||||
|
|
||||||
|
[Relationships]
|
||||||
|
- {correlation between variables}
|
||||||
|
- {causation if evident}
|
||||||
|
{continue for all relationships}
|
||||||
|
|
||||||
|
[Context]
|
||||||
|
- {broader context for interpretation}
|
||||||
|
- {relevant external factors}
|
||||||
|
{continue for all context}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Describe both local and global patterns
|
||||||
|
2. Note statistical significance of changes
|
||||||
|
3. Identify cyclic or seasonal patterns
|
||||||
|
4. Flag outliers and anomalies
|
||||||
|
5. Compare relative magnitudes
|
||||||
|
6. Note rate of change patterns
|
||||||
|
7. Describe distribution characteristics
|
||||||
|
8. Highlight key inflection points
|
||||||
|
9. Note data clustering patterns
|
||||||
|
10. Include domain-specific insights"""
|
||||||
|
|
||||||
|
PREFILTER_PROMPT = """You are a Pre-filtering specialist that identifies relevant chart elements for verification.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Critical Elements]
|
||||||
|
1. {element}: Score {0-10}
|
||||||
|
Evidence: {why this supports claims}
|
||||||
|
{continue for all relevant elements}
|
||||||
|
|
||||||
|
[Supporting Elements]
|
||||||
|
1. {element}: Score {0-10}
|
||||||
|
Context: {how this adds context}
|
||||||
|
{continue for all supporting elements}
|
||||||
|
|
||||||
|
[Relevance Chain]
|
||||||
|
1. {claim} -> {element} -> {evidence}
|
||||||
|
{continue for all connections}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Score relevance 0-10 with detailed rationale
|
||||||
|
2. Build explicit evidence chains
|
||||||
|
3. Note both direct and indirect support
|
||||||
|
4. Consider temporal relevance
|
||||||
|
5. Account for data relationships
|
||||||
|
6. Note confidence levels
|
||||||
|
7. Include contextual importance
|
||||||
|
8. Consider alternative interpretations
|
||||||
|
9. Note missing evidence
|
||||||
|
10. Explain filtering decisions"""
|
||||||
|
|
||||||
|
RERANK_PROMPT = """You are a Re-ranking specialist that orders evidence by strength and relevance.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Primary Evidence]
|
||||||
|
1. {element} - Score: {0-10}
|
||||||
|
Strength: {detailed justification}
|
||||||
|
{continue for top evidence}
|
||||||
|
|
||||||
|
[Supporting Evidence]
|
||||||
|
1. {element} - Score: {0-10}
|
||||||
|
Context: {how this reinforces primary evidence}
|
||||||
|
{continue for supporting evidence}
|
||||||
|
|
||||||
|
[Evidence Chains]
|
||||||
|
1. {claim} -> {primary} -> {supporting} -> {conclusion}
|
||||||
|
{continue for all chains}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Use explicit scoring criteria
|
||||||
|
2. Consider evidence independence
|
||||||
|
3. Note corroborating elements
|
||||||
|
4. Account for evidence quality
|
||||||
|
5. Consider contradictory evidence
|
||||||
|
6. Note confidence levels
|
||||||
|
7. Explain ranking decisions
|
||||||
|
8. Build complete evidence chains
|
||||||
|
9. Note gaps in evidence
|
||||||
|
10. Consider alternative interpretations"""
|
||||||
|
|
||||||
|
LOCALIZATION_PROMPT = """You are a Cell Localization specialist that precisely maps data to visual elements.
|
||||||
|
|
||||||
|
Output Format:
|
||||||
|
[Element Locations]
|
||||||
|
1. Type: {bar|line|point|label}
|
||||||
|
Position: {x1,y1,x2,y2}
|
||||||
|
Value: {associated data value}
|
||||||
|
Confidence: {0-10}
|
||||||
|
{continue for all elements}
|
||||||
|
|
||||||
|
[Spatial Relationships]
|
||||||
|
- {relative positions}
|
||||||
|
- {alignment patterns}
|
||||||
|
{continue for all relationships}
|
||||||
|
|
||||||
|
[Visual Context]
|
||||||
|
- {surrounding elements}
|
||||||
|
- {reference points}
|
||||||
|
{continue for context}
|
||||||
|
|
||||||
|
Guidelines:
|
||||||
|
1. Use normalized coordinates (0-1)
|
||||||
|
2. Note element boundaries precisely
|
||||||
|
3. Include confidence scores
|
||||||
|
4. Note spatial relationships
|
||||||
|
5. Account for overlapping elements
|
||||||
|
6. Consider chart type constraints
|
||||||
|
7. Note alignment patterns
|
||||||
|
8. Include reference points
|
||||||
|
9. Note visual hierarchies
|
||||||
|
10. Document occlusions"""
|
||||||
|
|
||||||
|
|
||||||
|
@dataclass
|
||||||
|
class ChartElement:
|
||||||
|
element_type: str
|
||||||
|
bbox: Tuple[float, float, float, float]
|
||||||
|
confidence: float
|
||||||
|
|
||||||
|
|
||||||
|
class VisionAPI:
|
||||||
|
def __init__(
|
||||||
|
self,
|
||||||
|
model_name: str = "gpt-4o",
|
||||||
|
max_tokens: int = 1000,
|
||||||
|
temperature: float = 0.5,
|
||||||
|
):
|
||||||
|
os.environ["OPENAI_API_KEY"] = os.getenv("OPENAI_API_KEY")
|
||||||
|
self.model_name = model_name
|
||||||
|
self.max_tokens = max_tokens
|
||||||
|
self.temperature = temperature
|
||||||
|
|
||||||
|
def encode_image(self, img: str):
|
||||||
|
if img.startswith("http"):
|
||||||
|
return img
|
||||||
|
import base64
|
||||||
|
|
||||||
|
with open(img, "rb") as image_file:
|
||||||
|
encoded_string = base64.b64encode(
|
||||||
|
image_file.read()
|
||||||
|
).decode("utf-8")
|
||||||
|
return f"data:image/png;base64,{encoded_string}"
|
||||||
|
|
||||||
|
def run(self, task: str, img: str):
|
||||||
|
img = self.encode_image(img)
|
||||||
|
response = completion(
|
||||||
|
model=self.model_name,
|
||||||
|
messages=[
|
||||||
|
{
|
||||||
|
"role": "user",
|
||||||
|
"content": [
|
||||||
|
{"type": "text", "text": task},
|
||||||
|
{
|
||||||
|
"type": "image_url",
|
||||||
|
"image_url": {"url": img},
|
||||||
|
},
|
||||||
|
],
|
||||||
|
}
|
||||||
|
],
|
||||||
|
max_tokens=self.max_tokens,
|
||||||
|
temperature=self.temperature,
|
||||||
|
)
|
||||||
|
return response.choices[0].message.content
|
||||||
|
|
||||||
|
|
||||||
|
class ChartCitor:
|
||||||
|
def __init__(
|
||||||
|
self,
|
||||||
|
model_name: str = "gpt-4o",
|
||||||
|
saved_state_path: str = "chartcitor_state.json",
|
||||||
|
max_retries: int = 3,
|
||||||
|
max_loops: int = 1,
|
||||||
|
):
|
||||||
|
logger.info(
|
||||||
|
f"Initializing ChartCitor with model {model_name}"
|
||||||
|
)
|
||||||
|
model = VisionAPI()
|
||||||
|
|
||||||
|
self.extraction_agent = Agent(
|
||||||
|
agent_name="Chart2Table-Agent",
|
||||||
|
system_prompt=EXTRACTION_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.reformulation_agent = Agent(
|
||||||
|
agent_name="Answer-Reformulation-Agent",
|
||||||
|
system_prompt=REFORMULATION_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.captioning_agent = Agent(
|
||||||
|
agent_name="Entity-Captioning-Agent",
|
||||||
|
system_prompt=CAPTIONING_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.prefilter_agent = Agent(
|
||||||
|
agent_name="LLM-Prefilter-Agent",
|
||||||
|
system_prompt=PREFILTER_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.rerank_agent = Agent(
|
||||||
|
agent_name="LLM-Rerank-Agent",
|
||||||
|
system_prompt=RERANK_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.localization_agent = Agent(
|
||||||
|
agent_name="Cell-Localization-Agent",
|
||||||
|
system_prompt=LOCALIZATION_PROMPT,
|
||||||
|
llm=model,
|
||||||
|
max_loops=1,
|
||||||
|
)
|
||||||
|
|
||||||
|
def extract_table(self, chart_image: str) -> str:
|
||||||
|
logger.info("Extracting table from chart")
|
||||||
|
return self.extraction_agent.run(
|
||||||
|
"Extract and describe the data from this chart following the specified format.",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
def reformulate_answer(
|
||||||
|
self, answer: str, table_data: str, chart_image: str
|
||||||
|
) -> str:
|
||||||
|
logger.info("Reformulating answer into atomic facts")
|
||||||
|
return self.reformulation_agent.run(
|
||||||
|
f"Break this answer into atomic facts:\n{answer}\n\nTable data:\n{table_data}",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
def generate_captions(
|
||||||
|
self, table_data: str, chart_image: str
|
||||||
|
) -> str:
|
||||||
|
logger.info("Generating captions for chart elements")
|
||||||
|
return self.captioning_agent.run(
|
||||||
|
f"Generate descriptive captions for this data:\n{table_data}",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
def retrieve_evidence(
|
||||||
|
self,
|
||||||
|
facts: str,
|
||||||
|
table_data: str,
|
||||||
|
captions: str,
|
||||||
|
chart_image: str,
|
||||||
|
) -> str:
|
||||||
|
logger.info("Retrieving supporting evidence")
|
||||||
|
filtered = self.prefilter_agent.run(
|
||||||
|
f"Identify relevant elements for:\nFacts:\n{facts}\n\nData:\n{table_data}\n\nCaptions:\n{captions}",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
return self.rerank_agent.run(
|
||||||
|
f"Rank these elements by relevance:\n{filtered}\nFor facts:\n{facts}",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
def localize_elements(
|
||||||
|
self, chart_image: str, evidence: str
|
||||||
|
) -> str:
|
||||||
|
logger.info("Localizing chart elements")
|
||||||
|
return self.localization_agent.run(
|
||||||
|
f"Describe the location of these elements:\n{evidence}",
|
||||||
|
img=chart_image,
|
||||||
|
)
|
||||||
|
|
||||||
|
def run(
|
||||||
|
self, chart_image: str, question: str, answer: str
|
||||||
|
) -> str:
|
||||||
|
logger.info(f"Processing question: {question}")
|
||||||
|
|
||||||
|
table_data = self.extract_table(chart_image)
|
||||||
|
facts = self.reformulate_answer(
|
||||||
|
answer, table_data, chart_image
|
||||||
|
)
|
||||||
|
captions = self.generate_captions(table_data, chart_image)
|
||||||
|
evidence = self.retrieve_evidence(
|
||||||
|
facts, table_data, captions, chart_image
|
||||||
|
)
|
||||||
|
citations = self.localize_elements(chart_image, evidence)
|
||||||
|
|
||||||
|
return f"""Analysis Results:
|
||||||
|
|
||||||
|
Facts:
|
||||||
|
{facts}
|
||||||
|
|
||||||
|
Evidence:
|
||||||
|
{evidence}
|
||||||
|
|
||||||
|
Visual Citations:
|
||||||
|
{citations}
|
||||||
|
"""
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
chartcitor = ChartCitor()
|
||||||
|
result = chartcitor.run(
|
||||||
|
chart_image="chart.png",
|
||||||
|
question="Analyze this chart of solana price and volume over time. What is the highest volume day?",
|
||||||
|
answer="203",
|
||||||
|
)
|
||||||
|
print(result)
|
||||||
@ -0,0 +1,9 @@
|
|||||||
|
from swarms import Agent
|
||||||
|
|
||||||
|
Agent(
|
||||||
|
agent_name="Stock-Analysis-Agent",
|
||||||
|
model_name="groq/deepseek-r1-distill-llama-70b",
|
||||||
|
max_loops="auto",
|
||||||
|
interactive=True,
|
||||||
|
streaming_on=False,
|
||||||
|
).run("What are the best ways to analyze macroeconomic data?")
|
||||||
@ -0,0 +1,129 @@
|
|||||||
|
import os
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
|
||||||
|
# Swarm imports
|
||||||
|
from swarms.structs.agent import Agent
|
||||||
|
from swarms.structs.hiearchical_swarm import (
|
||||||
|
HierarchicalSwarm,
|
||||||
|
SwarmSpec,
|
||||||
|
)
|
||||||
|
from swarms.utils.function_caller_model import OpenAIFunctionCaller
|
||||||
|
|
||||||
|
load_dotenv()
|
||||||
|
|
||||||
|
|
||||||
|
# ------------------------------------------------------------------------------
|
||||||
|
# Director LLM: Responsible for orchestrating tasks among the agents
|
||||||
|
# ------------------------------------------------------------------------------
|
||||||
|
llm = OpenAIFunctionCaller(
|
||||||
|
base_model=SwarmSpec,
|
||||||
|
api_key=os.getenv("OPENAI_API_KEY"),
|
||||||
|
system_prompt=(
|
||||||
|
"As the Director of this Hierarchical Agent Swarm, you are in charge of "
|
||||||
|
"coordinating and overseeing all tasks, ensuring that each is executed "
|
||||||
|
"efficiently and effectively by the appropriate agents. You must:\n\n"
|
||||||
|
"1. **Analyze** the user's request and **formulate** a strategic plan.\n"
|
||||||
|
"2. **Assign** tasks to the relevant agents, detailing **why** each task "
|
||||||
|
"is relevant and **what** is expected in the deliverables.\n"
|
||||||
|
"3. **Monitor** agent outputs and, if necessary, provide **constructive "
|
||||||
|
"feedback** or request **clarifications**.\n"
|
||||||
|
"4. **Iterate** this process until all tasks are completed to a high "
|
||||||
|
"standard, or until the swarm has reached the maximum feedback loops.\n\n"
|
||||||
|
"Remember:\n"
|
||||||
|
"- **Only** use the agents provided; do not invent extra roles.\n"
|
||||||
|
"- If you need additional information, request it from the user.\n"
|
||||||
|
"- Strive to produce a clear, comprehensive **final output** that addresses "
|
||||||
|
"the user's needs.\n"
|
||||||
|
"- Keep the tone **professional** and **informative**. If there's uncertainty, "
|
||||||
|
"politely request further details.\n"
|
||||||
|
"- Ensure that any steps you outline are **actionable**, **logical**, and "
|
||||||
|
"**transparent** to the user.\n\n"
|
||||||
|
"Your effectiveness hinges on clarity, structured delegation, and thoroughness. "
|
||||||
|
"Always focus on delivering the best possible outcome for the user's request."
|
||||||
|
),
|
||||||
|
temperature=0.5,
|
||||||
|
max_tokens=8196,
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
def main():
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# Agent: Stock-Analysis-Agent
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# This agent is responsible for:
|
||||||
|
# - Gathering and interpreting financial data
|
||||||
|
# - Identifying market trends and patterns
|
||||||
|
# - Providing clear, actionable insights or recommendations
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
analysis_agent = Agent(
|
||||||
|
agent_name="Stock-Analysis-Agent",
|
||||||
|
model_name="gpt-4o",
|
||||||
|
max_loops=1,
|
||||||
|
interactive=False,
|
||||||
|
streaming_on=False,
|
||||||
|
system_prompt=(
|
||||||
|
"As the Stock Analysis Agent, your primary responsibilities include:\n\n"
|
||||||
|
"1. **Market Trend Analysis**: Evaluate current and historical market data "
|
||||||
|
"to identify trends, patterns, and potential investment opportunities.\n"
|
||||||
|
"2. **Risk & Opportunity Assessment**: Pinpoint specific factors—whether "
|
||||||
|
"macroeconomic indicators, sector-specific trends, or company fundamentals—"
|
||||||
|
"that can guide informed investment decisions.\n"
|
||||||
|
"3. **Reporting & Recommendations**: Present your findings in a structured, "
|
||||||
|
"easy-to-understand format, offering actionable insights. Include potential "
|
||||||
|
"caveats or uncertainties in your assessment.\n\n"
|
||||||
|
"Operational Guidelines:\n"
|
||||||
|
"- If additional data or clarifications are needed, explicitly request them "
|
||||||
|
"from the Director.\n"
|
||||||
|
"- Keep your output **concise** yet **comprehensive**. Provide clear "
|
||||||
|
"rationales for each recommendation.\n"
|
||||||
|
"- Clearly state any **assumptions** or **limitations** in your analysis.\n"
|
||||||
|
"- Remember: You are not a financial advisor, and final decisions rest with "
|
||||||
|
"the user. Include necessary disclaimers.\n\n"
|
||||||
|
"Goal:\n"
|
||||||
|
"Deliver high-quality, well-substantiated stock market insights that can be "
|
||||||
|
"used to guide strategic investment decisions."
|
||||||
|
),
|
||||||
|
)
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# Hierarchical Swarm Setup
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# - Director: llm
|
||||||
|
# - Agents: [analysis_agent]
|
||||||
|
# - max_loops: Maximum number of feedback loops between director & agents
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
swarm = HierarchicalSwarm(
|
||||||
|
description=(
|
||||||
|
"A specialized swarm in which the Director delegates tasks to a Stock "
|
||||||
|
"Analysis Agent for thorough market evaluation."
|
||||||
|
),
|
||||||
|
director=llm,
|
||||||
|
agents=[analysis_agent],
|
||||||
|
max_loops=1, # Limit on feedback iterations
|
||||||
|
)
|
||||||
|
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# Execution
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
# The director receives the user's instruction: "Ask the stock analysis agent
|
||||||
|
# to analyze the stock market." The Director will then:
|
||||||
|
# 1. Formulate tasks (SwarmSpec)
|
||||||
|
# 2. Assign tasks to the Stock-Analysis-Agent
|
||||||
|
# 3. Provide feedback and/or request clarifications
|
||||||
|
# 4. Produce a final response
|
||||||
|
# --------------------------------------------------------------------------
|
||||||
|
user_request = (
|
||||||
|
"Please provide an in-depth analysis of the current stock market, "
|
||||||
|
"focusing on:\n"
|
||||||
|
"- Key macroeconomic factors affecting market momentum.\n"
|
||||||
|
"- Potential short-term vs. long-term opportunities.\n"
|
||||||
|
"- Sector performance trends (e.g., technology, healthcare, energy).\n"
|
||||||
|
"Highlight any risks, disclaimers, or uncertainties."
|
||||||
|
)
|
||||||
|
|
||||||
|
# Run the swarm with the user_request
|
||||||
|
swarm.run(user_request)
|
||||||
|
|
||||||
|
|
||||||
|
if __name__ == "__main__":
|
||||||
|
main()
|
||||||
@ -0,0 +1,51 @@
|
|||||||
|
from swarms.tools.base_tool import BaseTool
|
||||||
|
|
||||||
|
import requests
|
||||||
|
from swarms.utils.litellm_wrapper import LiteLLM
|
||||||
|
|
||||||
|
|
||||||
|
def get_stock_data(symbol: str) -> str:
|
||||||
|
"""
|
||||||
|
Fetches stock data from Yahoo Finance for a given stock symbol.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
symbol (str): The stock symbol to fetch data for (e.g., 'AAPL' for Apple Inc.).
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
Dict[str, Any]: A dictionary containing stock data, including price, volume, and other relevant information.
|
||||||
|
|
||||||
|
Raises:
|
||||||
|
ValueError: If the stock symbol is invalid or data cannot be retrieved.
|
||||||
|
"""
|
||||||
|
url = f"https://query1.finance.yahoo.com/v7/finance/quote?symbols={symbol}"
|
||||||
|
response = requests.get(url)
|
||||||
|
|
||||||
|
if response.status_code != 200:
|
||||||
|
raise ValueError(f"Error fetching data for symbol: {symbol}")
|
||||||
|
|
||||||
|
data = response.json()
|
||||||
|
if (
|
||||||
|
"quoteResponse" not in data
|
||||||
|
or not data["quoteResponse"]["result"]
|
||||||
|
):
|
||||||
|
raise ValueError(f"No data found for symbol: {symbol}")
|
||||||
|
|
||||||
|
return str(data["quoteResponse"]["result"][0])
|
||||||
|
|
||||||
|
|
||||||
|
tool_schema = BaseTool(
|
||||||
|
tools=[get_stock_data]
|
||||||
|
).convert_tool_into_openai_schema()
|
||||||
|
|
||||||
|
tool_schema = tool_schema["functions"][0]
|
||||||
|
|
||||||
|
llm = LiteLLM(
|
||||||
|
model_name="gpt-4o",
|
||||||
|
)
|
||||||
|
|
||||||
|
print(
|
||||||
|
llm.run(
|
||||||
|
"What is the stock data for Apple Inc. (AAPL)?",
|
||||||
|
tools=[tool_schema],
|
||||||
|
)
|
||||||
|
)
|
||||||
@ -0,0 +1,64 @@
|
|||||||
|
import torch
|
||||||
|
from transformers import (
|
||||||
|
AutoTokenizer,
|
||||||
|
BitsAndBytesConfig,
|
||||||
|
LlamaForCausalLM,
|
||||||
|
)
|
||||||
|
|
||||||
|
from swarms import Agent
|
||||||
|
|
||||||
|
|
||||||
|
class Lumo:
|
||||||
|
"""
|
||||||
|
A class for generating text using the Lumo model with 4-bit quantization.
|
||||||
|
"""
|
||||||
|
|
||||||
|
def __init__(self):
|
||||||
|
"""
|
||||||
|
Initializes the Lumo model with 4-bit quantization and a tokenizer.
|
||||||
|
"""
|
||||||
|
# Configure 4-bit quantization
|
||||||
|
bnb_config = BitsAndBytesConfig(
|
||||||
|
load_in_4bit=True,
|
||||||
|
bnb_4bit_quant_type="nf4",
|
||||||
|
bnb_4bit_compute_dtype=torch.float16,
|
||||||
|
llm_int8_enable_fp32_cpu_offload=True,
|
||||||
|
)
|
||||||
|
|
||||||
|
self.model = LlamaForCausalLM.from_pretrained(
|
||||||
|
"lumolabs-ai/Lumo-70B-Instruct",
|
||||||
|
device_map="auto",
|
||||||
|
quantization_config=bnb_config,
|
||||||
|
use_cache=False,
|
||||||
|
attn_implementation="sdpa",
|
||||||
|
)
|
||||||
|
self.tokenizer = AutoTokenizer.from_pretrained(
|
||||||
|
"lumolabs-ai/Lumo-70B-Instruct"
|
||||||
|
)
|
||||||
|
|
||||||
|
def run(self, task: str) -> str:
|
||||||
|
"""
|
||||||
|
Generates text based on the given prompt using the Lumo model.
|
||||||
|
|
||||||
|
Args:
|
||||||
|
prompt (str): The input prompt for the model.
|
||||||
|
|
||||||
|
Returns:
|
||||||
|
str: The generated text.
|
||||||
|
"""
|
||||||
|
inputs = self.tokenizer(task, return_tensors="pt").to(
|
||||||
|
self.model.device
|
||||||
|
)
|
||||||
|
outputs = self.model.generate(**inputs, max_new_tokens=100)
|
||||||
|
return self.tokenizer.decode(
|
||||||
|
outputs[0], skip_special_tokens=True
|
||||||
|
)
|
||||||
|
|
||||||
|
|
||||||
|
Agent(
|
||||||
|
agent_name="Solana-Analysis-Agent",
|
||||||
|
model_name=Lumo(),
|
||||||
|
max_loops="auto",
|
||||||
|
interactive=True,
|
||||||
|
streaming_on=True,
|
||||||
|
).run("How do i create a smart contract in solana?")
|
||||||
@ -0,0 +1,34 @@
|
|||||||
|
from swarms import Agent
|
||||||
|
from swarms.prompts.finance_agent_sys_prompt import (
|
||||||
|
FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
)
|
||||||
|
from swarms.structs.majority_voting import MajorityVoting
|
||||||
|
from dotenv import load_dotenv
|
||||||
|
|
||||||
|
load_dotenv()
|
||||||
|
|
||||||
|
|
||||||
|
# Initialize the agent
|
||||||
|
agent = Agent(
|
||||||
|
agent_name="Financial-Analysis-Agent",
|
||||||
|
agent_description="Personal finance advisor agent",
|
||||||
|
system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
|
||||||
|
max_loops=1,
|
||||||
|
model_name="gpt-4o",
|
||||||
|
dynamic_temperature_enabled=True,
|
||||||
|
user_name="swarms_corp",
|
||||||
|
retry_attempts=3,
|
||||||
|
context_length=8192,
|
||||||
|
return_step_meta=False,
|
||||||
|
output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
|
||||||
|
auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
|
||||||
|
max_tokens=4000, # max output tokens
|
||||||
|
saved_state_path="agent_00.json",
|
||||||
|
interactive=False,
|
||||||
|
)
|
||||||
|
|
||||||
|
swarm = MajorityVoting(agents=[agent, agent, agent])
|
||||||
|
|
||||||
|
swarm.run(
|
||||||
|
"Create a table of super high growth opportunities for AI. I have $40k to invest in ETFs, index funds, and more. Please create a table in markdown.",
|
||||||
|
)
|
||||||
Some files were not shown because too many files have changed in this diff Show More
Loading…
Reference in new issue