Merge pull request #242 from polywrap/dev

Dev Release March 14th

LICENSE

@@ -0,0 +1,22 @@
+The MIT License (MIT)
+
+Copyright (c) 2023 Polywrap Foundation
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in
+all copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
+THE SOFTWARE.
+

README.md

@@ -1,7 +1,46 @@
-# fund-public-goods-ai
-## Dev
-From Root:
-1. `nvm install && nvm use`
-2. `yarn`
-3. `yarn build`
-4. `yarn dev`
+# evo.sage
+![](./content/evo-sage-banner.png)
+
+---
+
+[Discord](https://discord.gg/k7UCsH3ps9) | [Website](https://fundpublicgoods.ai) | :star: the repo !  
+
+---
+
+## Welcome!
+
+evo.sage is an agent that specializes in streamlining resource allocation. Try it now at [fundpublicgoods.ai](https://fundpublicgoods.ai)
+
+![](./content/fundpublicgoods-ss.jpg)
+
+## Need Help?
+
+Join our [Discord community](https://discord.gg/k7UCsH3ps9) for support and discussions.
+
+[![Join us on Discord](https://invidget.switchblade.xyz/k7UCsH3ps9)](https://discord.com/invite/k7UCsH3ps9)
+
+If you have questions or encounter issues, please don't hesitate to [create a new issue](https://github.com/polywrap/evo.sage/issues/new) to get support.
+
+## How it works
+
+evo.sage is designed to generate funding allocation strategies based on the user's preferences and publicly available data. In its first implementation, it focuses on how to best allocate funds to Public Good Projects (PGPs) that were apart of past [GitCoin](https://www.gitcoin.co/) rounds.
+
+Digging a bit deeper, here are the steps the agent takes when creating an allocation strategy:
+
+1. **Find Relevant Projects.** Perform a vector similarity search across project data from all past Gitcoin rounds. Aggregate the results, filter out duplicates, and rerank the results based on the original prompt to arrive at the top ten. *Techniques used: [Similarity Search](https://www.pinecone.io/learn/what-is-similarity-search/), [LLM-based Reranking](https://medium.com/@foadmk/enhancing-data-retrieval-with-vector-databases-and-gpt-3-5-reranking-c58ec6061bde)*
+
+2. **Generate Holistic Evaluations.** Generate a comprehensive report for each project that breaks down its a) relevance, b) impact, and c) funding needs. *Techniques used: [Generated Knowledge Prompting](https://www.promptingguide.ai/techniques/knowledge), [Zero-Shot Prompting](https://www.promptingguide.ai/techniques/zeroshot), Summarization*
+
+3. **Compute Evaluation Scores.** Analyze each report and assign a numerical evaluation score from 0-10 for each of the three criteria. Combine these scores through a weighted average to arrive at the project’s overall score. Weight the allocation percentages in proportion to scores of the projects with addresses on the selected chain. *Techniques used: [RAG](https://www.promptingguide.ai/techniques/rag), Numerical Evaluations, Algorithmic Composition*
+
+![](./content/strategy-ss.png)
+
+The allocation strategy includes a report for each project summarizing the agent’s findings. 
+
+![](./content/report-ss.png)
+
+One critical aspect of the report is the impact section. The agent uses information from the project’s Gitcoin round applications to arrive at an intelligent estimate of the impact that a project has had.
+
+Another unique aspect of the report is that it estimates each project’s funding needs based on information like prior funding and team size. This help gives context on the project’s past funding sources, such as venture backing or grants.
+
+An important limitation to note is that this version of the agent only uses self-reported data from projects. But future versions could use a variety of on- and off-chain data from third parties.

web/app/layout.tsx

@@ -26,7 +26,7 @@ function Footer() {
         <span>a web3 agent by</span>
         <a
           className='underline font-semibold'
-          href='https://blog.polywrap.io'
+          href='https://polywrap.io'
           target='_blank'
           rel='noopener noreferrer'>
           polywrap

workers/fund_public_goods/lib/strategy/utils/generate_impact_funding_reports.py

@@ -36,7 +36,7 @@ def generate_impact_funding_reports(projects: list[tuple[Projects, list[Answer]]
         ("system", reports_prompt_template),
     ])
 
-    llm = ChatOpenAI(model="gpt-3.5-turbo-0125", max_tokens=500)
+    llm = ChatOpenAI(model="gpt-3.5-turbo-0125")
 
     reports_chain = reports_prompt | llm | StrOutputParser()
 

workers/fund_public_goods/lib/strategy/utils/generate_relevancy_reports.py

@@ -32,7 +32,7 @@ def generate_relevancy_reports(prompt: str, projects: list[tuple[Projects, list[
         ("system", reports_prompt_template),
     ])
 
-    llm = ChatOpenAI(model="gpt-3.5-turbo-0125", max_tokens=250)
+    llm = ChatOpenAI(model="gpt-3.5-turbo-0125")
 
     reports_chain = (
         reports_prompt |