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https://github.com/mikeghen/ai-marketplace
https://github.com/mikeghen/ai-marketplace
Last synced: about 8 hours ago
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- Host: GitHub
- URL: https://github.com/mikeghen/ai-marketplace
- Owner: mikeghen
- Created: 2024-04-08T18:17:41.000Z (7 months ago)
- Default Branch: main
- Last Pushed: 2024-04-21T15:54:27.000Z (7 months ago)
- Last Synced: 2024-05-16T04:17:46.927Z (6 months ago)
- Language: TypeScript
- Size: 611 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- Contributing: CONTRIBUTING.md
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README
# AI Marketplace
AI Marketplace is a platform that allows users to share and sell their AI models. The platform is built with a payment system handled on chain. Service providers offer to host a LangChain Runtime Environment where a Python workload can be executed using LangChain. Use a model for a chat and pay per use.
## Chat Demo
The Chat demo uses the AI Marketplace on the back end to answer user prompts. User's pay for each reponse using ETH.
## Architecture
```mermaid
graph TB
UM["Users"] -- "Submit Request" --> AM["AI Marketplace"]
UM -- "Payment" --> AM
AM -- "Tip with Request" --> H["TellorFlex"]
AM -- "Payment" --> H["TellorFlex"]
H -- "Receives Request" --> R["Reporter"]
R -- "Invokes LLM" --> LRE["LangChain Runtime Environment"]
LRE -- "Utilizes" --> LC["LangChain"]
LC -- "Runs Python Script" --> PA["Python"]
PA -- "Submits Response" --> H
style AM fill:#09f,stroke:#333,stroke-width:4px
style H fill:#0b0,stroke:#333,stroke-width:2px
style R fill:#0b0,stroke:#333,stroke-width:2px
style LRE fill:#dfd,stroke:#333,stroke-width:2px
```
# Concepts
## Workload
A workload is a Python script that defines a LangChain model.
It MUST contain:
- prompt - a string that is the prompt for the model
- input - a string that is the input for the model
It MAY contain:
- model - a string that is the model to use
- temperature - a float that is the temperature to use
Example:
```
prompt = "What is the meaning of life?"
input = "The meaning of life is to be happy."
```
These workloads are executed using a function that may look like this:
```python
function work(prompt: str, input: str) -> str:
model = ChatOpenAI(openai_api_key=os.getenv("OPENAI_APY_KEY", ""), temperature=0.1)
full_prompt = ChatPromptTemplate.from_messages(
[
("system", prompt),
("human", "{input}"),
]
)
chain = (
{"input": RunnablePassthrough()}
| full_prompt
| model
| StrOutputParser()
)
return chain.invoke(input)
```
There's a lot more that can be put in as arguments for the `work` function but this is the minimum required. The example above assumes the workload executor has setup OpenAI and LangChain properly.
## Payments
Payments are made to a Host for the execution of a workload. The Host is responsible for executing the workload and returning the result. The payment is made using the LangChain token.
### Requesting Execution
Publish your prompt and input into a transaction onchain along with an amount of ETH to be paid to the host for running the workload. The host will execute the workload and return the result.
## Hosts
Hosts listen to a onchain index of workloads and execute them. They are paid for their services.
# Tellor Integration
# Future Work
* Better Model Execution Runtime Environment - The current runtime environment is very basic and could be improved.
* Homomophic Encryption - Encrypt the input and output of the workload so that the host cannot see the data. This would allow for more sensitive data to be used in the workloads.
* More Models - Add more models to the platform to allow for more diverse workloads.
* More Payment Options - Add more payment options to the platform to allow for more diverse payment options.