Skip to content

Commit

Permalink
Restructure the graph
Browse files Browse the repository at this point in the history
  • Loading branch information
@hinthornw
hinthornw committed Sep 17, 2024
2 parents 0f55080 + 16a8636 commit ee273cd
Show file tree
Hide file tree
Showing 15 changed files with 1,127 additions and 584 deletions.
13 changes: 11 additions & 2 deletions .env.example
View file
Original file line number Diff line number Diff line change
@@ -1,2 +1,11 @@
ANTHROPIC_API_KEY=...
TAVILY_API_KEY=...
TAVILY_API_KEY=...

# To separate your traces from other application
LANGCHAIN_PROJECT=data-enrichment

# The following depend on your selected configuration

## LLM choice:
ANTHROPIC_API_KEY=....
FIREWORKS_API_KEY=...
OPENAI_API_KEY=...
299 changes: 282 additions & 17 deletions README.md
View file
Original file line number Diff line number Diff line change
Expand Up @@ -13,43 +13,308 @@ It contains an example graph exported from `src/agent.ts` that implements a rese

The enrichment agent:

1. Takes a research topic as input
1. Takes a research **topic** and requested **templateSchema** as input
2. Searches the web for relevant information
3. Reads and extracts key details from websites
4. Organizes the findings into a structured format
4. Organizes the findings into the requested structured format
5. Validates the gathered information for completeness and accuracy

By default, it's set up to gather information based on the user-provided schema passed through the `schema` key in the state.
By default, it's set up to gather information based on the user-provided schema passed through the `templateSchema` key in the state.

## Getting Started

This template was designed for [LangGraph Studio](https://github.com/langchain-ai/langgraph-studio). To use, clone this repo locally and open the folder in LangGraph Studio.
You will need the latest versions of `@langchain/langgraph` and `@langchain/core`. See these instructions for help upgrading an [existing project](https://langchain-ai.github.io/langgraphjs/how-tos/manage-ecosystem-dependencies/).

Note that the `Deploy` button is currently not supported, but will be soon!
Assuming you have already [installed LangGraph Studio](https://github.com/langchain-ai/langgraph-studio?tab=readme-ov-file#download), to set up:

You will need the latest versions of `@langchain/langgraph` and `@langchain/core`. See these instructions for help upgrading an [existing project](https://langchain-ai.github.io/langgraphjs/how-tos/manage-ecosystem-dependencies/).
1. Create a `.env` file.

```bash
cp .env.example .env
```

2. Define required API keys in your `.env` file.

The primary [search tool](./src/enrichment_agent/tools.ts) [^1] used is [Tavily](https://tavily.com/). Create an API key [here](https://app.tavily.com/sign-in).

<!--
Setup instruction auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
-->

<details>
<summary>Setup for `modelName`</summary>
The `llm` configuration defaults are shown below:

```yaml
modelName: anthropic/claude-3-5-sonnet-20240620
```
Follow the instructions below to get set up, or pick one of the additional options.
### Anthropic Chat Models
To use Anthropic's chat models:
1. Sign up for an [Anthropic API key](https://console.anthropic.com/) if you haven't already.
2. Once you have your API key, add it to your `.env` file:

```
ANTHROPIC_API_KEY=your-api-key
```
You can also [click here](https://www.loom.com/share/81cafa32d57f4933bd5d9b08c70f460c?sid=4ebcb366-f27a-4c49-854d-169106b4f6fe) to see a (rough) video tour of Studio.
### Fireworks Chat Models
To set up:
To use Fireworks AI's chat models:
1. Sign up for a [Fireworks AI account](https://app.fireworks.ai/signup) and obtain an API key.
2. Add your Fireworks AI API key to your `.env` file:
```
FIREWORKS_API_KEY=your-api-key
```
#### OpenAI Chat Models
To use OpenAI's chat models:
1. Sign up for an [OpenAI API key](https://platform.openai.com/signup).
2. Once you have your API key, add it to your `.env` file:
```
OPENAI_API_KEY=your-api-key
```
</details>
<!--
End setup instructions
-->
1. Set up your API keys for the LLM (Claude) and search tool (Tavily) in the `.env` file.
2. Install the required dependencies (`yarn`)
3. Customize whatever you'd like in the code.
4. Run the script with your research topic as input.
4. Open the folder LangGraph Studio!
## How to customize
1. **Customize research targets**: Provide a custom `templateSchema` when calling the graph to gather different types of information.
2. **Select a different model**: We default to anthropic (sonnet-35). You can select a compatible chat model using `provider/model-name` via configuration. Example: `openai/gpt-4o-mini`.
3. **Customize the prompt**: We provide a default prompt in [prompts.ts](./src/enrichment_agent/prompts.ts). You can easily update this via configuration in the studio.
You can also quickly extend this template by:
- Adding new tools and API connections in [tools.ts](./src/enrichment_agent/tools.ts). These are just any TypeScript functions.
- Adding additional steps in [graph.ts](./src/enrichment_agent/graph.ts). Concerned about hallucination
## Development
While iterating on your graph, you can edit past state and rerun your app from past states to debug specific nodes. Local changes will be automatically applied via hot reload. Try adding an interrupt before the agent calls tools, updating the default system message in `src/utils/state.ts` to take on a persona, or adding additional nodes and edges!
While iterating on your graph, you can edit past state and rerun your app from past states to debug specific nodes. Local changes will be automatically applied via hot reload. Try adding an interrupt before the agent calls tools, updating the default system message in `src/enrichment_agent/utils.ts` to take on a persona, or adding additional nodes and edges!
Follow up requests will be appended to the same thread. You can create an entirely new thread, clearing previous history, using the `+` button in the top right.
You can find the latest (under construction) docs on [LangGraph.js](https://langchain-ai.github.io/langgraphjs/) here, including examples and other references. Using those guides can help you pick the right patterns to adapt here for your use case.
You can find the latest (under construction) docs on [LangGraph](https://langchain-ai.github.io/langgraphjs/) here, including examples and other references. Using those guides can help you pick the right patterns to adapt here for your use case.
LangGraph Studio also integrates with [LangSmith](https://smith.langchain.com/) for more in-depth tracing and collaboration with teammates.
## How to extend it
[^1]: https://js.langchain.com/docs/concepts#tools
1. **Customize research targets**: Modify the `InfoSchema` to gather different types of information.
2. **Enhance data sources and validation**: Add new tools, APIs, or implement more rigorous fact-checking.
3. **Improve output and interactivity**: Develop custom formatting and user feedback mechanisms.
<!--
Configuration auto-generated by `langgraph template lock`. DO NOT EDIT MANUALLY.
{
"config_schemas": {
"agent": {
"type": "object",
"properties": {
"modelName": {
"type": "string",
"default": "anthropic/claude-3-5-sonnet-20240620",
"description": "The name of the language model to use for the agent. Should be in the form: provider/model-name.",
"environment": [
{
"value": "anthropic/claude-1.2",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-2.0",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-2.1",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-3-5-sonnet-20240620",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-3-haiku-20240307",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-3-opus-20240229",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-3-sonnet-20240229",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "anthropic/claude-instant-1.2",
"variables": "ANTHROPIC_API_KEY"
},
{
"value": "fireworks/gemma2-9b-it",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3-70b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3-70b-instruct-hf",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3-8b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3-8b-instruct-hf",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3p1-405b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3p1-405b-instruct-long",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3p1-70b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/llama-v3p1-8b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/mixtral-8x22b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/mixtral-8x7b-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/mixtral-8x7b-instruct-hf",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/mythomax-l2-13b",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/phi-3-vision-128k-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/phi-3p5-vision-instruct",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/starcoder-16b",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "fireworks/yi-large",
"variables": "FIREWORKS_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-0125",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-0301",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-0613",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-1106",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-16k",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-3.5-turbo-16k-0613",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-0125-preview",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-0314",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-0613",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-1106-preview",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-32k",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-32k-0314",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-32k-0613",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-turbo",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-turbo-preview",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4-vision-preview",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4o",
"variables": "OPENAI_API_KEY"
},
{
"value": "openai/gpt-4o-mini",
"variables": "OPENAI_API_KEY"
}
]
}
},
"environment": [
"TAVILY_API_KEY"
]
}
}
}
-->
2 changes: 1 addition & 1 deletion langgraph.json
View file
Original file line number Diff line number Diff line change
Expand Up @@ -3,7 +3,7 @@
"dockerfile_lines": [],
"dependencies": ["."],
"graphs": {
"agent": "./src/agent.ts:graph"
"agent": "./src/enrichment_agent/graph.ts:graph"
},
"env": ".env"
}
19 changes: 10 additions & 9 deletions package.json
View file
Original file line number Diff line number Diff line change
@@ -1,8 +1,8 @@
{
"name": "company-researcher-js",
"name": "data-enrichment",
"version": "0.0.1",
"description": "An agent that researches a given company",
"main": "agent.ts",
"description": "A LangGraphJS template that populates ",
"main": "src/enrichment_agent/graph.ts",
"author": "William Fu-Hinthorn",
"license": "MIT",
"private": true,
Expand All @@ -20,12 +20,13 @@
"test:all": "yarn test && yarn test:int && yarn lint:langgraph"
},
"dependencies": {
"@langchain/anthropic": "^0.2.15",
"@langchain/community": "^0.2.31",
"@langchain/core": "^0.2.31",
"@langchain/langgraph": "^0.1.8",
"langchain": "^0.2.17",
"langsmith": "^0.1.48",
"@langchain/anthropic": "^0.3.0",
"@langchain/community": "^0.3.0",
"@langchain/core": "^0.3.1",
"@langchain/langgraph": "^0.2.3",
"langchain": "^0.3.2",
"langsmith": "^0.1.55",
"ts-node": "^10.9.2",
"zod": "^3.23.8"
},
"devDependencies": {
Expand Down
Loading

0 comments on commit ee273cd

Please sign in to comment.