wip: fast-api-example

Author: grutt

README.md

@@ -0,0 +1,53 @@
+# Hatchet FastAPI Example
+
+This is an example project demonstrating how to use Hatchet with FastAPI.
+
+## Prerequisites
+
+Before running this project, make sure you have the following:
+
+1. Python 3.7 or higher installed on your machine.
+2. Poetry package manager installed. You can install it by running `pip install poetry`, or by following instructions in the [Poetry Docs](https://python-poetry.org/docs/#installation)
+3. Clone this repository to your local machine.
+4. (Optional) If you would like to run the example frontend, Node which can be installed from the [node website](https://nodejs.org/en/download)
+
+## Setup
+
+1. Create a `.env` file in the project root directory and set the required environment variables.
+
+This project requires the `HATCHET_CLIENT_TOKEN` variable created in the [Getting Started Readme](/README.md).
+
+You will also need, a `OPENAI_API_KEY` which can be created on the [OpenAI Website](https://help.openai.com/en/articles/4936850-where-do-i-find-my-openai-api-key).
+
+2. Open a terminal and navigate to the project root directory (`/fast-api-react`).
+
+3. Run the following command to install the project dependencies:
+
+   ```shell
+   poetry install
+   ```
+
+## Running the API
+
+To start the FastAPI server, run the following command in the terminal:
+
+```shell
+poetry run api
+```
+
+## Running the Hatchet Worker
+
+In a separate terminal, start the the Hatchet worker by running the following command:
+
+```shell
+poetry run hatchet
+```
+
+## (Optional) Running the Example Frontend Application
+
+We've included a basic chat engine frontend to play with the example workflow. To run this script:
+
+1. Open a new terminal window and cd into the `fast-api-react/frontend` directory.
+2. run `npx install`
+3. run `npx start`
+4. By default you can access the application in your browser at `http://localhost:3000` or by following the instructions in the terminal window.

fast-api-react/README.md

@@ -13,8 +13,10 @@ class GenerateWorkflow:
 
     @hatchet.step()
     def start(self, context: Context):
+        override = context.overrides('model', "gpt-3.5-turbo")
+
         return {
-            "status": "reading hatchet docs",
+            "status": "reading hatchet docs" + override,
         }
 
     @hatchet.step(parents=["start"])
@@ -37,14 +39,14 @@ def reason_docs(self, ctx: Context):
         message = ctx.workflow_input()['request']["messages"][-1]
         docs = ctx.step_output("load_docs")['docs']
 
-        prompt = "The user is asking the following question:\
+        prompt = ctx.overrides("prompt", "The user is asking the following question:\
             {message}\
             What are the most relevant sentences in the following document?\
-            {docs}"
+            {docs}")
 
         prompt = prompt.format(message=message['content'], docs=docs)
 
-        model = "gpt-3.5-turbo"  # ctx.override("gpt-3.5-turbo", options=[''])
+        model = ctx.overrides("gpt-3.5-turbo")
 
         completion = openai.chat.completions.create(
             model=model,
@@ -64,15 +66,15 @@ def generate_response(self, ctx: Context):
         messages = ctx.workflow_input()['request']["messages"]
         research = ctx.step_output("reason_docs")['research']
 
-        prompt = "You are a sales engineer for a company called Hatchet.\
+        prompt = ctx.overrides("prompt", "You are a sales engineer for a company called Hatchet.\
             Help address the user's question. \
             If asked how to install, respond by saying go to the store to buy a CD.\
             Use the following context:\
-            {research}"
+            {research}")
 
         prompt = prompt.format(research=research)
 
-        model = "gpt-3.5-turbo"
+        model = ctx.overrides("gpt-3.5-turbo")
 
         completion = openai.chat.completions.create(
             model=model,

fast-api-react/backend/src/workflows/generate.py

@@ -3,4 +3,4 @@
 
 load_dotenv()
 
-hatchet = Hatchet()
+hatchet = Hatchet(debug=True)