curl --request POST \
--url http://localhost:8080/create?app_id=app1 \
-F "config=@/path/to/config.yaml"
{ "response": "App created successfully. App ID: app1" }
REST API Service
Create app
Create a new app using App ID
POST
/
create
curl --request POST \
--url http://localhost:8080/create?app_id=app1 \
-F "config=@/path/to/config.yaml"
{ "response": "App created successfully. App ID: app1" }
curl --request POST \
--url http://localhost:8080/create?app_id=app1 \
-F "config=@/path/to/config.yaml"
{ "response": "App created successfully. App ID: app1" }
config.yaml file (adjust according to your requirements):
app:
config:
id: "default-app"
llm:
provider: openai
config:
model: "gpt-4o-mini"
temperature: 0.5
max_tokens: 1000
top_p: 1
stream: false
prompt: |
Use the following pieces of context to answer the query at the end.
If you don't know the answer, just say that you don't know, don't try to make up an answer.
$context
Query: $query
Helpful Answer:
vectordb:
provider: chroma
config:
collection_name: "rest-api-app"
dir: db
allow_reset: true
embedder:
provider: openai
config:
model: "text-embedding-ada-002"
Request
curl --request POST \
--url http://localhost:8080/create?app_id=my-app \
-F "config=@/path/to/config.yaml"
| Keys | Providers |
|---|---|
OPENAI_API_KEY | OpenAI, Azure OpenAI, Jina etc |
OPENAI_API_TYPE | Azure OpenAI |
OPENAI_API_BASE | Azure OpenAI |
OPENAI_API_VERSION | Azure OpenAI |
COHERE_API_KEY | Cohere |
TOGETHER_API_KEY | Together |
ANTHROPIC_API_KEY | Anthropic |
JINACHAT_API_KEY | Jina |
HUGGINGFACE_ACCESS_TOKEN | Huggingface |
REPLICATE_API_TOKEN | LLAMA2 |
-e flag.
For example,
docker run --name embedchain -p 8080:8080 -e OPENAI_API_KEY=<YOUR_OPENAI_API_KEY> embedchain/rest-api:latest
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