v0.1.9

premAI-io · Feb 8, 2024 · d38187d · d38187d
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diff --git a/.pre-commit-config.yaml b/.pre-commit-config.yaml
diff --git a/CNAME b/CNAME
diff --git a/LICENSE b/LICENSE
diff --git a/Manifest.in b/Manifest.in
diff --git a/README.md b/README.md
@@ -1,69 +1,30 @@
-<div align="center">
-  <h1 align="center">🚀 Prem Python SDK</h1>
-  <p align="center">The Prem Python SDK is a Python library for interacting with the <a href="https://github.com/premAI-io/prem-saas">Prem  API</a></p>
-
-[![PyPI version](https://img.shields.io/pypi/v/premai.svg)](https://pypi.org/project/premai/)
-[![GitHub contributors](https://img.shields.io/github/contributors/premAI-io/prem-python-sdk.svg)](https://github.com/premAI-io/prem-python-sdk/graphs/contributors)
-[![GitHub last commit](https://img.shields.io/github/last-commit/premAI-io/prem-python-sdk.svg)](https://github.com/premAI-io/prem-python-sdk/commits/master)
-[![GitHub top language](https://img.shields.io/github/languages/top/premAI-io/prem-python-sdk.svg)](https://github.com/premAI-io/prem-python-sdk)
-[![GitHub issues](https://img.shields.io/github/issues/premAI-io/prem-python-sdk.svg)](https://github.com/premAI-io/prem-python-sdk/issues)
-</div>
-
-
-<details>
-    <summary>Table of Contents</summary>
-    <ol>
-        <li><a href="#installation">Installation</a></li>
-        <li><a href="#usage">Usage</a></li>
-        <ol>
-            <li><a href="#getting-started">Getting Started</a></li>
-            <li><a href="#completions">Completions</a></li>
-            <li><a href="#embeddings">Embeddings</a></li>
-            <li><a href="#data-points">DataPoints</a></li>
-        </ol>
-    </ol>
-</details>
 
-## Installation
-
-### From Source
-
-1. Clone the Prem Python SDK repository:
+# Prem Python SDK
 
-   ```bash
-   git clone https://github.com/premAI-io/prem-python-sdk.git
-   ``````
+## Installation
 
-2. Install the SDK
-    ```bash
-    cd prem-python-sdk
-    python -m venv venv
-    source venv/bin/activate
-    pip install .
-    ```
-### From PyPI
 You can also install the Prem Python SDK directly from PyPI.
 
 ```bash
-python -m venv venv
-source venv/bin/activate
 pip install premai
 ```
+
 ## Usage
 ### Getting Started
 To use the Prem Python SDK, you need to obtain an API key from the Prem platform. You can then create a `Prem` instance to make requests to the API.
 
 ```python
-from prem import Prem
+from premai import Prem
 
-api_key = "YOUR_API_KEY"
-base_url = "https://api.prem.com"  # Update with the base URL of the Prem API
+client = Prem(
+    api_key=YOUR_API_KEY
+)
 
-client = Prem(api_key=api_key, base_url=base_url)
+project_id = YOUR_PROJECT_ID
 ```
 
-### Completions
-The `completions` module allows you to generate completions based on user input. Here's an example:
+### Chat completion
+The `chat.completions` module allows you to generate completions based on user input. Here's an example:
 
 ```python
 messages = [
@@ -73,45 +34,27 @@ messages = [
 model = "gpt-3.5-turbo"
 
 # Create completion
-response = client.completions.create(project_id=1, messages=messages, model=model, stream=False)
-print(response)
+response = client.chat.completions.create(
+    project_id=project_id,
+    messages=messages,
+    model=model,
+    stream=False
+)
+
+print(response.choices)
+
+# Create completion with stream
+response = client.chat.completions.create(
+    project_id=project_id,
+    messages=messages,
+    model=model,
+    stream=True
+)
+
+for chunk in response:
+    if chunk.choices[0].delta["content"]:
+        print(chunk.choices[0].delta["content"], end="")
+
+print(f"\nTrace ID: {response.trace_id}")
 ```
 
-### Embeddings
-The `embeddings` module enables you to create embeddings for given input. Example:
-
-```python
-input_text = "What is a transformer?"
-model = "text-embedding-ada-002"
-
-# Create embeddings
-response = client.embeddings.create(project_id=1, input=input_text, model=model)
-print(response)
-```
-
-### Data Points
-The `datapoints` module allows you to manage data points, including creating, updating, retrieving, and deleting. Example:
-```python
-input_text = "What is a transformer?"
-output_text = "A transformer is a deep learning model that uses self-attention."
-
-# Create 10 data points
-for _ in range(10):
-    data_point = client.datapoints.create(project_id=1, input=input_text, output=output_text, positive=True)
-
-# Update the last data point
-patched_data_point = client.datapoints.update(datapoint_id=data_point.id, data={"positive": False})
-
-# Retrieve the updated data point
-print(client.datapoints.retrieve(datapoint_id=data_point.id))
-
-# Delete the updated data point
-client.datapoints.delete(datapoint_id=data_point.id)
-
-# List all data points
-datapoints = client.datapoints.list(project_id=1)
-print("Total number of datapoints:", len(datapoints))
-for datapoint in datapoints:
-    print("Deleted data point with ID:", datapoint.id)
-    client.datapoints.delete(datapoint_id=datapoint.id)
-```
diff --git a/dev-requirements.txt b/dev-requirements.txt
diff --git a/docs/Makefile b/docs/Makefile
diff --git a/docs/source/conf.py b/docs/source/conf.py
diff --git a/docs/source/index.rst b/docs/source/index.rst
diff --git a/docs/source/prem.client.rst b/docs/source/prem.client.rst
diff --git a/docs/source/prem.resources.completions.rst b/docs/source/prem.resources.completions.rst
diff --git a/docs/source/prem.resources.datapoints.rst b/docs/source/prem.resources.datapoints.rst
diff --git a/docs/source/prem.resources.embeddings.rst b/docs/source/prem.resources.embeddings.rst
diff --git a/docs/source/prem.resources.rst b/docs/source/prem.resources.rst
diff --git a/prem/__init__.py b/prem/__init__.py