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README.md

@@ -1,12 +1,12 @@
+
 ---
-title: Llm Sambanova Main
-emoji: 🏢
-colorFrom: purple
-colorTo: blue
+title: llm_sambanova_main 
+emoji: 🔥
+colorFrom: indigo
+colorTo: indigo
 sdk: gradio
 sdk_version: 5.7.0
-app_file: app.py
+app_file: run.py
 pinned: false
+hf_oauth: true
 ---
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

requirements.txt

@@ -0,0 +1,3 @@
+gradio-client @ git+https://github.com/gradio-app/gradio@afd75def9e979d9b255a6d22d33a3aee63b6f225#subdirectory=client/python
+https://gradio-pypi-previews.s3.amazonaws.com/afd75def9e979d9b255a6d22d33a3aee63b6f225/gradio-5.7.0-py3-none-any.whl
+openai>=1.0.0

run.ipynb

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+{"cells": [{"cell_type": "markdown", "id": "302934307671667531413257853548643485645", "metadata": {}, "source": ["# Gradio Demo: llm_sambanova"]}, {"cell_type": "code", "execution_count": null, "id": "272996653310673477252411125948039410165", "metadata": {}, "outputs": [], "source": ["!pip install -q gradio openai>=1.0.0 "]}, {"cell_type": "code", "execution_count": null, "id": "288918539441861185822528903084949547379", "metadata": {}, "outputs": [], "source": ["# This is a simple general-purpose chatbot built on top of SambaNova API. \n", "# Before running this, make sure you have exported your SambaNova API key as an environment variable:\n", "# export SAMBANOVA_API_KEY=\"your-sambanova-api-key\"\n", "\n", "import os\n", "import gradio as gr\n", "from openai import OpenAI\n", "\n", "api_key = os.getenv(\"SAMBANOVA_API_KEY\")\n", "\n", "client = OpenAI(\n", "    base_url=\"https://api.sambanova.ai/v1/\",\n", "    api_key=api_key,\n", ")\n", "\n", "def predict(message, history):\n", "    history.append({\"role\": \"user\", \"content\": message})\n", "    stream = client.chat.completions.create(messages=history, model=\"Meta-Llama-3.1-70B-Instruct-8k\", stream=True)\n", "    chunks = []\n", "    for chunk in stream:\n", "        chunks.append(chunk.choices[0].delta.content or \"\")\n", "        yield \"\".join(chunks)\n", "\n", "demo = gr.ChatInterface(predict, type=\"messages\")\n", "\n", "if __name__ == \"__main__\":\n", "    demo.launch()\n", "\n"]}], "metadata": {}, "nbformat": 4, "nbformat_minor": 5}

run.py

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+# This is a simple general-purpose chatbot built on top of SambaNova API. 
+# Before running this, make sure you have exported your SambaNova API key as an environment variable:
+# export SAMBANOVA_API_KEY="your-sambanova-api-key"
+
+import os
+import gradio as gr
+from openai import OpenAI
+
+api_key = os.getenv("SAMBANOVA_API_KEY")
+
+client = OpenAI(
+    base_url="https://api.sambanova.ai/v1/",
+    api_key=api_key,
+)
+
+def predict(message, history):
+    history.append({"role": "user", "content": message})
+    stream = client.chat.completions.create(messages=history, model="Meta-Llama-3.1-70B-Instruct-8k", stream=True)
+    chunks = []
+    for chunk in stream:
+        chunks.append(chunk.choices[0].delta.content or "")
+        yield "".join(chunks)
+
+demo = gr.ChatInterface(predict, type="messages")
+
+if __name__ == "__main__":
+    demo.launch()
+