Spaces:
Running
on
Zero
Running
on
Zero
Update app.py
Browse files
app.py
CHANGED
@@ -1,4 +1,6 @@
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import os
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import spaces
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import threading
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import time
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@@ -18,26 +20,28 @@ OLLAMA_SERVICE_THREAD.start()
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print("Giving ollama serve a moment")
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time.sleep(10)
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-
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import copy
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import gradio as gr
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from ollama import Client
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client = Client(host='http://localhost:11434', timeout=
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL_ID = os.environ.get("MODEL_ID", "google/gemma-2-
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MODEL_NAME = MODEL_ID.split("/")[-1]
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TITLE = "<h1><center>
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DESCRIPTION = f"""
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<h3>MODEL: <a href="https://hf.co/{MODEL_ID}">{MODEL_NAME}</a></h3>
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<center>
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<p>
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<br>
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</p>
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</center>
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"""
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@@ -54,10 +58,10 @@ h3 {
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}
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"""
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@spaces.GPU()
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def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
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print(f'history is - {history}')
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conversation = []
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for prompt, answer in history:
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conversation.extend([
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@@ -69,7 +73,7 @@ def stream_chat(message: str, history: list, temperature: float, max_new_tokens:
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print(f"Conversation is -\n{conversation}")
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response = client.chat(
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model=
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messages=conversation,
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stream=True,
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options={
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import os
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#remove this if in CPU
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import spaces
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import threading
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import time
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print("Giving ollama serve a moment")
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time.sleep(10)
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# Modify the model to what you want
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model = "gemma2:27b"
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subprocess.run(f"~/ollama pull {model}", shell=True)
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import copy
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import gradio as gr
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from ollama import Client
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client = Client(host='http://localhost:11434', timeout=120)
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HF_TOKEN = os.environ.get("HF_TOKEN", None)
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MODEL_ID = os.environ.get("MODEL_ID", "google/gemma-2-27b-it")
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MODEL_NAME = MODEL_ID.split("/")[-1]
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TITLE = "<h1><center>ollama-Chat</center></h1>"
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DESCRIPTION = f"""
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<h3>MODEL: <a href="https://hf.co/{MODEL_ID}">{MODEL_NAME}</a></h3>
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<center>
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<p>Feel free to test models with ollama.
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<br>
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Easy to modify and running models even in CPU.
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</p>
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</center>
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"""
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}
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"""
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# Remove this if in CPU
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@spaces.GPU()
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def stream_chat(message: str, history: list, temperature: float, max_new_tokens: int, top_p: float, top_k: int, penalty: float):
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conversation = []
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for prompt, answer in history:
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conversation.extend([
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print(f"Conversation is -\n{conversation}")
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response = client.chat(
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model=model,
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messages=conversation,
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stream=True,
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options={
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