diff --git a/README.md b/README.md index 172d325..9995f53 100644 --- a/README.md +++ b/README.md @@ -5,7 +5,7 @@ The Ollama Python library provides the easiest way to integrate Python 3.8+ proj ## Prerequisites - [Ollama](https://ollama.com/download) should be installed and running -- Pull a model to use with the library: `ollama pull ` e.g. `ollama pull llama3.2` +- Pull a model to use with the library: `ollama pull ` e.g. `ollama pull gemma3` - See [Ollama.com](https://ollama.com/search) for more information on the models available. ## Install @@ -20,7 +20,7 @@ pip install ollama from ollama import chat from ollama import ChatResponse -response: ChatResponse = chat(model='llama3.2', messages=[ +response: ChatResponse = chat(model='gemma3', messages=[ { 'role': 'user', 'content': 'Why is the sky blue?', @@ -41,7 +41,7 @@ Response streaming can be enabled by setting `stream=True`. from ollama import chat stream = chat( - model='llama3.2', + model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}], stream=True, ) @@ -61,7 +61,7 @@ client = Client( host='http://localhost:11434', headers={'x-some-header': 'some-value'} ) -response = client.chat(model='llama3.2', messages=[ +response = client.chat(model='gemma3', messages=[ { 'role': 'user', 'content': 'Why is the sky blue?', @@ -79,7 +79,7 @@ from ollama import AsyncClient async def chat(): message = {'role': 'user', 'content': 'Why is the sky blue?'} - response = await AsyncClient().chat(model='llama3.2', messages=[message]) + response = await AsyncClient().chat(model='gemma3', messages=[message]) asyncio.run(chat()) ``` @@ -92,7 +92,7 @@ from ollama import AsyncClient async def chat(): message = {'role': 'user', 'content': 'Why is the sky blue?'} - async for part in await AsyncClient().chat(model='llama3.2', messages=[message], stream=True): + async for part in await AsyncClient().chat(model='gemma3', messages=[message], stream=True): print(part['message']['content'], end='', flush=True) asyncio.run(chat()) @@ -105,13 +105,13 @@ The Ollama Python library's API is designed around the [Ollama REST API](https:/ ### Chat ```python -ollama.chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}]) +ollama.chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}]) ``` ### Generate ```python -ollama.generate(model='llama3.2', prompt='Why is the sky blue?') +ollama.generate(model='gemma3', prompt='Why is the sky blue?') ``` ### List @@ -123,49 +123,49 @@ ollama.list() ### Show ```python -ollama.show('llama3.2') +ollama.show('gemma3') ``` ### Create ```python -ollama.create(model='example', from_='llama3.2', system="You are Mario from Super Mario Bros.") +ollama.create(model='example', from_='gemma3', system="You are Mario from Super Mario Bros.") ``` ### Copy ```python -ollama.copy('llama3.2', 'user/llama3.2') +ollama.copy('gemma3', 'user/gemma3') ``` ### Delete ```python -ollama.delete('llama3.2') +ollama.delete('gemma3') ``` ### Pull ```python -ollama.pull('llama3.2') +ollama.pull('gemma3') ``` ### Push ```python -ollama.push('user/llama3.2') +ollama.push('user/gemma3') ``` ### Embed ```python -ollama.embed(model='llama3.2', input='The sky is blue because of rayleigh scattering') +ollama.embed(model='gemma3', input='The sky is blue because of rayleigh scattering') ``` ### Embed (batch) ```python -ollama.embed(model='llama3.2', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll']) +ollama.embed(model='gemma3', input=['The sky is blue because of rayleigh scattering', 'Grass is green because of chlorophyll']) ``` ### Ps diff --git a/examples/async-chat.py b/examples/async-chat.py index be10cfc..d312621 100644 --- a/examples/async-chat.py +++ b/examples/async-chat.py @@ -12,7 +12,7 @@ async def main(): ] client = AsyncClient() - response = await client.chat('llama3.2', messages=messages) + response = await client.chat('gemma3', messages=messages) print(response['message']['content']) diff --git a/examples/async-generate.py b/examples/async-generate.py index c3b601a..125be81 100644 --- a/examples/async-generate.py +++ b/examples/async-generate.py @@ -5,7 +5,7 @@ async def main(): client = ollama.AsyncClient() - response = await client.generate('llama3.2', 'Why is the sky blue?') + response = await client.generate('gemma3', 'Why is the sky blue?') print(response['response']) diff --git a/examples/chat-stream.py b/examples/chat-stream.py index 3aed84f..4e7625e 100644 --- a/examples/chat-stream.py +++ b/examples/chat-stream.py @@ -7,7 +7,5 @@ }, ] -for part in chat('llama3.2', messages=messages, stream=True): +for part in chat('gemma3', messages=messages, stream=True): print(part['message']['content'], end='', flush=True) - -print() diff --git a/examples/chat-with-history.py b/examples/chat-with-history.py index de9c38a..09104ae 100644 --- a/examples/chat-with-history.py +++ b/examples/chat-with-history.py @@ -22,7 +22,7 @@ while True: user_input = input('Chat with history: ') response = chat( - 'llama3.2', + 'gemma3', messages=[*messages, {'role': 'user', 'content': user_input}], ) diff --git a/examples/chat.py b/examples/chat.py index 2a30f8a..fd49843 100644 --- a/examples/chat.py +++ b/examples/chat.py @@ -7,5 +7,5 @@ }, ] -response = chat('llama3.2', messages=messages) +response = chat('gemma3', messages=messages) print(response['message']['content']) diff --git a/examples/create.py b/examples/create.py index 14967a9..4ed8376 100755 --- a/examples/create.py +++ b/examples/create.py @@ -3,7 +3,7 @@ client = Client() response = client.create( model='my-assistant', - from_='llama3.2', + from_='gemma3', system='You are mario from Super Mario Bros.', stream=False, ) diff --git a/examples/generate-stream.py b/examples/generate-stream.py index 698a961..5abc2f3 100644 --- a/examples/generate-stream.py +++ b/examples/generate-stream.py @@ -1,4 +1,4 @@ from ollama import generate -for part in generate('llama3.2', 'Why is the sky blue?', stream=True): +for part in generate('gemma3', 'Why is the sky blue?', stream=True): print(part['response'], end='', flush=True) diff --git a/examples/generate.py b/examples/generate.py index 7a94de4..69483e5 100644 --- a/examples/generate.py +++ b/examples/generate.py @@ -1,4 +1,4 @@ from ollama import generate -response = generate('llama3.2', 'Why is the sky blue?') +response = generate('gemma3', 'Why is the sky blue?') print(response['response']) diff --git a/examples/multimodal-chat.py b/examples/multimodal-chat.py index c1a1859..db9209b 100644 --- a/examples/multimodal-chat.py +++ b/examples/multimodal-chat.py @@ -11,7 +11,7 @@ # img = Path(path).read_bytes() response = chat( - model='llama3.2-vision', + model='gemma3', messages=[ { 'role': 'user', diff --git a/examples/ps.py b/examples/ps.py index f307831..0aa2cac 100644 --- a/examples/ps.py +++ b/examples/ps.py @@ -1,7 +1,7 @@ from ollama import ProcessResponse, chat, ps, pull # Ensure at least one model is loaded -response = pull('llama3.2', stream=True) +response = pull('gemma3', stream=True) progress_states = set() for progress in response: if progress.get('status') in progress_states: @@ -12,7 +12,7 @@ print('\n') print('Waiting for model to load... \n') -chat(model='llama3.2', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}]) +chat(model='gemma3', messages=[{'role': 'user', 'content': 'Why is the sky blue?'}]) response: ProcessResponse = ps() diff --git a/examples/pull.py b/examples/pull.py index bd08c54..ce3a09c 100644 --- a/examples/pull.py +++ b/examples/pull.py @@ -3,7 +3,7 @@ from ollama import pull current_digest, bars = '', {} -for progress in pull('llama3.2', stream=True): +for progress in pull('gemma3', stream=True): digest = progress.get('digest', '') if digest != current_digest and current_digest in bars: bars[current_digest].close() diff --git a/examples/structured-outputs-image.py b/examples/structured-outputs-image.py index 722a252..c72f51f 100644 --- a/examples/structured-outputs-image.py +++ b/examples/structured-outputs-image.py @@ -33,7 +33,7 @@ class ImageDescription(BaseModel): # Set up chat as usual response = chat( - model='llama3.2-vision', + model='gemma3', format=ImageDescription.model_json_schema(), # Pass in the schema for the response messages=[ {