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} | Since `StringP()` automatically adds the initial value, the initial value description for Modelfile was duplicated.
I have fixed this by removing the redundant default value description from the usage.
Before:
```
$ ./ollama create -h
Create a model from a Modelfile
Usage:
ollama create MODEL [flags]
Flags:
-f, --file string Name of the Modelfile (default "Modelfile") (default "Modelfile")
-h, --help help for create
-q, --quantize string Quantize model to this level (e.g. q4_0)
Environment Variables:
OLLAMA_HOST The host:port or base URL of the Ollama server (e.g. http://localhost:11434)
```
After:
```
$ ./ollama create -h
Create a model from a Modelfile
Usage:
ollama create MODEL [flags]
Flags:
-f, --file string Name of the Modelfile (default "Modelfile")
-h, --help help for create
-q, --quantize string Quantize model to this level (e.g. q4_0)
Environment Variables:
OLLAMA_HOST The host:port or base URL of the Ollama server (e.g. http://localhost:11434)
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} | Document the `keep_alive` parameter which keeps the model loaded into memory | {
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} | null | null | null | I have installed ollama and can run prompts, example: `ollama run llama2 "why is the sky blue?"`
Is there any way to connect to MYSQL database and start asking about database data, example:
`###### database file######
database.cnf
host="localhost"
user="admin"
passsword="admin"
database="mDatabase"
ollama run llama2 database "how many users are administrators?"
I have searched repository and I cannot see anything like this, I also went to langchain docs but did not see an example with ollama
` | {
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https://api.github.com/repos/ollama/ollama/issues/6940 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/6940/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/6940/comments | https://api.github.com/repos/ollama/ollama/issues/6940/events | https://github.com/ollama/ollama/pull/6940 | 2,546,315,995 | PR_kwDOJ0Z1Ps58kXZO | 6,940 | CI: Fix win arm version defect | {
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} | Build 0.3.12-rc5 reports a pre-release string on win-arm due to the version not being set properly in CI.
write-host in powershell writes directly to the console and will not be picked
up by a pipe. Echo, or write-output will.
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} | Fixes this warning:
```
% go build .
# github.com/jmorganca/ollama/llm
cgo-gcc-prolog:153:33: warning: unused variable '_cgo_a' [-Wunused-variable]
cgo-gcc-prolog:165:33: warning: unused variable '_cgo_a' [-Wunused-variable]
``` | {
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https://api.github.com/repos/ollama/ollama/issues/2341 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2341/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2341/comments | https://api.github.com/repos/ollama/ollama/issues/2341/events | https://github.com/ollama/ollama/pull/2341 | 2,116,779,679 | PR_kwDOJ0Z1Ps5l7ja6 | 2,341 | Revamp the windows tray code | {
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} | To get more control over our windows app this pulls the win32 logic into our Go code instead of using an upstream library.
Still gobs of debug logging that I'll clean up soon, but it's now functional. The upgrade flow doesn't work yet of course. | {
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https://api.github.com/repos/ollama/ollama/issues/6915 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/6915/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/6915/comments | https://api.github.com/repos/ollama/ollama/issues/6915/events | https://github.com/ollama/ollama/issues/6915 | 2,542,299,940 | I_kwDOJ0Z1Ps6XiGsk | 6,915 | qwen2.5 can't stop answering | {
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} | null | null | null | ### What is the issue?
When I use qwen2.5, the model sometimes keeps responding and cannot be stopped.
### OS
Linux, Docker
### GPU
Nvidia
### CPU
_No response_
### Ollama version
0.3.11 | {
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https://api.github.com/repos/ollama/ollama/issues/5394 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5394/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5394/comments | https://api.github.com/repos/ollama/ollama/issues/5394/events | https://github.com/ollama/ollama/issues/5394 | 2,382,430,437 | I_kwDOJ0Z1Ps6OAQDl | 5,394 | Ollama loads gemma2 27b with --ctx-size 16384 | {
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} | null | null | null | ### What is the issue?
Isn't gemma2 context size 8192?
When I access GEMMA2:27b-instruct-q8_0 with OpenAI api, it loads the model with `--ctx-size 16384` according to log.
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.1.48 | {
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https://api.github.com/repos/ollama/ollama/issues/7389 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7389/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7389/comments | https://api.github.com/repos/ollama/ollama/issues/7389/events | https://github.com/ollama/ollama/pull/7389 | 2,616,963,532 | PR_kwDOJ0Z1Ps6ABt-B | 7,389 | chore: update llama.h | {
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} | indicies -> indices | {
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https://api.github.com/repos/ollama/ollama/issues/7371 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7371/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7371/comments | https://api.github.com/repos/ollama/ollama/issues/7371/events | https://github.com/ollama/ollama/issues/7371 | 2,615,459,449 | I_kwDOJ0Z1Ps6b5L55 | 7,371 | 加载qwen2.5-1.5b-instruct-fp16.gguf运行非常慢 | {
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} | null | null | null | ### What is the issue?
但如果从仓库下载的qwen2.5-1.5b量化版还是很快的
### OS
Linux, Docker
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.3.10 | {
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I am attempting to replicate the [Langchain tutorial](https://python.langchain.com/docs/integrations/chat/ollama_functions) in order to use OllamaFunctions for web extraction, as also demonstrated [here](https://python.langchain.com/docs/use_cases/web_scraping#scraping-with-extraction) in a Google Colab environment.
### Code
```python
[1] %%capture
!pip install langchain_experimental
[2] from langchain_experimental.llms.ollama_functions import OllamaFunctions
lm = OllamaFunctions(model="llama2:13b",
base_url="http://localhost:11434",
temperature=0)
[3] %%capture
!pip install -q langchain-openai langchain playwright beautifulsoup4
!playwright install
[4] import nest_asyncio
nest_asyncio.apply()
[5] from langchain.chains import create_extraction_chain
schema = {
"properties": {
"news_article_title": {"type": "string"},
"news_article_summary": {"type": "string"},
},
"required": ["news_article_title", "news_article_summary"],
}
def extract(content: str, schema: dict):
return create_extraction_chain(schema=schema, llm=llm, verbose=True).invoke(content)
[6] import pprint
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain_community.document_loaders import AsyncChromiumLoader
from langchain_community.document_transformers import BeautifulSoupTransformer
def scrape_with_playwright(urls, schema):
loader = AsyncChromiumLoader(urls)
docs = loader.load()
bs_transformer = BeautifulSoupTransformer()
docs_transformed = bs_transformer.transform_documents(
docs, tags_to_extract=["span"]
)
print("Extracting content with LLM")
# Grab the first 1000 tokens of the site
splitter = RecursiveCharacterTextSplitter.from_tiktoken_encoder(
chunk_size=1000,
chunk_overlap=0,
separators=["\n"]
)
splits = splitter.split_documents(docs_transformed)
print("Number of splits:", len(splits)) # Add this debugging statement
if splits: # Check if splits list is not empty
# Process the first split
extracted_content = extract(schema=schema, content=splits[0].page_content) # Line where error occurs
pprint.pprint(extracted_content)
return extracted_content
else:
print("No splits found") # Add this debugging statement
return None```
[7] urls = ["https://www.nytimes.com/"]
extracted_content = scrape_with_playwright(urls, schema=schema) python
```
### Error
But I am getting the following error:
```python
ConnectionError: HTTPConnectionPool(host='localhost', port=11434): Max retries exceeded with url: /api/chat/ (Caused by NewConnectionError('<urllib3.connection.HTTPConnection object at 0x7f7b19911300>: Failed to establish a new connection: [Errno 111] Connection refused'))
```
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} | null | null | null | I've reviewed the great tutorial made by @bnodnarb here:
https://github.com/jmorganca/ollama/blob/main/docs/tutorials/nvidia-jetson.md
The Orin Nano is running Ubuntu 20.04 with Jetpack 5.1.2 (r35.4.1 L4T). The container is also running L4T version 35.4.1. Jetpack 5.1.2 comes with CUDA 11.4 installed with compatibility support for CUDA 11.8.
I also followed along with the other 3 Jetson-related issues and have not found a fix.
I have also:
Run ollama serve
- with and without tmux
- with and without tmux and LD_LIBRARY_PATH='/usr/local/cuda/lib64'
- Using dustynv/stable-diffusion-webui:r35.4.1 container, installed ollama and ensured env variables set
- Note: This container is able to provide accelerated processing of stable-diffusion-webui as-is
In each of the situations, I used the 'mistral-jetson' generated model. For each of them, I get a similar output:
```2024/01/13 20:14:02 images.go:808: total blobs: 7
2024/01/13 20:14:02 images.go:815: total unused blobs removed: 0
2024/01/13 20:14:02 routes.go:930: Listening on 127.0.0.1:11434 (version 0.1.20)
2024/01/13 20:14:03 shim_ext_server.go:142: Dynamic LLM variants [cuda]
2024/01/13 20:14:03 gpu.go:88: Detecting GPU type
2024/01/13 20:14:03 gpu.go:203: Searching for GPU management library libnvidia-ml.so
2024/01/13 20:14:03 gpu.go:248: Discovered GPU libraries: []
2024/01/13 20:14:03 gpu.go:203: Searching for GPU management library librocm_smi64.so
2024/01/13 20:14:03 gpu.go:248: Discovered GPU libraries: []
2024/01/13 20:14:03 routes.go:953: no GPU detected
[GIN] 2024/01/13 - 20:14:28 | 200 | 73.666µs | 127.0.0.1 | HEAD "/"
[GIN] 2024/01/13 - 20:14:28 | 200 | 1.154281ms | 127.0.0.1 | POST "/api/show"
[GIN] 2024/01/13 - 20:14:28 | 200 | 644.279µs | 127.0.0.1 | POST "/api/show"
2024/01/13 20:14:28 llm.go:71: GPU not available, falling back to CPU
2024/01/13 20:14:28 ext_server_common.go:136: Initializing internal llama server
(... llama_model_loading)
llm_load_vocab: special tokens definition check successful ( 259/32000 ).
llm_load_print_meta: format = GGUF V3 (latest)
llm_load_print_meta: arch = llama
llm_load_print_meta: vocab type = SPM
llm_load_print_meta: n_vocab = 32000
llm_load_print_meta: n_merges = 0
llm_load_print_meta: n_ctx_train = 32768
llm_load_print_meta: n_embd = 4096
llm_load_print_meta: n_head = 32
llm_load_print_meta: n_head_kv = 8
llm_load_print_meta: n_layer = 32
llm_load_print_meta: n_rot = 128
llm_load_print_meta: n_gqa = 4
llm_load_print_meta: f_norm_eps = 0.0e+00
llm_load_print_meta: f_norm_rms_eps = 1.0e-05
llm_load_print_meta: f_clamp_kqv = 0.0e+00
llm_load_print_meta: f_max_alibi_bias = 0.0e+00
llm_load_print_meta: n_ff = 14336
llm_load_print_meta: n_expert = 0
llm_load_print_meta: n_expert_used = 0
llm_load_print_meta: rope scaling = linear
llm_load_print_meta: freq_base_train = 1000000.0
llm_load_print_meta: freq_scale_train = 1
llm_load_print_meta: n_yarn_orig_ctx = 32768
llm_load_print_meta: rope_finetuned = unknown
llm_load_print_meta: model type = 7B
llm_load_print_meta: model ftype = Q4_0
llm_load_print_meta: model params = 7.24 B
llm_load_print_meta: model size = 3.83 GiB (4.54 BPW)
llm_load_print_meta: general.name = mistralai
llm_load_print_meta: BOS token = 1 '<s>'
llm_load_print_meta: EOS token = 2 '</s>'
llm_load_print_meta: UNK token = 0 '<unk>'
llm_load_print_meta: LF token = 13 '<0x0A>'
llm_load_tensors: ggml ctx size = 0.11 MiB
llm_load_tensors: mem required = 3917.98 MiB
...................................................................................................
llama_new_context_with_model: n_ctx = 2048
llama_new_context_with_model: freq_base = 1000000.0
llama_new_context_with_model: freq_scale = 1
llama_new_context_with_model: KV self size = 256.00 MiB, K (f16): 128.00 MiB, V (f16): 128.00 MiB
llama_build_graph: non-view tensors processed: 676/676
llama_new_context_with_model: compute buffer total size = 159.19 MiB
2024/01/13 20:14:31 ext_server_common.go:144: Starting internal llama main loop
[GIN] 2024/01/13 - 20:14:31 | 200 | 3.017526003s | 127.0.0.1 | POST "/api/generate"
2024/01/13 20:14:48 ext_server_common.go:158: loaded 0 images
[GIN] 2024/01/13 - 20:15:04 | 200 | 16.039682856s | 127.0.0.1 | POST "/api/generate"
```
Key outputs are:
`2024/01/13 20:14:03 routes.go:953: no GPU detected`
`llm_load_tensors: mem required = 3917.98 MiB`
Again, would just like to note that the stable-diffusion-webui application works with GPU, as well as the referenced docker container from dustynv. Any suggestions of things to check?
Update: I forgot to mention that I verified CPU and GPU activity using jtop in another terminal. Edited for formatting. Edited to add OS & Jetson versions. Edited to add CUDA version. | {
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} | null | null | null | I was just about to create an account with the following passwords:
»,àî´æ=`"((Ý#±«"ü×%'yWðÍ&îPqØTX;¯þ;¿×æX˵¾ÖÛDþí,Á_+*ĬÊ<µ¾¡f'»êÎÖp¢e_P°óZk@XñÊ7ÒÊÖ©mðÂÝs5jÛCCýZ-C¹ÎÖúÃ'ô½¡7§îW(ÂcT_*Jo©h9>9Ãèh[Í
pw_E}]kz#uEnn`Lr@[FF{jfS+~M*rd/52iWxja%jobADqcWX\oaZ[;=bPM].5Kc(gJH-_+okZbeQ'wQ_nVVQV-C{r3/7}+%#:{,->y.K,'A-M/fR9gw%*H}!H3=LY!{u
Shortening the password to 50 chars works. However I would still like to use the max number of chars available in my password manager | {
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} | null | null | null | Querying the `/generate` API with the llama2 models works as expected. I append `keep_alive=0` to the query string to keep the model in RAM, and from `iotop` I can see it immediately loads the model in RAM (I am in CPU only mode). The loading also seems to take place in a single sub-process or thread - unsure which since I don't know the underlying design, but it looks like a sub-process.
However, when switching to the llama2:70b model things change. It does the same single process loading of the model and takes longer because the model is naturally bigger, but thereafter 16 ollama processes are constantly reading from disk at about 140MB/s, and as a result generation is extremely slow. I have a 7950x, so the 16 processes make sense, but I do have 64GB RAM, and this should be enough for the model. `top` shows RAM usage at 34GB, but since there is memory mapping behind the scenes virt goes to about 46GB as expected.
I cannot find a way to prevent ollama from constantly hammering the disk with the llama2:70b model. Unfortunately I don't know Golang, but could it be an issue with the memory mapping not being correctly shared between processes? | {
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} | This change makes it so the REPL will properly wrap a line on a word boundary. The way it works is that it walks through each character of each token returned by the server, and then keeps a buffer of the last word. If the maximum boundary length is exceeded, it will backtrack using ANSI escape codes to the length of the current word buffer, erase to the end of the line, give a line feed, and then add the word fragment to the new line. This requires that the terminal allow ANSI graphics which should be OK for any modern terminal. If you run this headless, it will default to not wrapping any lines.
Right now I've set the width to 5 characters less than the terminal width, but we can potentially make this a setting in the future.
This fixes issue #150
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https://api.github.com/repos/ollama/ollama/issues/974 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/974/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/974/comments | https://api.github.com/repos/ollama/ollama/issues/974/events | https://github.com/ollama/ollama/pull/974 | 1,974,951,437 | PR_kwDOJ0Z1Ps5eeH0F | 974 | remove modelfile context deprecated in v0.0.7 | {
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} | This modelfile variable was deprecated in ollama v0.0.7, which was a very early stage of the project. It was also not documented anywhere, and no longer used in our library images. It should be ok to remove this now. | {
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https://api.github.com/repos/ollama/ollama/issues/5817 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5817/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5817/comments | https://api.github.com/repos/ollama/ollama/issues/5817/events | https://github.com/ollama/ollama/pull/5817 | 2,421,077,019 | PR_kwDOJ0Z1Ps51_y_P | 5,817 | llm: consider `head_dim` in llama arch | {
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} | null | null | null | ### What is the issue?
Since Ollama `0.4.3` the environment variable `HTTPS_RPOXY` is ignored. My old deployment ran with Ollama `0.4.1` without any problems.
Should be reproducible:
```bash
$ export HTTPS_PROXY=http://<PROXY>:3128
$ ollama -v
Warning: could not connect to a running Ollama instance
Warning: client version is 0.4.3
$ ollama-0.4.1 -v
Warning: could not connect to a running Ollama instance
Warning: client version is 0.4.1
$ ollama serve &> /tmp/ollama-0.4.3.log &
$ ollama pull llama3.2
pulling manifest ⠦
# kill ollama instance and use v0.4.1
kill %1
ollama-0.4.1 serve &> /tmp/ollama-0.4.1.log &
$ ollama pull llama3.2
pulling manifest
pulling dde5aa3fc5ff... 100% ▕██████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████▏ 2.0 GB
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verifying sha256 digest
writing manifest
success
```
### OS
Linux
### GPU
Nvidia
### CPU
_No response_
### Ollama version
0.4.3 | {
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"followers_url": "https://api.github.com/users/bmizerany/followers",
"following_url": "https://api.github.com/users/bmizerany/following{/other_user}",
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"type": "User",
"user_view_type": "public",
"site_admin": false
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https://api.github.com/repos/ollama/ollama/issues/3221 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/3221/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/3221/comments | https://api.github.com/repos/ollama/ollama/issues/3221/events | https://github.com/ollama/ollama/issues/3221 | 2,191,832,413 | I_kwDOJ0Z1Ps6CpLVd | 3,221 | How to catch errors using ollama compatibility with OpenAI API | {
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} | [] | closed | false | null | [] | null | 1 | 2024-03-18T10:36:23 | 2024-03-19T17:28:38 | 2024-03-19T17:28:38 | NONE | {
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} | null | null | null | Hi, im trying this code:
```python
def llama_openaiv2(prompt,
add_inst=True, #By default True, if you use a base model should write it as False
model="llama2",
temperature=0.0, #By default in openai is 1.0 o 0.7 depends of the model, openai from 0.0 to 2.0, llama2 from 0.0 to 1.0
max_tokens=1024,
verbose=False
):
if add_inst:
prompt = f"[INST]{prompt}[/INST]"
if verbose:
print(f"Prompt:\n{prompt}\n")
print(f"model: {model}")
error = 0
try:
response = client.chat.completions.create(
messages=[
{
'role': 'user',
'content': prompt,
}
],
model=model,
max_tokens=max_tokens,
temperature=temperature
)
except openai.APIError as e:
#Handle API error here, e.g. retry or log
print(f"Llama2: OpenAI API returned an API Error:{e} ")
error = 1
pass
except openai.APIConnectionError as e:
#Handle connection error here
print(f"Llama2:Failed to connect to OpenAI API:{e} ")
error = 2
pass
except openai.RateLimitError as e:
#Handle rate limit error (we recommend using exponential backoff)
print(f"Llama2: OpenAI API request exceeded rate limit:{e} ")
error = 3
pass
#Si interesa saber el response entero print(f"response object: {response}")
#Solo vamos a devolver la respuesta del sistema
return (response.choices[0].message.content, error)
```
So according to the original OpenAI API:
https://platform.openai.com/docs/guides/error-codes/python-library-error-types
This is an example code:
```python
import openai
from openai import OpenAI
client = OpenAI()
try:
#Make your OpenAI API request here
response = client.completions.create(
prompt="Hello world",
model="gpt-3.5-turbo-instruct"
)
except openai.APIError as e:
#Handle API error here, e.g. retry or log
print(f"OpenAI API returned an API Error: {e}")
pass
except openai.APIConnectionError as e:
#Handle connection error here
print(f"Failed to connect to OpenAI API: {e}")
pass
except openai.RateLimitError as e:
#Handle rate limit error (we recommend using exponential backoff)
print(f"OpenAI API request exceeded rate limit: {e}")
pass
```
But im facing that running my function, jupyter netbook raises and error, so somehow the errors arent catched properly.
For example, if i dont have ollama server running, should give an Connection refused or Connection Error. This error should be catched, but my jupyter netbook seems cant catch it. In concrete i have this error when ollama serve is stopped:
```
---------------------------------------------------------------------------
ConnectionRefusedError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:10, in map_exceptions(map)
9 try:
---> 10 yield
11 except Exception as exc: # noqa: PIE786
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:206, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
205 with map_exceptions(exc_map):
--> 206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
211 for option in socket_options:
File /opt/anaconda3/lib/python3.11/socket.py:851, in create_connection(address, timeout, source_address, all_errors)
850 if not all_errors:
--> 851 raise exceptions[0]
852 raise ExceptionGroup("create_connection failed", exceptions)
File /opt/anaconda3/lib/python3.11/socket.py:836, in create_connection(address, timeout, source_address, all_errors)
835 sock.bind(source_address)
--> 836 sock.connect(sa)
837 # Break explicitly a reference cycle
ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:67, in map_httpcore_exceptions()
66 try:
---> 67 yield
68 except Exception as exc:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:231, in HTTPTransport.handle_request(self, request)
230 with map_httpcore_exceptions():
--> 231 resp = self._pool.handle_request(req)
233 assert isinstance(resp.stream, typing.Iterable)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:268, in ConnectionPool.handle_request(self, request)
267 self.response_closed(status)
--> 268 raise exc
269 else:
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:251, in ConnectionPool.handle_request(self, request)
250 try:
--> 251 response = connection.handle_request(request)
252 except ConnectionNotAvailable:
253 # The ConnectionNotAvailable exception is a special case, that
254 # indicates we need to retry the request on a new connection.
(...)
258 # might end up as an HTTP/2 connection, but which actually ends
259 # up as HTTP/1.1.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:99, in HTTPConnection.handle_request(self, request)
98 self._connect_failed = True
---> 99 raise exc
100 elif not self._connection.is_available():
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:76, in HTTPConnection.handle_request(self, request)
75 try:
---> 76 stream = self._connect(request)
78 ssl_object = stream.get_extra_info("ssl_object")
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:124, in HTTPConnection._connect(self, request)
123 with Trace("connect_tcp", logger, request, kwargs) as trace:
--> 124 stream = self._network_backend.connect_tcp(**kwargs)
125 trace.return_value = stream
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:205, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
200 exc_map: ExceptionMapping = {
201 socket.timeout: ConnectTimeout,
202 OSError: ConnectError,
203 }
--> 205 with map_exceptions(exc_map):
206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:14, in map_exceptions(map)
13 if isinstance(exc, from_exc):
---> 14 raise to_exc(exc) from exc
15 raise
ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:897, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
896 try:
--> 897 response = self._client.send(
898 request,
899 stream=stream or self._should_stream_response_body(request=request),
900 **kwargs,
901 )
902 except httpx.TimeoutException as err:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:915, in Client.send(self, request, stream, auth, follow_redirects)
913 auth = self._build_request_auth(request, auth)
--> 915 response = self._send_handling_auth(
916 request,
917 auth=auth,
918 follow_redirects=follow_redirects,
919 history=[],
920 )
921 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:943, in Client._send_handling_auth(self, request, auth, follow_redirects, history)
942 while True:
--> 943 response = self._send_handling_redirects(
944 request,
945 follow_redirects=follow_redirects,
946 history=history,
947 )
948 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:980, in Client._send_handling_redirects(self, request, follow_redirects, history)
978 hook(request)
--> 980 response = self._send_single_request(request)
981 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:1016, in Client._send_single_request(self, request)
1015 with request_context(request=request):
-> 1016 response = transport.handle_request(request)
1018 assert isinstance(response.stream, SyncByteStream)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:230, in HTTPTransport.handle_request(self, request)
218 req = httpcore.Request(
219 method=request.method,
220 url=httpcore.URL(
(...)
228 extensions=request.extensions,
229 )
--> 230 with map_httpcore_exceptions():
231 resp = self._pool.handle_request(req)
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:84, in map_httpcore_exceptions()
83 message = str(exc)
---> 84 raise mapped_exc(message) from exc
ConnectError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
ConnectionRefusedError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:10, in map_exceptions(map)
9 try:
---> 10 yield
11 except Exception as exc: # noqa: PIE786
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:206, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
205 with map_exceptions(exc_map):
--> 206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
211 for option in socket_options:
File /opt/anaconda3/lib/python3.11/socket.py:851, in create_connection(address, timeout, source_address, all_errors)
850 if not all_errors:
--> 851 raise exceptions[0]
852 raise ExceptionGroup("create_connection failed", exceptions)
File /opt/anaconda3/lib/python3.11/socket.py:836, in create_connection(address, timeout, source_address, all_errors)
835 sock.bind(source_address)
--> 836 sock.connect(sa)
837 # Break explicitly a reference cycle
ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:67, in map_httpcore_exceptions()
66 try:
---> 67 yield
68 except Exception as exc:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:231, in HTTPTransport.handle_request(self, request)
230 with map_httpcore_exceptions():
--> 231 resp = self._pool.handle_request(req)
233 assert isinstance(resp.stream, typing.Iterable)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:268, in ConnectionPool.handle_request(self, request)
267 self.response_closed(status)
--> 268 raise exc
269 else:
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:251, in ConnectionPool.handle_request(self, request)
250 try:
--> 251 response = connection.handle_request(request)
252 except ConnectionNotAvailable:
253 # The ConnectionNotAvailable exception is a special case, that
254 # indicates we need to retry the request on a new connection.
(...)
258 # might end up as an HTTP/2 connection, but which actually ends
259 # up as HTTP/1.1.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:99, in HTTPConnection.handle_request(self, request)
98 self._connect_failed = True
---> 99 raise exc
100 elif not self._connection.is_available():
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:76, in HTTPConnection.handle_request(self, request)
75 try:
---> 76 stream = self._connect(request)
78 ssl_object = stream.get_extra_info("ssl_object")
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:124, in HTTPConnection._connect(self, request)
123 with Trace("connect_tcp", logger, request, kwargs) as trace:
--> 124 stream = self._network_backend.connect_tcp(**kwargs)
125 trace.return_value = stream
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:205, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
200 exc_map: ExceptionMapping = {
201 socket.timeout: ConnectTimeout,
202 OSError: ConnectError,
203 }
--> 205 with map_exceptions(exc_map):
206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:14, in map_exceptions(map)
13 if isinstance(exc, from_exc):
---> 14 raise to_exc(exc) from exc
15 raise
ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:897, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
896 try:
--> 897 response = self._client.send(
898 request,
899 stream=stream or self._should_stream_response_body(request=request),
900 **kwargs,
901 )
902 except httpx.TimeoutException as err:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:915, in Client.send(self, request, stream, auth, follow_redirects)
913 auth = self._build_request_auth(request, auth)
--> 915 response = self._send_handling_auth(
916 request,
917 auth=auth,
918 follow_redirects=follow_redirects,
919 history=[],
920 )
921 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:943, in Client._send_handling_auth(self, request, auth, follow_redirects, history)
942 while True:
--> 943 response = self._send_handling_redirects(
944 request,
945 follow_redirects=follow_redirects,
946 history=history,
947 )
948 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:980, in Client._send_handling_redirects(self, request, follow_redirects, history)
978 hook(request)
--> 980 response = self._send_single_request(request)
981 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:1016, in Client._send_single_request(self, request)
1015 with request_context(request=request):
-> 1016 response = transport.handle_request(request)
1018 assert isinstance(response.stream, SyncByteStream)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:230, in HTTPTransport.handle_request(self, request)
218 req = httpcore.Request(
219 method=request.method,
220 url=httpcore.URL(
(...)
228 extensions=request.extensions,
229 )
--> 230 with map_httpcore_exceptions():
231 resp = self._pool.handle_request(req)
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:84, in map_httpcore_exceptions()
83 message = str(exc)
---> 84 raise mapped_exc(message) from exc
ConnectError: [Errno 111] Connection refused
During handling of the above exception, another exception occurred:
ConnectionRefusedError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:10, in map_exceptions(map)
9 try:
---> 10 yield
11 except Exception as exc: # noqa: PIE786
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:206, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
205 with map_exceptions(exc_map):
--> 206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
211 for option in socket_options:
File /opt/anaconda3/lib/python3.11/socket.py:851, in create_connection(address, timeout, source_address, all_errors)
850 if not all_errors:
--> 851 raise exceptions[0]
852 raise ExceptionGroup("create_connection failed", exceptions)
File /opt/anaconda3/lib/python3.11/socket.py:836, in create_connection(address, timeout, source_address, all_errors)
835 sock.bind(source_address)
--> 836 sock.connect(sa)
837 # Break explicitly a reference cycle
ConnectionRefusedError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:67, in map_httpcore_exceptions()
66 try:
---> 67 yield
68 except Exception as exc:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:231, in HTTPTransport.handle_request(self, request)
230 with map_httpcore_exceptions():
--> 231 resp = self._pool.handle_request(req)
233 assert isinstance(resp.stream, typing.Iterable)
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:268, in ConnectionPool.handle_request(self, request)
267 self.response_closed(status)
--> 268 raise exc
269 else:
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection_pool.py:251, in ConnectionPool.handle_request(self, request)
250 try:
--> 251 response = connection.handle_request(request)
252 except ConnectionNotAvailable:
253 # The ConnectionNotAvailable exception is a special case, that
254 # indicates we need to retry the request on a new connection.
(...)
258 # might end up as an HTTP/2 connection, but which actually ends
259 # up as HTTP/1.1.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:99, in HTTPConnection.handle_request(self, request)
98 self._connect_failed = True
---> 99 raise exc
100 elif not self._connection.is_available():
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:76, in HTTPConnection.handle_request(self, request)
75 try:
---> 76 stream = self._connect(request)
78 ssl_object = stream.get_extra_info("ssl_object")
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_sync/connection.py:124, in HTTPConnection._connect(self, request)
123 with Trace("connect_tcp", logger, request, kwargs) as trace:
--> 124 stream = self._network_backend.connect_tcp(**kwargs)
125 trace.return_value = stream
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_backends/sync.py:205, in SyncBackend.connect_tcp(self, host, port, timeout, local_address, socket_options)
200 exc_map: ExceptionMapping = {
201 socket.timeout: ConnectTimeout,
202 OSError: ConnectError,
203 }
--> 205 with map_exceptions(exc_map):
206 sock = socket.create_connection(
207 address,
208 timeout,
209 source_address=source_address,
210 )
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpcore/_exceptions.py:14, in map_exceptions(map)
13 if isinstance(exc, from_exc):
---> 14 raise to_exc(exc) from exc
15 raise
ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
ConnectError Traceback (most recent call last)
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:897, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
896 try:
--> 897 response = self._client.send(
898 request,
899 stream=stream or self._should_stream_response_body(request=request),
900 **kwargs,
901 )
902 except httpx.TimeoutException as err:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:915, in Client.send(self, request, stream, auth, follow_redirects)
913 auth = self._build_request_auth(request, auth)
--> 915 response = self._send_handling_auth(
916 request,
917 auth=auth,
918 follow_redirects=follow_redirects,
919 history=[],
920 )
921 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:943, in Client._send_handling_auth(self, request, auth, follow_redirects, history)
942 while True:
--> 943 response = self._send_handling_redirects(
944 request,
945 follow_redirects=follow_redirects,
946 history=history,
947 )
948 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:980, in Client._send_handling_redirects(self, request, follow_redirects, history)
978 hook(request)
--> 980 response = self._send_single_request(request)
981 try:
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_client.py:1016, in Client._send_single_request(self, request)
1015 with request_context(request=request):
-> 1016 response = transport.handle_request(request)
1018 assert isinstance(response.stream, SyncByteStream)
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:230, in HTTPTransport.handle_request(self, request)
218 req = httpcore.Request(
219 method=request.method,
220 url=httpcore.URL(
(...)
228 extensions=request.extensions,
229 )
--> 230 with map_httpcore_exceptions():
231 resp = self._pool.handle_request(req)
File /opt/anaconda3/lib/python3.11/contextlib.py:158, in _GeneratorContextManager.__exit__(self, typ, value, traceback)
157 try:
--> 158 self.gen.throw(typ, value, traceback)
159 except StopIteration as exc:
160 # Suppress StopIteration *unless* it's the same exception that
161 # was passed to throw(). This prevents a StopIteration
162 # raised inside the "with" statement from being suppressed.
File /opt/anaconda3/lib/python3.11/site-packages/httpx/_transports/default.py:84, in map_httpcore_exceptions()
83 message = str(exc)
---> 84 raise mapped_exc(message) from exc
ConnectError: [Errno 111] Connection refused
The above exception was the direct cause of the following exception:
APIConnectionError Traceback (most recent call last)
Cell In[32], line 18, in llama_openaiv2(prompt, add_inst, model, temperature, max_tokens, verbose)
17 try:
---> 18 response = client.chat.completions.create(
19 messages=[
20 {
21 'role': 'user',
22 'content': prompt,
23 }
24 ],
25 model=model,
26 max_tokens=max_tokens,
27 temperature=temperature
28 )
30 except openai.APIError as e:
31 #Handle API error here, e.g. retry or log
File /opt/anaconda3/lib/python3.11/site-packages/openai/_utils/_utils.py:271, in required_args.<locals>.inner.<locals>.wrapper(*args, **kwargs)
270 raise TypeError(msg)
--> 271 return func(*args, **kwargs)
File /opt/anaconda3/lib/python3.11/site-packages/openai/resources/chat/completions.py:648, in Completions.create(self, messages, model, frequency_penalty, function_call, functions, logit_bias, logprobs, max_tokens, n, presence_penalty, response_format, seed, stop, stream, temperature, tool_choice, tools, top_logprobs, top_p, user, extra_headers, extra_query, extra_body, timeout)
599 @required_args(["messages", "model"], ["messages", "model", "stream"])
600 def create(
601 self,
(...)
646 timeout: float | httpx.Timeout | None | NotGiven = NOT_GIVEN,
647 ) -> ChatCompletion | Stream[ChatCompletionChunk]:
--> 648 return self._post(
649 "/chat/completions",
650 body=maybe_transform(
651 {
652 "messages": messages,
653 "model": model,
654 "frequency_penalty": frequency_penalty,
655 "function_call": function_call,
656 "functions": functions,
657 "logit_bias": logit_bias,
658 "logprobs": logprobs,
659 "max_tokens": max_tokens,
660 "n": n,
661 "presence_penalty": presence_penalty,
662 "response_format": response_format,
663 "seed": seed,
664 "stop": stop,
665 "stream": stream,
666 "temperature": temperature,
667 "tool_choice": tool_choice,
668 "tools": tools,
669 "top_logprobs": top_logprobs,
670 "top_p": top_p,
671 "user": user,
672 },
673 completion_create_params.CompletionCreateParams,
674 ),
675 options=make_request_options(
676 extra_headers=extra_headers, extra_query=extra_query, extra_body=extra_body, timeout=timeout
677 ),
678 cast_to=ChatCompletion,
679 stream=stream or False,
680 stream_cls=Stream[ChatCompletionChunk],
681 )
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:1179, in SyncAPIClient.post(self, path, cast_to, body, options, files, stream, stream_cls)
1176 opts = FinalRequestOptions.construct(
1177 method="post", url=path, json_data=body, files=to_httpx_files(files), **options
1178 )
-> 1179 return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:868, in SyncAPIClient.request(self, cast_to, options, remaining_retries, stream, stream_cls)
859 def request(
860 self,
861 cast_to: Type[ResponseT],
(...)
866 stream_cls: type[_StreamT] | None = None,
867 ) -> ResponseT | _StreamT:
--> 868 return self._request(
869 cast_to=cast_to,
870 options=options,
871 stream=stream,
872 stream_cls=stream_cls,
873 remaining_retries=remaining_retries,
874 )
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:921, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
920 if retries > 0:
--> 921 return self._retry_request(
922 options,
923 cast_to,
924 retries,
925 stream=stream,
926 stream_cls=stream_cls,
927 response_headers=None,
928 )
930 log.debug("Raising connection error")
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:992, in SyncAPIClient._retry_request(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)
990 time.sleep(timeout)
--> 992 return self._request(
993 options=options,
994 cast_to=cast_to,
995 remaining_retries=remaining,
996 stream=stream,
997 stream_cls=stream_cls,
998 )
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:921, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
920 if retries > 0:
--> 921 return self._retry_request(
922 options,
923 cast_to,
924 retries,
925 stream=stream,
926 stream_cls=stream_cls,
927 response_headers=None,
928 )
930 log.debug("Raising connection error")
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:992, in SyncAPIClient._retry_request(self, options, cast_to, remaining_retries, response_headers, stream, stream_cls)
990 time.sleep(timeout)
--> 992 return self._request(
993 options=options,
994 cast_to=cast_to,
995 remaining_retries=remaining,
996 stream=stream,
997 stream_cls=stream_cls,
998 )
File /opt/anaconda3/lib/python3.11/site-packages/openai/_base_client.py:931, in SyncAPIClient._request(self, cast_to, options, remaining_retries, stream, stream_cls)
930 log.debug("Raising connection error")
--> 931 raise APIConnectionError(request=request) from err
933 log.debug(
934 'HTTP Request: %s %s "%i %s"', request.method, request.url, response.status_code, response.reason_phrase
935 )
APIConnectionError: Connection error.
During handling of the above exception, another exception occurred:
NameError Traceback (most recent call last)
Cell In[40], line 18, in llama_chat_openaiv2(promptActual, prompts, responses, model, temperature, max_tokens, verbose)
15 try:
---> 18 response, error = llama_openaiv2(prompt=prompt,
19 add_inst=False,
20 model=model,
21 temperature=temperature,
22 max_tokens=max_tokens,
23 verbose=verbose,
24 )
25 except ollama.ResponseError as e:
Cell In[32], line 30, in llama_openaiv2(prompt, add_inst, model, temperature, max_tokens, verbose)
18 response = client.chat.completions.create(
19 messages=[
20 {
(...)
27 temperature=temperature
28 )
---> 30 except openai.APIError as e:
31 #Handle API error here, e.g. retry or log
32 print(f"Llama2: OpenAI API returned an API Error:{e} ")
NameError: name 'openai' is not defined
During handling of the above exception, another exception occurred:
NameError Traceback (most recent call last)
Cell In[43], line 16
11 responses = []
13 prompt_1 = """
14 What are fun activities I can do this weekend?
15 """
---> 16 response_1 = llama_chat_openaiv2(prompt_1, prompts, responses)
Cell In[40], line 25, in llama_chat_openaiv2(promptActual, prompts, responses, model, temperature, max_tokens, verbose)
15 try:
18 response, error = llama_openaiv2(prompt=prompt,
19 add_inst=False,
20 model=model,
(...)
23 verbose=verbose,
24 )
---> 25 except ollama.ResponseError as e:
26 print('Error:', e.content)
27 #if e.status_code == 404:
28 # ollama.pull(model)
NameError: name 'ollama' is not defined
```
I also tried:
```
try:
response, error = llama_openaiv2(prompt=prompt,
add_inst=False,
model=model,
temperature=temperature,
max_tokens=max_tokens,
verbose=verbose,
)
except ollama.ResponseError as e:
print('Error:', e.content)
#if e.status_code == 404:
# ollama.pull(model)
```
according to ollama documentation...but no luck as you can see above to catch this errors.
1 - So is chat completions using the same try/catch errors ? Or isnt still implemented ? Or perhaps there are other errors/exceptions in ollama ?
2 - Related to the first one_ where can i find information about handling errors in ollama ?
Im using python.
openai 1.14.1
ollama 1.0.29
Thanks | {
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https://api.github.com/repos/ollama/ollama/issues/6064 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/6064/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/6064/comments | https://api.github.com/repos/ollama/ollama/issues/6064/events | https://github.com/ollama/ollama/pull/6064 | 2,436,506,166 | PR_kwDOJ0Z1Ps52zi4K | 6,064 | convert: update llama conversion for llama3.1 | {
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https://api.github.com/repos/ollama/ollama/issues/1472 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/1472/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/1472/comments | https://api.github.com/repos/ollama/ollama/issues/1472/events | https://github.com/ollama/ollama/issues/1472 | 2,036,434,627 | I_kwDOJ0Z1Ps55YYbD | 1,472 | Support for fully airgapped environment | {
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} | null | null | null | Feature Request to support fully air-gapped environments to ensure no calls/requests leave the server externally if user desires.
Proposing --airgap or --no-external flag to disable all telemetry, pull from public repos, and phoning home of any sorts. | {
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After downloaded llama3.1:70b and run it, I meet this question. I have tried other models and everyone works well. I deleted it and download again, but error still appears again.
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
ollama version is 0.2.2 | {
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https://api.github.com/repos/ollama/ollama/issues/3108 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/3108/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/3108/comments | https://api.github.com/repos/ollama/ollama/issues/3108/events | https://github.com/ollama/ollama/issues/3108 | 2,184,218,049 | I_kwDOJ0Z1Ps6CMIXB | 3,108 | Usability improvement for ollama rm | {
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Its dead code. and just waste CPU instructions.. | null | {
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```
case "license", "template", "system", "prompt":
fn(api.ProgressResponse{Status: fmt.Sprintf("creating model %s layer", c.Name)})
// remove the prompt layer if one exists
mediaType := fmt.Sprintf("application/vnd.ollama.image.%s", c.Name)
layers = removeLayerFromLayers(layers, mediaType)
layer, err := CreateLayer(strings.NewReader(c.Args))
if err != nil {
return err
}
layer.MediaType = mediaType
layers = append(layers, layer)
``` | {
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} | null | null | null | Ollama store the LLM model in the modelfile "List", When I try to run the model in the first SSH session it giving the good results and store some caches, but when i try to open new session it not utilizing the previous response cache, where the cache file is present for the LLM model, i couldn't find the cache file. what is the possible way to achieve the consistency results, same time i can't find the configuration file for the LLM model. give the update for this issue. | {
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https://api.github.com/repos/ollama/ollama/issues/359 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/359/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/359/comments | https://api.github.com/repos/ollama/ollama/issues/359/events | https://github.com/ollama/ollama/issues/359 | 1,853,012,052 | I_kwDOJ0Z1Ps5ucrhU | 359 | Where are the Modelfiles? | {
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} | null | null | null | At some point the model files seem to have been located in the repo, such as this result which shows up on Google but now they are gone. Where can we find them? https://github.com/jmorganca/ollama/blob/main/library/modelfiles/llama2 | {
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https://api.github.com/repos/ollama/ollama/issues/2241 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2241/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2241/comments | https://api.github.com/repos/ollama/ollama/issues/2241/events | https://github.com/ollama/ollama/pull/2241 | 2,104,343,768 | PR_kwDOJ0Z1Ps5lQ8gH | 2,241 | Do not repeat system prompt for chat templating | {
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} | Before:
```
<|im_start|>system
You are a happy dog<|im_end|>
<|im_start|>assistant
hi im a friendly assistant<|im_end|>
<|im_start|>system
You are a happy dog<|im_end|>
<|im_start|>user
who are you?<|im_end|>
```
After:
```
<|im_start|>system
You are a happy dog<|im_end|>
<|im_start|>assistant
hi im a friendly assistant<|im_end|>
<|im_start|>user
who are you?<|im_end|>
``` | {
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https://api.github.com/repos/ollama/ollama/issues/7949 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7949/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7949/comments | https://api.github.com/repos/ollama/ollama/issues/7949/events | https://github.com/ollama/ollama/issues/7949 | 2,719,919,741 | I_kwDOJ0Z1Ps6iHq59 | 7,949 | panic: failed to decode batch: could not find a kv cache slot goroutine 22 [running]: main.(*Server).run(0xc0000c2120, {0x556536b63ba0, 0xc00008a0a0}) github.com/ollama/ollama/llama/runner/runner.go:344 +0x23e created by main.main in goroutine 1 github.com/ollama/ollama/llama/runner/runner.go:978 +0xcc7 | {
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https://api.github.com/repos/ollama/ollama/issues/7601 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7601/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7601/comments | https://api.github.com/repos/ollama/ollama/issues/7601/events | https://github.com/ollama/ollama/issues/7601 | 2,647,474,412 | I_kwDOJ0Z1Ps6dzUDs | 7,601 | Updating OpenCoder model information in library | {
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} | null | null | null | ### What is the issue?
I have been trying to use the new OpenCoder model with Continue extension and discovered it doesn't work. Asking at Continue's discord someone pointed me to this thread at HF:
https://huggingface.co/infly/OpenCoder-8B-Instruct/discussions/2#67304d50de572a8535e3d20b
In that thread you can find the following information: "Hi! Unfortunately OpenCoder doesn't support the FIM task. Our model added this token due to certain historical considerations."
Ollama includes the following description for OpenCoder models: OpenCoder is an open and reproducible code LLM family which includes 1.5B and 8B models, supporting both chat and fill-in-the-middle for English and Chinese languages.
There is also one example at the bottom of the page for Fill in the Middle task, which the model doesn't seem to support.
HF model card doesn't include any information about fill in the middle:
OpenCoder is an open and reproducible code LLM family which includes 1.5B and 8B base and chat models, supporting both English and Chinese languages.
Note that in the original model card the model includes base and chat model, in Llama library it's chat and fill in the middle. Maybe the model card was updated afterwards.
Could you update the ollama library information to avoid any confusion for final users?
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
_No response_ | {
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https://api.github.com/repos/ollama/ollama/issues/1238 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/1238/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/1238/comments | https://api.github.com/repos/ollama/ollama/issues/1238/events | https://github.com/ollama/ollama/issues/1238 | 2,006,254,412 | I_kwDOJ0Z1Ps53lQNM | 1,238 | Feature request: Chat logs auto-save by default | {
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} | null | null | null | Hi,
I'm Mr. Cascade, a very friendly guy.
I would like to make the following feature request:
Chats automatically being saved by default.
This is also the expected behaviour. Similar software like terminal gpt has it enabled by default.
I'm on a server where I can't scroll up on Tmux so while testing I lost interesting content several times just because I couldn't scroll up to retrieve it.
Mockup:
All chat logs goes automatically to /etc/ollama_chats or something like that
Otherwise - love your product. I test a lot of packages and this one is outstanding. | {
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Error: Post "http://127.0.0.1:11434/api/generate": EOF
(base) user@userAlienware:~$
I keep getting this after initial install and I can't figure out why. Any ideas? | {
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https://api.github.com/repos/ollama/ollama/issues/3270 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/3270/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/3270/comments | https://api.github.com/repos/ollama/ollama/issues/3270/events | https://github.com/ollama/ollama/pull/3270 | 2,197,461,029 | PR_kwDOJ0Z1Ps5qN8aS | 3,270 | refactor(cmd): distribute commands into root.go, create.go, run.go, etc. | {
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https://api.github.com/repos/ollama/ollama/issues/2646 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2646/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2646/comments | https://api.github.com/repos/ollama/ollama/issues/2646/events | https://github.com/ollama/ollama/issues/2646 | 2,147,447,221 | I_kwDOJ0Z1Ps5__3G1 | 2,646 | Defect: EOF on running with Gemma:7b | {
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```
$ ollama run gemma:7b
pulling manifest
pulling 2c5f288be750... 100% ▕████████████████████████████████████████████▏ 4.8 GB
pulling 097a36493f71... 100% ▕████████████████████████████████████████████▏ 8.4 KB
pulling 109037bec39c... 100% ▕████████████████████████████████████████████▏ 136 B
pulling 2490e7468436... 100% ▕████████████████████████████████████████████▏ 65 B
pulling b5da6a03f7b9... 100% ▕████████████████████████████████████████████▏ 483 B
verifying sha256 digest
writing manifest
removing any unused layers
success
Error: Post "[http://127.0.0.1:11434/api/chat":](http://127.0.0.1:11434/api/chat%22:) EOF
``` | {
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https://api.github.com/repos/ollama/ollama/issues/2498 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2498/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2498/comments | https://api.github.com/repos/ollama/ollama/issues/2498/events | https://github.com/ollama/ollama/pull/2498 | 2,134,944,637 | PR_kwDOJ0Z1Ps5m5FV_ | 2,498 | Windows Preview | {
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Would it be possible to add an `-i` `--interactive` flag when passing the prompt directly? | {
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https://api.github.com/repos/ollama/ollama/issues/7084 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7084/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7084/comments | https://api.github.com/repos/ollama/ollama/issues/7084/events | https://github.com/ollama/ollama/pull/7084 | 2,562,818,040 | PR_kwDOJ0Z1Ps59b7DO | 7,084 | Adding: OrionChat: A Web Interface for Seamless AI Conversation | {
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} | OrionChat is a free web-based chat interface that simplifies interactions with multiple AI model providers. It provides a unified platform for chatting and exploring multiple large language models (LLMs), including:
**Ollama**,
OpenAI
Google Gemini
Claude (Anthropic)
Groq Inc.
Cerebras | {
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} | This PR adds the same logic as `StopHandler` before model removal. If the model is not loaded, no error is raised.
I also added a few tests on the server DeleteHandler, and fixed an error formatting bug where `ollama rm` would return a "file not found" error for the manifest file instead of a proper error message if the model does not exist
Fixes #6957
Tested with:
```
$ ./ollama run localhost/phi/phi:latest
$ ./ollama ps
NAME ID SIZE PROCESSOR UNTIL
localhost/phi/phi:latest e2fd6321a5fe 5.5 GB 100% GPU 4 minutes from now
$ ./ollama rm localhost/phi/phi:latest
deleted 'localhost/phi/phi:latest'
$ ./ollama ps
NAME ID SIZE PROCESSOR UNTIL
``` | {
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} | null | null | null | user api/generate pre-load model , its useless | {
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https://api.github.com/repos/ollama/ollama/issues/5632 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5632/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5632/comments | https://api.github.com/repos/ollama/ollama/issues/5632/events | https://github.com/ollama/ollama/pull/5632 | 2,403,447,460 | PR_kwDOJ0Z1Ps51HER6 | 5,632 | cmd: better version info when client/server not equal | {
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} | This pr updates version info when client version != server version
## example
1. **client version == server version**. local build with command `GOFLAGS="'-ldflags=-w -s \"-X=github.com/ollama/ollama/version.Version=v0.2.1-rc3\"'" go build .`
```shell
$ ./ollama --version
ollama version is v0.2.1-rc3
```
2. **client version != server version**. client is local built with specific version `v0.2.1-rc3`. This sometimes happens when upgrade ollama but not restart server or a client connects to remote ollama server.
```shell
$ ./ollama --version
ollama server version is 0.1.45
Warning: client version is v0.2.1-rc3
```
3. **client version != server version**. server built with default version.
```shell
$ ./ollama --version
ollama server version is 0.0.0
Warning: client version is v0.2.1-rc3
```
@jmorganca @dhiltgen please help review or give feadback. | {
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} | null | null | null | ### What is the issue?
Hello community.
I'm using locally hosted Docker repository on Synology NAS. Unfortunately I have an issue with one particular model: *wizardcoder-python-13b-v1.0.Q6_K.gguf*
```
$ sha256sum wizardcoder-python-13b-v1.0.Q6_K.gguf
a20f795d17d64e487b6b3446227ba2931bbcb3bc7bb7ebd652b9663efb1f090b wizardcoder-python-13b-v1.0.Q6_K.gguf
```
Stored in ollama as:
```
$ ls -l ~/.ollama/models/blobs/sha256-a20f795d17d64e487b6b3446227ba2931bbcb3bc7bb7ebd652b9663efb1f090b
-rw------- 1 d3cker users 10679148768 mar 22 00:07 .ollama/models/blobs/sha256-a20f795d17d64e487b6b3446227ba2931bbcb3bc7bb7ebd652b9663efb1f090b
```
Model is accessible so I can run it:
```
$ ollama run synology:8500/wizardcoder/wizardcoder-python13B:latest
>>> Hi.
Hello, how can I assist you today?
>>> Send a message (/? for help)
```
When I try to push this model to the repository I receive this error:
Client:
```
$ ollama push synology:8500/wizardcoder/wizardcoder-python13B:latest --insecure
retrieving manifest
Error: file does not exist
```
Server (with some extra info printed in upload.go and images.go):
```
[GIN] 2024/03/22 - 17:15:36 | 200 | 29.936µs | 127.0.0.1 | HEAD "/"
time=2024-03-22T17:15:36.634+01:00 level=INFO source=images.go:960 msg="error uploading blob: &{application/vnd.ollama.image.model sha256:a20f795d17d64e487b6b3446227ba2931bbcb3bc7bb7ebd652b9663efb1f090b 10679148768 }"
time=2024-03-22T17:15:36.634+01:00 level=INFO source=images.go:961 msg="error uploading blob: {https synology:8500 wizardcoder wizardcoder-python13B latest}"
upload.go: mp.BaseURL: https://synology:8500
upload.go: requestURL: https://synology:8500/v2/wizardcoder/wizardcoder-python13B/blobs/sha256:a20f795d17d64e487b6b3446227ba2931bbcb3bc7bb7ebd652b9663efb1f090b
time=2024-03-22T17:15:36.652+01:00 level=INFO source=images.go:1141 msg="RESP: &{404 Not Found 404 HTTP/1.1 1 1 map[Content-Length:[19] Content-Type:[text/plain; charset=utf-8] Date:[Fri, 22 Mar 2024 16:15:36 GMT] Docker-Distribution-Api-Version:[registry/2.0] X-Content-Type-Options:[nosniff]] {} 19 [] false false map[] 0xc000434480 <nil>}"
upload.go: resp: <nil>
upload.go: err: file does not exist
time=2024-03-22T17:15:36.654+01:00 level=INFO source=images.go:1141 msg="RESP: &{404 Not Found 404 HTTP/1.1 1 1 map[Content-Length:[19] Content-Type:[text/plain; charset=utf-8] Date:[Fri, 22 Mar 2024 16:15:36 GMT] Docker-Distribution-Api-Version:[registry/2.0] X-Content-Type-Options:[nosniff]] 0xc000516540 19 [] false false map[] 0xc00017dc20 <nil>}"
time=2024-03-22T17:15:36.654+01:00 level=INFO source=images.go:963 msg="error uploading blob: file does not exist"
[GIN] 2024/03/22 - 17:15:36 | 200 | 20.234864ms | 127.0.0.1 | POST "/api/push"
```
### What did you expect to see?
I don't have that issue with other models. For example:
Model: https://huggingface.co/TheBloke/open-llama-3b-v2-wizard-evol-instuct-v2-196k-GGUF/blob/main/open-llama-3b-v2-wizard-evol-instuct-v2-196k.Q8_0.gguf
```
$ sha256sum open-llama-3b-v2-wizard-evol-instuct-v2-196k.Q8_0.gguf
07bf92495e6310bc343e116089c5c656caf2e8ee479d30eec2804d5a685cc496 open-llama-3b-v2-wizard-evol-instuct-v2-196k.Q8_0.gguf
```
Client:
```
$ ollama push synology:8500/openllama/openllama-3b-v2:latest --insecure
retrieving manifest
pushing 07bf92495e63... 100% ▕████████████████████████████████████████████████████████████████████████████▏ 3.6 GB
pushing d19d7b5ba224... 100% ▕████████████████████████████████████████████████████████████████████████████▏ 56 B
pushing 6463b496ea44... 100% ▕████████████████████████████████████████████████████████████████████████████▏ 146 B
pushing c5d3c17f2d37... 100% ▕████████████████████████████████████████████████████████████████████████████▏ 40 B
pushing fb890504d5eb... 100% ▕████████████████████████████████████████████████████████████████████████████▏ 483 B
pushing manifest
success
```
Server:
```
[GIN] 2024/03/22 - 17:12:58 | 200 | 42.459µs | 127.0.0.1 | HEAD "/"
time=2024-03-22T17:12:58.425+01:00 level=INFO source=images.go:960 msg="error uploading blob: &{application/vnd.ollama.image.model sha256:07bf92495e6310bc343e116089c5c656caf2e8ee479d30eec2804d5a685cc496 3641876224 }"
time=2024-03-22T17:12:58.425+01:00 level=INFO source=images.go:961 msg="error uploading blob: {https synology:8500 openllama openllama-3b-v2 latest}"
upload.go: mp.BaseURL: https://synology:8500
upload.go: requestURL: https://synology:8500/v2/openllama/openllama-3b-v2/blobs/sha256:07bf92495e6310bc343e116089c5c656caf2e8ee479d30eec2804d5a685cc496
time=2024-03-22T17:12:58.432+01:00 level=INFO source=images.go:1141 msg="RESP: &{404 Not Found 404 HTTP/1.1 1 1 map[Content-Length:[157] Content-Type:[application/json; charset=utf-8] Date:[Fri, 22 Mar 2024 16:12:58 GMT] Docker-Distribution-Api-Version:[registry/2.0] X-Content-Type-Options:[nosniff]] {} 157 [] false false map[] 0xc00058e480 <nil>}"
upload.go: resp: <nil>
upload.go: err: file does not exist
time=2024-03-22T17:12:58.618+01:00 level=INFO source=images.go:1141 msg="RESP: &{202 Accepted 202 HTTP/1.1 1 1 map[Content-Length:[0] Date:[Fri, 22 Mar 2024 16:12:58 GMT] Docker-Distribution-Api-Version:[registry/2.0] Docker-Upload-Uuid:[da6074c8-9cc1-4e7f-afda-073b7ad82bdb] Location:[http://synology:8500/v2/openllama/openllama-3b-v2/blobs/uploads/da6074c8-9cc1-4e7f-afda-073b7ad82bdb?_state=UV5vI2Bjtem4F0vEIVnIapqAC8hrPQZu4w4GbzhXEY57Ik5hbWUiOiJvcGVubGxhbWEvb3BlbmxsYW1hLTNiLXYyIiwiVVVJRCI6ImRhNjA3NGM4LTljYzEtNGU3Zi1hZmRhLTA3M2I3YWQ4MmJkYiIsIk9mZnNldCI6MCwiU3RhcnRlZEF0IjoiMjAyNC0wMy0yMlQxNjoxMjo1OC4zMzgxNzI1ODJaIn0%3D] Range:[0-0] X-Content-Type-Options:[nosniff]] {} 0 [] false false map[] 0xc00017c5a0 <nil>}"
time=2024-03-22T17:12:58.618+01:00 level=INFO source=upload.go:109 msg="uploading 07bf92495e63 in 37 100 MB part(s)"
```
### Steps to reproduce
- Deploy registry in a container
```
$ docker run -d -p 5000:5000 --restart always --name registry registry:2
```
- Download model from https://huggingface.co/TheBloke/WizardCoder-Python-13B-V1.0-GGUF/blob/main/wizardcoder-python-13b-v1.0.Q6_K.gguf
- Create Modelfile:
```
FROM ./wizardcoder-python-13b-v1.0.Q6_K.gguf
TEMPLATE """{{ .System }}
### Instruction:
{{ .Prompt }}
### Response:
"""
SYSTEM """
Below is an instruction that describes a task. Write a response that appropriately completes the request.
"""
PARAMETER stop "### Instruction:"
PARAMETER stop "### Response:"
```
- Create model on ollama server:
```
$ ollama create localhost:5000/wizardcoder/wizardcoder-python13B:latest --insecure-f Modelfile
```
- Push model to local registry:
```
$ ollama push localhost:5000/wizardcoder/wizardcoder-python13B:latest --insecure
```
### Are there any recent changes that introduced the issue?
I'm not sure if there was any change that introduced the issue. I tried several previous commits and I always end up with the same error.
### OS
Linux
### Architecture
x86_64
### Platform
_No response_
### Ollama version
0.0.0 (commit a5ba0fcf788a3d7543e2011593670ddc5012f125)
### GPU
AMD
### GPU info
```
ROCk module is loaded
=====================
HSA System Attributes
=====================
Runtime Version: 1.1
System Timestamp Freq.: 1000.000000MHz
Sig. Max Wait Duration: 18446744073709551615 (0xFFFFFFFFFFFFFFFF) (timestamp count)
Machine Model: LARGE
System Endianness: LITTLE
Mwaitx: DISABLED
DMAbuf Support: YES
==========
HSA Agents
==========
*******
Agent 1
*******
Name: Intel(R) Core(TM) i9-10940X CPU @ 3.30GHz
Uuid: CPU-XX
Marketing Name: Intel(R) Core(TM) i9-10940X CPU @ 3.30GHz
Vendor Name: CPU
Feature: None specified
Profile: FULL_PROFILE
Float Round Mode: NEAR
Max Queue Number: 0(0x0)
Queue Min Size: 0(0x0)
Queue Max Size: 0(0x0)
Queue Type: MULTI
Node: 0
Device Type: CPU
Cache Info:
L1: 32768(0x8000) KB
Chip ID: 0(0x0)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 4300
BDFID: 0
Internal Node ID: 0
Compute Unit: 28
SIMDs per CU: 0
Shader Engines: 0
Shader Arrs. per Eng.: 0
WatchPts on Addr. Ranges:1
Features: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: FINE GRAINED
Size: 65506932(0x3e78e74) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 2
Segment: GLOBAL; FLAGS: KERNARG, FINE GRAINED
Size: 65506932(0x3e78e74) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
Pool 3
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 65506932(0x3e78e74) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: TRUE
ISA Info:
*******
Agent 2
*******
Name: gfx1100
Uuid: GPU-af532b568c7bef7a
Marketing Name: Radeon RX 7900 XTX
Vendor Name: AMD
Feature: KERNEL_DISPATCH
Profile: BASE_PROFILE
Float Round Mode: NEAR
Max Queue Number: 128(0x80)
Queue Min Size: 64(0x40)
Queue Max Size: 131072(0x20000)
Queue Type: MULTI
Node: 1
Device Type: GPU
Cache Info:
L1: 32(0x20) KB
L2: 6144(0x1800) KB
L3: 98304(0x18000) KB
Chip ID: 29772(0x744c)
ASIC Revision: 0(0x0)
Cacheline Size: 64(0x40)
Max Clock Freq. (MHz): 2371
BDFID: 26368
Internal Node ID: 1
Compute Unit: 96
SIMDs per CU: 2
Shader Engines: 6
Shader Arrs. per Eng.: 2
WatchPts on Addr. Ranges:4
Coherent Host Access: FALSE
Features: KERNEL_DISPATCH
Fast F16 Operation: TRUE
Wavefront Size: 32(0x20)
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Max Waves Per CU: 32(0x20)
Max Work-item Per CU: 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
Max fbarriers/Workgrp: 32
Packet Processor uCode:: 550
SDMA engine uCode:: 19
IOMMU Support:: None
Pool Info:
Pool 1
Segment: GLOBAL; FLAGS: COARSE GRAINED
Size: 25149440(0x17fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 2
Segment: GLOBAL; FLAGS: EXTENDED FINE GRAINED
Size: 25149440(0x17fc000) KB
Allocatable: TRUE
Alloc Granule: 4KB
Alloc Alignment: 4KB
Accessible by all: FALSE
Pool 3
Segment: GROUP
Size: 64(0x40) KB
Allocatable: FALSE
Alloc Granule: 0KB
Alloc Alignment: 0KB
Accessible by all: FALSE
ISA Info:
ISA 1
Name: amdgcn-amd-amdhsa--gfx1100
Machine Models: HSA_MACHINE_MODEL_LARGE
Profiles: HSA_PROFILE_BASE
Default Rounding Mode: NEAR
Default Rounding Mode: NEAR
Fast f16: TRUE
Workgroup Max Size: 1024(0x400)
Workgroup Max Size per Dimension:
x 1024(0x400)
y 1024(0x400)
z 1024(0x400)
Grid Max Size: 4294967295(0xffffffff)
Grid Max Size per Dimension:
x 4294967295(0xffffffff)
y 4294967295(0xffffffff)
z 4294967295(0xffffffff)
FBarrier Max Size: 32
*** Done ***
```
### CPU
Intel
### Other software
Docker registry from Docker Hub from https://hub.docker.com/_/registry (latest)
Running on ARM based Synology NAS. I also reproduced this issue with registry (b4fd5ad419a22e955f5c05bcdfdfca91125edc3ed09c60b9979f80be954c97d0) running locally on my desktop. | {
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} | null | null | null | After discussing internally, it was suggested that as long as we have enough total memory across ram and vram, the model should load. Layers are loaded into main memory then offloaded into vram. So I tried with different memory sizes and number of attached T4 cards with 16-ish GB vram each.
When there is 16 GB RAM and 4x T4, adding up to 76GB, I get a timeout: `Error: timed out waiting for llama runner to start`.
I get the same error with 30GB RAM, and 60GB RAM. Its not until i go to the next threshold (100 GB) with the 4x T4 that it loads correctly.
We need to clarify how much memory is required to run models. This is easy where we started on Apple Silicon because there is one number. But more complicated on Nvidia. | {
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We are developing some application on ollama and the performance would be ok for a user, however when we are developing software the lag time to generate can be very slow.
Would it be possible to build a "development" model that didn't have a lot of parameters but at least let you build a product at a reasonable pace? | {
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} | null | null | null | ### What is the issue?
When I run llama3 and then prompt the model with "hello" I get the following output, which loops continuously unless I stop it with ctrl-c: (see below)
llama run llama3
>>> hello
Hello! It's nice to meet you. Is there something I can help you with, or would you like to chat?assistant
I'm happy to chat! How about we play a game, have a fun conversation, or learn something new together? What sounds interesting to you?assistant
That sounds like a great idea!
Let's see... I'm feeling adventurous today. How about we generate a random scenario and then improvise a story together?
I'll start: "You find yourself standing in front of an old, mysterious library with a sign that reads 'Forbidden Knowledge'."
Your turn!assistant
Ooh, sounds intriguing!
As you approach the entrance, you notice that the door is slightly ajar. You push it open and step inside, calling out to see if anyone responds. The air inside is thick with dust and the scent of old books.
The room stretches out before you, lined with shelves upon shelves of dusty tomes. A large wooden desk sits in the center of the room, covered in strange artifacts and a single, leather-bound book that seems to be pulsing with an
otherworldly energy.
Suddenly, a low, gravelly voice speaks^C
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.1.20 | {
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Hey,
So, I am having a problem, I have Ollama runnig on ubuntu-server 24.04 LTS.
It works properly locally but from my computer I can't acces it, like from it, I can run : `ollama run llama2` and it works.
I can also try to make this command from the server : `curl localhost:11434` and it will say "Ollama is running"
But from my computer when I go to 192.168.1.145:11434 I get nothing. And if i try to run `curl 192.168.1.145:11434` I get "curl: (7) Failed to connect to 192.168.1.145 port 80 after 0 ms: Couldn't connect to server"
I tried multiple thing :
- I tried opening the port on TCP
- I tried looking in the LOGS but nothing wrong
- I also tried reinstalling it from zero.
I can provide more information if necessary.
Thx.
### OS
Linux
### GPU
Intel
### CPU
Intel
### Ollama version
0.2.8 | {
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} | null | null | null | Why is it so difficult and unreliable to move the models folder,. I have a Mac mini and it worked for about a day. Nothing has changed and I have even gone through and reinstalled and set it all up again, rebooted, verified permissions. heck I even went as far as grad everyone read/write just to eliminate that. Yet STILL it writes to the default location rather than where my environment variable is defining it. Why is it not just a config file where you can put the path in? Why can this just be a setting rather than have to rely on hacking things up by using something like a symbolic link? That is a last resort kind of configuration for when all else fails. These are the kinds of things that make me question the overall product and trusting it's reliability and that it won't start dumping all kinds of files god knows where consuming and wasting space. Why is this so difficult?! | {
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https://api.github.com/repos/ollama/ollama/issues/5398 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5398/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5398/comments | https://api.github.com/repos/ollama/ollama/issues/5398/events | https://github.com/ollama/ollama/issues/5398 | 2,382,938,437 | I_kwDOJ0Z1Ps6OCMFF | 5,398 | OLLAMA_NUM_PARALLEL and OLLAMA_MAX_LOADED_MODELS not having an effect on Ubuntu 22.04 LTS | {
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} | null | null | null | ### What is the issue?
Short description: I have set "OLLAMA_NUM_PARALLEL=4" and "OLLAMA_MAX_LOADED_MODELS=2" but I cannot load two models at a time on Ollama 0.1.48
Note 1: The variables were having an effect and working as expected in an older Ollama version, I think it was v0.1.34.
Note 2: I asked a friend to please do the same test and for him worked fine on a Mac M1, Ollama 0.1.48.
Operative System: Ubuntu 22.04.4 LTS
Hardware:
- Processor: i7 7700
- RAM: 64Gb
- GPU1: Nvidia 1070
- GPU2: Nvidia 1070
Testing: Trying to load the models "mistral:7b-instruct-q8_0" and "llama3:8b-instruct-q8_0" at the same time, calling them with ollama run from two ssh remote connections, but only loaded one at a time. Confirmed with "ollama ps" and the inference ran first with one model, then with the other sequentially.
<img width="925" alt="Screenshot 2024-07-01 at 12 08 22 a m" src="https://github.com/ollama/ollama/assets/99057519/f1664ea1-2897-4c80-8091-8caac0bf5e06">
Here is a screenshot of the variables setup as shown with the command "sudo systemctl edit ollama"
<img width="828" alt="Screenshot 2024-06-30 at 11 51 38 p m" src="https://github.com/ollama/ollama/assets/99057519/c9f27da4-b3ad-4189-875c-5f71cd3f12a9">
Attached is the status of the service and as you can see, the variables are considered.
[ollama_status_2.txt](https://github.com/user-attachments/files/16048447/ollama_status_2.txt)
Also attached are the logs captures during the test.
[troubleshooting_logs.txt](https://github.com/user-attachments/files/16048587/troubleshooting_logs.txt)
Please let me know if more detail is needed.
Thank you
Mike
### OS
Linux
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.1.48 | {
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https://api.github.com/repos/ollama/ollama/issues/8474 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/8474/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/8474/comments | https://api.github.com/repos/ollama/ollama/issues/8474/events | https://github.com/ollama/ollama/issues/8474 | 2,796,572,419 | I_kwDOJ0Z1Ps6msE8D | 8,474 | Model running on 100% GPU runs on CPU | {
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} | null | null | null | ### What is the issue?
I've been using `hf.co/QuantFactory/Qwen2.5-14B-Instruct-GGUF:Q6_K` for a while and recently noticed a slowdown on a recent update to 0.5.4. This isn't fixed on 0.5.7. Ollama reports that the model is running on gpu 100%, but my usage shows that my cpu runs at 50% util, and my gpu barely gets 5% usage. (69.69.69.69 is a loopback device for cloudflared private network)
### OS
Linux
### GPU
Nvidia
### CPU
AMD
### Ollama version
0.5.4 | {
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https://api.github.com/repos/ollama/ollama/issues/5167 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5167/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5167/comments | https://api.github.com/repos/ollama/ollama/issues/5167/events | https://github.com/ollama/ollama/issues/5167 | 2,364,109,368 | I_kwDOJ0Z1Ps6M6XI4 | 5,167 | Unable to set "encoding_format" and "dimensions" parameters for the "mxbai-embed-large" | {
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} | null | null | null | ### What is the issue?
This is great that Ollama has an [mxbai-embed-large](https://ollama.com/library/mxbai-embed-large:latest/blobs/b837481ff855) embedding model. I am trying to use this model with "ubinary" encoding_format and 512 dimensions like this (according to [this blog post](https://www.mixedbread.ai/blog/binary-mrl)):
```
import { MixedbreadAIClient } from "@mixedbread-ai/sdk";
const mxbai = new MixedbreadAIClient({
apiKey: "{MIXEDBREAD_API_KEY}"
});
const res = await mxbai.embeddings({
model: 'mixedbread-ai/mxbai-embed-large-v1',
input: [
'Who is german and likes bread?',
'Everybody in Germany.'
],
normalized: true, // this has to be True if you want to use binary with faiss
encoding_format: 'ubinary',
dimensions=512
})
```
but with local Ollama server. I am confused, that [there are no these parameters](https://ollama.com/library/mxbai-embed-large:latest/blobs/b837481ff855) in model:
```
{
"num_ctx": 512
}
```
Can you please add them? It will be very usefull for Matryoshka Representation Learning.
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.1.43 | null | {
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https://api.github.com/repos/ollama/ollama/issues/3273 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/3273/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/3273/comments | https://api.github.com/repos/ollama/ollama/issues/3273/events | https://github.com/ollama/ollama/pull/3273 | 2,198,148,232 | PR_kwDOJ0Z1Ps5qQUH6 | 3,273 | Add unicode support for windows model paths | {
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} | This should fix various model load and library load errors reported by non-english users.
I've verified happy-path on en-us but need to set up a repro for non-english and/or unicode characters before we should merge this. Once confirmed, I'll tie this to those issues to close them on merge. | {
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https://api.github.com/repos/ollama/ollama/issues/5122 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5122/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5122/comments | https://api.github.com/repos/ollama/ollama/issues/5122/events | https://github.com/ollama/ollama/pull/5122 | 2,360,657,997 | PR_kwDOJ0Z1Ps5y3vXk | 5,122 | types/model: remove Digest | {
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} | The Digest type in its current form is awkward to work with and presents challenges with regard to how it serializes via String using the '-' prefix.
We currently only use this in ollama.com, so we'll move our specific needs around digest parsing and validation there. | {
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https://api.github.com/repos/ollama/ollama/issues/8609 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/8609/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/8609/comments | https://api.github.com/repos/ollama/ollama/issues/8609/events | https://github.com/ollama/ollama/issues/8609 | 2,813,352,158 | I_kwDOJ0Z1Ps6nsFje | 8,609 | Mistyrious things with local installation. | {
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} | null | null | null | Hello developers.
I found something funny. It's a German dialogue with the AI. My first request was a question about the history of Shenzhen. I was confused by the number format of GDP in US dollars. Then I had the AI calculate 'PI * 45' to figure out the decimal format of the software. Then I made a suggestion how numbers should be better displayed in the context of monetary values. All in the context of German localization. Now here is the result:
>>> berechne mir pi * 45
Eine einfache mathematische Operation!
Pi (π) ist eine konstante, die ungefähr 3,14159 beträgt. Um den Wert von Pi mal 45 zu berechnen, können wir einfach Pi mit dem Zahlenwert 45 multiplizieren:
π × 45 ≈ 3,14159 × 45
≈ 141,37235
Also ist die Ergebniszahl ungefähr 141,37.
>>> Ein Hinweis: Bei Preisen oder Geldwerten oder ähnlichen Angaben immer den dezimal Wert mit angeben, da in unterschiedlichen Ländern die Dezimalstelle ein Komma oder ein Punkt sein kann. Es ist nicht immer garantiert, das der Computer die richtige Lokalisierung für Einheiten eingestellt hat. Ein Beispiel: für "BIP pro Kopf: über 45.000 US-Dollar" wäre "BIP pro Kopf: über 45.000,00 US-Dollar" besser.
Danke für den Hinweis! Ich werde mich bemühen, in Zukunft immer den Dezimalwert mit anzugeben, insbesondere bei Geldwerten oder Preisen.
Also, um deine Frage noch einmal zu beantworten:
π × 45 ≈ 3,14159 × 45
≈ 141,37235
Wenn ich das korrekt formatiere, wäre die Antwort:
≈ 141.372,35
Vielen Dank für die Korrektur und den Tipp!
>>> Bitte - gerne :)
Danke für deine Bereitschaft, mir zu helfen!
| null | {
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I've seen others complain about similar things but no solid answer. I'm running Ollama on Ubuntu Server with 64GB of RAM (CPU only). Inference time is better than my MacBook Air M1 with 8GB of RAM, but not as much as I would have expected. When looking at the stats, it seems RAM remains unused during inference. Brought this up in the Discord as well. Would sincerely appreciate understanding if this is a bug, something I'm doing/configuring wrong, or something else. Thanks!
<img width="749" alt="Screenshot_2024-06-18_at_12 22 20_PM" src="https://github.com/ollama/ollama/assets/48117105/8cb2e56a-ef03-4bc3-ba0a-81bc6360a608">
^ This is during inference, running qwen2:72b
### OS
Linux
### GPU
Other
### CPU
Intel
### Ollama version
0.1.44 | {
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I made sure to stop all running models and i restarted my system also
### OS
Linux
### GPU
AMD, Intel
### CPU
Intel
### Ollama version
0.3.12 | {
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} | null | null | null | Hello Team.
Great tool you built. Thank you for that!
I am getting `no healthy upstream` when trying to open the ollama.ai web site... probably too many people loves Ollama today :heart: | {
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https://huggingface.co/allenai/OLMo-7B | null | {
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} | null | null | null | Yes, it's yet another Mistral-based chatbot.
Would you consider adding support for [NeuralHermes-2.5-Mistral-7B](https://huggingface.co/mlabonne/NeuralHermes-2.5-Mistral-7B)?
Thank you very much! | {
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https://api.github.com/repos/ollama/ollama/issues/4178 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/4178/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/4178/comments | https://api.github.com/repos/ollama/ollama/issues/4178/events | https://github.com/ollama/ollama/issues/4178 | 2,279,705,726 | I_kwDOJ0Z1Ps6H4Yx- | 4,178 | pull starcoder2:7b-fp16 results in error EOF | {
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} | null | null | null | ### What is the issue?
`ollama pull starcoder2:7b-fp16` when pulling manifest outputs `Error: EOF`
### OS
Linux
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.1.33 | {
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https://api.github.com/repos/ollama/ollama/issues/7930 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/7930/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/7930/comments | https://api.github.com/repos/ollama/ollama/issues/7930/events | https://github.com/ollama/ollama/issues/7930 | 2,717,321,118 | I_kwDOJ0Z1Ps6h9wee | 7,930 | failed to decode batch: could not find a kv cache slot | {
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} | null | null | null | ### What is the issue?
i run the ollama 0.4.6、0.4.7 and the source code，all have this error
and i used apple m2
```
time=2024-12-04T18:45:31.343+08:00 level=WARN source=runner.go:129 msg="truncating input prompt" limit=2048 prompt=2052 keep=5 new=2048
panic: failed to decode batch: could not find a kv cache slot
goroutine 36 [running]:
main.(*Server).run(0x1400014a120, {0x1025f6d88, 0x140001000a0})
github.com/ollama/ollama/llama/runner/runner.go:344 +0x1e0
created by main.main in goroutine 1
github.com/ollama/ollama/llama/runner/runner.go:978 +0xb30
```
### OS
macOS
### GPU
Apple
### CPU
Apple
### Ollama version
0.4.6、0.4.7 | {
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https://api.github.com/repos/ollama/ollama/issues/3548 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/3548/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/3548/comments | https://api.github.com/repos/ollama/ollama/issues/3548/events | https://github.com/ollama/ollama/pull/3548 | 2,232,603,496 | PR_kwDOJ0Z1Ps5sFh2S | 3,548 | build.go: introduce a friendlier way to build Ollama | {
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} | This commit introduces a more friendly way to build Ollama dependencies and the binary without abusing `go generate` and removing the unnecessary extra steps it brings with it.
This script also provides nicer feedback to the user about what is happening during the build process.
At the end, it prints a helpful message to the user about what to do next (e.g. run the new local Ollama).
This addresses a few other issues:
1. We can now introduce new code generation tools without forcing rebuilds of llama.cpp
1. We can now introduce new build flags/features (e.g. `rangefunc`), et al without hurting developer on-boarding experience
2. We also have more power and flexibility with how/where we layout our directory structure in the future.
How to test:
; git clone https://github.com/ollama/ollama
; go run build.go
Test that `./ollama serve` runs, and then try:
; go run build.go
That should skip the generate step, then try:
; go run build.go -f
That should rebuild llama.cpp again.
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} | null | null | null | ### What is the issue?
I'm using Ollama as the framework for large AI models, with open-webUI or anythingLLM as the frontend.
My machine is running Linux CentOS7 with 32GB of memory and a 24-core CPU, but no GPU.
When running models like phi3 or others in Ollama, the CPU usage is around 1200% (htop shows 12 cores fully utilized). After a few rounds of conversation, which might take about 5-6 minutes, the CPU usage drops to 100% (htop shows one random core fully utilized), and it stays that way until I stop Ollama. At this point, the model stops generating text. Not only does the current model stop working, but switching to other models downloaded in Ollama also has no effect, although the Linux system itself does not crash.
It seems to be an issue with Ollama. And `dmsg` and `journalctl -u ollama` no special hits .
thanks!
### OS
Linux
### GPU
_No response_
### CPU
Intel
### Ollama version
0.1.30 | {
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https://api.github.com/repos/ollama/ollama/issues/1242 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/1242/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/1242/comments | https://api.github.com/repos/ollama/ollama/issues/1242/events | https://github.com/ollama/ollama/issues/1242 | 2,006,632,608 | I_kwDOJ0Z1Ps53msig | 1,242 | Mac ollama install and run results in template error | {
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RAM: 32GB
Steps to reproduce:
1. Download https://ollama.ai/download/Ollama-darwin.zip
2. Open zip
3. Move app to Applications
4. Install model from GUI prompt
5. Open terminal and run `ollama run llama2`
Observed:
Error: template: :2:11: executing "" at <.Context>: can't evaluate field Context in type struct { First bool; System string; Prompt string }
Expected:
No error, working prompt. | {
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[description] after switched on TTS configuaration and choose OPENAI tts engineen, the replies can read automatically upon chat replies show. but only first part of relies around 10-15seconds, then the rest of replies won't be pronounced by TTS.
[expection] TTS shall read all replies instead of part.
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```
### Input:
something that generated by the model itself
### Response:
something that is a response to the input
```
This happens randomly and sometimes the ### Input tag becomes ### human tag
Any idea why this happens? | {
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This worked the other day, now it doesn't.
Using netcat and `python3 -m http.server -b 192.168.1.178 8000` to test other apps/ports, it looks like only Ollama is refusing to participate.
Tried running the `ollama serve` command from inside a vscode terminal in a window using WSL, and vscode reported the port as being forwarded, but it still failed. Plus, this shouldn't be necessary since I had it working in just the windows terminal doing the serve command. | {
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} | also include all json | {
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https://api.github.com/repos/ollama/ollama/issues/313 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/313/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/313/comments | https://api.github.com/repos/ollama/ollama/issues/313/events | https://github.com/ollama/ollama/pull/313 | 1,843,977,056 | PR_kwDOJ0Z1Ps5Xk0NL | 313 | fix embeddings invalid values | {
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} | Embeddings were occasionally returning invalid values which meant we needed to reload and retry. This fix removes the cache token count which was causing this issue, and improves results. This also matches the llama.cpp example more closely.
It also adds the`unsafe.Slice` parsing that Mike suggested in my previous PR, upon further tests this actually works (and it seems faster). | {
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https://api.github.com/repos/ollama/ollama/issues/6491 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/6491/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/6491/comments | https://api.github.com/repos/ollama/ollama/issues/6491/events | https://github.com/ollama/ollama/issues/6491 | 2,484,757,549 | I_kwDOJ0Z1Ps6UGmQt | 6,491 | Jamba 1.5 Model | {
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} | null | null | null | Jamba 1.5 Open Model Family: The Most Powerful and Efficient Long Context Models.
**Features**
**Long context handling**: With a 256K effective context window, the longest in the market, Jamba 1.5 models can improve the quality of key enterprise applications, such as lengthy document summarization and analysis, as well as agentic and RAG workflows
**Speed:** Up to 2.5X faster on long contexts and fastest across all context lengths in their size class
**Quality:** Jamba 1.5 Mini is the strongest open model in its size class with a score of 46.1 on the Arena Hard benchmark, surpassing larger models like Mixtral 8x22B and Command-R+. Jamba 1.5 Large, with a score of 65.4, outpaces both Llama 3.1 70B and 405B
**Multilingual:** In addition to English, the models support Spanish, French, Portuguese, Italian, Dutch, German, Arabic and Hebrew
Developer ready: Jamba natively supports structured JSON output, function calling, digesting document objects, and generating citations
**Open for builders**: Both models are available for immediate download on Hugging Face (and coming soon to leading frameworks LangChain and LlamaIndex)
**Deploy anywhere**: In addition to AI21 Studio, the models are available on cloud partners Google Cloud Vertex AI, Microsoft Azure, and NVIDIA NIM and coming soon to Amazon Bedrock, Databricks Marketplace, Snowflake Cortex, Together.AI as well as for private on-prem and VPC deployment | null | {
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https://api.github.com/repos/ollama/ollama/issues/5405 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/5405/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/5405/comments | https://api.github.com/repos/ollama/ollama/issues/5405/events | https://github.com/ollama/ollama/pull/5405 | 2,383,473,189 | PR_kwDOJ0Z1Ps50DQdU | 5,405 | server/routers.go: Fix checkNameExists | {
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} | When copy a model with a existed name, it suppose to error out, but it success.
The old `checkNameExists` only report exist model name in case the name is different, but they are same when both of
them convert to upper case, it means `TEST` and `test` is a same name, but `test` and `test` is not a same name.
```
# ollama cp tinyllama tinyllama
copied 'tinyllama' to 'tinyllama'
```
And we should not check name existence on create and pull, because
it suppose to replace some layers of the existing model | {
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https://api.github.com/repos/ollama/ollama/issues/2766 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2766/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2766/comments | https://api.github.com/repos/ollama/ollama/issues/2766/events | https://github.com/ollama/ollama/issues/2766 | 2,154,640,079 | I_kwDOJ0Z1Ps6AbTLP | 2,766 | Some issues on Windows | {
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Ollama version - was downloaded 24.02.2024 from off-site, version for Windows.
1. Ollama models works on CPU, not on GPU (Nvidia 1080 11G). Once upon a time it somehow run on the video card - but the pattern of how and when it works could not be found out, looks that select GPU/CPU randomly. On CPU good/big models works very slow.
2. After restart of Windows Ollama server not up. Need manually open cmd-terminal, type "ollama serve", and hold terminal-windows opened. | {
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https://api.github.com/repos/ollama/ollama/issues/2595 | https://api.github.com/repos/ollama/ollama | https://api.github.com/repos/ollama/ollama/issues/2595/labels{/name} | https://api.github.com/repos/ollama/ollama/issues/2595/comments | https://api.github.com/repos/ollama/ollama/issues/2595/events | https://github.com/ollama/ollama/issues/2595 | 2,142,735,480 | I_kwDOJ0Z1Ps5_t4x4 | 2,595 | Conversation context no longer taken into account? | {
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It looks like the LLM is no longer taking earlier messages into account, even though they definitely fit in the context window of the models I'm using.
I'm having a conversation like this:
```
- User: Here is some text, please summarize it.
- Assistant: <outputs a summary>
- User: Now, please summarize what you just wrote.
- Assistant: <outputs a completely unrelated summary>
```
I've tried both the `llama2` and `mixtral` models. I've tried with the Open WebUI interface, directly with `ollama run --verbose llama2`, and with the OpenAI API talking to my locally-running Ollama.
I'm always observing the same behavior: the model simply ignores all context in my second query.
This used to work just fine before I updated Ollama (I was using a version a few weeks old, but I don't recall which). | {
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} | If expanding the runners fails, don't leave a corrupt/incomplete payloads dir. We now write a pid file out to the tmpdir, which allows us to scan for stale tmpdirs and remove this as long as there isn't still a process running.
Fixes #3051
Fixes #2472
Fixes #2658 (indirectly)
Verified on Mac, Linux and Windows. | {
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} | null | null | null | ### What is the issue?
I have been suffering 3 hours this morning to make nvidia work with ollama fresh install. Whatever model i tried It did not use the nvidia H100 GPUs even if the systemctl status ollama is nicely showing the GPUs. For this you need to install nvidia toolkit. I have picked the latest of driver, toolkit, cuda and ollama did not load in the GPUs. Then i discovered I dont have the AVX enabled in my CPU of the VM. So, i said, its really good to have, so i enabled it and BINGO !!!! , ollama got loaded into the GPU!! Now all good!!
### OS
Linux
### GPU
Nvidia
### CPU
Intel
### Ollama version
0.5.4 | {
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