[vllm-model error]: unable to run https://microsoft.github.io/graphrag/posts/get_started/

[riyajatar37003]

unable to run get started with vllm hoted model

[42 rows x 5 columns] 🚀 create_base_extracted_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... 🚀 create_summarized_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... ❌ create_base_entity_graph None ⠴ GraphRAG Indexer ├── Loading Input (text) - 1 files loaded (0 filtered) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 0:00:00 ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities └── create_base_entity_graph ❌ Errors occurred during the pipeline run, see logs for more details.

Steps to reproduce

i am using graphrag from source with git clone

1. python -m vllm.entrypoints.openai.api_server --model "Mixtral-8x7B-Instruct-v0.1/snapshots/5c79a376139be989ef1838f360bf4f1f256d7aec" --tensor-parallel-size 8 --dtype float16
2. mkdir -p ./ragtest/input
3. curl https://www.gutenberg.org/cache/epub/24022/pg24022.txt > ./ragtest/input/book.txt

GraphRAG Config Used

encoding_model: cl100k_base skip_workflows: [] llm: api_key: "" type: openai_chat # or azure_openai_chat model: '/Mixtral-8x7B-Instruct-v0.1/snapshots/5c79a376139be989ef1838f360bf4f1f256d7aec' model_supports_json: false # recommended if this is available for your model.

max_tokens: 4000

request_timeout: 180.0

api_base: "http://localhost:8000/v1"

api_version: 2024-02-15-preview

organization:

deployment_name:

tokens_per_minute: 150_000 # set a leaky bucket throttle

requests_per_minute: 10_000 # set a leaky bucket throttle

max_retries: 10

max_retry_wait: 10.0

sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times

concurrent_requests: 25 # the number of parallel inflight requests that may be made

temperature: 0 # temperature for sampling

top_p: 1 # top-p sampling

n: 1 # Number of completions to generate

parallelization: stagger: 0.3

num_threads: 50 # the number of threads to use for parallel processing

async_mode: threaded # or asyncio

embeddings:

parallelization: override the global parallelization settings for embeddings

async_mode: threaded # or asyncio llm: api_key: {open_ai_key} type: openai_embedding # or azure_openai_embedding model: text-embedding-3-small api_base: open_ai_url

api_version: 2024-02-15-preview

# organization: <organization_id>
# deployment_name: <azure_model_deployment_name>
# tokens_per_minute: 150_000 # set a leaky bucket throttle
# requests_per_minute: 10_000 # set a leaky bucket throttle
# max_retries: 10
# max_retry_wait: 10.0
# sleep_on_rate_limit_recommendation: true # whether to sleep when azure suggests wait-times
# concurrent_requests: 25 # the number of parallel inflight requests that may be made
# batch_size: 16 # the number of documents to send in a single request
# batch_max_tokens: 8191 # the maximum number of tokens to send in a single request
# target: required # or optional

chunks: size: 1200 overlap: 100 group_by_columns: [id] # by default, we don't allow chunks to cross documents

input: type: file # or blob file_type: text # or csv base_dir: "input" file_encoding: utf-8 file_pattern: ".*\.txt$"

cache: type: file # or blob base_dir: "cache"

connection_string:

container_name:

storage: type: file # or blob base_dir: "output/${timestamp}/artifacts"

connection_string:

container_name:

reporting: type: file # or console, blob base_dir: "output/${timestamp}/reports"

connection_string:

container_name:

entity_extraction:

llm: override the global llm settings for this task

parallelization: override the global parallelization settings for this task

async_mode: override the global async_mode settings for this task

prompt: "prompts/entity_extraction.txt" entity_types: [organization,person,geo,event] max_gleanings: 1

summarize_descriptions:

llm: override the global llm settings for this task

parallelization: override the global parallelization settings for this task

async_mode: override the global async_mode settings for this task

prompt: "prompts/summarize_descriptions.txt" max_length: 500

claim_extraction:

llm: override the global llm settings for this task

parallelization: override the global parallelization settings for this task

async_mode: override the global async_mode settings for this task

enabled: true

prompt: "prompts/claim_extraction.txt" description: "Any claims or facts that could be relevant to information discovery." max_gleanings: 1

community_reports:

llm: override the global llm settings for this task

parallelization: override the global parallelization settings for this task

async_mode: override the global async_mode settings for this task

prompt: "prompts/community_report.txt" max_length: 2000 max_input_length: 8000

cluster_graph: max_cluster_size: 10

embed_graph: enabled: false # if true, will generate node2vec embeddings for nodes

num_walks: 10

walk_length: 40

window_size: 2

iterations: 3

random_seed: 597832

umap: enabled: false # if true, will generate UMAP embeddings for nodes

snapshots: graphml: false raw_entities: false top_level_nodes: false

local_search:

text_unit_prop: 0.5

community_prop: 0.1

conversation_history_max_turns: 5

top_k_mapped_entities: 10

top_k_relationships: 10

max_tokens: 12000

global_search:

max_tokens: 12000

data_max_tokens: 12000

map_max_tokens: 1000

reduce_max_tokens: 2000

concurrency: 32

Logs and screenshots

NFO: ::1:39062 - "POST /v1/chat/completions HTTP/1.1" 400 Bad Request ERROR 07-15 11:17:42 api_server.py:247] Error in applying chat template from request: Conversation roles must alternate user/assistant/user/

[42 rows x 5 columns] 🚀 create_base_extracted_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... 🚀 create_summarized_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... ❌ create_base_entity_graph None ⠴ GraphRAG Indexer ├── Loading Input (text) - 1 files loaded (0 filtered) ━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━ 100% 0:00:00 0:00:00 ├── create_base_text_units ├── create_base_extracted_entities ├── create_summarized_entities └── create_base_entity_graph ❌ Errors occurred during the pipeline run, see logs for more details.

Error code: 404 - {'error': {'code': 'DeploymentNotFound', 'message': 'The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again.'}}\n", "source": "Error code: 404 - {'error': {'code': 'DeploymentNotFound', 'message': 'The API deployment for this resource does not exist. If you created the deployment within the last 5 minutes, please wait a moment and try again.'}}"

[ngoanpv]

pls check the vllm log to ensure you serve the model correct

[riyajatar37003]

i tested and i can make a post request to the same endpoint

[riyajatar37003]

now this is coming ERROR 07-16 12:08:18 api_server.py:247] Error in applying chat template from request: Conversation roles must alternate user/assistant/user/assistant/...

[ngoanpv]

It seems the problem with chat template of mixtral.

Create the Jinja template file as shown below, for example, named mixtral.jinja:

{%- for message in messages %}
      {%- if message['role'] == 'system' -%}
          {{- message['content'] -}}
      {%- else -%}
          {%- if message['role'] == 'user' -%}
              {{-'[INST] ' + message['content'].rstrip() + ' [/INST]'-}}
          {%- else -%}
              {{-'' + message['content'] + '</s>' -}}
          {%- endif -%}
      {%- endif -%}
  {%- endfor -%}
  {%- if add_generation_prompt -%}
      {{-''-}}
  {%- endif -%}

Add this template file when using vllm:

python -m vllm.entrypoints.openai.api_server \
  --model /ngoanpv/model/path \
  --dtype float16 \
  --api-key 'random_api_key' \
  --chat-template mixtral.jinja 

[riyajatar37003]

thanks it worked.