flowertreeML
commented
3 months ago same issue
Closed YP-Yang closed 3 months ago
flowertreeML
commented
3 months ago same issue
BrennonTWilliams
commented
3 months ago I am having this problem too
sdjd93dj
commented
3 months ago Same issue
superposition
commented
3 months ago Same
menghongtao
commented
3 months ago I think the error occurs when LLM results is not json format in the map seach step. You can change another model or use a really simple test text file, and test agin.
Grant512
commented
3 months ago I have a same issue. when i trace LLM log, the system prompt is not affect. i dont know why
liyoung1992
commented
3 months ago same issue
natoverse
commented
3 months ago Consolidating alternate model issues here: #657
yurochang
commented
3 months ago Same question, and it seems did not solved in other issues.
Consolidating alternate model issues here: #657
awaescher
commented
3 months ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File: /graphrag/query/structured_search/global_search/search.py, method: _map_response_single_batch
#search_messages = [
# {"role": "system", "content": search_prompt},
# {"role": "user", "content": query},
#]
search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
peixikk
commented
3 months ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File:
/graphrag/query/structured_search/global_search/search.py, method:_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
thank you!
sam234990
commented
3 months ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File:
/graphrag/query/structured_search/global_search/search.py, method:_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
Thank you, this really works for me.
awaescher
commented
2 months ago I can't believe this is true, I mean wtf?!
Mila-1001
commented
2 months ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File:
/graphrag/query/structured_search/global_search/search.py, method:_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
Wow!!! thank youοΌ
MisterAndry
commented
2 months ago Is there any way to fix this without changing the graphrag source code? Maybe it is possible to change the behavior of Ollama model with modelfile? Or some other way? I'm asking because I can't change the source code after deploying my application.
Hannover1992
commented
2 months ago Same Issue
settings encoding_model: cl100k_base skip_workflows: [] llm: api_key: ${GRAPHRAG_API_KEY} type: openai_chat # or azure_openai_chat model: llama3.1
max_tokens: 2000
api_base: http://127.0.0.1:11434/v1
max_retries: 1
concurrent_requests: 1 # the number of parallel inflight requests that may be made
parallelization: stagger: 0.3
async_mode: threaded # or asyncio
embeddings:
async_mode: threaded # or asyncio llm: api_key: ${GRAPHRAG_API_KEY} type: openai_embedding # or azure_openai_embedding model: bge-large:latest api_base: http://127.0.0.1:11434/v1
treeaaa
commented
2 months ago ε樣ηει‘
ε°ζ΄ζ°οΌζηΌηΎζη樑εηΈ½ζ―θΏει樣ηη‘ζηΎ©θ¨ζ―οΌ
python -m graphrag.query --root ./myfolder --method global "δΈ»θ¦δΈ»ι‘ζ―δ»ιΊΌ" "δΈ»θ¦δΈ»ι‘ζ―'δΈ»θ¦δΈ»ι‘ζ―δ»ιΊΌ'"
ζηΌηΎζηζ¬ε° Ollama ε―¦δΎ (0.3.0) δΌΌδΉεΏ½η₯δΊη³»η΅±ζη€ΊοΌζιιζεε°ε ©εζη€ΊζΌζ₯ε¨δΈθ΅·δ½Ώε Άε·₯δ½οΌ
ζδ»ΆοΌ
/graphrag/query/structured_search/global_search/search.pyοΌζΉζ³οΌ_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
thanks so much. you ara a hero.
this also sccuess slove the problem -> https://github.com/ollama/ollama/issues/6176#issuecomment-2287204224
zhang-jingzhe
commented
1 month ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File:
/graphrag/query/structured_search/global_search/search.py, method:_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
It works for me, thanks a lot!
worstkid92
commented
1 month ago Same issue
Small update: I found out that my model always returned nosense like this:
python -m graphrag.query --root ./myfolder --method global "What are the main topics" "The main topic is 'What are the main topics'"
I found out that my local Ollama instance (0.3.0) seemed to ignore the system prompt and I got it working by manually stitching together the two prompts into one:
File:
/graphrag/query/structured_search/global_search/search.py, method:_map_response_single_batch#search_messages = [ # {"role": "system", "content": search_prompt}, # {"role": "user", "content": query}, #] search_messages = [ {"role": "user", "content": search_prompt + "\n\n### USER QUESTION ### \n\n" + query} ]
Wow! Thank you !
Coder-Dilip
commented
7 hours ago Guys try this:
Make new Folder.
Inside that folder make ragtest folder.
Then use command graphrag init --root ./ragtest to initialize the workspace.
Inside that ./ragtest folder, copy your previous output folder you got from running all the workflows successfully.
now ask question to graph again. Surprisingly it works for me.
Describe the issue
I use local LLM to run graphrag and completed all workflows successfully, but graphrag failed to answer any question given the provided data
I found there's an error like below, don't know if it is the cause RuntimeError: Failed to generate valid JSON output 00:33:57,636 graphrag.index.reporting.file_workflow_callbacks INFO Community Report Extraction Error details=None 00:33:57,636 graphrag.index.verbs.graph.report.strategies.graph_intelligence.run_graph_intelligence WARNING No report found for community: 0
my local LLM is llama3 in ollama and nomic-embed-text-v1.5.Q5_K_M.gguf in LM-studio
the input file book.txt is just the same as in the GraphRAG Get Started doc: curl https://www.gutenberg.org/cache/epub/24022/pg24022.txt > ./ragtest/input/book.txt
Steps to reproduce
No response
GraphRAG Config Used
this is my .env file GRAPHRAG_API_KEY=ollama
this is my setting.yaml file
Logs and screenshots
this is the terminal output (GraphRAG) D:\AI\RAG\GraphRAG>python -m graphrag.index --root . π Reading settings from settings.yaml D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(*args, **kwds) π create_base_text_units id ... n_tokens 0 680dd6d2a970a49082fa4f34bf63a34e ... 300 1 95f1f8f5bdbf0bee3a2c6f2f4a4907f6 ... 300 2 3a450ed2b7fb1e5fce66f92698c13824 ... 300 3 95b143eba145d91eacae7be3e4ebaf0c ... 300 4 c390f1b92e2888f78b58f6af5b12afa0 ... 300 .. ... ... ... 226 972bb34ddd371530f06d006480526d3e ... 300 227 2f918cd94d1825eb5cbdc2a9d3ce094e ... 300 228 eec5fc1a2be814473698e220b303dc1b ... 300 229 535f6bed392a62760401b1d4f2aa5e2f ... 300 230 9e59af410db84b25757e3bf90e036f39 ... 155
[231 rows x 5 columns] π create_base_extracted_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... π create_summarized_entities entity_graph 0 <graphml xmlns="http://graphml.graphdrawing.or... π create_base_entity_graph level clustered_graph 0 0 <graphml xmlns="http://graphml.graphdrawing.or... 1 1 <graphml xmlns="http://graphml.graphdrawing.or... 2 2 <graphml xmlns="http://graphml.graphdrawing.or... 3 3 <graphml xmlns="http://graphml.graphdrawing.or... D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(*args, *kwds) D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(args, **kwds) π create_final_entities id ... description_embedding 0 b45241d70f0e43fca764df95b2b81f77 ... [-0.048254746943712234, 0.044550925493240356, ... 1 4119fd06010c494caa07f439b333f4c5 ... [0.002416445640847087, 0.08019110560417175, -0... 2 d3835bf3dda84ead99deadbeac5d0d7d ... [-0.0010763887548819184, 0.04444070905447006, ... 3 077d2820ae1845bcbb1803379a3d1eae ... [-0.02357032336294651, 0.03006734512746334, -0... 4 3671ea0dd4e84c1a9b02c5ab2c8f4bac ... [0.02192544937133789, 0.009480239823460579, -0... .. ... ... ... 179 7ffa3a064bce468082739c5a164df5a3 ... [-0.0039461092092096806, 0.07387872040271759, ... 180 ce36d1d637cf4a4e93f5e37ffbc6bd76 ... [0.019510895013809204, 0.07107631862163544, -0... 181 eeb9c02c0efa4131b9e95d33c31019fc ... [-0.030116630718111992, 0.12038293480873108, -... 182 7b2472c5dd9949c58828413387b94659 ... [-0.018994171172380447, 0.06742893904447556, -... 183 bdddcb17ba6c408599dd395ce64f960a ... [-0.03383741155266762, 0.06317673623561859, -0...
[369 rows x 8 columns] D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(*args, **kwds) D:\anaconda3\envs\GraphRAG\Lib\site-packages\datashaper\engine\verbs\convert.py:72: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_datetime without passing
errorsand catch exceptions explicitly instead datetime_column = pd.to_datetime(column, errors="ignore") D:\anaconda3\envs\GraphRAG\Lib\site-packages\datashaper\engine\verbs\convert.py:72: UserWarning: Could not infer format, so each element will be parsed individually, falling back todateutil. To ensure parsing is consistent and as-expected, please specify a format. datetime_column = pd.to_datetime(column, errors="ignore") π create_final_nodes level title type ... top_level_node_id x y 0 0 "CHARLES DICKENS" "PERSON" ... b45241d70f0e43fca764df95b2b81f77 0 0 1 0 "ARTHUR RACKHAM" "PERSON" ... 4119fd06010c494caa07f439b333f4c5 0 0 2 0 "JANET BLENKINSHIP" "PERSON" ... d3835bf3dda84ead99deadbeac5d0d7d 0 0 3 0 "J. B. LIPPINCOTT COMPANY" "ORGANIZATION" ... 077d2820ae1845bcbb1803379a3d1eae 0 0 4 0 "SUZANNE SHELL" ... 3671ea0dd4e84c1a9b02c5ab2c8f4bac 0 0 ... ... ... ... ... ... .. .. 1471 3 "PROJECT GUTENBERG'S CONCEPT" ... 7ffa3a064bce468082739c5a164df5a3 0 0 1472 3 "MICHAEL HART" "PERSON" ... ce36d1d637cf4a4e93f5e37ffbc6bd76 0 0 1473 3 "PG SEARCH FACILITY" "EVENT" ... eeb9c02c0efa4131b9e95d33c31019fc 0 0 1474 3 "WWW.GUTENBERG.ORG" ... 7b2472c5dd9949c58828413387b94659 0 0 1475 3 "EMAIL NEWSLETTER" "EVENT" ... bdddcb17ba6c408599dd395ce64f960a 0 0[1476 rows x 14 columns] D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(*args, *kwds) D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(args, **kwds) π create_final_communities id ... text_unit_ids 0 2 ... [0546d296a4d3bb0486bd0c94c01dc9be,0d6bc6e701a0... 1 3 ... [13f70e4c705fb134466c125b05af3440,3a450ed2b7fb... 2 15 ... [2a1f194b20e1c3a19176deba9b13b65c,3789fbe1d06a... 3 0 ... [0e13fd0aca5720eb614104772f20077b,0eb69b9f79f6... 4 7 ... [02182df5c36e5e2f734fc8706162fc69,4033108a1f27... 5 4 ... [95b143eba145d91eacae7be3e4ebaf0c,c390f1b92e28... 6 8 ... [0bc408d042e6d08bf8c345bff1b25fe8,4df2a9b3b21d... 7 17 ... [a2ff22727e335a64c636fa57134bb2f4,c057b2b3188a... 8 14 ... [282f8e11aee6349166c4f948df48e16e, 1a8c077ae18... 9 13 ... [28d4847787f924c12e78665c4dae6428,a31b7f9a68e9... 10 16 ... [0fd302f483e5cbe68789a30ac366e604,2f92cbc7a359... 11 11 ... [4865f50de7547514f317fcfee5bc6e55] 12 18 ... [3dc28534d84425a9cdd91f68958255a7,6a13906fb4f9... 13 9 ... [206aad72da92cb4fcb0c5ba8818e7d5f,92ff0f51be82... 14 10 ... [320c285a98f252d567b2005902763e5c, 320c285a98f... 15 6 ... [1236f696b79265de838991eb0f3d341a, 1236f696b79... 16 1 ... [0bc408d042e6d08bf8c345bff1b25fe8,20d307388baf... 17 5 ... [5d2b320242efa6c0a00d078906384495,736ac01b79d0... 18 12 ... [ebaa02f7e877ff91c3acfad450b7e1d1, 1c4390f57a2... 19 26 ... [0546d296a4d3bb0486bd0c94c01dc9be,0d6bc6e701a0... 20 34 ... [13f70e4c705fb134466c125b05af3440,3a450ed2b7fb... 21 21 ... [0e13fd0aca5720eb614104772f20077b,0eb69b9f79f6... 22 39 ... [02182df5c36e5e2f734fc8706162fc69,4033108a1f27... 23 35 ... [59505f0ab347d856c834be817ede9e63,7b678bbc20b8... 24 31 ... [155aebf0490ccb996a86bb7f6d4cc2e2,2545ffae9f16... 25 29 ... [6997e1ff5fabcfa641c9a291850a1981,85d62478a6d1... 26 40 ... [4df2a9b3b21d15ed7b34eb5970611c19, 0368649fcb6... 27 23 ... [1d57ed63a57765dc6072e2524e0f8c2b,282f8e11aee6... 28 19 ... [2818d4194a37f4573f7a83b49cd59b21,d222d20d61ef... 29 20 ... [15f8920aa56b63eafb97b2f8873782c8,1dcbc2287618... 30 22 ... [15f8920aa56b63eafb97b2f8873782c8,1c4390f57a2a... 31 24 ... [359b2df5aa75c64840a175a5c9e7e37c,3f910c43801e... 32 27 ... [12c823fe2af9519eb1c85b2659a3a87e,155aebf0490c... 33 30 ... [6997e1ff5fabcfa641c9a291850a1981,85d62478a6d1... 34 32 ... [155aebf0490ccb996a86bb7f6d4cc2e2,3dc650065076... 35 28 ... [5788cf5f0b27187d91fb0056f7d800fa,d95d1ec14f9c... 36 25 ... [5788cf5f0b27187d91fb0056f7d800fa,7ed8b64d3fcf... 37 37 ... 38 36 ... [13f70e4c705fb134466c125b05af3440,59505f0ab347... 39 33 ... [2f7a9e610f25e033dc2a4917e5f57870] 40 38 ... [0b41f41ca4493f16999f35a6d6a531c7, 0b41f41ca44... 41 43 ... [0546d296a4d3bb0486bd0c94c01dc9be,0d6bc6e701a0... 42 42 ... [0e13fd0aca5720eb614104772f20077b,0eb69b9f79f6... 43 44 ... [1d5a3ea2bdc7eb02878c9733fae3924b,23f97a28c076... 44 41 ... [e13bd32de400dd73792d45f5d18b72ea,fd56f460d645... 45 45 ... [0e13fd0aca5720eb614104772f20077b,0eb69b9f79f6... 46 46 ... [21e1f454a64f4522c8629742edb7ced6,22d74ccd8712...
[47 rows x 6 columns] π join_text_units_to_entity_ids text_unit_ids ... id 0 680dd6d2a970a49082fa4f34bf63a34e ... 680dd6d2a970a49082fa4f34bf63a34e 1 95f1f8f5bdbf0bee3a2c6f2f4a4907f6 ... 95f1f8f5bdbf0bee3a2c6f2f4a4907f6 2 0546d296a4d3bb0486bd0c94c01dc9be ... 0546d296a4d3bb0486bd0c94c01dc9be 3 0d6bc6e701a0025632e41dc3387c641d ... 0d6bc6e701a0025632e41dc3387c641d 4 13f70e4c705fb134466c125b05af3440 ... 13f70e4c705fb134466c125b05af3440 .. ... ... ... 223 b3c35247f91923027d9bd7d476467f4f ... b3c35247f91923027d9bd7d476467f4f 224 e8cf7d2eec5c3bcbeefc60d9f15941ed ... e8cf7d2eec5c3bcbeefc60d9f15941ed 225 eec5fc1a2be814473698e220b303dc1b ... eec5fc1a2be814473698e220b303dc1b 226 f96b5ddf7fae853edbc4d916f66c623f ... f96b5ddf7fae853edbc4d916f66c623f 227 958e8453c6299cf980b3e6f962240699 ... 958e8453c6299cf980b3e6f962240699
[228 rows x 3 columns] D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(*args, *kwds) D:\anaconda3\envs\GraphRAG\Lib\site-packages\numpy\core\fromnumeric.py:59: FutureWarning: 'DataFrame.swapaxes' is deprecated and will be removed in a future version. Please use 'DataFrame.transpose' instead. return bound(args, **kwds) D:\anaconda3\envs\GraphRAG\Lib\site-packages\datashaper\engine\verbs\convert.py:65: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_numeric without passing
errorsand catch exceptions explicitly instead column_numeric = cast(pd.Series, pd.to_numeric(column, errors="ignore")) π create_final_relationships source target weight ... source_degree target_degree rank 0 "CHARLES DICKENS" "A CHRISTMAS CAROL" 1.0 ... 1 2 3 1 "ARTHUR RACKHAM" "A CHRISTMAS CAROL" 1.0 ... 1 2 3 2 "JANET BLENKINSHIP" "ONLINE DISTRIBUTED PROOFREADING TEAM" 1.0 ... 1 2 3 3 "J. B. LIPPINCOTT COMPANY" "PUBLICATION OF A CHRISTMAS CAROL" 1.0 ... 1 1 2 4 "SUZANNE SHELL" "ONLINE DISTRIBUTED PROOFREADING TEAM" 1.0 ... 1 2 3 .. ... ... ... ... ... ... ... 340 "VOLUNTEERS" "PROJECT GUTENBERGβ’" 1.0 ... 1 2 3 341 "DONATIONS" "PROJECT GUTENBERGβ’" 1.0 ... 2 2 4 342 "IRS" "COMPLIANCE" 1.0 ... 1 1 2 343 "PROFESSOR MICHAEL S. HART" "PROJECT GUTENBERG'S CONCEPT" 1.0 ... 1 1 2 344 "PG SEARCH FACILITY" "WWW.GUTENBERG.ORG" 1.0 ... 1 1 2[345 rows x 10 columns] π join_text_units_to_relationship_ids id relationship_ids 0 95f1f8f5bdbf0bee3a2c6f2f4a4907f6 [bc70fee2061541148833d19e86f225b3, 0fc15cc3b44... 1 8f05c8e8b3b9837fd079d58e372f2d30 [1ca41537c47c4752a17a44d1d7086d96, a2b1621a3e4... 2 9f76ed77ea7b876cf2b18cfa6544bf0c [1ca41537c47c4752a17a44d1d7086d96, df40ad480a3... 3 c390f1b92e2888f78b58f6af5b12afa0 [1ca41537c47c4752a17a44d1d7086d96, 0d8fde01d72... 4 2818d4194a37f4573f7a83b49cd59b21 [7e0d14ca308b4796bdc675a64bd3a36e, de04830d6e4... .. ... ... 187 f96b5ddf7fae853edbc4d916f66c623f [36870a3393f6413e9bf647168eb6977a] 188 b3c35247f91923027d9bd7d476467f4f [4fe3ff52700c491f8cc650aadb4d7cb0, f1f6f6435a4... 189 972bb34ddd371530f06d006480526d3e [0af2ca1c090843ea92679fd14c1fbc9a, f0c578614b2... 190 eec5fc1a2be814473698e220b303dc1b [1b06d3e53ffd4771952fbef04d1e666c, 60dce7d8bc1... 191 958e8453c6299cf980b3e6f962240699 [6915637e8d124fdc8473111d501e3703, 2233f319291...
[192 rows x 2 columns] π create_final_community_reports community ... id 0 46 ... d888d52d-c77f-4aff-bdea-4663922ea729 1 41 ... 8042150c-1581-4cfb-a6f8-7a0381fce758 2 42 ... 6f507306-78f0-4ee4-82b9-22eb1da39bfd 3 43 ... 7f1da666-5837-4f31-a478-cff51b07901a 4 44 ... 470365a0-fcfb-4f69-b3d6-67e1fc18eb4d 5 19 ... e5fe0812-0108-4ef1-88fc-a424e31bac6d 6 20 ... d1d6caea-2f3b-4c9c-8e88-6cb1f6f0e0d7 7 21 ... a1f0f398-d8c0-425a-b14f-13b0f0acc233 8 24 ... 15c17bd6-3c6c-4715-a87d-053965ebfa42 9 25 ... 307e735b-745e-4b0c-bcda-acdf92821671 10 26 ... 27c6d49e-e541-4f06-8a87-7d5cbefc72e7 11 27 ... 8ac85ef6-5a33-4494-9993-12637a727f43 12 28 ... 61eb826a-5729-487c-b3da-d280bf8ed42a 13 29 ... 34e4168e-4814-4804-a3fd-b7df9c8ffbf2 14 30 ... 1d276f1c-c89c-4adc-802e-e6749d1ba3c5 15 31 ... 2ef5e8bb-d276-4dab-829d-7a83e2b362f8 16 32 ... 413262ce-f4f6-41b5-9d67-4b35394e372b 17 33 ... 6b6bc9c6-6524-4e3f-81f1-1c3df1d33978 18 34 ... 43faf618-5028-489d-af26-e1d1b8a1a995 19 35 ... 35b64048-4a40-42bc-9d8a-9f290972873d 20 36 ... 6ea36c61-6a58-4b70-8e61-4f78fc06b5d6 21 37 ... dbc49043-eb78-4a82-944c-e1b36343e119 22 38 ... eea1d31d-c828-4f0a-8ddf-c5395c880b08 23 10 ... 98466546-5b9c-467d-a5b9-7cdc5748d832 24 11 ... 29a68cd2-8e2d-4267-84a7-7ac6b17abf40 25 13 ... 6e46377f-0257-4346-9a11-db842350a22c 26 14 ... c7377d80-6584-4982-bbb3-51f6ae4c45c3 27 16 ... cdab5616-9997-4f70-8b1d-c974d1e14979 28 17 ... 808ca4e2-1be2-4247-9330-4e26d930f409 29 18 ... 5b9a2c2c-2ecf-4870-a2fe-619320c9c5d5 30 4 ... eb3a1f3e-b50f-43f7-b580-40690283b4cf 31 5 ... 0d25de96-686c-4f5b-b06d-9eb35e8259e8 32 6 ... d9351192-1394-4ee9-8fc1-da1d2e03177c 33 9 ... 58f235d4-e59b-4436-bd84-97a3a57682c5
[34 rows x 10 columns] π create_final_text_units id ... relationship_ids 0 95f1f8f5bdbf0bee3a2c6f2f4a4907f6 ... [bc70fee2061541148833d19e86f225b3, 0fc15cc3b44... 1 c390f1b92e2888f78b58f6af5b12afa0 ... [1ca41537c47c4752a17a44d1d7086d96, 0d8fde01d72... 2 4df2a9b3b21d15ed7b34eb5970611c19 ... [7e0d14ca308b4796bdc675a64bd3a36e, 39d31f770cf... 3 4033108a1f27d8d4a3caaa923d459730 ... [feb9ddd0ac2949178f26a36949aa5422, 1fa6d3118bd... 4 dbf014d7f9bcf97aa06ace38b6e41ccb ... [62c65bbae33c4ee9a21b61f6f454c4b4, 30b7034c446... .. ... ... ... 226 427f29edf102f108c55aa868214fa411 ... None 227 2f918cd94d1825eb5cbdc2a9d3ce094e ... None 228 f44ec9393fd5cd1b28914e4203dcd7b9 ... None 229 3fedcfeffb43c689a33ffa06897ad045 ... None 230 01e84646075b255eab0a34d872336a89 ... None
[231 rows x 6 columns] D:\anaconda3\envs\GraphRAG\Lib\site-packages\datashaper\engine\verbs\convert.py:72: FutureWarning: errors='ignore' is deprecated and will raise in a future version. Use to_datetime without passing
errorsand catch exceptions explicitly instead datetime_column = pd.to_datetime(column, errors="ignore") π create_base_documents id ... title 0 c305886e4aa2f6efcf64b57762777055 ... book.txt[1 rows x 4 columns] π create_final_documents id ... title 0 c305886e4aa2f6efcf64b57762777055 ... book.txt
[1 rows x 4 columns] β ΄ GraphRAG Indexer βββ Loading Input (InputFileType.text) - 1 files loaded (0 filtered) ββββββββββββββββββββββββββββββ 100% 0:00:00 0:00:00 βββ create_base_text_units βββ create_base_extracted_entities βββ create_summarized_entities βββ create_base_entity_graph βββ create_final_entities βββ create_final_nodes βββ create_final_communities βββ join_text_units_to_entity_ids βββ create_final_relationships βββ join_text_units_to_relationship_ids βββ create_final_community_reports βββ create_final_text_units βββ create_base_documents βββ create_final_documents π All workflows completed successfully.
(GraphRAG) D:\AI\RAG\GraphRAG>python -m graphrag.query --root . --method global "What are the top themes in this story"
INFO: Reading settings from settings.yaml D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\query\indexer_adapters.py:71: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy entity_df["community"] = entity_df["community"].fillna(-1) D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\query\indexer_adapters.py:72: SettingWithCopyWarning: A value is trying to be set on a copy of a slice from a DataFrame. Try using .loc[row_indexer,col_indexer] = value instead
See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy entity_df["community"] = entity_df["community"].astype(int) creating llm client with {'api_key': 'REDACTED,len=6', 'type': "openai_chat", 'model': 'llama3', 'max_tokens': 4000, 'request_timeout': 180.0, 'api_base': 'http://localhost:11434/v1', 'api_version': None, 'organization': None, 'proxy': None, 'cognitive_services_endpoint': None, 'deployment_name': None, 'model_supports_json': True, 'tokens_per_minute': 0, 'requests_per_minute': 0, 'max_retries': 10, 'max_retry_wait': 10.0, 'sleep_on_rate_limit_recommendation': True, 'concurrent_requests': 25} Error parsing search response json Traceback (most recent call last): File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\query\structured_search\global_search\search.py", line 194, in _map_response_single_batch processed_response = self.parse_search_response(search_response) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\query\structured_search\global_search\search.py", line 232, in parse_search_response parsed_elements = json.loads(search_response)["points"] ^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\json__init__.py", line 346, in loads return _default_decoder.decode(s) ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\json\decoder.py", line 337, in decode obj, end = self.raw_decode(s, idx=_w(s, 0).end()) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\json\decoder.py", line 355, in raw_decode raise JSONDecodeError("Expecting value", s, err.value) from None json.decoder.JSONDecodeError: Expecting value: line 1 column 1 (char 0)
SUCCESS: Global Search Response: I am sorry but I am unable to answer this question given the provided data.
and these are from the indexing-engine.log
00:27:14,883 httpx INFO HTTP Request: POST http://localhost:1234/v1/embeddings "HTTP/1.1 200 OK" 00:27:14,927 graphrag.llm.base.rate_limiting_llm INFO perf - llm.embedding "Process" with 13 retries took 0.13999999999941792. input_tokens=958, output_tokens=0 00:27:15,113 httpx INFO HTTP Request: POST http://localhost:1234/v1/embeddings "HTTP/1.1 200 OK" 00:27:15,152 graphrag.llm.base.rate_limiting_llm INFO perf - llm.embedding "Process" with 13 retries took 0.14100000000144064. input_tokens=896, output_tokens=0 00:27:15,166 datashaper.workflow.workflow INFO executing verb drop 00:27:15,176 datashaper.workflow.workflow INFO executing verb filter 00:27:15,181 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_entities.parquet 00:27:15,320 graphrag.index.run INFO Running workflow: create_final_nodes... 00:27:15,320 graphrag.index.run INFO dependencies for create_final_nodes: ['create_base_entity_graph'] 00:27:15,320 graphrag.index.run INFO read table from storage: create_base_entity_graph.parquet 00:27:15,325 datashaper.workflow.workflow INFO executing verb layout_graph 00:27:15,575 datashaper.workflow.workflow INFO executing verb unpack_graph 00:27:15,632 datashaper.workflow.workflow INFO executing verb unpack_graph 00:27:15,759 datashaper.workflow.workflow INFO executing verb filter 00:27:15,779 datashaper.workflow.workflow INFO executing verb drop 00:27:15,789 datashaper.workflow.workflow INFO executing verb select 00:27:15,798 datashaper.workflow.workflow INFO executing verb rename 00:27:15,804 datashaper.workflow.workflow INFO executing verb join 00:27:15,814 datashaper.workflow.workflow INFO executing verb convert 00:27:15,835 datashaper.workflow.workflow INFO executing verb rename 00:27:15,835 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_nodes.parquet 00:27:15,946 graphrag.index.run INFO Running workflow: create_final_communities... 00:27:15,946 graphrag.index.run INFO dependencies for create_final_communities: ['create_base_entity_graph'] 00:27:15,946 graphrag.index.run INFO read table from storage: create_base_entity_graph.parquet 00:27:15,962 datashaper.workflow.workflow INFO executing verb unpack_graph 00:27:16,9 datashaper.workflow.workflow INFO executing verb unpack_graph 00:27:16,56 datashaper.workflow.workflow INFO executing verb aggregate_override 00:27:16,66 datashaper.workflow.workflow INFO executing verb join 00:27:16,76 datashaper.workflow.workflow INFO executing verb join 00:27:16,96 datashaper.workflow.workflow INFO executing verb concat 00:27:16,105 datashaper.workflow.workflow INFO executing verb filter 00:27:16,202 datashaper.workflow.workflow INFO executing verb aggregate_override 00:27:16,222 datashaper.workflow.workflow INFO executing verb join 00:27:16,233 datashaper.workflow.workflow INFO executing verb filter 00:27:16,252 datashaper.workflow.workflow INFO executing verb fill 00:27:16,265 datashaper.workflow.workflow INFO executing verb merge 00:27:16,276 datashaper.workflow.workflow INFO executing verb copy 00:27:16,282 datashaper.workflow.workflow INFO executing verb select 00:27:16,282 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_communities.parquet 00:27:16,393 graphrag.index.run INFO Running workflow: join_text_units_to_entity_ids... 00:27:16,393 graphrag.index.run INFO dependencies for join_text_units_to_entity_ids: ['create_final_entities'] 00:27:16,403 graphrag.index.run INFO read table from storage: create_final_entities.parquet 00:27:16,435 datashaper.workflow.workflow INFO executing verb select 00:27:16,440 datashaper.workflow.workflow INFO executing verb unroll 00:27:16,456 datashaper.workflow.workflow INFO executing verb aggregate_override 00:27:16,460 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table join_text_units_to_entity_ids.parquet 00:27:16,557 graphrag.index.run INFO Running workflow: create_final_relationships... 00:27:16,557 graphrag.index.run INFO dependencies for create_final_relationships: ['create_base_entity_graph', 'create_final_nodes'] 00:27:16,557 graphrag.index.run INFO read table from storage: create_base_entity_graph.parquet 00:27:16,567 graphrag.index.run INFO read table from storage: create_final_nodes.parquet 00:27:16,587 datashaper.workflow.workflow INFO executing verb unpack_graph 00:27:16,652 datashaper.workflow.workflow INFO executing verb filter 00:27:16,682 datashaper.workflow.workflow INFO executing verb rename 00:27:16,696 datashaper.workflow.workflow INFO executing verb filter 00:27:16,728 datashaper.workflow.workflow INFO executing verb drop 00:27:16,738 datashaper.workflow.workflow INFO executing verb compute_edge_combined_degree 00:27:16,748 datashaper.workflow.workflow INFO executing verb convert 00:27:16,778 datashaper.workflow.workflow INFO executing verb convert 00:27:16,778 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_relationships.parquet 00:27:16,888 graphrag.index.run INFO Running workflow: join_text_units_to_relationship_ids... 00:27:16,888 graphrag.index.run INFO dependencies for join_text_units_to_relationship_ids: ['create_final_relationships'] 00:27:16,888 graphrag.index.run INFO read table from storage: create_final_relationships.parquet 00:27:16,914 datashaper.workflow.workflow INFO executing verb select 00:27:16,924 datashaper.workflow.workflow INFO executing verb unroll 00:27:16,936 datashaper.workflow.workflow INFO executing verb aggregate_override 00:27:16,954 datashaper.workflow.workflow INFO executing verb select 00:27:16,954 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table join_text_units_to_relationship_ids.parquet 00:27:17,55 graphrag.index.run INFO Running workflow: create_final_community_reports... 00:27:17,55 graphrag.index.run INFO dependencies for create_final_community_reports: ['create_final_relationships', 'create_final_nodes'] 00:27:17,55 graphrag.index.run INFO read table from storage: create_final_relationships.parquet 00:27:17,55 graphrag.index.run INFO read table from storage: create_final_nodes.parquet 00:27:17,90 datashaper.workflow.workflow INFO executing verb prepare_community_reports_nodes 00:27:17,112 datashaper.workflow.workflow INFO executing verb prepare_community_reports_edges 00:27:17,128 datashaper.workflow.workflow INFO executing verb restore_community_hierarchy 00:27:17,144 datashaper.workflow.workflow INFO executing verb prepare_community_reports 00:27:17,144 graphrag.index.verbs.graph.report.prepare_community_reports INFO Number of nodes at level=3 => 369 00:27:17,163 graphrag.index.verbs.graph.report.prepare_community_reports INFO Number of nodes at level=2 => 369 00:27:17,176 graphrag.index.verbs.graph.report.prepare_community_reports INFO Number of nodes at level=1 => 369 00:27:17,222 graphrag.index.verbs.graph.report.prepare_community_reports INFO Number of nodes at level=0 => 369 00:27:17,295 datashaper.workflow.workflow INFO executing verb create_community_reports 00:27:27,992 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK" 00:27:27,992 graphrag.llm.base.rate_limiting_llm INFO perf - llm.chat "create_community_report" with 0 retries took 10.688000000000102. input_tokens=2532, output_tokens=439 00:27:29,735 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK" 00:27:38,699 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK" 00:27:47,543 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK" 00:27:56,478 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK" 00:27:56,479 graphrag.index.graph.extractors.community_reports.community_reports_extractor ERROR error generating community report Traceback (most recent call last): File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\index\graph\extractors\community_reports\community_reports_extractor.py", line 58, in call await self._llm( File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\openai\json_parsing_llm.py", line 34, in call result = await self._delegate(input, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\openai\openai_token_replacing_llm.py", line 37, in call return await self._delegate(input, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\openai\openai_history_tracking_llm.py", line 33, in call output = await self._delegate(input, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\caching_llm.py", line 104, in call result = await self._delegate(input, kwargs) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\rate_limiting_llm.py", line 177, in call result, start = await execute_with_retry() ^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\rate_limiting_llm.py", line 159, in execute_with_retry async for attempt in retryer: File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\tenacity\asyncio__init.py", line 166, in anext do = await self.iter(retry_state=self._retry_state) ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\tenacity\asyncio__init.py", line 153, in iter result = await action(retry_state) ^^^^^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\tenacity_utils.py", line 99, in inner return call(*args, **kwargs) ^^^^^^^^^^^^^^^^^^^^^ File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\tenacity\init__.py", line 398, in
self._add_action_func(lambda rs: rs.outcome.result())
^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GraphRAG\Lib\concurrent\futures_base.py", line 449, in result
return self. get_result()
^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GraphRAG\Lib\concurrent\futures_base.py", line 401, in get_result
raise self._exception
File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\rate_limiting_llm.py", line 165, in execute_with_retry
return await do_attempt(), start
^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\rate_limiting_llm.py", line 147, in do_attempt
return await self._delegate(input, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\base\base_llm.py", line 48, in call__
return await self._invoke_json(input, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\openai\openai_chat_llm.py", line 90, in _invoke_json
raise RuntimeError(FAILED_TO_CREATE_JSON_ERROR)
RuntimeError: Failed to generate valid JSON output
00:27:56,482 graphrag.index.reporting.file_workflow_callbacks INFO Community Report Extraction Error details=None
00:27:56,482 graphrag.index.verbs.graph.report.strategies.graph_intelligence.run_graph_intelligence WARNING No report found for community: 45
00:28:09,522 httpx INFO HTTP Request: POST http://localhost:11434/v1/chat/completions "HTTP/1.1 200 OK"
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File "D:\anaconda3\envs\GraphRAG\Lib\site-packages\graphrag\llm\openai\openai_chat_llm.py", line 90, in _invoke_json
raise RuntimeError(FAILED_TO_CREATE_JSON_ERROR)
RuntimeError: Failed to generate valid JSON output
00:33:57,636 graphrag.index.reporting.file_workflow_callbacks INFO Community Report Extraction Error details=None
00:33:57,636 graphrag.index.verbs.graph.report.strategies.graph_intelligence.run_graph_intelligence WARNING No report found for community: 0
00:33:57,663 datashaper.workflow.workflow INFO executing verb window
00:33:57,665 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_community_reports.parquet
00:33:57,791 graphrag.index.run INFO Running workflow: create_final_text_units...
00:33:57,791 graphrag.index.run INFO dependencies for create_final_text_units: ['join_text_units_to_relationship_ids', 'create_base_text_units', 'join_text_units_to_entity_ids']
00:33:57,791 graphrag.index.run INFO read table from storage: join_text_units_to_relationship_ids.parquet
00:33:57,794 graphrag.index.run INFO read table from storage: create_base_text_units.parquet
00:33:57,796 graphrag.index.run INFO read table from storage: join_text_units_to_entity_ids.parquet
00:33:57,825 datashaper.workflow.workflow INFO executing verb select
00:33:57,839 datashaper.workflow.workflow INFO executing verb rename
00:33:57,853 datashaper.workflow.workflow INFO executing verb join
00:33:57,869 datashaper.workflow.workflow INFO executing verb join
00:33:57,886 datashaper.workflow.workflow INFO executing verb aggregate_override
00:33:57,901 datashaper.workflow.workflow INFO executing verb select
00:33:57,903 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_text_units.parquet
00:33:58,12 graphrag.index.run INFO Running workflow: create_base_documents...
00:33:58,12 graphrag.index.run INFO dependencies for create_base_documents: ['create_final_text_units']
00:33:58,13 graphrag.index.run INFO read table from storage: create_final_text_units.parquet
00:33:58,44 datashaper.workflow.workflow INFO executing verb unroll
00:33:58,60 datashaper.workflow.workflow INFO executing verb select
00:33:58,74 datashaper.workflow.workflow INFO executing verb rename
00:33:58,90 datashaper.workflow.workflow INFO executing verb join
00:33:58,107 datashaper.workflow.workflow INFO executing verb aggregate_override
00:33:58,123 datashaper.workflow.workflow INFO executing verb join
00:33:58,141 datashaper.workflow.workflow INFO executing verb rename
00:33:58,155 datashaper.workflow.workflow INFO executing verb convert
00:33:58,173 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_base_documents.parquet
00:33:58,278 graphrag.index.run INFO Running workflow: create_final_documents...
00:33:58,278 graphrag.index.run INFO dependencies for create_final_documents: ['create_base_documents']
00:33:58,278 graphrag.index.run INFO read table from storage: create_base_documents.parquet
00:33:58,312 datashaper.workflow.workflow INFO executing verb rename
00:33:58,314 graphrag.index.emit.parquet_table_emitter INFO emitting parquet table create_final_documents.parquet
Additional Information