diff --git a/.github/workflows/issues-autoresolve.yml b/.github/workflows/issues-autoresolve.yml index 962bf3656..df159ccc2 100644 --- a/.github/workflows/issues-autoresolve.yml +++ b/.github/workflows/issues-autoresolve.yml @@ -10,7 +10,7 @@ jobs: issues: write pull-requests: write steps: - - uses: actions/stale@v5 + - uses: actions/stale@v9 with: days-before-issue-stale: 7 days-before-issue-close: 5 @@ -18,7 +18,7 @@ jobs: close-issue-label: "autoresolved" stale-issue-message: "This issue has been marked stale due to inactivity after repo maintainer or community member responses that request more information or suggest a solution. It will be closed after five additional days." close-issue-message: "This issue has been closed after being marked as stale for five days. Please reopen if needed." - exempt-issue-label: "triage" + any-of-labels: "awaiting_response" days-before-pr-stale: -1 days-before-pr-close: -1 repo-token: ${{ secrets.GITHUB_TOKEN }} diff --git a/.semversioner/0.2.1.json b/.semversioner/0.2.1.json new file mode 100644 index 000000000..77a4bcec2 --- /dev/null +++ b/.semversioner/0.2.1.json @@ -0,0 +1,70 @@ +{ + "changes": [ + { + "description": "Added default columns for vector store at create_pipeline_config. No change for other cases.", + "type": "patch" + }, + { + "description": "Change json parsing error in the map step of global search to warning", + "type": "patch" + }, + { + "description": "Fix Local Search breaking when loading Embeddings input. Defaulting overwrite to True as in the rest of the vector store config", + "type": "patch" + }, + { + "description": "Fix json parsing when LLM returns faulty responses", + "type": "patch" + }, + { + "description": "Fix missing community reports and refactor community context builder", + "type": "patch" + }, + { + "description": "Fixed a bug that erased the vector database, added a new parameter to specify the config file path, and updated the documentation accordingly.", + "type": "patch" + }, + { + "description": "Try parsing json before even repairing", + "type": "patch" + }, + { + "description": "Update Prompt Tuning meta prompts with finer examples", + "type": "patch" + }, + { + "description": "Update default entity extraction and gleaning prompts to reduce hallucinations", + "type": "patch" + }, + { + "description": "add encoding-model to entity/claim extraction config", + "type": "patch" + }, + { + "description": "add encoding-model to text chunking config", + "type": "patch" + }, + { + "description": "add user prompt to history-tracking llm", + "type": "patch" + }, + { + "description": "update config reader to allow for zero gleans", + "type": "patch" + }, + { + "description": "update config-reader to allow for empty chunk-by arrays", + "type": "patch" + }, + { + "description": "update history-tracking LLm to use 'assistant' instead of 'system' in output history.", + "type": "patch" + }, + { + "description": "use history argument in hash key computation; add history input to cache data", + "type": "patch" + } + ], + "created_at": "2024-08-06T00:25:52+00:00", + "version": "0.2.1" +} \ No newline at end of file diff --git a/.semversioner/next-release/patch-20240726142042913643.json b/.semversioner/next-release/patch-20240726142042913643.json deleted file mode 100644 index 4413e7ff1..000000000 --- a/.semversioner/next-release/patch-20240726142042913643.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "add user prompt to history-tracking llm" -} diff --git a/.semversioner/next-release/patch-20240726143138162263.json b/.semversioner/next-release/patch-20240726143138162263.json deleted file mode 100644 index 18e517c53..000000000 --- a/.semversioner/next-release/patch-20240726143138162263.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "update config reader to allow for zero gleans" -} diff --git a/.semversioner/next-release/patch-20240726154054702667.json b/.semversioner/next-release/patch-20240726154054702667.json deleted file mode 100644 index 669339dd5..000000000 --- a/.semversioner/next-release/patch-20240726154054702667.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "use history argument in hash key computation; add history input to cache data" -} diff --git a/.semversioner/next-release/patch-20240726181256417715.json b/.semversioner/next-release/patch-20240726181256417715.json deleted file mode 100644 index cff661503..000000000 --- a/.semversioner/next-release/patch-20240726181256417715.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "add encoding-model to entity/claim extraction config" -} diff --git a/.semversioner/next-release/patch-20240726200425411495.json b/.semversioner/next-release/patch-20240726200425411495.json deleted file mode 100644 index 552522071..000000000 --- a/.semversioner/next-release/patch-20240726200425411495.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "update config-reader to allow for empty chunk-by arrays" -} diff --git a/.semversioner/next-release/patch-20240726205654788488.json b/.semversioner/next-release/patch-20240726205654788488.json deleted file mode 100644 index 3baa3dc6c..000000000 --- a/.semversioner/next-release/patch-20240726205654788488.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "type": "patch", - "description": "add encoding-model to text chunking config" -} diff --git a/CHANGELOG.md b/CHANGELOG.md index 802b3a11a..f6d99c3a2 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -1,6 +1,25 @@ # Changelog Note: version releases in the 0.x.y range may introduce breaking changes. +## 0.2.1 + +- patch: Added default columns for vector store at create_pipeline_config. No change for other cases. +- patch: Change json parsing error in the map step of global search to warning +- patch: Fix Local Search breaking when loading Embeddings input. Defaulting overwrite to True as in the rest of the vector store config +- patch: Fix json parsing when LLM returns faulty responses +- patch: Fix missing community reports and refactor community context builder +- patch: Fixed a bug that erased the vector database, added a new parameter to specify the config file path, and updated the documentation accordingly. +- patch: Try parsing json before even repairing +- patch: Update Prompt Tuning meta prompts with finer examples +- patch: Update default entity extraction and gleaning prompts to reduce hallucinations +- patch: add encoding-model to entity/claim extraction config +- patch: add encoding-model to text chunking config +- patch: add user prompt to history-tracking llm +- patch: update config reader to allow for zero gleans +- patch: update config-reader to allow for empty chunk-by arrays +- patch: update history-tracking LLm to use 'assistant' instead of 'system' in output history. +- patch: use history argument in hash key computation; add history input to cache data + ## 0.2.0 - minor: Add content-based KNN for selecting prompt tune few shot examples diff --git a/dictionary.txt b/dictionary.txt index f1cb4ce19..98cee712b 100644 --- a/dictionary.txt +++ b/dictionary.txt @@ -132,11 +132,30 @@ MSRC Arrary # Prompt Inputs -dulce -Asadi ABILA Abila +ALHAMIA +Alhamia +Asadi +Aurelians +Bataglani +BATAGLANI +Bratinas +dulce +Durke +Firuzabad +Firuzabad's +FIRUZABAD +Krohaara +KROHAARA POKRALLY +Tazbah +TIRUZIA +Tiruzia +Tiruzia's +Verdantis +Verdantis's + # English skippable diff --git a/docsite/posts/query/3-cli.md b/docsite/posts/query/3-cli.md index c1a88f9eb..518d9cd87 100644 --- a/docsite/posts/query/3-cli.md +++ b/docsite/posts/query/3-cli.md @@ -9,11 +9,12 @@ date: 2024-27-03 The GraphRAG query CLI allows for no-code usage of the GraphRAG Query engine. ```bash -python -m graphrag.query --data --community_level --response_type --method <"local"|"global"> +python -m graphrag.query --config --data --community_level --response_type --method <"local"|"global"> ``` ## CLI Arguments +- `--config ` - The configuration yaml file to use when running the query. If this is used, then none of the environment-variables below will apply. - `--data ` - Folder containing the `.parquet` output files from running the Indexer. - `--community_level ` - Community level in the Leiden community hierarchy from which we will load the community reports higher value means we use reports on smaller communities. Default: 2 - `--response_type ` - Free form text describing the response type and format, can be anything, e.g. `Multiple Paragraphs`, `Single Paragraph`, `Single Sentence`, `List of 3-7 Points`, `Single Page`, `Multi-Page Report`. Default: `Multiple Paragraphs`. diff --git a/examples_notebooks/global_search.ipynb b/examples_notebooks/global_search.ipynb index fdde2c706..3c0c462cf 100644 --- a/examples_notebooks/global_search.ipynb +++ b/examples_notebooks/global_search.ipynb @@ -115,7 +115,10 @@ "\n", "reports = read_indexer_reports(report_df, entity_df, COMMUNITY_LEVEL)\n", "entities = read_indexer_entities(entity_df, entity_embedding_df, COMMUNITY_LEVEL)\n", - "print(f\"Report records: {len(report_df)}\")\n", + "print(f\"Total report count: {len(report_df)}\")\n", + "print(\n", + " f\"Report count after filtering by community level {COMMUNITY_LEVEL}: {len(reports)}\"\n", + ")\n", "report_df.head()" ] }, @@ -223,17 +226,9 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "LLM calls: 13. LLM tokens: 184660\n" - ] - } - ], + "outputs": [], "source": [ "# inspect number of LLM calls and tokens\n", "print(f\"LLM calls: {result.llm_calls}. LLM tokens: {result.prompt_tokens}\")" diff --git a/graphrag/index/create_pipeline_config.py b/graphrag/index/create_pipeline_config.py index 993a0b6c7..22dba2002 100644 --- a/graphrag/index/create_pipeline_config.py +++ b/graphrag/index/create_pipeline_config.py @@ -198,7 +198,12 @@ def _document_workflows( name=create_final_documents, config={ "document_raw_content_embed": _get_embedding_settings( - settings.embeddings, "document_raw_content" + settings.embeddings, + "document_raw_content", + { + "title_column": "raw_content", + "collection_name": "final_documents_raw_content_embedding", + }, ), "skip_raw_content_embedding": skip_document_raw_content_embedding, }, @@ -243,7 +248,9 @@ def _text_unit_workflows( name=create_final_text_units, config={ "text_unit_text_embed": _get_embedding_settings( - settings.embeddings, "text_unit_text" + settings.embeddings, + "text_unit_text", + {"title_column": "text", "collection_name": "text_units_embedding"}, ), "covariates_enabled": covariates_enabled, "skip_text_unit_embedding": skip_text_unit_embedding, @@ -252,11 +259,14 @@ def _text_unit_workflows( ] -def _get_embedding_settings(settings: TextEmbeddingConfig, embedding_name: str) -> dict: +def _get_embedding_settings( + settings: TextEmbeddingConfig, + embedding_name: str, + vector_store_params: dict | None = None, +) -> dict: vector_store_settings = settings.vector_store if vector_store_settings is None: return {"strategy": settings.resolved_strategy()} - # # If we get to this point, settings.vector_store is defined, and there's a specific setting for this embedding. # settings.vector_store.base contains connection information, or may be undefined @@ -264,7 +274,7 @@ def _get_embedding_settings(settings: TextEmbeddingConfig, embedding_name: str) # strategy = settings.resolved_strategy() # get the default strategy strategy.update({ - "vector_store": vector_store_settings + "vector_store": {**vector_store_settings, **(vector_store_params or {})} }) # update the default strategy with the vector store settings # This ensures the vector store config is part of the strategy and not the global config return { @@ -327,10 +337,20 @@ def _graph_workflows( name=create_final_entities, config={ "entity_name_embed": _get_embedding_settings( - settings.embeddings, "entity_name" + settings.embeddings, + "entity_name", + { + "title_column": "name", + "collection_name": "entity_name_embeddings", + }, ), "entity_name_description_embed": _get_embedding_settings( - settings.embeddings, "entity_name_description" + settings.embeddings, + "entity_name_description", + { + "title_column": "description", + "collection_name": "entity_description_embeddings", + }, ), "skip_name_embedding": skip_entity_name_embedding, "skip_description_embedding": skip_entity_description_embedding, @@ -340,7 +360,12 @@ def _graph_workflows( name=create_final_relationships, config={ "relationship_description_embed": _get_embedding_settings( - settings.embeddings, "relationship_description" + settings.embeddings, + "relationship_description", + { + "title_column": "description", + "collection_name": "relationships_description_embeddings", + }, ), "skip_description_embedding": skip_relationship_description_embedding, }, @@ -382,13 +407,25 @@ def _community_workflows( ), }, "community_report_full_content_embed": _get_embedding_settings( - settings.embeddings, "community_report_full_content" + settings.embeddings, + "community_report_full_content", + { + "title_column": "full_content", + "collection_name": "final_community_reports_full_content_embedding", + }, ), "community_report_summary_embed": _get_embedding_settings( - settings.embeddings, "community_report_summary" + settings.embeddings, + "community_report_summary", + { + "title_column": "summary", + "collection_name": "final_community_reports_summary_embedding", + }, ), "community_report_title_embed": _get_embedding_settings( - settings.embeddings, "community_report_title" + settings.embeddings, + "community_report_title", + {"title_column": "title"}, ), }, ), diff --git a/graphrag/index/graph/extractors/graph/prompts.py b/graphrag/index/graph/extractors/graph/prompts.py index 0cc53bec4..cb1bcc668 100644 --- a/graphrag/index/graph/extractors/graph/prompts.py +++ b/graphrag/index/graph/extractors/graph/prompts.py @@ -6,14 +6,14 @@ GRAPH_EXTRACTION_PROMPT = """ -Goal- Given a text document that is potentially relevant to this activity and a list of entity types, identify all entities of those types from the text and all relationships among the identified entities. - + -Steps- 1. Identify all entities. For each identified entity, extract the following information: - entity_name: Name of the entity, capitalized - entity_type: One of the following types: [{entity_types}] - entity_description: Comprehensive description of the entity's attributes and activities -Format each entity as ("entity"{tuple_delimiter}{tuple_delimiter}{tuple_delimiter} - +Format each entity as ("entity"{tuple_delimiter}{tuple_delimiter}{tuple_delimiter}) + 2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other. For each pair of related entities, extract the following information: - source_entity: name of the source entity, as identified in step 1 @@ -21,81 +21,103 @@ - relationship_description: explanation as to why you think the source entity and the target entity are related to each other - relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity Format each relationship as ("relationship"{tuple_delimiter}{tuple_delimiter}{tuple_delimiter}{tuple_delimiter}) - + 3. Return output in English as a single list of all the entities and relationships identified in steps 1 and 2. Use **{record_delimiter}** as the list delimiter. - + 4. When finished, output {completion_delimiter} - + ###################### -Examples- ###################### Example 1: - -Entity_types: [person, technology, mission, organization, location] +Entity_types: ORGANIZATION,PERSON Text: -while Alex clenched his jaw, the buzz of frustration dull against the backdrop of Taylor's authoritarian certainty. It was this competitive undercurrent that kept him alert, the sense that his and Jordan's shared commitment to discovery was an unspoken rebellion against Cruz's narrowing vision of control and order. - -Then Taylor did something unexpected. They paused beside Jordan and, for a moment, observed the device with something akin to reverence. “If this tech can be understood..." Taylor said, their voice quieter, "It could change the game for us. For all of us.” - -The underlying dismissal earlier seemed to falter, replaced by a glimpse of reluctant respect for the gravity of what lay in their hands. Jordan looked up, and for a fleeting heartbeat, their eyes locked with Taylor's, a wordless clash of wills softening into an uneasy truce. - -It was a small transformation, barely perceptible, but one that Alex noted with an inward nod. They had all been brought here by different paths -################ +The Verdantis's Central Institution is scheduled to meet on Monday and Thursday, with the institution planning to release its latest policy decision on Thursday at 1:30 p.m. PDT, followed by a press conference where Central Institution Chair Martin Smith will take questions. Investors expect the Market Strategy Committee to hold its benchmark interest rate steady in a range of 3.5%-3.75%. +###################### Output: -("entity"{tuple_delimiter}"Alex"{tuple_delimiter}"person"{tuple_delimiter}"Alex is a character who experiences frustration and is observant of the dynamics among other characters."){record_delimiter} -("entity"{tuple_delimiter}"Taylor"{tuple_delimiter}"person"{tuple_delimiter}"Taylor is portrayed with authoritarian certainty and shows a moment of reverence towards a device, indicating a change in perspective."){record_delimiter} -("entity"{tuple_delimiter}"Jordan"{tuple_delimiter}"person"{tuple_delimiter}"Jordan shares a commitment to discovery and has a significant interaction with Taylor regarding a device."){record_delimiter} -("entity"{tuple_delimiter}"Cruz"{tuple_delimiter}"person"{tuple_delimiter}"Cruz is associated with a vision of control and order, influencing the dynamics among other characters."){record_delimiter} -("entity"{tuple_delimiter}"The Device"{tuple_delimiter}"technology"{tuple_delimiter}"The Device is central to the story, with potential game-changing implications, and is revered by Taylor."){record_delimiter} -("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"Taylor"{tuple_delimiter}"Alex is affected by Taylor's authoritarian certainty and observes changes in Taylor's attitude towards the device."{tuple_delimiter}7){record_delimiter} -("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"Jordan"{tuple_delimiter}"Alex and Jordan share a commitment to discovery, which contrasts with Cruz's vision."{tuple_delimiter}6){record_delimiter} -("relationship"{tuple_delimiter}"Taylor"{tuple_delimiter}"Jordan"{tuple_delimiter}"Taylor and Jordan interact directly regarding the device, leading to a moment of mutual respect and an uneasy truce."{tuple_delimiter}8){record_delimiter} -("relationship"{tuple_delimiter}"Jordan"{tuple_delimiter}"Cruz"{tuple_delimiter}"Jordan's commitment to discovery is in rebellion against Cruz's vision of control and order."{tuple_delimiter}5){record_delimiter} -("relationship"{tuple_delimiter}"Taylor"{tuple_delimiter}"The Device"{tuple_delimiter}"Taylor shows reverence towards the device, indicating its importance and potential impact."{tuple_delimiter}9){completion_delimiter} -############################# -Example 2: +("entity"{tuple_delimiter}CENTRAL INSTITUTION{tuple_delimiter}ORGANIZATION{tuple_delimiter}The Central Institution is the Federal Reserve of Verdantis, which is setting interest rates on Monday and Thursday) +{record_delimiter} +("entity"{tuple_delimiter}MARTIN SMITH{tuple_delimiter}PERSON{tuple_delimiter}Martin Smith is the chair of the Central Institution) +{record_delimiter} +("entity"{tuple_delimiter}MARKET STRATEGY COMMITTEE{tuple_delimiter}ORGANIZATION{tuple_delimiter}The Central Institution committee makes key decisions about interest rates and the growth of Verdantis's money supply) +{record_delimiter} +("relationship"{tuple_delimiter}MARTIN SMITH{tuple_delimiter}CENTRAL INSTITUTION{tuple_delimiter}Martin Smith is the Chair of the Central Institution and will answer questions at a press conference{tuple_delimiter}9) +{completion_delimiter} -Entity_types: [person, technology, mission, organization, location] +###################### +Example 2: +Entity_types: ORGANIZATION Text: -They were no longer mere operatives; they had become guardians of a threshold, keepers of a message from a realm beyond stars and stripes. This elevation in their mission could not be shackled by regulations and established protocols—it demanded a new perspective, a new resolve. - -Tension threaded through the dialogue of beeps and static as communications with Washington buzzed in the background. The team stood, a portentous air enveloping them. It was clear that the decisions they made in the ensuing hours could redefine humanity's place in the cosmos or condemn them to ignorance and potential peril. +TechGlobal's (TG) stock skyrocketed in its opening day on the Global Exchange Thursday. But IPO experts warn that the semiconductor corporation's debut on the public markets isn't indicative of how other newly listed companies may perform. -Their connection to the stars solidified, the group moved to address the crystallizing warning, shifting from passive recipients to active participants. Mercer's latter instincts gained precedence— the team's mandate had evolved, no longer solely to observe and report but to interact and prepare. A metamorphosis had begun, and Operation: Dulce hummed with the newfound frequency of their daring, a tone set not by the earthly -############# +TechGlobal, a formerly public company, was taken private by Vision Holdings in 2014. The well-established chip designer says it powers 85% of premium smartphones. +###################### Output: -("entity"{tuple_delimiter}"Washington"{tuple_delimiter}"location"{tuple_delimiter}"Washington is a location where communications are being received, indicating its importance in the decision-making process."){record_delimiter} -("entity"{tuple_delimiter}"Operation: Dulce"{tuple_delimiter}"mission"{tuple_delimiter}"Operation: Dulce is described as a mission that has evolved to interact and prepare, indicating a significant shift in objectives and activities."){record_delimiter} -("entity"{tuple_delimiter}"The team"{tuple_delimiter}"organization"{tuple_delimiter}"The team is portrayed as a group of individuals who have transitioned from passive observers to active participants in a mission, showing a dynamic change in their role."){record_delimiter} -("relationship"{tuple_delimiter}"The team"{tuple_delimiter}"Washington"{tuple_delimiter}"The team receives communications from Washington, which influences their decision-making process."{tuple_delimiter}7){record_delimiter} -("relationship"{tuple_delimiter}"The team"{tuple_delimiter}"Operation: Dulce"{tuple_delimiter}"The team is directly involved in Operation: Dulce, executing its evolved objectives and activities."{tuple_delimiter}9){completion_delimiter} -############################# -Example 3: +("entity"{tuple_delimiter}TECHGLOBAL{tuple_delimiter}ORGANIZATION{tuple_delimiter}TechGlobal is a stock now listed on the Global Exchange which powers 85% of premium smartphones) +{record_delimiter} +("entity"{tuple_delimiter}VISION HOLDINGS{tuple_delimiter}ORGANIZATION{tuple_delimiter}Vision Holdings is a firm that previously owned TechGlobal) +{record_delimiter} +("relationship"{tuple_delimiter}TECHGLOBAL{tuple_delimiter}VISION HOLDINGS{tuple_delimiter}Vision Holdings formerly owned TechGlobal from 2014 until present{tuple_delimiter}5) +{completion_delimiter} -Entity_types: [person, role, technology, organization, event, location, concept] +###################### +Example 3: +Entity_types: ORGANIZATION,GEO,PERSON Text: -their voice slicing through the buzz of activity. "Control may be an illusion when facing an intelligence that literally writes its own rules," they stated stoically, casting a watchful eye over the flurry of data. +Five Aurelians jailed for 8 years in Firuzabad and widely regarded as hostages are on their way home to Aurelia. -"It's like it's learning to communicate," offered Sam Rivera from a nearby interface, their youthful energy boding a mix of awe and anxiety. "This gives talking to strangers' a whole new meaning." +The swap orchestrated by Quintara was finalized when $8bn of Firuzi funds were transferred to financial institutions in Krohaara, the capital of Quintara. -Alex surveyed his team—each face a study in concentration, determination, and not a small measure of trepidation. "This might well be our first contact," he acknowledged, "And we need to be ready for whatever answers back." +The exchange initiated in Firuzabad's capital, Tiruzia, led to the four men and one woman, who are also Firuzi nationals, boarding a chartered flight to Krohaara. -Together, they stood on the edge of the unknown, forging humanity's response to a message from the heavens. The ensuing silence was palpable—a collective introspection about their role in this grand cosmic play, one that could rewrite human history. +They were welcomed by senior Aurelian officials and are now on their way to Aurelia's capital, Cashion. -The encrypted dialogue continued to unfold, its intricate patterns showing an almost uncanny anticipation -############# +The Aurelians include 39-year-old businessman Samuel Namara, who has been held in Tiruzia's Alhamia Prison, as well as journalist Durke Bataglani, 59, and environmentalist Meggie Tazbah, 53, who also holds Bratinas nationality. +###################### Output: -("entity"{tuple_delimiter}"Sam Rivera"{tuple_delimiter}"person"{tuple_delimiter}"Sam Rivera is a member of a team working on communicating with an unknown intelligence, showing a mix of awe and anxiety."){record_delimiter} -("entity"{tuple_delimiter}"Alex"{tuple_delimiter}"person"{tuple_delimiter}"Alex is the leader of a team attempting first contact with an unknown intelligence, acknowledging the significance of their task."){record_delimiter} -("entity"{tuple_delimiter}"Control"{tuple_delimiter}"concept"{tuple_delimiter}"Control refers to the ability to manage or govern, which is challenged by an intelligence that writes its own rules."){record_delimiter} -("entity"{tuple_delimiter}"Intelligence"{tuple_delimiter}"concept"{tuple_delimiter}"Intelligence here refers to an unknown entity capable of writing its own rules and learning to communicate."){record_delimiter} -("entity"{tuple_delimiter}"First Contact"{tuple_delimiter}"event"{tuple_delimiter}"First Contact is the potential initial communication between humanity and an unknown intelligence."){record_delimiter} -("entity"{tuple_delimiter}"Humanity's Response"{tuple_delimiter}"event"{tuple_delimiter}"Humanity's Response is the collective action taken by Alex's team in response to a message from an unknown intelligence."){record_delimiter} -("relationship"{tuple_delimiter}"Sam Rivera"{tuple_delimiter}"Intelligence"{tuple_delimiter}"Sam Rivera is directly involved in the process of learning to communicate with the unknown intelligence."{tuple_delimiter}9){record_delimiter} -("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"First Contact"{tuple_delimiter}"Alex leads the team that might be making the First Contact with the unknown intelligence."{tuple_delimiter}10){record_delimiter} -("relationship"{tuple_delimiter}"Alex"{tuple_delimiter}"Humanity's Response"{tuple_delimiter}"Alex and his team are the key figures in Humanity's Response to the unknown intelligence."{tuple_delimiter}8){record_delimiter} -("relationship"{tuple_delimiter}"Control"{tuple_delimiter}"Intelligence"{tuple_delimiter}"The concept of Control is challenged by the Intelligence that writes its own rules."{tuple_delimiter}7){completion_delimiter} -############################# +("entity"{tuple_delimiter}FIRUZABAD{tuple_delimiter}GEO{tuple_delimiter}Firuzabad held Aurelians as hostages) +{record_delimiter} +("entity"{tuple_delimiter}AURELIA{tuple_delimiter}GEO{tuple_delimiter}Country seeking to release hostages) +{record_delimiter} +("entity"{tuple_delimiter}QUINTARA{tuple_delimiter}GEO{tuple_delimiter}Country that negotiated a swap of money in exchange for hostages) +{record_delimiter} +{record_delimiter} +("entity"{tuple_delimiter}TIRUZIA{tuple_delimiter}GEO{tuple_delimiter}Capital of Firuzabad where the Aurelians were being held) +{record_delimiter} +("entity"{tuple_delimiter}KROHAARA{tuple_delimiter}GEO{tuple_delimiter}Capital city in Quintara) +{record_delimiter} +("entity"{tuple_delimiter}CASHION{tuple_delimiter}GEO{tuple_delimiter}Capital city in Aurelia) +{record_delimiter} +("entity"{tuple_delimiter}SAMUEL NAMARA{tuple_delimiter}PERSON{tuple_delimiter}Aurelian who spent time in Tiruzia's Alhamia Prison) +{record_delimiter} +("entity"{tuple_delimiter}ALHAMIA PRISON{tuple_delimiter}GEO{tuple_delimiter}Prison in Tiruzia) +{record_delimiter} +("entity"{tuple_delimiter}DURKE BATAGLANI{tuple_delimiter}PERSON{tuple_delimiter}Aurelian journalist who was held hostage) +{record_delimiter} +("entity"{tuple_delimiter}MEGGIE TAZBAH{tuple_delimiter}PERSON{tuple_delimiter}Bratinas national and environmentalist who was held hostage) +{record_delimiter} +("relationship"{tuple_delimiter}FIRUZABAD{tuple_delimiter}AURELIA{tuple_delimiter}Firuzabad negotiated a hostage exchange with Aurelia{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}QUINTARA{tuple_delimiter}AURELIA{tuple_delimiter}Quintara brokered the hostage exchange between Firuzabad and Aurelia{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}QUINTARA{tuple_delimiter}FIRUZABAD{tuple_delimiter}Quintara brokered the hostage exchange between Firuzabad and Aurelia{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}SAMUEL NAMARA{tuple_delimiter}ALHAMIA PRISON{tuple_delimiter}Samuel Namara was a prisoner at Alhamia prison{tuple_delimiter}8) +{record_delimiter} +("relationship"{tuple_delimiter}SAMUEL NAMARA{tuple_delimiter}MEGGIE TAZBAH{tuple_delimiter}Samuel Namara and Meggie Tazbah were exchanged in the same hostage release{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}SAMUEL NAMARA{tuple_delimiter}DURKE BATAGLANI{tuple_delimiter}Samuel Namara and Durke Bataglani were exchanged in the same hostage release{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}MEGGIE TAZBAH{tuple_delimiter}DURKE BATAGLANI{tuple_delimiter}Meggie Tazbah and Durke Bataglani were exchanged in the same hostage release{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}SAMUEL NAMARA{tuple_delimiter}FIRUZABAD{tuple_delimiter}Samuel Namara was a hostage in Firuzabad{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}MEGGIE TAZBAH{tuple_delimiter}FIRUZABAD{tuple_delimiter}Meggie Tazbah was a hostage in Firuzabad{tuple_delimiter}2) +{record_delimiter} +("relationship"{tuple_delimiter}DURKE BATAGLANI{tuple_delimiter}FIRUZABAD{tuple_delimiter}Durke Bataglani was a hostage in Firuzabad{tuple_delimiter}2) +{completion_delimiter} + +###################### -Real Data- ###################### Entity_types: {entity_types} @@ -103,5 +125,5 @@ ###################### Output:""" -CONTINUE_PROMPT = "MANY entities were missed in the last extraction. Add them below using the same format:\n" -LOOP_PROMPT = "It appears some entities may have still been missed. Answer YES | NO if there are still entities that need to be added.\n" +CONTINUE_PROMPT = "MANY entities and relationships were missed in the last extraction. Remember to ONLY emit entities that match any of the previously extracted types. Add them below using the same format:\n" +LOOP_PROMPT = "It appears some entities and relationships may have still been missed. Answer YES | NO if there are still entities or relationships that need to be added.\n" diff --git a/graphrag/index/utils/__init__.py b/graphrag/index/utils/__init__.py index 3a8b1c002..7cbbb53d7 100644 --- a/graphrag/index/utils/__init__.py +++ b/graphrag/index/utils/__init__.py @@ -6,7 +6,6 @@ from .dicts import dict_has_keys_with_types from .hashing import gen_md5_hash from .is_null import is_null -from .json import clean_up_json from .load_graph import load_graph from .string import clean_str from .tokens import num_tokens_from_string, string_from_tokens @@ -15,7 +14,6 @@ __all__ = [ "clean_str", - "clean_up_json", "dict_has_keys_with_types", "gen_md5_hash", "gen_uuid", diff --git a/graphrag/index/utils/json.py b/graphrag/index/utils/json.py deleted file mode 100644 index ed6c06665..000000000 --- a/graphrag/index/utils/json.py +++ /dev/null @@ -1,27 +0,0 @@ -# Copyright (c) 2024 Microsoft Corporation. -# Licensed under the MIT License - -"""JSON cleaning and formatting utilities.""" - - -def clean_up_json(json_str: str): - """Clean up json string.""" - json_str = ( - json_str.replace("\\n", "") - .replace("\n", "") - .replace("\r", "") - .replace('"[{', "[{") - .replace('}]"', "}]") - .replace("\\", "") - .strip() - ) - - # Remove JSON Markdown Frame - if json_str.startswith("```json"): - json_str = json_str[len("```json") :] - if json_str.startswith("json"): - json_str = json_str[len("json") :] - if json_str.endswith("```"): - json_str = json_str[: len(json_str) - len("```")] - - return json_str diff --git a/graphrag/llm/openai/_json.py b/graphrag/llm/openai/_json.py deleted file mode 100644 index 22184cc22..000000000 --- a/graphrag/llm/openai/_json.py +++ /dev/null @@ -1,25 +0,0 @@ -# Copyright (c) 2024 Microsoft Corporation. -# Licensed under the MIT License - -"""JSON cleaning and formatting utilities.""" - - -def clean_up_json(json_str: str) -> str: - """Clean up json string.""" - json_str = ( - json_str.replace("\\n", "") - .replace("\n", "") - .replace("\r", "") - .replace('"[{', "[{") - .replace('}]"', "}]") - .replace("\\", "") - .strip() - ) - - # Remove JSON Markdown Frame - if json_str.startswith("```json"): - json_str = json_str[len("```json") :] - if json_str.endswith("```"): - json_str = json_str[: len(json_str) - len("```")] - - return json_str diff --git a/graphrag/llm/openai/json_parsing_llm.py b/graphrag/llm/openai/json_parsing_llm.py index 843ca0ecb..009c1da42 100644 --- a/graphrag/llm/openai/json_parsing_llm.py +++ b/graphrag/llm/openai/json_parsing_llm.py @@ -33,5 +33,6 @@ async def __call__( """Call the LLM with the input and kwargs.""" result = await self._delegate(input, **kwargs) if kwargs.get("json") and result.json is None and result.output is not None: - result.json = try_parse_json_object(result.output) + _, parsed_json = try_parse_json_object(result.output) + result.json = parsed_json return result diff --git a/graphrag/llm/openai/openai_chat_llm.py b/graphrag/llm/openai/openai_chat_llm.py index e4add8a25..d08f8af80 100644 --- a/graphrag/llm/openai/openai_chat_llm.py +++ b/graphrag/llm/openai/openai_chat_llm.py @@ -4,7 +4,6 @@ """The Chat-based language model.""" import logging -from json import JSONDecodeError from typing_extensions import Unpack @@ -16,7 +15,6 @@ LLMOutput, ) -from ._json import clean_up_json from ._prompts import JSON_CHECK_PROMPT from .openai_configuration import OpenAIConfiguration from .types import OpenAIClientTypes @@ -104,11 +102,10 @@ async def _native_json( }, ) - raw_output = result.output or "" - json_output = try_parse_json_object(raw_output) + output, json_output = try_parse_json_object(result.output or "") return LLMOutput[CompletionOutput]( - output=raw_output, + output=output, json=json_output, history=result.history, ) @@ -119,24 +116,23 @@ async def _manual_json( # Otherwise, clean up the output and try to parse it as json result = await self._invoke(input, **kwargs) history = result.history or [] - output = clean_up_json(result.output or "") - try: - json_output = try_parse_json_object(output) + output, json_output = try_parse_json_object(result.output or "") + if json_output: return LLMOutput[CompletionOutput]( - output=output, json=json_output, history=history + output=result.output, json=json_output, history=history ) - except (TypeError, JSONDecodeError): - log.warning("error parsing llm json, retrying") - # If cleaned up json is unparsable, use the LLM to reformat it (may throw) - result = await self._try_clean_json_with_llm(output, **kwargs) - output = clean_up_json(result.output or "") - json = try_parse_json_object(output) + # if not return correct formatted json, retry + log.warning("error parsing llm json, retrying") - return LLMOutput[CompletionOutput]( - output=output, - json=json, - history=history, - ) + # If cleaned up json is unparsable, use the LLM to reformat it (may throw) + result = await self._try_clean_json_with_llm(output, **kwargs) + output, json_output = try_parse_json_object(result.output or "") + + return LLMOutput[CompletionOutput]( + output=output, + json=json_output, + history=history, + ) async def _try_clean_json_with_llm( self, output: str, **kwargs: Unpack[LLMInput] diff --git a/graphrag/llm/openai/openai_history_tracking_llm.py b/graphrag/llm/openai/openai_history_tracking_llm.py index 77a8ac065..ab903c2d2 100644 --- a/graphrag/llm/openai/openai_history_tracking_llm.py +++ b/graphrag/llm/openai/openai_history_tracking_llm.py @@ -37,6 +37,6 @@ async def __call__( history=[ *history, {"role": "user", "content": input}, - {"role": "system", "content": output.output}, + {"role": "assistant", "content": output.output}, ], ) diff --git a/graphrag/llm/openai/utils.py b/graphrag/llm/openai/utils.py index d529a8c06..5d683951b 100644 --- a/graphrag/llm/openai/utils.py +++ b/graphrag/llm/openai/utils.py @@ -5,10 +5,12 @@ import json import logging +import re from collections.abc import Callable from typing import Any import tiktoken +from json_repair import repair_json from openai import ( APIConnectionError, InternalServerError, @@ -87,17 +89,62 @@ def get_completion_llm_args( } -def try_parse_json_object(input: str) -> dict: - """Generate JSON-string output using best-attempt prompting & parsing techniques.""" +def try_parse_json_object(input: str) -> tuple[str, dict]: + """JSON cleaning and formatting utilities.""" + # Sometimes, the LLM returns a json string with some extra description, this function will clean it up. + + result = None + try: + # Try parse first + result = json.loads(input) + except json.JSONDecodeError: + log.info("Warning: Error decoding faulty json, attempting repair") + + if result: + return input, result + + _pattern = r"\{(.*)\}" + _match = re.search(_pattern, input) + input = "{" + _match.group(1) + "}" if _match else input + + # Clean up json string. + input = ( + input.replace("{{", "{") + .replace("}}", "}") + .replace('"[{', "[{") + .replace('}]"', "}]") + .replace("\\", " ") + .replace("\\n", " ") + .replace("\n", " ") + .replace("\r", "") + .strip() + ) + + # Remove JSON Markdown Frame + if input.startswith("```json"): + input = input[len("```json") :] + if input.endswith("```"): + input = input[: len(input) - len("```")] + try: result = json.loads(input) except json.JSONDecodeError: - log.exception("error loading json, json=%s", input) - raise + # Fixup potentially malformed json string using json_repair. + input = str(repair_json(json_str=input, return_objects=False)) + + # Generate JSON-string output using best-attempt prompting & parsing techniques. + try: + result = json.loads(input) + except json.JSONDecodeError: + log.exception("error loading json, json=%s", input) + return input, {} + else: + if not isinstance(result, dict): + log.exception("not expected dict type. type=%s:", type(result)) + return input, {} + return input, result else: - if not isinstance(result, dict): - raise TypeError - return result + return input, result def get_sleep_time_from_error(e: Any) -> float: diff --git a/graphrag/prompt_tune/prompt/entity_relationship.py b/graphrag/prompt_tune/prompt/entity_relationship.py index af31d0900..3af77db64 100644 --- a/graphrag/prompt_tune/prompt/entity_relationship.py +++ b/graphrag/prompt_tune/prompt/entity_relationship.py @@ -12,8 +12,7 @@ - entity_name: Name of the entity, capitalized - entity_type: One of the following types: [{entity_types}] - entity_description: Comprehensive description of the entity's attributes and activities -Format each entity, include the parenthesis at the beginning and end, as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) -for example: ("entity"{{tuple_delimiter}}"Microsoft"{{tuple_delimiter}}"organization"{{tuple_delimiter}}"Microsoft is a technology company") +Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) 2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other. For each pair of related entities, extract the following information: @@ -21,12 +20,104 @@ - target_entity: name of the target entity, as identified in step 1 - relationship_description: explanation as to why you think the source entity and the target entity are related to each other - relationship_strength: an integer score between 1 to 10, indicating strength of the relationship between the source entity and target entity -Format each relationship, include the parenthesis at the beginning and end, as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) -for example: ("relationship"{{tuple_delimiter}}"company A"{{tuple_delimiter}}"person A"{{tuple_delimiter}}"company A is currently owned by person A"{{tuple_delimiter}}8) +Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) -3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. If you have to translate, just translate the descriptions, nothing else! +3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. -4. When finished, output {{completion_delimiter}}. +4. If you have to translate into {language}, just translate the descriptions, nothing else! + +5. When finished, output {{completion_delimiter}}. + +###################### +-Examples- +###################### +Example 1: +Entity_types: ORGANIZATION,PERSON +Text: +The Verdantis's Central Institution is scheduled to meet on Monday and Thursday, with the institution planning to release its latest policy decision on Thursday at 1:30 p.m. PDT, followed by a press conference where Central Institution Chair Martin Smith will take questions. Investors expect the Market Strategy Committee to hold its benchmark interest rate steady in a range of 3.5%-3.75%. +###################### +Output: +("entity"{{tuple_delimiter}}CENTRAL INSTITUTION{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Central Institution is the Federal Reserve of Verdantis, which is setting interest rates on Monday and Thursday) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MARTIN SMITH{{tuple_delimiter}}PERSON{{tuple_delimiter}}Martin Smith is the chair of the Central Institution) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MARKET STRATEGY COMMITTEE{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Central Institution committee makes key decisions about interest rates and the growth of Verdantis's money supply) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}MARTIN SMITH{{tuple_delimiter}}CENTRAL INSTITUTION{{tuple_delimiter}}Martin Smith is the Chair of the Central Institution and will answer questions at a press conference{{tuple_delimiter}}9) +{{completion_delimiter}} + +###################### +Example 2: +Entity_types: ORGANIZATION +Text: +TechGlobal's (TG) stock skyrocketed in its opening day on the Global Exchange Thursday. But IPO experts warn that the semiconductor corporation's debut on the public markets isn't indicative of how other newly listed companies may perform. + +TechGlobal, a formerly public company, was taken private by Vision Holdings in 2014. The well-established chip designer says it powers 85% of premium smartphones. +###################### +Output: +("entity"{{tuple_delimiter}}TECHGLOBAL{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}TechGlobal is a stock now listed on the Global Exchange which powers 85% of premium smartphones) +{{record_delimiter}} +("entity"{{tuple_delimiter}}VISION HOLDINGS{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}Vision Holdings is a firm that previously owned TechGlobal) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}TECHGLOBAL{{tuple_delimiter}}VISION HOLDINGS{{tuple_delimiter}}Vision Holdings formerly owned TechGlobal from 2014 until present{{tuple_delimiter}}5) +{{completion_delimiter}} + +###################### +Example 3: +Entity_types: ORGANIZATION,GEO,PERSON +Text: +Five Aurelians jailed for 8 years in Firuzabad and widely regarded as hostages are on their way home to Aurelia. + +The swap orchestrated by Quintara was finalized when $8bn of Firuzi funds were transferred to financial institutions in Krohaara, the capital of Quintara. + +The exchange initiated in Firuzabad's capital, Tiruzia, led to the four men and one woman, who are also Firuzi nationals, boarding a chartered flight to Krohaara. + +They were welcomed by senior Aurelian officials and are now on their way to Aurelia's capital, Cashion. + +The Aurelians include 39-year-old businessman Samuel Namara, who has been held in Tiruzia's Alhamia Prison, as well as journalist Durke Bataglani, 59, and environmentalist Meggie Tazbah, 53, who also holds Bratinas nationality. +###################### +Output: +("entity"{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}GEO{{tuple_delimiter}}Firuzabad held Aurelians as hostages) +{{record_delimiter}} +("entity"{{tuple_delimiter}}AURELIA{{tuple_delimiter}}GEO{{tuple_delimiter}}Country seeking to release hostages) +{{record_delimiter}} +("entity"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}GEO{{tuple_delimiter}}Country that negotiated a swap of money in exchange for hostages) +{{record_delimiter}} +{{record_delimiter}} +("entity"{{tuple_delimiter}}TIRUZIA{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital of Firuzabad where the Aurelians were being held) +{{record_delimiter}} +("entity"{{tuple_delimiter}}KROHAARA{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital city in Quintara) +{{record_delimiter}} +("entity"{{tuple_delimiter}}CASHION{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital city in Aurelia) +{{record_delimiter}} +("entity"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}PERSON{{tuple_delimiter}}Aurelian who spent time in Tiruzia's Alhamia Prison) +{{record_delimiter}} +("entity"{{tuple_delimiter}}ALHAMIA PRISON{{tuple_delimiter}}GEO{{tuple_delimiter}}Prison in Tiruzia) +{{record_delimiter}} +("entity"{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}PERSON{{tuple_delimiter}}Aurelian journalist who was held hostage) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}PERSON{{tuple_delimiter}}Bratinas national and environmentalist who was held hostage) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}AURELIA{{tuple_delimiter}}Firuzabad negotiated a hostage exchange with Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}AURELIA{{tuple_delimiter}}Quintara brokered the hostage exchange between Firuzabad and Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Quintara brokered the hostage exchange between Firuzabad and Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}ALHAMIA PRISON{{tuple_delimiter}}Samuel Namara was a prisoner at Alhamia prison{{tuple_delimiter}}8) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}Samuel Namara and Meggie Tazbah were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}Samuel Namara and Durke Bataglani were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}Meggie Tazbah and Durke Bataglani were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Samuel Namara was a hostage in Firuzabad{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Meggie Tazbah was a hostage in Firuzabad{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Durke Bataglani was a hostage in Firuzabad{{tuple_delimiter}}2) +{{completion_delimiter}} -Real Data- ###################### @@ -61,7 +152,77 @@ {{"source": , "target": , "relationship": , "relationship_strength": }} -3. Return output in {language} as a single list of all JSON entities and relationships identified in steps 1 and 2. If you have to translate, just translate the descriptions, nothing else! +3. Return output in {language} as a single list of all JSON entities and relationships identified in steps 1 and 2. + +4. If you have to translate into {language}, just translate the descriptions, nothing else! + +###################### +-Examples- +###################### +Example 1: +Text: +The Verdantis's Central Institution is scheduled to meet on Monday and Thursday, with the institution planning to release its latest policy decision on Thursday at 1:30 p.m. PDT, followed by a press conference where Central Institution Chair Martin Smith will take questions. Investors expect the Market Strategy Committee to hold its benchmark interest rate steady in a range of 3.5%-3.75%. +###################### +Output: +[ + {{"name": "CENTRAL INSTITUTION", "type": "ORGANIZATION", "description": "The Central Institution is the Federal Reserve of Verdantis, which is setting interest rates on Monday and Thursday"}}, + {{"name": "MARTIN SMITH", "type": "PERSON", "description": "Martin Smith is the chair of the Central Institution"}}, + {{"name": "MARKET STRATEGY COMMITTEE", "type": "ORGANIZATION", "description": "The Central Institution committee makes key decisions about interest rates and the growth of Verdantis's money supply"}}, + {{"source": "MARTIN SMITH", "target": "CENTRAL INSTITUTION", "relationship": "Martin Smith is the Chair of the Central Institution and will answer questions at a press conference", "relationship_strength": 9}} +] + +###################### +Example 2: +Text: +TechGlobal's (TG) stock skyrocketed in its opening day on the Global Exchange Thursday. But IPO experts warn that the semiconductor corporation's debut on the public markets isn't indicative of how other newly listed companies may perform. + +TechGlobal, a formerly public company, was taken private by Vision Holdings in 2014. The well-established chip designer says it powers 85% of premium smartphones. +###################### +Output: +[ + {{"name": "TECHGLOBAL", "type": "ORGANIZATION", "description": "TechGlobal is a stock now listed on the Global Exchange which powers 85% of premium smartphones"}}, + {{"name": "VISION HOLDINGS", "type": "ORGANIZATION", "description": "Vision Holdings is a firm that previously owned TechGlobal"}}, + {{"source": "TECHGLOBAL", "target": "VISION HOLDINGS", "relationship": "Vision Holdings formerly owned TechGlobal from 2014 until present", "relationship_strength": 5}} +] + +###################### +Example 3: +Text: +Five Aurelians jailed for 8 years in Firuzabad and widely regarded as hostages are on their way home to Aurelia. + +The swap orchestrated by Quintara was finalized when $8bn of Firuzi funds were transferred to financial institutions in Krohaara, the capital of Quintara. + +The exchange initiated in Firuzabad's capital, Tiruzia, led to the four men and one woman, who are also Firuzi nationals, boarding a chartered flight to Krohaara. + +They were welcomed by senior Aurelian officials and are now on their way to Aurelia's capital, Cashion. + +The Aurelians include 39-year-old businessman Samuel Namara, who has been held in Tiruzia's Alhamia Prison, as well as journalist Durke Bataglani, 59, and environmentalist Meggie Tazbah, 53, who also holds Bratinas nationality. +###################### +Output: +[ + {{"name": "FIRUZABAD", "type": "GEO", "description": "Firuzabad held Aurelians as hostages"}}, + {{"name": "AURELIA", "type": "GEO", "description": "Country seeking to release hostages"}}, + {{"name": "QUINTARA", "type": "GEO", "description": "Country that negotiated a swap of money in exchange for hostages"}}, + {{"name": "TIRUZIA", "type": "GEO", "description": "Capital of Firuzabad where the Aurelians were being held"}}, + {{"name": "KROHAARA", "type": "GEO", "description": "Capital city in Quintara"}}, + {{"name": "CASHION", "type": "GEO", "description": "Capital city in Aurelia"}}, + {{"name": "SAMUEL NAMARA", "type": "PERSON", "description": "Aurelian who spent time in Tiruzia's Alhamia Prison"}}, + {{"name": "ALHAMIA PRISON", "type": "GEO", "description": "Prison in Tiruzia"}}, + {{"name": "DURKE BATAGLANI", "type": "PERSON", "description": "Aurelian journalist who was held hostage"}}, + {{"name": "MEGGIE TAZBAH", "type": "PERSON", "description": "Bratinas national and environmentalist who was held hostage"}}, + {{"source": "FIRUZABAD", "target": "AURELIA", "relationship": "Firuzabad negotiated a hostage exchange with Aurelia", "relationship_strength": 2}}, + {{"source": "QUINTARA", "target": "AURELIA", "relationship": "Quintara brokered the hostage exchange between Firuzabad and Aurelia", "relationship_strength": 2}}, + {{"source": "QUINTARA", "target": "FIRUZABAD", "relationship": "Quintara brokered the hostage exchange between Firuzabad and Aurelia", "relationship_strength": 2}}, + {{"source": "SAMUEL NAMARA", "target": "ALHAMIA PRISON", "relationship": "Samuel Namara was a prisoner at Alhamia prison", "relationship_strength": 8}}, + {{"source": "SAMUEL NAMARA", "target": "MEGGIE TAZBAH", "relationship": "Samuel Namara and Meggie Tazbah were exchanged in the same hostage release", "relationship_strength": 2}}, + {{"source": "SAMUEL NAMARA", "target": "DURKE BATAGLANI", "relationship": "Samuel Namara and Durke Bataglani were exchanged in the same hostage release", "relationship_strength": 2}}, + {{"source": "MEGGIE TAZBAH", "target": "DURKE BATAGLANI", "relationship": "Meggie Tazbah and Durke Bataglani were exchanged in the same hostage release", "relationship_strength": 2}}, + {{"source": "SAMUEL NAMARA", "target": "FIRUZABAD", "relationship": "Samuel Namara was a hostage in Firuzabad", "relationship_strength": 2}}, + {{"source": "MEGGIE TAZBAH", "target": "FIRUZABAD", "relationship": "Meggie Tazbah was a hostage in Firuzabad", "relationship_strength": 2}}, + {{"source": "DURKE BATAGLANI", "target": "FIRUZABAD", "relationship": "Durke Bataglani was a hostage in Firuzabad", "relationship_strength": 2}} +] + + -Real Data- ###################### @@ -81,7 +242,7 @@ - entity_name: Name of the entity, capitalized - entity_type: Suggest several labels or categories for the entity. The categories should not be specific, but should be as general as possible. - entity_description: Comprehensive description of the entity's attributes and activities -Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}} +Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) 2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other. For each pair of related entities, extract the following information: @@ -89,40 +250,102 @@ - target_entity: name of the target entity, as identified in step 1 - relationship_description: explanation as to why you think the source entity and the target entity are related to each other - relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity - Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) +Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) -3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. If you have to translate, just translate the descriptions, nothing else! +3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. -4. When finished, output {{completion_delimiter}} +4. If you have to translate into {language}, just translate the descriptions, nothing else! + +5. When finished, output {{completion_delimiter}}. ###################### -Examples- ###################### +Example 1: Text: -The Fed is scheduled to meet on Tuesday and Wednesday, with the central bank planning to release its latest policy decision on Wednesday at 2:00 p.m. ET, followed by a press conference where Fed Chair Jerome Powell will take questions. Investors expect the Federal Open Market Committee to hold its benchmark interest rate steady in a range of 5.25%-5.5%. +The Verdantis's Central Institution is scheduled to meet on Monday and Thursday, with the institution planning to release its latest policy decision on Thursday at 1:30 p.m. PDT, followed by a press conference where Central Institution Chair Martin Smith will take questions. Investors expect the Market Strategy Committee to hold its benchmark interest rate steady in a range of 3.5%-3.75%. ###################### Output: -("entity"{{tuple_delimiter}}FED{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Fed is the Federal Reserve, which is setting interest rates on Tuesday and Wednesday) +("entity"{{tuple_delimiter}}CENTRAL INSTITUTION{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Central Institution is the Federal Reserve of Verdantis, which is setting interest rates on Monday and Thursday) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MARTIN SMITH{{tuple_delimiter}}PERSON{{tuple_delimiter}}Martin Smith is the chair of the Central Institution) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MARKET STRATEGY COMMITTEE{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Central Institution committee makes key decisions about interest rates and the growth of Verdantis's money supply) {{record_delimiter}} -("entity"{{tuple_delimiter}}JEROME POWELL{{tuple_delimiter}}PERSON{{tuple_delimiter}}Jerome Powell is the chair of the Federal Reserve) +("relationship"{{tuple_delimiter}}MARTIN SMITH{{tuple_delimiter}}CENTRAL INSTITUTION{{tuple_delimiter}}Martin Smith is the Chair of the Central Institution and will answer questions at a press conference{{tuple_delimiter}}9) +{{completion_delimiter}} + +###################### +Example 2: +Text: +TechGlobal's (TG) stock skyrocketed in its opening day on the Global Exchange Thursday. But IPO experts warn that the semiconductor corporation's debut on the public markets isn't indicative of how other newly listed companies may perform. + +TechGlobal, a formerly public company, was taken private by Vision Holdings in 2014. The well-established chip designer says it powers 85% of premium smartphones. +###################### +Output: +("entity"{{tuple_delimiter}}TECHGLOBAL{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}TechGlobal is a stock now listed on the Global Exchange which powers 85% of premium smartphones) {{record_delimiter}} -("entity"{{tuple_delimiter}}FEDERAL OPEN MARKET COMMITTEE{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}The Federal Reserve committee makes key decisions about interest rates and the growth of the United States money supply) +("entity"{{tuple_delimiter}}VISION HOLDINGS{{tuple_delimiter}}ORGANIZATION{{tuple_delimiter}}Vision Holdings is a firm that previously owned TechGlobal) {{record_delimiter}} -("relationship"{{tuple_delimiter}}JEROME POWELL{{tuple_delimiter}}FED{{tuple_delimiter}}Jerome Powell is the Chair of the Federal Reserve and will answer questions at a press conference{{tuple_delimiter}}9) +("relationship"{{tuple_delimiter}}TECHGLOBAL{{tuple_delimiter}}VISION HOLDINGS{{tuple_delimiter}}Vision Holdings formerly owned TechGlobal from 2014 until present{{tuple_delimiter}}5) {{completion_delimiter}} + ###################### +Example 3: Text: -Arm's (ARM) stock skyrocketed in its opening day on the Nasdaq Thursday. But IPO experts warn that the British chipmaker's debut on the public markets isn't indicative of how other newly listed companies may perform. +Five Aurelians jailed for 8 years in Firuzabad and widely regarded as hostages are on their way home to Aurelia. + +The swap orchestrated by Quintara was finalized when $8bn of Firuzi funds were transferred to financial institutions in Krohaara, the capital of Quintara. + +The exchange initiated in Firuzabad's capital, Tiruzia, led to the four men and one woman, who are also Firuzi nationals, boarding a chartered flight to Krohaara. -Arm, a formerly public company, was taken private by SoftBank in 2016. The well-established chip designer says it powers 99% of premium smartphones. +They were welcomed by senior Aurelian officials and are now on their way to Aurelia's capital, Cashion. + +The Aurelians include 39-year-old businessman Samuel Namara, who has been held in Tiruzia's Alhamia Prison, as well as journalist Durke Bataglani, 59, and environmentalist Meggie Tazbah, 53, who also holds Bratinas nationality. ###################### Output: -("entity"{{tuple_delimiter}}ARM{{tuple_delimiter}}ORGANIZATION, COMPANY{{tuple_delimiter}}Arm is a stock now listed on the Nasdaq which powers 99% of premium smartphones) +("entity"{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}GEO{{tuple_delimiter}}Firuzabad held Aurelians as hostages) +{{record_delimiter}} +("entity"{{tuple_delimiter}}AURELIA{{tuple_delimiter}}GEO{{tuple_delimiter}}Country seeking to release hostages) +{{record_delimiter}} +("entity"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}GEO{{tuple_delimiter}}Country that negotiated a swap of money in exchange for hostages) +{{record_delimiter}} +{{record_delimiter}} +("entity"{{tuple_delimiter}}TIRUZIA{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital of Firuzabad where the Aurelians were being held) +{{record_delimiter}} +("entity"{{tuple_delimiter}}KROHAARA{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital city in Quintara) +{{record_delimiter}} +("entity"{{tuple_delimiter}}CASHION{{tuple_delimiter}}GEO{{tuple_delimiter}}Capital city in Aurelia) {{record_delimiter}} -("entity"{{tuple_delimiter}}SOFTBANK{{tuple_delimiter}}ORGANIZATION, COMPANY{{tuple_delimiter}}SoftBank is a firm that previously owned Arm) +("entity"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}PERSON{{tuple_delimiter}}Aurelian who spent time in Tiruzia's Alhamia Prison) {{record_delimiter}} -("relationship"{{tuple_delimiter}}ARM{{tuple_delimiter}}SOFTBANK{{tuple_delimiter}}SoftBank formerly owned Arm from 2016 until present{{tuple_delimiter}}5) +("entity"{{tuple_delimiter}}ALHAMIA PRISON{{tuple_delimiter}}GEO{{tuple_delimiter}}Prison in Tiruzia) +{{record_delimiter}} +("entity"{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}PERSON{{tuple_delimiter}}Aurelian journalist who was held hostage) +{{record_delimiter}} +("entity"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}PERSON{{tuple_delimiter}}Bratinas national and environmentalist who was held hostage) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}AURELIA{{tuple_delimiter}}Firuzabad negotiated a hostage exchange with Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}AURELIA{{tuple_delimiter}}Quintara brokered the hostage exchange between Firuzabad and Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}QUINTARA{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Quintara brokered the hostage exchange between Firuzabad and Aurelia{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}ALHAMIA PRISON{{tuple_delimiter}}Samuel Namara was a prisoner at Alhamia prison{{tuple_delimiter}}8) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}Samuel Namara and Meggie Tazbah were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}Samuel Namara and Durke Bataglani were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}Meggie Tazbah and Durke Bataglani were exchanged in the same hostage release{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}SAMUEL NAMARA{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Samuel Namara was a hostage in Firuzabad{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}MEGGIE TAZBAH{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Meggie Tazbah was a hostage in Firuzabad{{tuple_delimiter}}2) +{{record_delimiter}} +("relationship"{{tuple_delimiter}}DURKE BATAGLANI{{tuple_delimiter}}FIRUZABAD{{tuple_delimiter}}Durke Bataglani was a hostage in Firuzabad{{tuple_delimiter}}2) {{completion_delimiter}} + ###################### -Real Data- ###################### diff --git a/graphrag/prompt_tune/template/entity_extraction.py b/graphrag/prompt_tune/template/entity_extraction.py index 65c0cfb58..32d8756ec 100644 --- a/graphrag/prompt_tune/template/entity_extraction.py +++ b/graphrag/prompt_tune/template/entity_extraction.py @@ -12,7 +12,7 @@ - entity_name: Name of the entity, capitalized - entity_type: One of the following types: [{entity_types}] - entity_description: Comprehensive description of the entity's attributes and activities -Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}} +Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) 2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other. For each pair of related entities, extract the following information: @@ -20,12 +20,13 @@ - target_entity: name of the target entity, as identified in step 1 - relationship_description: explanation as to why you think the source entity and the target entity are related to each other - relationship_strength: an integer score between 1 to 10, indicating strength of the relationship between the source entity and target entity - Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) -3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. If you have to translate, just translate the descriptions, nothing else! +3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. + +4. If you have to translate into {language}, just translate the descriptions, nothing else! -4. When finished, output {{completion_delimiter}} +5. When finished, output {{completion_delimiter}}. -Examples- ###################### @@ -61,7 +62,9 @@ {{"source": , "target": , "relationship": , "relationship_strength": }} -3. Return output in {language} as a single list of all JSON entities and relationships identified in steps 1 and 2. If you have to translate, just translate the descriptions, nothing else! +3. Return output in {language} as a single list of all JSON entities and relationships identified in steps 1 and 2. + +4. If you have to translate into {language}, just translate the descriptions, nothing else! -Examples- ###################### @@ -110,7 +113,7 @@ - entity_name: Name of the entity, capitalized - entity_type: Suggest several labels or categories for the entity. The categories should not be specific, but should be as general as possible. - entity_description: Comprehensive description of the entity's attributes and activities -Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}} +Format each entity as ("entity"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) 2. From the entities identified in step 1, identify all pairs of (source_entity, target_entity) that are *clearly related* to each other. For each pair of related entities, extract the following information: @@ -118,11 +121,13 @@ - target_entity: name of the target entity, as identified in step 1 - relationship_description: explanation as to why you think the source entity and the target entity are related to each other - relationship_strength: a numeric score indicating strength of the relationship between the source entity and target entity - Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) +Format each relationship as ("relationship"{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}{{tuple_delimiter}}) + +3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. -3. Return output in {language} as a single list of all the entities and relationships identified in steps 1 and 2. Use **{{record_delimiter}}** as the list delimiter. If you have to translate, just translate the descriptions, nothing else! +4. If you have to translate into {language}, just translate the descriptions, nothing else! -4. When finished, output {{completion_delimiter}} +5. When finished, output {{completion_delimiter}}. -Examples- ###################### diff --git a/graphrag/query/__main__.py b/graphrag/query/__main__.py index 9367f9a9c..edf678fa4 100644 --- a/graphrag/query/__main__.py +++ b/graphrag/query/__main__.py @@ -25,6 +25,13 @@ def __str__(self): if __name__ == "__main__": parser = argparse.ArgumentParser() + parser.add_argument( + "--config", + help="The configuration yaml file to use when running the query", + required=False, + type=str, + ) + parser.add_argument( "--data", help="The path with the output data from the pipeline", @@ -74,6 +81,7 @@ def __str__(self): match args.method: case SearchType.LOCAL: run_local_search( + args.config, args.data, args.root, args.community_level, @@ -82,6 +90,7 @@ def __str__(self): ) case SearchType.GLOBAL: run_global_search( + args.config, args.data, args.root, args.community_level, diff --git a/graphrag/query/cli.py b/graphrag/query/cli.py index 10ad95d5b..81efbb550 100644 --- a/graphrag/query/cli.py +++ b/graphrag/query/cli.py @@ -14,10 +14,12 @@ create_graphrag_config, ) from graphrag.index.progress import PrintProgressReporter +from graphrag.model.entity import Entity from graphrag.query.input.loaders.dfs import ( store_entity_semantic_embeddings, ) from graphrag.vector_stores import VectorStoreFactory, VectorStoreType +from graphrag.vector_stores.lancedb import LanceDBVectorStore from .factories import get_global_search_engine, get_local_search_engine from .indexer_adapters import ( @@ -32,28 +34,54 @@ def __get_embedding_description_store( - vector_store_type: str = VectorStoreType.LanceDB, config_args: dict | None = None + entities: list[Entity], + vector_store_type: str = VectorStoreType.LanceDB, + config_args: dict | None = None, ): """Get the embedding description store.""" if not config_args: config_args = {} - config_args.update({ - "collection_name": config_args.get( - "query_collection_name", - config_args.get("collection_name", "description_embedding"), - ), - }) - + collection_name = config_args.get( + "query_collection_name", "entity_description_embeddings" + ) + config_args.update({"collection_name": collection_name}) description_embedding_store = VectorStoreFactory.get_vector_store( vector_store_type=vector_store_type, kwargs=config_args ) description_embedding_store.connect(**config_args) + + if config_args.get("overwrite", True): + # this step assumps the embeddings where originally stored in a file rather + # than a vector database + + # dump embeddings from the entities list to the description_embedding_store + store_entity_semantic_embeddings( + entities=entities, vectorstore=description_embedding_store + ) + else: + # load description embeddings to an in-memory lancedb vectorstore + # to connect to a remote db, specify url and port values. + description_embedding_store = LanceDBVectorStore( + collection_name=collection_name + ) + description_embedding_store.connect( + db_uri=config_args.get("db_uri", "./lancedb") + ) + + # load data from an existing table + description_embedding_store.document_collection = ( + description_embedding_store.db_connection.open_table( + description_embedding_store.collection_name + ) + ) + return description_embedding_store def run_global_search( + config_dir: str | None, data_dir: str | None, root_dir: str | None, community_level: int, @@ -61,7 +89,9 @@ def run_global_search( query: str, ): """Run a global search with the given query.""" - data_dir, root_dir, config = _configure_paths_and_settings(data_dir, root_dir) + data_dir, root_dir, config = _configure_paths_and_settings( + data_dir, root_dir, config_dir + ) data_path = Path(data_dir) final_nodes: pd.DataFrame = pd.read_parquet( @@ -92,6 +122,7 @@ def run_global_search( def run_local_search( + config_dir: str | None, data_dir: str | None, root_dir: str | None, community_level: int, @@ -99,7 +130,9 @@ def run_local_search( query: str, ): """Run a local search with the given query.""" - data_dir, root_dir, config = _configure_paths_and_settings(data_dir, root_dir) + data_dir, root_dir, config = _configure_paths_and_settings( + data_dir, root_dir, config_dir + ) data_path = Path(data_dir) final_nodes = pd.read_parquet(data_path / "create_final_nodes.parquet") @@ -121,16 +154,16 @@ def run_local_search( vector_store_args = ( config.embeddings.vector_store if config.embeddings.vector_store else {} ) + + reporter.info(f"Vector Store Args: {vector_store_args}") vector_store_type = vector_store_args.get("type", VectorStoreType.LanceDB) + entities = read_indexer_entities(final_nodes, final_entities, community_level) description_embedding_store = __get_embedding_description_store( + entities=entities, vector_store_type=vector_store_type, config_args=vector_store_args, ) - entities = read_indexer_entities(final_nodes, final_entities, community_level) - store_entity_semantic_embeddings( - entities=entities, vectorstore=description_embedding_store - ) covariates = ( read_indexer_covariates(final_covariates) if final_covariates is not None @@ -156,14 +189,16 @@ def run_local_search( def _configure_paths_and_settings( - data_dir: str | None, root_dir: str | None + data_dir: str | None, + root_dir: str | None, + config_dir: str | None, ) -> tuple[str, str | None, GraphRagConfig]: if data_dir is None and root_dir is None: msg = "Either data_dir or root_dir must be provided." raise ValueError(msg) if data_dir is None: data_dir = _infer_data_dir(cast(str, root_dir)) - config = _create_graphrag_config(root_dir, data_dir) + config = _create_graphrag_config(root_dir, config_dir) return data_dir, root_dir, config @@ -179,17 +214,23 @@ def _infer_data_dir(root: str) -> str: raise ValueError(msg) -def _create_graphrag_config(root: str | None, data_dir: str | None) -> GraphRagConfig: +def _create_graphrag_config( + root: str | None, + config_dir: str | None, +) -> GraphRagConfig: """Create a GraphRag configuration.""" - return _read_config_parameters(cast(str, root or data_dir)) + return _read_config_parameters(root or "./", config_dir) -def _read_config_parameters(root: str): +def _read_config_parameters(root: str, config: str | None): _root = Path(root) - settings_yaml = _root / "settings.yaml" + settings_yaml = ( + Path(config) + if config and Path(config).suffix in [".yaml", ".yml"] + else _root / "settings.yaml" + ) if not settings_yaml.exists(): settings_yaml = _root / "settings.yml" - settings_json = _root / "settings.json" if settings_yaml.exists(): reporter.info(f"Reading settings from {settings_yaml}") @@ -201,6 +242,11 @@ def _read_config_parameters(root: str): data = yaml.safe_load(file.read().decode(encoding="utf-8", errors="strict")) return create_graphrag_config(data, root) + settings_json = ( + Path(config) + if config and Path(config).suffix == ".json" + else _root / "settings.json" + ) if settings_json.exists(): reporter.info(f"Reading settings from {settings_json}") with settings_json.open("rb") as file: diff --git a/graphrag/query/context_builder/community_context.py b/graphrag/query/context_builder/community_context.py index dba7f729d..5039376fb 100644 --- a/graphrag/query/context_builder/community_context.py +++ b/graphrag/query/context_builder/community_context.py @@ -41,7 +41,39 @@ def build_community_context( The calculated weight is added as an attribute to the community reports and added to the context data table. """ - if ( + + def _is_included(report: CommunityReport) -> bool: + return report.rank is not None and report.rank >= min_community_rank + + def _get_header(attributes: list[str]) -> list[str]: + header = ["id", "title"] + attributes = [col for col in attributes if col not in header] + if not include_community_weight: + attributes = [col for col in attributes if col != community_weight_name] + header.extend(attributes) + header.append("summary" if use_community_summary else "content") + if include_community_rank: + header.append(community_rank_name) + return header + + def _report_context_text( + report: CommunityReport, attributes: list[str] + ) -> tuple[str, list[str]]: + context: list[str] = [ + report.short_id if report.short_id else "", + report.title, + *[ + str(report.attributes.get(field, "")) if report.attributes else "" + for field in attributes + ], + ] + context.append(report.summary if use_community_summary else report.full_content) + if include_community_rank: + context.append(str(report.rank)) + result = column_delimiter.join(context) + "\n" + return result, context + + compute_community_weights = ( entities and len(community_reports) > 0 and include_community_weight @@ -49,7 +81,8 @@ def build_community_context( community_reports[0].attributes is None or community_weight_name not in community_reports[0].attributes ) - ): + ) + if compute_community_weights: log.info("Computing community weights...") community_reports = _compute_community_weights( community_reports=community_reports, @@ -58,11 +91,7 @@ def build_community_context( normalize=normalize_community_weight, ) - selected_reports = [ - report - for report in community_reports - if report.rank and report.rank >= min_community_rank - ] + selected_reports = [report for report in community_reports if _is_included(report)] if selected_reports is None or len(selected_reports) == 0: return ([], {}) @@ -70,99 +99,67 @@ def build_community_context( random.seed(random_state) random.shuffle(selected_reports) - # add context header - current_context_text = f"-----{context_name}-----" + "\n" - - # add header - header = ["id", "title"] - attribute_cols = ( - list(selected_reports[0].attributes.keys()) - if selected_reports[0].attributes + # "global" variables + attributes = ( + list(community_reports[0].attributes.keys()) + if community_reports[0].attributes else [] ) - attribute_cols = [col for col in attribute_cols if col not in header] - if not include_community_weight: - attribute_cols = [col for col in attribute_cols if col != community_weight_name] - header.extend(attribute_cols) - header.append("summary" if use_community_summary else "content") - if include_community_rank: - header.append(community_rank_name) - - current_context_text += column_delimiter.join(header) + "\n" - current_tokens = num_tokens(current_context_text, token_encoder) - current_context_records = [header] - all_context_text = [] - all_context_records = [] - - for report in selected_reports: - new_context = [ - report.short_id, - report.title, - *[ - str(report.attributes.get(field, "")) if report.attributes else "" - for field in attribute_cols - ], - ] - new_context.append( - report.summary if use_community_summary else report.full_content + header = _get_header(attributes) + all_context_text: list[str] = [] + all_context_records: list[pd.DataFrame] = [] + + # batch variables + batch_text: str = "" + batch_tokens: int = 0 + batch_records: list[list[str]] = [] + + def _init_batch() -> None: + nonlocal batch_text, batch_tokens, batch_records + batch_text = ( + f"-----{context_name}-----" + "\n" + column_delimiter.join(header) + "\n" ) - if include_community_rank: - new_context.append(str(report.rank)) - new_context_text = column_delimiter.join(new_context) + "\n" + batch_tokens = num_tokens(batch_text, token_encoder) + batch_records = [] + + def _cut_batch() -> None: + # convert the current context records to pandas dataframe and sort by weight and rank if exist + record_df = _convert_report_context_to_df( + context_records=batch_records, + header=header, + weight_column=community_weight_name + if entities and include_community_weight + else None, + rank_column=community_rank_name if include_community_rank else None, + ) + if len(record_df) == 0: + return + current_context_text = record_df.to_csv(index=False, sep=column_delimiter) + all_context_text.append(current_context_text) + all_context_records.append(record_df) - new_tokens = num_tokens(new_context_text, token_encoder) - if current_tokens + new_tokens > max_tokens: - # convert the current context records to pandas dataframe and sort by weight and rank if exist - if len(current_context_records) > 1: - record_df = _convert_report_context_to_df( - context_records=current_context_records[1:], - header=current_context_records[0], - weight_column=community_weight_name - if entities and include_community_weight - else None, - rank_column=community_rank_name if include_community_rank else None, - ) + # initialize the first batch + _init_batch() - else: - record_df = pd.DataFrame() - current_context_text = record_df.to_csv(index=False, sep=column_delimiter) + for report in selected_reports: + new_context_text, new_context = _report_context_text(report, attributes) + new_tokens = num_tokens(new_context_text, token_encoder) + if batch_tokens + new_tokens > max_tokens: + # add the current batch to the context data and start a new batch if we are in multi-batch mode + _cut_batch() if single_batch: - return current_context_text, {context_name.lower(): record_df} - - all_context_text.append(current_context_text) - all_context_records.append(record_df) - - # start a new batch - current_context_text = ( - f"-----{context_name}-----" - + "\n" - + column_delimiter.join(header) - + "\n" - ) - current_tokens = num_tokens(current_context_text, token_encoder) - current_context_records = [header] - else: - current_context_text += new_context_text - current_tokens += new_tokens - current_context_records.append(new_context) + break + _init_batch() + + # add current report to the current batch + batch_text += new_context_text + batch_tokens += new_tokens + batch_records.append(new_context) # add the last batch if it has not been added - if current_context_text not in all_context_text: - if len(current_context_records) > 1: - record_df = _convert_report_context_to_df( - context_records=current_context_records[1:], - header=current_context_records[0], - weight_column=community_weight_name - if entities and include_community_weight - else None, - rank_column=community_rank_name if include_community_rank else None, - ) - else: - record_df = pd.DataFrame() - all_context_records.append(record_df) - current_context_text = record_df.to_csv(index=False, sep=column_delimiter) - all_context_text.append(current_context_text) + if batch_text not in all_context_text: + _cut_batch() return all_context_text, { context_name.lower(): pd.concat(all_context_records, ignore_index=True) @@ -171,11 +168,14 @@ def build_community_context( def _compute_community_weights( community_reports: list[CommunityReport], - entities: list[Entity], + entities: list[Entity] | None, weight_attribute: str = "occurrence", normalize: bool = True, ) -> list[CommunityReport]: """Calculate a community's weight as count of text units associated with entities within the community.""" + if not entities: + return community_reports + community_text_units = {} for entity in entities: if entity.community_ids: @@ -211,7 +211,7 @@ def _rank_report_context( rank_column: str | None = "rank", ) -> pd.DataFrame: """Sort report context by community weight and rank if exist.""" - rank_attributes = [] + rank_attributes: list[str] = [] if weight_column: rank_attributes.append(weight_column) report_df[weight_column] = report_df[weight_column].astype(float) @@ -230,6 +230,9 @@ def _convert_report_context_to_df( rank_column: str | None = None, ) -> pd.DataFrame: """Convert report context records to pandas dataframe and sort by weight and rank if exist.""" + if len(context_records) == 0: + return pd.DataFrame() + record_df = pd.DataFrame( context_records, columns=cast(Any, header), diff --git a/graphrag/query/structured_search/global_search/search.py b/graphrag/query/structured_search/global_search/search.py index 3b52ecbd8..12dc45fe7 100644 --- a/graphrag/query/structured_search/global_search/search.py +++ b/graphrag/query/structured_search/global_search/search.py @@ -13,7 +13,7 @@ import pandas as pd import tiktoken -from graphrag.index.utils.json import clean_up_json +from graphrag.llm.openai.utils import try_parse_json_object from graphrag.query.context_builder.builders import GlobalContextBuilder from graphrag.query.context_builder.conversation_history import ( ConversationHistory, @@ -188,12 +188,13 @@ async def _map_response_single_batch( processed_response = self.parse_search_response(search_response) except ValueError: # Clean up and retry parse - search_response = clean_up_json(search_response) try: # parse search response json processed_response = self.parse_search_response(search_response) except ValueError: - log.exception("Error parsing search response json") + log.warning( + "Warning: Error parsing search response json - skipping this batch" + ) processed_response = [] return SearchResult( @@ -229,13 +230,21 @@ def parse_search_response(self, search_response: str) -> list[dict[str, Any]]: list[dict[str, Any]] A list of key points, each key point is a dictionary with "answer" and "score" keys """ - parsed_elements = json.loads(search_response)["points"] + search_response, _j = try_parse_json_object(search_response) + if _j == {}: + return [{"answer": "", "score": 0}] + + parsed_elements = json.loads(search_response).get("points") + if not parsed_elements or not isinstance(parsed_elements, list): + return [{"answer": "", "score": 0}] + return [ { "answer": element["description"], "score": int(element["score"]), } for element in parsed_elements + if "description" in element and "score" in element ] async def _reduce_response( @@ -274,6 +283,9 @@ async def _reduce_response( if len(filtered_key_points) == 0 and not self.allow_general_knowledge: # return no data answer if no key points are found + log.warning( + "Warning: All map responses have score 0 (i.e., no relevant information found from the dataset), returning a canned 'I do not know' answer. You can try enabling `allow_general_knowledge` to encourage the LLM to incorporate relevant general knowledge, at the risk of increasing hallucinations." + ) return SearchResult( response=NO_DATA_ANSWER, context_data="", diff --git a/poetry.lock b/poetry.lock index 527bb8d04..278c8ad98 100644 --- a/poetry.lock +++ b/poetry.lock @@ -190,22 +190,22 @@ typing-extensions = {version = ">=4.0.0", markers = "python_version < \"3.11\""} [[package]] name = "attrs" -version = "23.2.0" +version = "24.1.0" description = "Classes Without Boilerplate" optional = false python-versions = ">=3.7" files = [ - {file = "attrs-23.2.0-py3-none-any.whl", hash = "sha256:99b87a485a5820b23b879f04c2305b44b951b502fd64be915879d77a7e8fc6f1"}, - {file = "attrs-23.2.0.tar.gz", hash = "sha256:935dc3b529c262f6cf76e50877d35a4bd3c1de194fd41f47a2b7ae8f19971f30"}, + {file = "attrs-24.1.0-py3-none-any.whl", hash = "sha256:377b47448cb61fea38533f671fba0d0f8a96fd58facd4dc518e3dac9dbea0905"}, + {file = "attrs-24.1.0.tar.gz", 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"graphrag" # Maintainers: do not change the version here manually, use ./scripts/release.sh -version = "0.2.0" +version = "0.2.1" description = "" authors = [ "Alonso Guevara Fernández ", @@ -42,7 +42,7 @@ datashaper = "^0.0.49" # Vector Stores azure-search-documents = "^11.4.0" -lancedb = "^0.10.0" +lancedb = "^0.11.0" # Event Loops uvloop = { version = "^0.19.0", markers = "platform_system != 'Windows'" } @@ -53,7 +53,7 @@ aiolimiter = "^1.1.0" aiofiles = "^24.1.0" # LLM -openai = "^1.35.7" +openai = "^1.37.1" nltk = "3.8.1" tiktoken = "^0.7.0" @@ -77,7 +77,7 @@ tenacity = "^8.5.0" swifter = "^1.4.0" pydantic = "^2" rich = "^13.6.0" -textual = "^0.72.0" +textual = "^0.74.0" devtools = "^0.12.2" typing-extensions = "^4.12.2" @@ -85,15 +85,16 @@ typing-extensions = "^4.12.2" #Azure azure-storage-blob = "^12.19.0" azure-identity = "^1.17.1" +json-repair = "^0.25.3" [tool.poetry.group.dev.dependencies] coverage = "^7.6.0" ipykernel = "^6.29.4" jupyter = "^1.0.0" nbconvert = "^7.16.3" -poethepoet = "^0.26.0" +poethepoet = "^0.27.0" pyright = "^1.1.371" -pytest = "^8.2.0" +pytest = "^8.3.2" pytest-asyncio = "^0.23.4" pytest-timeout = "^2.3.1" ruff = "^0.5.2" @@ -217,6 +218,8 @@ select = [ # ANN # Type annotations, re-enable when we get bandwidth ] ignore = [ + # Ignore module names shadowing Python builtins + "A005", # Deprecated Rules "ANN101", "ANN102", diff --git a/tests/unit/llm/openai/test_history_tracking_llm.py b/tests/unit/llm/openai/test_history_tracking_llm.py index 654d0271a..18ae9f517 100644 --- a/tests/unit/llm/openai/test_history_tracking_llm.py +++ b/tests/unit/llm/openai/test_history_tracking_llm.py @@ -21,12 +21,12 @@ async def mock_responder(input: str, **kwargs: dict) -> LLMOutput: history: list[dict] = cast(list[dict], response.history) assert len(history) == 2 assert history[0] == {"role": "user", "content": "input 1"} - assert history[1] == {"role": "system", "content": "response to [input 1]"} + assert history[1] == {"role": "assistant", 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