Light GraphRAG (#4585)

### What problem does this PR solve?

#4543

### Type of change

- [x] New Feature (non-breaking change which adds functionality)

graphrag/general/community_reports_extractor.py

@@ -0,0 +1,141 @@
+# Copyright (c) 2024 Microsoft Corporation.
+# Licensed under the MIT License
+"""
+Reference:
+ - [graphrag](https://github.com/microsoft/graphrag)
+"""
+
+import logging
+import json
+import re
+import traceback
+from typing import Callable
+from dataclasses import dataclass
+import networkx as nx
+import pandas as pd
+from graphrag.general import leiden
+from graphrag.general.community_report_prompt import COMMUNITY_REPORT_PROMPT
+from graphrag.general.extractor import Extractor
+from graphrag.general.leiden import add_community_info2graph
+from rag.llm.chat_model import Base as CompletionLLM
+from graphrag.utils import ErrorHandlerFn, perform_variable_replacements, dict_has_keys_with_types
+from rag.utils import num_tokens_from_string
+from timeit import default_timer as timer
+
+
+@dataclass
+class CommunityReportsResult:
+    """Community reports result class definition."""
+
+    output: list[str]
+    structured_output: list[dict]
+
+
+class CommunityReportsExtractor(Extractor):
+    """Community reports extractor class definition."""
+
+    _extraction_prompt: str
+    _output_formatter_prompt: str
+    _on_error: ErrorHandlerFn
+    _max_report_length: int
+
+    def __init__(
+            self,
+            llm_invoker: CompletionLLM,
+            get_entity: Callable | None = None,
+            set_entity: Callable | None = None,
+            get_relation: Callable | None = None,
+            set_relation: Callable | None = None,
+            max_report_length: int | None = None,
+    ):
+        super().__init__(llm_invoker, get_entity=get_entity, set_entity=set_entity, get_relation=get_relation, set_relation=set_relation)
+        """Init method definition."""
+        self._llm = llm_invoker
+        self._extraction_prompt = COMMUNITY_REPORT_PROMPT
+        self._max_report_length = max_report_length or 1500
+
+    def __call__(self, graph: nx.Graph, callback: Callable | None = None):
+        for node_degree in graph.degree:
+            graph.nodes[str(node_degree[0])]["rank"] = int(node_degree[1])
+
+        communities: dict[str, dict[str, list]] = leiden.run(graph, {})
+        total = sum([len(comm.items()) for _, comm in communities.items()])
+        res_str = []
+        res_dict = []
+        over, token_count = 0, 0
+        st = timer()
+        for level, comm in communities.items():
+            logging.info(f"Level {level}: Community: {len(comm.keys())}")
+            for cm_id, ents in comm.items():
+                weight = ents["weight"]
+                ents = ents["nodes"]
+                ent_df = pd.DataFrame(self._get_entity_(ents)).dropna()#[{"entity": n, **graph.nodes[n]} for n in ents])
+                ent_df["entity"] = ent_df["entity_name"]
+                del ent_df["entity_name"]
+                rela_df = pd.DataFrame(self._get_relation_(list(ent_df["entity"]), list(ent_df["entity"]), 10000))
+                rela_df["source"] = rela_df["src_id"]
+                rela_df["target"] = rela_df["tgt_id"]
+                del rela_df["src_id"]
+                del rela_df["tgt_id"]
+
+                prompt_variables = {
+                    "entity_df": ent_df.to_csv(index_label="id"),
+                    "relation_df": rela_df.to_csv(index_label="id")
+                }
+                text = perform_variable_replacements(self._extraction_prompt, variables=prompt_variables)
+                gen_conf = {"temperature": 0.3}
+                try:
+                    response = self._chat(text, [{"role": "user", "content": "Output:"}], gen_conf)
+                    token_count += num_tokens_from_string(text + response)
+                    response = re.sub(r"^[^\{]*", "", response)
+                    response = re.sub(r"[^\}]*$", "", response)
+                    response = re.sub(r"\{\{", "{", response)
+                    response = re.sub(r"\}\}", "}", response)
+                    logging.debug(response)
+                    response = json.loads(response)
+                    if not dict_has_keys_with_types(response, [
+                                ("title", str),
+                                ("summary", str),
+                                ("findings", list),
+                                ("rating", float),
+                                ("rating_explanation", str),
+                            ]):
+                        continue
+                    response["weight"] = weight
+                    response["entities"] = ents
+                except Exception as e:
+                    logging.exception("CommunityReportsExtractor got exception")
+                    self._on_error(e, traceback.format_exc(), None)
+                    continue
+
+                add_community_info2graph(graph, ents, response["title"])
+                res_str.append(self._get_text_output(response))
+                res_dict.append(response)
+                over += 1
+                if callback:
+                    callback(msg=f"Communities: {over}/{total}, elapsed: {timer() - st}s, used tokens: {token_count}")
+
+        return CommunityReportsResult(
+            structured_output=res_dict,
+            output=res_str,
+        )
+
+    def _get_text_output(self, parsed_output: dict) -> str:
+        title = parsed_output.get("title", "Report")
+        summary = parsed_output.get("summary", "")
+        findings = parsed_output.get("findings", [])
+
+        def finding_summary(finding: dict):
+            if isinstance(finding, str):
+                return finding
+            return finding.get("summary")
+
+        def finding_explanation(finding: dict):
+            if isinstance(finding, str):
+                return ""
+            return finding.get("explanation")
+
+        report_sections = "\n\n".join(
+            f"## {finding_summary(f)}\n\n{finding_explanation(f)}" for f in findings
+        )
+        return f"# {title}\n\n{summary}\n\n{report_sections}"