### What problem does this PR solve?


### Type of change

- [x] Performance Improvement

### What problem does this PR solve?

Improve GraphRAG similarity sensitivity to numeric differences. #8444.

### Type of change

- [x] Refactoring

### What problem does this PR solve?

This PR investigates the cause of #7957.

TL;DR: Incorrect similarity calculations lead to too many candidates.
Since candidate selection involves interaction with the LLM, this causes
significant delays in the program.

What this PR does:

1. **Fix similarity calculation**:
When processing a 64 pages government document, the corrected similarity
calculation reduces the number of candidates from over 100,000 to around
16,000. With a default batch size of 100 pairs per LLM call, this fix
reduces unnecessary LLM interactions from over 1,000 calls to around
160, a roughly 10x improvement.
2. **Add concurrency and timeout limits**: 
Up to 5 entity types are processed in "parallel", each with a 180-second
timeout. These limits may be configurable in future updates.
3. **Improve logging**:
The candidate resolution process now reports progress in real time.
4. **Mitigates potential concurrency risks**


### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)
- [x] Refactoring

## Problem Description
Multiple files in the RAGFlow project contain closure trap issues when
using lambda functions with `trio.open_nursery()`. This problem causes
concurrent tasks created in loops to reference the same variable,
resulting in all tasks processing the same data (the data from the last
iteration) rather than each task processing its corresponding data from
the loop.

## Issue Details
When using a `lambda` to create a closure function and passing it to
`nursery.start_soon()` within a loop, the lambda function captures a
reference to the loop variable rather than its value. For example:

```python
# Problematic code
async with trio.open_nursery() as nursery:
    for d in docs:
        nursery.start_soon(lambda: doc_keyword_extraction(chat_mdl, d, topn))
```

In this pattern, when concurrent tasks begin execution, `d` has already
become the value after the loop ends (typically the last element),
causing all tasks to use the same data.

## Fix Solution
Changed the way concurrent tasks are created with `nursery.start_soon()`
by leveraging Trio's API design to directly pass the function and its
arguments separately:

```python
# Fixed code
async with trio.open_nursery() as nursery:
    for d in docs:
        nursery.start_soon(doc_keyword_extraction, chat_mdl, d, topn)
```

This way, each task uses the parameter values at the time of the
function call, rather than references captured through closures.

## Fixed Files
Fixed closure traps in the following files:

1. `rag/svr/task_executor.py`: 3 fixes, involving document keyword
extraction, question generation, and tag processing
2. `rag/raptor.py`: 1 fix, involving document summarization
3. `graphrag/utils.py`: 2 fixes, involving graph node and edge
processing
4. `graphrag/entity_resolution.py`: 2 fixes, involving entity resolution
and graph node merging
5. `graphrag/general/mind_map_extractor.py`: 2 fixes, involving document
processing
6. `graphrag/general/extractor.py`: 3 fixes, involving content
processing and graph node/edge merging
7. `graphrag/general/community_reports_extractor.py`: 1 fix, involving
community report extraction

## Potential Impact
This fix resolves a serious concurrency issue that could have caused:
- Data processing errors (processing duplicate data)
- Performance degradation (all tasks working on the same data)
- Inconsistent results (some data not being processed)

After the fix, all concurrent tasks should correctly process their
respective data, improving system correctness and reliability.

### Related Issue: 
https://github.com/infiniflow/ragflow/issues/6653 

### Environment:
Using nightly version [ece5903]

Elasticsearch database

Thanks for the review! My fault! I realize my initial testing wasn't
passed.

In graphrag/entity_resolution.py 
 `sub_connect_graph` is a set like` {'HELLO', 'Hi', 'How are you'}`, 
Neither accessing `.nodes` nor `.nodes()` will work, **it still causes
`AttributeError: 'set' object has no attribute 'nodes'`**

In graphrag/general/extractor.py  
The `list.extend() `method performs an in-place operation, directly
modifying the original list and returning ‘None’ rather than the
modified list.
Neither accessing
`sorted(set(node0_attrs[attr].extend(node1_attrs.get(attr, []))))` nor
`sorted(set(node0_attrs[attr].extend(node1_attrs[attr])))` will work,
**it still causes `TypeError: 'NoneType' object is not iterable`**
### Type of change

- [ ] Bug Fix AttributeError: graphrag/entity_resolution.py 
- [ ] Bug Fix TypeError: graphrag/general/extractor.py

### Related Issue: #6653
### Environment:

Using nightly version

Elasticsearch database

### Bug Description:
When clicking the "Entity Resolution" button in KnowledgeGraph,
encountered the following errors:

graphrag/entity_resolution.py

```
list(sub_connect_graph.nodes) AttributeError
```

graphrag/general/extractor.py
```
node0_attrs[attr] = sorted(set(node0_attrs[attr].extend(node1_attrs[attr])))
TypeError: 'NoneType' object is not iterable
```
```
for attr in ["keywords", "source_id"]:  
 KeyError I think attribute "keywords" is in edges not nodes
```
graphrag/utils.py
```
settings.docStoreConn.delete()  # Sync function called as async
```
### Changes Made:

Fixed AttributeError in entity_resolution.py by properly handling graph
nodes

Fixed TypeError and KeyError in extractor.py by separate operations

Corrected async/sync mismatch in document deletion call

### What problem does this PR solve?

EntityResolution batch

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

### What problem does this PR solve?

Removed set_entity and set_relation to avoid accessing doc engine during
graph computation.
Introduced GraphChange to avoid writing unchanged chunks.

### Type of change

- [x] Performance Improvement

### What problem does this PR solve?

#6352

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

### What problem does this PR solve?

Optimized graphrag again

### Type of change

- [x] Performance Improvement

### What problem does this PR solve?

Refactored DocumentService.update_progress

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

### What problem does this PR solve?

close issue #5600 

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

Signed-off-by: yihong0618 <zouzou0208@gmail.com>

### What problem does this PR solve?

Fix nursery.start_soon. Close #5575

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

### What problem does this PR solve?

Made task_executor async to speedup parsing

### Type of change

- [x] Performance Improvement

### What problem does this PR solve?

#4543

### Type of change

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

### What problem does this PR solve?

#4045

### Type of change

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

### What problem does this PR solve?

Use consistent log file names, introduced initLogger

### Type of change

- [ ] Bug Fix (non-breaking change which fixes an issue)
- [ ] New Feature (non-breaking change which adds functionality)
- [ ] Documentation Update
- [x] Refactoring
- [ ] Performance Improvement
- [ ] Other (please describe):

### What problem does this PR solve?

### Type of change

- [x] Refactoring

### What problem does this PR solve?
Simplify the usage of dictionaries

### Type of change

- [x] Refactoring

---------

Co-authored-by: Kevin Hu <kevinhu.sh@gmail.com>

### What problem does this PR solve?

#2270 

### Type of change

- [x] Bug Fix (non-breaking change which fixes an issue)

Signed-off-by: Jin Hai <haijin.chn@gmail.com>

### What problem does this PR solve?

#1594

### Type of change

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