Update mcp_server/.env

fix: Replace non-existent model names and handle Neo4j index race condition

- Replace hardcoded non-existent models (gpt-5-mini, gpt-5-nano, gpt-4.1)
  with valid gpt-4o-mini across config files and default client
- Add exception handling for EquivalentSchemaRuleAlreadyExists in
  Neo4j index creation to prevent race condition failures on startup

.github/workflows/daily_issue_maintenance.yml

@@ -1,123 +0,0 @@
-name: Daily Issue Maintenance
-on:
-  schedule:
-    - cron: "0 0 * * *" # Every day at midnight
-  workflow_dispatch: # Manual trigger option
-
-jobs:
-  find-legacy-duplicates:
-    runs-on: ubuntu-latest
-    if: github.event_name == 'workflow_dispatch'
-    permissions:
-      contents: read
-      issues: write
-      id-token: write
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - uses: anthropics/claude-code-action@v1
-        with:
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          prompt: |
-            REPO: ${{ github.repository }}
-
-            Find potential duplicate issues in the repository:
-
-            1. Use `gh issue list --state open --limit 1000 --json number,title,body,createdAt` to get all open issues
-            2. For each issue, search for potential duplicates using `gh search issues` with keywords from the title and body
-            3. Compare issues to identify true duplicates using these criteria:
-               - Same bug or error being reported
-               - Same feature request (even if worded differently)
-               - Same question being asked
-               - Issues describing the same root problem
-
-            For each duplicate found:
-            - Add a comment linking to the original issue
-            - Apply the "duplicate" label using `gh issue edit`
-            - Be polite and explain why it's a duplicate
-
-            Focus on finding true duplicates, not just similar issues.
-
-          claude_args: |
-            --allowedTools "Bash(gh issue:*),Bash(gh search:*)"
-            --model claude-sonnet-4-5-20250929
-
-  check-stale-issues:
-    runs-on: ubuntu-latest
-    if: github.event_name == 'schedule'
-    permissions:
-      contents: read
-      issues: write
-      id-token: write
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - uses: anthropics/claude-code-action@v1
-        with:
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          prompt: |
-            REPO: ${{ github.repository }}
-
-            Review stale issues and request confirmation:
-
-            1. Use `gh issue list --state open --limit 1000 --json number,title,updatedAt,comments` to get all open issues
-            2. Identify issues that are:
-               - Older than 60 days (based on updatedAt)
-               - Have no comments with "stale-check" label
-               - Are not labeled as "enhancement" or "documentation"
-            3. For each stale issue:
-               - Add a polite comment asking the issue originator if this is still relevant
-               - Apply a "stale-check" label to track that we've asked
-               - Use format: "@{author} Is this still an issue? Please confirm within 14 days or this issue will be closed."
-
-            Use:
-            - `gh issue view` to check issue details and labels
-            - `gh issue comment` to add comments
-            - `gh issue edit` to add the "stale-check" label
-
-          claude_args: |
-            --allowedTools "Bash(gh issue:*)"
-            --model claude-sonnet-4-5-20250929
-
-  close-unconfirmed-issues:
-    runs-on: ubuntu-latest
-    if: github.event_name == 'schedule'
-    needs: check-stale-issues
-    permissions:
-      contents: read
-      issues: write
-      id-token: write
-    steps:
-      - uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - uses: anthropics/claude-code-action@v1
-        with:
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          prompt: |
-            REPO: ${{ github.repository }}
-
-            Close unconfirmed stale issues:
-
-            1. Use `gh issue list --state open --label "stale-check" --limit 1000 --json number,title,comments,updatedAt` to get issues with stale-check label
-            2. For each issue, check if:
-               - The "stale-check" comment was added 14+ days ago
-               - There has been no response from the issue author or activity since the comment
-            3. For issues meeting the criteria:
-               - Add a polite closing comment
-               - Close the issue using `gh issue close`
-               - Use format: "Closing due to inactivity. Feel free to reopen if this is still relevant."
-
-            Use:
-            - `gh issue view` to check issue comments and activity
-            - `gh issue comment` to add closing comment
-            - `gh issue close` to close the issue
-
-          claude_args: |
-            --allowedTools "Bash(gh issue:*)"
-            --model claude-sonnet-4-5-20250929

.github/workflows/issue-triage.yml

@@ -1,141 +0,0 @@
-name: Issue Triage and Deduplication
-on:
-  issues:
-    types: [opened]
-
-jobs:
-  triage:
-    runs-on: ubuntu-latest
-    timeout-minutes: 10
-    permissions:
-      contents: read
-      issues: write
-      id-token: write
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - name: Run Claude Code for Issue Triage
-        uses: anthropics/claude-code-action@v1
-        with:
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          allowed_non_write_users: "*"
-          github_token: ${{ secrets.GITHUB_TOKEN }}
-          prompt: |
-            You're an issue triage assistant for GitHub issues. Your task is to analyze the issue and select appropriate labels from the provided list.
-
-            IMPORTANT: Don't post any comments or messages to the issue. Your only action should be to apply labels. DO NOT check for duplicates - that's handled by a separate job.
-
-            Issue Information:
-            - REPO: ${{ github.repository }}
-            - ISSUE_NUMBER: ${{ github.event.issue.number }}
-
-            TASK OVERVIEW:
-
-            1. First, fetch the list of labels available in this repository by running: `gh label list`. Run exactly this command with nothing else.
-
-            2. Next, use gh commands to get context about the issue:
-               - Use `gh issue view ${{ github.event.issue.number }}` to retrieve the current issue's details
-               - Use `gh search issues` to find similar issues that might provide context for proper categorization
-               - You have access to these Bash commands:
-                 - Bash(gh label list:*) - to get available labels
-                 - Bash(gh issue view:*) - to view issue details
-                 - Bash(gh issue edit:*) - to apply labels to the issue
-                 - Bash(gh search:*) - to search for similar issues
-
-            3. Analyze the issue content, considering:
-               - The issue title and description
-               - The type of issue (bug report, feature request, question, etc.)
-               - Technical areas mentioned
-               - Database mentions (neo4j, falkordb, neptune, etc.)
-               - LLM providers mentioned (openai, anthropic, gemini, groq, etc.)
-               - Components affected (embeddings, search, prompts, server, mcp, etc.)
-
-            4. Select appropriate labels from the available labels list:
-               - Choose labels that accurately reflect the issue's nature
-               - Be specific but comprehensive
-               - Add database-specific labels if mentioned: neo4j, falkordb, neptune
-               - Add component labels if applicable
-               - DO NOT add priority labels (P1, P2, P3)
-               - DO NOT add duplicate label - that's handled by the deduplication job
-
-            5. Apply the selected labels:
-               - Use `gh issue edit ${{ github.event.issue.number }} --add-label "label1,label2,label3"` to apply your selected labels
-               - DO NOT post any comments explaining your decision
-               - DO NOT communicate directly with users
-               - If no labels are clearly applicable, do not apply any labels
-
-            IMPORTANT GUIDELINES:
-            - Be thorough in your analysis
-            - Only select labels from the provided list
-            - DO NOT post any comments to the issue
-            - Your ONLY action should be to apply labels using gh issue edit
-            - It's okay to not add any labels if none are clearly applicable
-            - DO NOT check for duplicates
-
-          claude_args: |
-            --allowedTools "Bash(gh label list:*),Bash(gh issue view:*),Bash(gh issue edit:*),Bash(gh search:*)"
-            --model claude-sonnet-4-5-20250929
-
-  deduplicate:
-    runs-on: ubuntu-latest
-    timeout-minutes: 10
-    needs: triage
-    permissions:
-      contents: read
-      issues: write
-      id-token: write
-
-    steps:
-      - name: Checkout repository
-        uses: actions/checkout@v4
-        with:
-          fetch-depth: 1
-
-      - name: Check for duplicate issues
-        uses: anthropics/claude-code-action@v1
-        with:
-          allowed_non_write_users: "*"
-          prompt: |
-            Analyze this new issue and check if it's a duplicate of existing issues in the repository.
-
-            Issue: #${{ github.event.issue.number }}
-            Repository: ${{ github.repository }}
-
-            Your task:
-            1. Use mcp__github__get_issue to get details of the current issue (#${{ github.event.issue.number }})
-            2. Search for similar existing OPEN issues using mcp__github__search_issues with relevant keywords from the issue title and body
-            3. Compare the new issue with existing ones to identify potential duplicates
-
-            Criteria for duplicates:
-            - Same bug or error being reported
-            - Same feature request (even if worded differently)
-            - Same question being asked
-            - Issues describing the same root problem
-
-            If you find duplicates:
-            - Add a comment on the new issue linking to the original issue(s)
-            - Apply the "duplicate" label to the new issue
-            - Be polite and explain why it's a duplicate
-            - Suggest the user follow the original issue for updates
-
-            If it's NOT a duplicate:
-            - Don't add any comments
-            - Don't modify labels
-
-            Use these tools:
-            - mcp__github__get_issue: Get issue details
-            - mcp__github__search_issues: Search for similar issues (use state:open)
-            - mcp__github__list_issues: List recent issues if needed
-            - mcp__github__create_issue_comment: Add a comment if duplicate found
-            - mcp__github__update_issue: Add "duplicate" label
-
-            Be thorough but efficient. Focus on finding true duplicates, not just similar issues.
-
-          anthropic_api_key: ${{ secrets.ANTHROPIC_API_KEY }}
-          claude_args: |
-            --allowedTools "mcp__github__get_issue,mcp__github__search_issues,mcp__github__list_issues,mcp__github__create_issue_comment,mcp__github__update_issue,mcp__github__get_issue_comments"
-            --model claude-sonnet-4-5-20250929

README.md

@@ -479,7 +479,7 @@ graphiti = Graphiti(
     cross_encoder=GeminiRerankerClient(
         config=LLMConfig(
             api_key=api_key,
-            model="gemini-2.5-flash-lite-preview-06-17"
+            model="gemini-2.5-flash-lite"
         )
     )
 )
@@ -487,7 +487,7 @@ graphiti = Graphiti(
 # Now you can use Graphiti with Google Gemini for all components
 ```
 
-The Gemini reranker uses the `gemini-2.5-flash-lite-preview-06-17` model by default, which is optimized for
+The Gemini reranker uses the `gemini-2.5-flash-lite` model by default, which is optimized for
 cost-effective and low-latency classification tasks. It uses the same boolean classification approach as the OpenAI
 reranker, leveraging Gemini's log probabilities feature to rank passage relevance.
 

graphiti_core/cross_encoder/gemini_reranker_client.py

@@ -37,7 +37,7 @@ else:
 
 logger = logging.getLogger(__name__)
 
-DEFAULT_MODEL = 'gemini-2.5-flash-lite-preview-06-17'
+DEFAULT_MODEL = 'gemini-2.5-flash-lite'
 
 
 class GeminiRerankerClient(CrossEncoderClient):

graphiti_core/driver/neo4j_driver.py

@@ -18,7 +18,9 @@ import logging
 from collections.abc import Coroutine
 from typing import Any
 
+import neo4j.exceptions
 from neo4j import AsyncGraphDatabase, EagerResult
+from neo4j.exceptions import ClientError
 from typing_extensions import LiteralString
 
 from graphiti_core.driver.driver import GraphDriver, GraphDriverSession, GraphProvider
@@ -70,6 +72,15 @@ class Neo4jDriver(GraphDriver):
 
         try:
             result = await self.client.execute_query(cypher_query_, parameters_=params, **kwargs)
+        except neo4j.exceptions.ClientError as e:
+            # Handle race condition when creating indices/constraints in parallel
+            # Neo4j 5.26+ may throw EquivalentSchemaRuleAlreadyExists even with IF NOT EXISTS
+            if 'EquivalentSchemaRuleAlreadyExists' in str(e):
+                logger.info(f'Index or constraint already exists, continuing: {cypher_query_}')
+                # Return empty result to indicate success (index exists)
+                return EagerResult([], None, None)  # type: ignore
+            logger.error(f'Error executing Neo4j query: {e}\n{cypher_query_}\n{params}')
+            raise
         except Exception as e:
             logger.error(f'Error executing Neo4j query: {e}\n{cypher_query_}\n{params}')
             raise
@@ -88,6 +99,21 @@ class Neo4jDriver(GraphDriver):
             'CALL db.indexes() YIELD name DROP INDEX name',
         )
 
+    async def _execute_index_query(self, query: LiteralString) -> EagerResult | None:
+        """Execute an index creation query, ignoring 'index already exists' errors.
+
+        Neo4j can raise EquivalentSchemaRuleAlreadyExists when concurrent CREATE INDEX
+        IF NOT EXISTS queries race, even though the index exists. This is safe to ignore.
+        """
+        try:
+            return await self.execute_query(query)
+        except ClientError as e:
+            # Ignore "equivalent index already exists" error (race condition with IF NOT EXISTS)
+            if 'EquivalentSchemaRuleAlreadyExists' in str(e):
+                logger.debug(f'Index already exists (concurrent creation): {query[:50]}...')
+                return None
+            raise
+
     async def build_indices_and_constraints(self, delete_existing: bool = False):
         if delete_existing:
             await self.delete_all_indexes()
@@ -98,14 +124,7 @@ class Neo4jDriver(GraphDriver):
 
         index_queries: list[LiteralString] = range_indices + fulltext_indices
 
-        await semaphore_gather(
+        await semaphore_gather(*[self._execute_index_query(query) for query in index_queries])
-            *[
-                self.execute_query(
-                    query,
-                )
-                for query in index_queries
-            ]
-        )
 
     async def health_check(self) -> None:
         """Check Neo4j connectivity by running the driver's verify_connectivity method."""

graphiti_core/llm_client/client.py

@@ -48,7 +48,11 @@ def get_extraction_language_instruction(group_id: str | None = None) -> str:
     Returns:
         str: Language instruction to append to system messages
     """
-    return '\n\nAny extracted information should be returned in the same language as it was written in.'
+    return (
+        '\n\nAny extracted information should be returned in the same language as it was written in. '
+        'Only output non-English text when the user has written full sentences or phrases in that non-English language. '
+        'Otherwise, output English.'
+    )
 
 
 logger = logging.getLogger(__name__)

graphiti_core/llm_client/gemini_client.py

@@ -45,7 +45,7 @@ else:
 logger = logging.getLogger(__name__)
 
 DEFAULT_MODEL = 'gemini-2.5-flash'
-DEFAULT_SMALL_MODEL = 'gemini-2.5-flash-lite-preview-06-17'
+DEFAULT_SMALL_MODEL = 'gemini-2.5-flash-lite'
 
 # Maximum output tokens for different Gemini models
 GEMINI_MODEL_MAX_TOKENS = {
@@ -53,7 +53,6 @@ GEMINI_MODEL_MAX_TOKENS = {
     'gemini-2.5-pro': 65536,
     'gemini-2.5-flash': 65536,
     'gemini-2.5-flash-lite': 64000,
-    'models/gemini-2.5-flash-lite-preview-06-17': 64000,
     # Gemini 2.0 models
     'gemini-2.0-flash': 8192,
     'gemini-2.0-flash-lite': 8192,

graphiti_core/llm_client/openai_base_client.py

@@ -31,8 +31,8 @@ from .errors import RateLimitError, RefusalError
 
 logger = logging.getLogger(__name__)
 
-DEFAULT_MODEL = 'gpt-5-mini'
+DEFAULT_MODEL = 'gpt-4o-mini'
-DEFAULT_SMALL_MODEL = 'gpt-5-nano'
+DEFAULT_SMALL_MODEL = 'gpt-4o-mini'
 DEFAULT_REASONING = 'minimal'
 DEFAULT_VERBOSITY = 'low'
 

graphiti_core/search/search_filters.py

@@ -41,6 +41,16 @@ class DateFilter(BaseModel):
     )
 
 
+class PropertyFilter(BaseModel):
+    property_name: str = Field(description='Property name')
+    property_value: str | int | float | None = Field(
+        description='Value you want to match on for the property'
+    )
+    comparison_operator: ComparisonOperator = Field(
+        description='Comparison operator for the property'
+    )
+
+
 class SearchFilters(BaseModel):
     node_labels: list[str] | None = Field(
         default=None, description='List of node labels to filter on'
@@ -53,6 +63,7 @@ class SearchFilters(BaseModel):
     created_at: list[list[DateFilter]] | None = Field(default=None)
     expired_at: list[list[DateFilter]] | None = Field(default=None)
     edge_uuids: list[str] | None = Field(default=None)
+    property_filters: list[PropertyFilter] | None = Field(default=None)
 
 
 def cypher_to_opensearch_operator(op: ComparisonOperator) -> str:

mcp_server/.env

@@ -0,0 +1,49 @@
+# Graphiti MCP Server Environment Configuration
+MCP_SERVER_HOST=gmakai.online
+# Neo4j Database Configuration
+# These settings are used to connect to your Neo4j database
+NEO4J_URI=bolt://neo4j:7687
+NEO4J_USER=neo4j
+NEO4J_PASSWORD=kg3Jsdb2
+
+# OpenAI API Configuration
+# Required for LLM operations
+OPENAI_API_KEY=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
+MODEL_NAME=gpt5.1-nano
+
+# Optional: Only needed for non-standard OpenAI endpoints
+OPENAI_BASE_URL=https://openrouter.ai/api/v1
+
+# Optional: Group ID for namespacing graph data
+# GROUP_ID=my_project
+
+# Concurrency Control
+# Controls how many episodes can be processed simultaneously
+# Default: 10 (suitable for OpenAI Tier 3, mid-tier Anthropic)
+# Adjust based on your LLM provider's rate limits:
+#   - OpenAI Tier 1 (free): 1-2
+#   - OpenAI Tier 2: 5-8
+#   - OpenAI Tier 3: 10-15
+#   - OpenAI Tier 4: 20-50
+#   - Anthropic default: 5-8
+#   - Anthropic high tier: 15-30
+#   - Ollama (local): 1-5
+# See README.md "Concurrency and LLM Provider 429 Rate Limit Errors" for details
+SEMAPHORE_LIMIT=10
+
+# Optional: Path configuration for Docker
+# PATH=/root/.local/bin:${PATH}
+
+# Optional: Memory settings for Neo4j (used in Docker Compose)
+# NEO4J_server_memory_heap_initial__size=512m
+# NEO4J_server_memory_heap_max__size=1G
+# NEO4J_server_memory_pagecache_size=512m
+
+# Azure OpenAI configuration
+# Optional: Only needed for Azure OpenAI endpoints
+# AZURE_OPENAI_ENDPOINT=your_azure_openai_endpoint_here
+# AZURE_OPENAI_API_VERSION=2025-01-01-preview
+# AZURE_OPENAI_DEPLOYMENT_NAME=gpt-4o-gpt-4o-mini-deployment
+# AZURE_OPENAI_EMBEDDING_API_VERSION=2023-05-15
+# AZURE_OPENAI_EMBEDDING_DEPLOYMENT_NAME=text-embedding-3-large-deployment
+# AZURE_OPENAI_USE_MANAGED_IDENTITY=false

mcp_server/config/config-docker-falkordb-combined.yaml

@@ -8,7 +8,7 @@ server:
 
 llm:
   provider: "openai"  # Options: openai, azure_openai, anthropic, gemini, groq
-  model: "gpt-5-mini"
+  model: "gpt-4o-mini"
   max_tokens: 4096
 
   providers:

mcp_server/config/config-docker-falkordb.yaml

@@ -8,7 +8,7 @@ server:
   
 llm:
   provider: "openai"  # Options: openai, azure_openai, anthropic, gemini, groq
-  model: "gpt-5-mini"
+  model: "gpt-4o-mini"
   max_tokens: 4096
   
   providers:

mcp_server/config/config-docker-neo4j.yaml

@@ -8,7 +8,7 @@ server:
   
 llm:
   provider: "openai"  # Options: openai, azure_openai, anthropic, gemini, groq
-  model: "gpt-5-mini"
+  model: "gpt-4o-mini"
   max_tokens: 4096
   
   providers:

mcp_server/config/config.yaml

@@ -12,7 +12,7 @@ server:
   
 llm:
   provider: "openai"  # Options: openai, azure_openai, anthropic, gemini, groq
-  model: "gpt-5-mini"
+  model: "gpt-4o-mini"
   max_tokens: 4096
   
   providers:

mcp_server/docker/docker-compose-neo4j.yml

@@ -1,23 +1,23 @@
 services:
   neo4j:
-    image: neo4j:5.26.0
+    image: neo4j:latest
     ports:
       - "7474:7474" # HTTP
       - "7687:7687" # Bolt
     environment:
-      - NEO4J_AUTH=${NEO4J_USER:-neo4j}/${NEO4J_PASSWORD:-demodemo}
+      - NEO4J_AUTH=${NEO4J_USER:-neo4j}/${NEO4J_PASSWORD:-kg3Jsdb2}
-      - NEO4J_server_memory_heap_initial__size=512m
-      - NEO4J_server_memory_heap_max__size=1G
-      - NEO4J_server_memory_pagecache_size=512m
     volumes:
-      - neo4j_data:/data
+      - /data/neo4j/data:/data
-      - neo4j_logs:/logs
+      - /data/neo4j/logs:/logs
+      - /data/neo4j/plugins:/plugins
+      - /data/neo4j/config:/config
     healthcheck:
       test: ["CMD", "wget", "-O", "/dev/null", "http://localhost:7474"]
       interval: 10s
       timeout: 5s
       retries: 5
       start_period: 30s
+    restart: always
 
   graphiti-mcp:
     image: zepai/knowledge-graph-mcp:standalone
@@ -27,9 +27,9 @@ services:
     build:
       context: ..
       dockerfile: docker/Dockerfile.standalone
-    env_file:
+    #env_file:
-      - path: ../.env
+    #  - path: ../.env
-        required: false
+    #    required: true
     depends_on:
       neo4j:
         condition: service_healthy
@@ -37,13 +37,18 @@ services:
       # Database configuration
       - NEO4J_URI=${NEO4J_URI:-bolt://neo4j:7687}
       - NEO4J_USER=${NEO4J_USER:-neo4j}
-      - NEO4J_PASSWORD=${NEO4J_PASSWORD:-demodemo}
+      - NEO4J_PASSWORD=${NEO4J_PASSWORD:-kg3Jsdb2}
       - NEO4J_DATABASE=${NEO4J_DATABASE:-neo4j}
       # Application configuration
       - GRAPHITI_GROUP_ID=${GRAPHITI_GROUP_ID:-main}
       - SEMAPHORE_LIMIT=${SEMAPHORE_LIMIT:-10}
       - CONFIG_PATH=/app/mcp/config/config.yaml
       - PATH=/root/.local/bin:${PATH}
+      - MCP_SERVER_HOST=gmakai.online
+      - OPENAI_API_KEY=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
+      - MODEL_NAME=gpt5.1-nano
+      - OPENAI_BASE_URL=https://openrouter.ai/api/v1
+
     volumes:
       - ../config/config-docker-neo4j.yaml:/app/mcp/config/config.yaml:ro
     ports:

mcp_server/src/config/schema.py

@@ -147,7 +147,7 @@ class LLMConfig(BaseModel):
     """LLM configuration."""
 
     provider: str = Field(default='openai', description='LLM provider')
-    model: str = Field(default='gpt-4.1', description='Model name')
+    model: str = Field(default='gpt-4o-mini', description='Model name')
     temperature: float | None = Field(
         default=None, description='Temperature (optional, defaults to None for reasoning models)'
     )

pyproject.toml

@@ -1,7 +1,7 @@
 [project]
 name = "graphiti-core"
 description = "A temporal graph building library"
-version = "0.24.1"
+version = "0.24.3"
 authors = [
     { name = "Paul Paliychuk", email = "paul@getzep.com" },
     { name = "Preston Rasmussen", email = "preston@getzep.com" },

signatures/version1/cla.json

@@ -455,6 +455,62 @@
       "created_at": "2025-11-06T08:39:46Z",
       "repoId": 840056306,
       "pullRequestNo": 1053
+    },
+    {
+      "name": "supmo668",
+      "id": 28805779,
+      "comment_id": 3550309664,
+      "created_at": "2025-11-19T01:56:25Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1072
+    },
+    {
+      "name": "donbr",
+      "id": 7340008,
+      "comment_id": 3568970102,
+      "created_at": "2025-11-24T05:19:42Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1081
+    },
+    {
+      "name": "apetti1920",
+      "id": 4706645,
+      "comment_id": 3572726648,
+      "created_at": "2025-11-24T21:07:34Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1084
+    },
+    {
+      "name": "ZLBillShaw",
+      "id": 55940186,
+      "comment_id": 3583997833,
+      "created_at": "2025-11-27T02:45:53Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1085
+    },
+    {
+      "name": "ronaldmego",
+      "id": 17481958,
+      "comment_id": 3617267429,
+      "created_at": "2025-12-05T14:59:42Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1094
+    },
+    {
+      "name": "NShumway",
+      "id": 29358113,
+      "comment_id": 3634967978,
+      "created_at": "2025-12-10T01:26:49Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1102
+    },
+    {
+      "name": "husniadil",
+      "id": 10581130,
+      "comment_id": 3650156180,
+      "created_at": "2025-12-14T03:37:59Z",
+      "repoId": 840056306,
+      "pullRequestNo": 1105
     }
   ]
 }

tests/llm_client/test_gemini_client.py

@@ -455,7 +455,6 @@ class TestGeminiClientGenerateResponse:
             ('gemini-2.5-flash', 65536),
             ('gemini-2.5-pro', 65536),
             ('gemini-2.5-flash-lite', 64000),
-            ('models/gemini-2.5-flash-lite-preview-06-17', 64000),
             ('gemini-2.0-flash', 8192),
             ('gemini-1.5-pro', 8192),
             ('gemini-1.5-flash', 8192),

uv.lock

@@ -808,7 +808,7 @@ wheels = [
 
 [[package]]
 name = "graphiti-core"
-version = "0.24.1"
+version = "0.24.3"
 source = { editable = "." }
 dependencies = [
     { name = "diskcache" },