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deer-flow/.env.example

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# Application Settings
DEBUG=True
APP_ENV=development
# docker build args
NEXT_PUBLIC_API_URL="http://localhost:8000/api"
AGENT_RECURSION_LIMIT=30
# CORS settings
# Comma-separated list of allowed origins for CORS requests
# Example: ALLOWED_ORIGINS=http://localhost:3000,http://example.com
ALLOWED_ORIGINS=http://localhost:3000
# Enable or disable MCP server configuration, the default is false.
# Please enable this feature before securing your front-end and back-end in a managed environment.
# Otherwise, you system could be compromised.
ENABLE_MCP_SERVER_CONFIGURATION=false
# Enable or disable PYTHON_REPL configuration, the default is false.
# Please enable this feature before securing your in a managed environment.
# Otherwise, you system could be compromised.
ENABLE_PYTHON_REPL=false
# Search Engine, Supported values: tavily (recommended), duckduckgo, brave_search, arxiv, searx
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SEARCH_API=tavily
TAVILY_API_KEY=tvly-xxx
# SEARX_HOST=xxx # Required only if SEARCH_API is searx.(compatible with both Searx and SearxNG)
# BRAVE_SEARCH_API_KEY=xxx # Required only if SEARCH_API is brave_search
# JINA_API_KEY=jina_xxx # Optional, default is None
# Optional, RAG provider
# RAG_PROVIDER=vikingdb_knowledge_base
# VIKINGDB_KNOWLEDGE_BASE_API_URL="api-knowledgebase.mlp.cn-beijing.volces.com"
# VIKINGDB_KNOWLEDGE_BASE_API_AK="AKxxx"
# VIKINGDB_KNOWLEDGE_BASE_API_SK=""
# VIKINGDB_KNOWLEDGE_BASE_RETRIEVAL_SIZE=15
# RAG_PROVIDER=ragflow
# RAGFLOW_API_URL="http://localhost:9388"
# RAGFLOW_API_KEY="ragflow-xxx"
# RAGFLOW_RETRIEVAL_SIZE=10
# RAGFLOW_CROSS_LANGUAGES=English,Chinese,Spanish,French,German,Japanese,Korean # Optional. To use RAGFlow's cross-language search, please separate each language with a single comma
# RAG_PROVIDER=dify
# DIFY_API_URL="https://api.dify.ai/v1"
# DIFY_API_KEY="dataset-xxx"
# MOI is a hybrid database that mainly serves enterprise users (https://www.matrixorigin.io/matrixone-intelligence)
# RAG_PROVIDER=moi
# MOI_API_URL="https://cluster.matrixonecloud.cn"
# MOI_API_KEY="xxx-xxx-xxx-xxx"
# MOI_RETRIEVAL_SIZE=10
# MOI_LIST_LIMIT=10
# RAG_PROVIDER: milvus (using free milvus instance on zilliz cloud: https://docs.zilliz.com/docs/quick-start )
# RAG_PROVIDER=milvus
# MILVUS_URI=<endpoint_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_USER=<username_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_PASSWORD=<password_of_self_hosted_milvus_or_zilliz_cloud>
# MILVUS_COLLECTION=documents
# MILVUS_EMBEDDING_PROVIDER=openai # support openai,dashscope
# MILVUS_EMBEDDING_BASE_URL=
# MILVUS_EMBEDDING_MODEL=
# MILVUS_EMBEDDING_API_KEY=
# MILVUS_AUTO_LOAD_EXAMPLES=true
# RAG_PROVIDER: milvus (using milvus lite on Mac or Linux)
# RAG_PROVIDER=milvus
# MILVUS_URI=./milvus_demo.db
# MILVUS_COLLECTION=documents
# MILVUS_EMBEDDING_PROVIDER=openai # support openai,dashscope
# MILVUS_EMBEDDING_BASE_URL=
# MILVUS_EMBEDDING_MODEL=
# MILVUS_EMBEDDING_API_KEY=
# MILVUS_AUTO_LOAD_EXAMPLES=true
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# Optional, volcengine TTS for generating podcast
VOLCENGINE_TTS_APPID=xxx
VOLCENGINE_TTS_ACCESS_TOKEN=xxx
# VOLCENGINE_TTS_CLUSTER=volcano_tts # Optional, default is volcano_tts
# VOLCENGINE_TTS_VOICE_TYPE=BV700_V2_streaming # Optional, default is BV700_V2_streaming
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# Option, for langsmith tracing and monitoring
# LANGSMITH_TRACING=true
# LANGSMITH_ENDPOINT="https://api.smith.langchain.com"
# LANGSMITH_API_KEY="xxx"
# LANGSMITH_PROJECT="xxx"
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# [!NOTE]
# For model settings and other configurations, please refer to `docs/configuration_guide.md`
feat: Enhance chat streaming and tool call processing (#498) * feat: Enhance chat streaming and tool call processing - Added support for MongoDB checkpointer in the chat streaming workflow. - Introduced functions to process tool call chunks and sanitize arguments. - Improved event message creation with additional metadata. - Enhanced error handling for JSON serialization in event messages. - Updated the frontend to convert escaped characters in tool call arguments. - Refactored the workflow input preparation and initial message processing. - Added new dependencies for MongoDB integration and tool argument sanitization. * fix: Update MongoDB checkpointer configuration to use LANGGRAPH_CHECKPOINT_DB_URL * feat: Add support for Postgres checkpointing and update README with database recommendations * feat: Implement checkpoint saver functionality and update MongoDB connection handling * refactor: Improve code formatting and readability in app.py and json_utils.py * refactor: Clean up commented code and improve formatting in server.py * refactor: Remove unused imports and improve code organization in app.py * refactor: Improve code organization and remove unnecessary comments in app.py * chore: use langgraph-checkpoint-postgres==2.0.21 to avoid the JSON convert issue in the latest version, implement chat stream persistant with Postgres * feat: add MongoDB and PostgreSQL support for LangGraph checkpointing, enhance environment variable handling * fix: update comments for clarity on Windows event loop policy * chore: remove empty code changes in MongoDB and PostgreSQL checkpoint tests * chore: clean up unused imports and code in checkpoint-related files * chore: remove empty code changes in test_checkpoint.py * chore: remove empty code changes in test_checkpoint.py * chore: remove empty code changes in test_checkpoint.py * test: update status code assertions in MCP endpoint tests to allow for 403 responses * test: update MCP endpoint tests to assert specific status codes and enable MCP server configuration * chore: remove unnecessary environment variables from unittest workflow * fix: invert condition for MCP server configuration check to raise 403 when disabled * chore: remove pymongo from test dependencies in uv.lock * chore: optimize the _get_agent_name method * test: enhance ChatStreamManager tests for PostgreSQL and MongoDB initialization * test: add persistence tests for ChatStreamManager with PostgreSQL and MongoDB * test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB * test: enhance persistence tests for ChatStreamManager with PostgreSQL and MongoDB to verify message aggregation * test: add unit tests for ChatStreamManager with PostgreSQL and MongoDB * test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB * test: add unit tests for ChatStreamManager initialization with PostgreSQL and MongoDB --------- Co-authored-by: Willem Jiang <willem.jiang@gmail.com>
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# Option, for langgraph mongodb checkpointer
# Enable LangGraph checkpoint saver, supports MongoDB, Postgres
#LANGGRAPH_CHECKPOINT_SAVER=true
# Set the database URL for saving checkpoints
#LANGGRAPH_CHECKPOINT_DB_URL=mongodb://localhost:27017/
#LANGGRAPH_CHECKPOINT_DB_URL=postgresql://localhost:5432/postgres