Lang2SQL/.env.example at af21b3ff0e4a25ba05e3c6bb78dfb344c1c190ea · CausalInferenceLab/Lang2SQL · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
###############################################
############## LLM API SELECTION ##############
###############################################

# LLM_PROVIDER=openai
# OPEN_AI_KEY=sk-proj-----
# OPEN_AI_LLM_MODEL=gpt-4.1

# LLM_PROVIDER=gemini
# GEMINI_API_KEY=
# GEMINI_LLM_MODEL=gemini-2.0-flash-lite

LLM_PROVIDER=azure
AZURE_OPENAI_LLM_ENDPOINT=https://-------.openai.azure.com/
AZURE_OPENAI_LLM_KEY=-
AZURE_OPENAI_LLM_MODEL=gpt4o
AZURE_OPENAI_LLM_API_VERSION=2024-07-01-preview

# LLM_PROVIDER=ollama
# OLLAMA_LLM_BASE_URL=
# OLLAMA_LLM_MODEL=

# LLM_PROVIDER=huggingface
# HUGGING_FACE_LLM_REPO_ID=
# HUGGING_FACE_LLM_ENDPOINT=
# HUGGING_FACE_LLM_API_TOKEN=

# LLM_PROVIDER=bedrock
# AWS_BEDROCK_LLM_ACCESS_KEY_ID=
# AWS_BEDROCK_LLM_SECRET_ACCESS_KEY=
# AWS_BEDROCK_LLM_REGION=us-west-2
# AWS_BEDROCK_LLM_ENDPOINT_URL=https://bedrock.us-west-2.amazonaws.com
# AWS_BEDROCK_LLM_MODEL=anthropic.claude-3-5-sonnet-20241022-v2:0\

###############################################
########### Embedding API SElECTION ###########
###############################################
# Only used if you are using an LLM that does not natively support embedding (openai or Azure)
# EMBEDDING_PROVIDER='openai'
# OPEN_AI_EMBEDDING_MODEL='text-embedding-ada-002'

# EMBEDDING_PROVIDER=azure
# AZURE_OPENAI_EMBEDDING_ENDPOINT=https://-------.openai.azure.com/openai/deployments
# AZURE_OPENAI_EMBEDDING_KEY=-
# AZURE_OPENAI_EMBEDDING_MODEL='textembeddingada002' # This is the "deployment" on Azure you want to use for embeddings. Not the base model. Valid base model is text-embedding-ada-002
# AZURE_OPENAI_EMBEDDING_API_VERSION=2023-09-15-preview

# EMBEDDING_PROVIDER='ollama'
# EMBEDDING_BASE_PATH='http://host.docker.internal:11434'
# EMBEDDING_MODEL='nomic-embed-text:latest'
# EMBEDDING_MODEL_MAX_CHUNK_LENGTH=8192

EMBEDDING_PROVIDER='bedrock'
AWS_BEDROCK_EMBEDDING_ACCESS_KEY_ID=--
AWS_BEDROCK_EMBEDDING_SECRET_ACCESS_KEY=-/-+-+-
AWS_BEDROCK_EMBEDDING_REGION=us-west-2
AWS_BEDROCK_EMBEDDING_MODEL=amazon.titan-embed-text-v2:0

# EMBEDDING_PROVIDER='gemini'
# GEMINI_EMBEDDING_API_KEY=
# EMBEDDING_MODEL='text-embedding-004'

# EMBEDDING_PROVIDER='huggingface'
# HUGGING_FACE_EMBEDDING_REPO_ID=
# HUGGING_FACE_EMBEDDING_MODEL=
# HUGGING_FACE_EMBEDDING_API_TOKEN=

DATAHUB_SERVER = 'http://-.-.-.-:-'


###############################################
######## Database Connector SELECTION #########
###############################################

# clickhouse
# DB_TYPE=clickhouse
# CLICKHOUSE_HOST=_._._._
# CLICKHOUSE_PORT=9000
# CLICKHOUSE_USER=_
# CLICKHOUSE_PASSWORD=_
# CLICKHOUSE_DATABASE=_

# databricks
# DB_TYPE=databricks
# DATABRICKS_HOST=_
# DATABRICKS_HTTP_PATH=_
# DATABRICKS_ACCESS_TOKEN=_

# duckdb
# DB_TYPE=duckdb
# DUCKDB_PATH=./data/duckdb.db

# mariadb
# DB_TYPE=mariadb
# MARIADB_HOST=_
# MARIADB_PORT=3306
# MARIADB_USER=_
# MARIADB_PASSWORD=_
# MARIADB_DATABASE=_

# mysql
# DB_TYPE=mysql
# MYSQL_HOST=_
# MYSQL_PORT=3306
# MYSQL_USER=_
# MYSQL_PASSWORD=_
# MYSQL_DATABASE=_

# oracle
# DB_TYPE=oracle
# ORACLE_HOST=_
# ORACLE_PORT=1521
# ORACLE_USER=_
# ORACLE_PASSWORD=_
# ORACLE_DATABASE=_
# ORACLE_SERVICE_NAME=_

# postgres
# DB_TYPE=postgres
# POSTGRES_HOST=_
# POSTGRES_PORT=5432
# POSTGRES_USER=_
# POSTGRES_PASSWORD=_
# POSTGRES_DATABASE=_

# snowflake
# DB_TYPE=snowflake
# SNOWFLAKE_USER=_
# SNOWFLAKE_PASSWORD=_
# SNOWFLAKE_ACCOUNT=_

# sqlite
# DB_TYPE=sqlite
# SQLITE_PATH=./data/sqlite.db