Merge pull request #149 from mindsdb/main

Release 3.1.1

.github/workflows/release.yml

@@ -1,9 +1,8 @@
 name: Release
 
 on:
-  push:
-    branches:
-      - stable
+  release:
+    types: [published]
 
 jobs:
   test:

.github/workflows/mindsdb_python_sdk.yml → .github/workflows/test_prs.yml

@@ -3,8 +3,7 @@ name: PR workflow
 on:
   pull_request:
     branches:
-      - stable
-      - staging
+      - main
 
 jobs:
   test:

examples/using_agents_with_streaming_with_retrieval.py

@@ -14,7 +14,7 @@
 
 agent.add_file('./data/tokaido-rulebook.pdf', 'rule book for the board game Tokaido')
 
-question = "what are the rules for the game takaido?"
+question = "what are the rules for the game tokaido?"
 
 # Stream the completion
 completion_stream = agent.completion_stream([{'question': question, 'answer': None}])
@@ -30,4 +30,4 @@
         full_response += chunk
 
 print("\n\nFull response:")
-print(full_response)
+print(full_response)

examples/using_agents_with_text2sql_streaming.py

@@ -0,0 +1,54 @@
+import mindsdb_sdk
+from uuid import uuid4
+import os
+
+con = mindsdb_sdk.connect()
+
+open_ai_key = os.getenv('OPENAI_API_KEY')
+model_name = 'gpt-4'
+
+# Now create an agent that will use the model we just created.
+agent = con.agents.create(name=f'mindsdb_sql_agent_{model_name}_{uuid4().hex}',
+                          model='gpt-4')
+
+
+# Set up a Postgres data source with our new agent.
+data_source = 'postgres'
+connection_args = {
+    "user": "demo_user",
+    "password": "demo_password",
+    "host": "samples.mindsdb.com",
+    "port": "5432",
+    "database": "demo",
+    "schema": "demo_data"
+}
+description = 'mindsdb demo database'
+database = con.databases.create(
+    f'mindsdb_sql_agent_datasource_{uuid4().hex}',
+    data_source,
+    connection_args
+)
+
+# Actually connect the agent to the datasource.
+agent.add_database(database.name, [], description)
+
+
+question = 'How many three-bedroom houses were sold in 2008?'
+
+completion_stream = agent.completion_stream([{'question': question, 'answer': None}])
+
+# Process the streaming response
+full_response = ""
+for chunk in completion_stream:
+    print(chunk)  # Print the entire chunk for debugging
+    if isinstance(chunk, dict):
+        if 'output' in chunk:
+            full_response += chunk['output']
+    elif isinstance(chunk, str):
+        full_response += chunk
+
+print("\n\nFull response:")
+print(full_response)
+
+con.databases.drop(database.name)
+con.agents.drop(agent.name)

examples/using_database_mind_text2sql.py

@@ -8,11 +8,8 @@
 # Load MindsDB API key from environment variable. or set it here.
 MINDSDB_API_KEY = os.getenv('MINDSDB_API_KEY')
 
-# Set the model name for mind to use
-model_name = 'gpt-4'
-
 # Set the base URL for the MindsDB LiteLLM proxy.
-base_url = 'https://ai.dev.mindsdb.com'
+base_url = 'https://llm.mdb.ai'
 
 
 # Connect to MindsDB LiteLLM proxy.
@@ -42,7 +39,6 @@
     api_key= MINDSDB_API_KEY,
     name = f'my_house_data_mind_{uuid4().hex}',
     data_source_configs=[pg_config],
-    model= model_name
 )
 
 # Actually pass in our tool to get a SQL completion.

mindsdb_sdk/__about__.py

@@ -1,6 +1,6 @@
 __title__ = 'mindsdb_sdk'
 __package_name__ = 'mindsdb_sdk'
-__version__ = '3.1.0'
+__version__ = '3.1.1'
 __description__ = "MindsDB Python SDK, provides an SDK to use a remote mindsdb instance"
 __email__ = "[email protected]"
 __author__ = 'MindsDB Inc'

mindsdb_sdk/connectors/rest_api.py

@@ -279,7 +279,7 @@ def agent_completion(self, project: str, name: str, messages: List[dict]):
     @_try_relogin
     def agent_completion_stream(self, project: str, name: str, messages: List[dict]):
         url = self.url + f'/api/projects/{project}/agents/{name}/completions/stream'
-        stream = requests.post(url, json={'messages': messages}, stream=True)
+        stream = self.session.post(url, json={'messages': messages}, stream=True)
         client = SSEClient(stream)
         for chunk in client.events():
             # Stream objects loaded from SSE events 'data' param.