Merge pull request #3 from agno-agi/v1.4.6

V1.4.6

Author: ysolanky

README.md

@@ -1,4 +1,4 @@
-## Agent Api
+## Agent API
 
 This repo contains the code for a production-grade agentic system built with:
 
@@ -42,13 +42,7 @@ Required: Set the `OPENAI_API_KEY` environment variable using
 export OPENAI_API_KEY=***
 ```
 
-> you may use any model provider, just need to update the agents in the /agents folder
-
-Optional: Set the `EXA_API_KEY` if you'd like to use Exa search
-
-```sh
-export EXA_API_KEY=***
-```
+> You may use any supported model provider, just need to update the respective Agent, Team or Workflow.
 
 3. Start the workspace:
 

agents/sage.py

@@ -7,11 +7,12 @@
 from agno.tools.duckduckgo import DuckDuckGoTools
 from agno.vectordb.pgvector import PgVector, SearchType
 
+from agents.settings import agent_settings
 from db.session import db_url
 
 
 def get_sage(
-    model_id: str = "gpt-4o",
+    model_id: Optional[str] = None,
     user_id: Optional[str] = None,
     session_id: Optional[str] = None,
     debug_mode: bool = True,
@@ -22,12 +23,18 @@ def get_sage(
         additional_context += f"You are interacting with the user: {user_id}"
         additional_context += "</context>"
 
+    model_id = model_id or agent_settings.gpt_4
+
     return Agent(
         name="Sage",
         agent_id="sage",
         user_id=user_id,
         session_id=session_id,
-        model=OpenAIChat(id=model_id),
+        model=OpenAIChat(
+            id=model_id,
+            max_tokens=agent_settings.default_max_completion_tokens,
+            temperature=agent_settings.default_temperature,
+        ),
         # Tools available to the agent
         tools=[DuckDuckGoTools()],
         # Storage for the agent

agents/scholar.py

@@ -6,15 +6,18 @@
 from agno.storage.agent.postgres import PostgresAgentStorage
 from agno.tools.duckduckgo import DuckDuckGoTools
 
+from agents.settings import agent_settings
 from db.session import db_url
 
 
 def get_scholar(
-    model_id: str = "gpt-4o",
+    model_id: Optional[str] = None,
     user_id: Optional[str] = None,
     session_id: Optional[str] = None,
     debug_mode: bool = True,
 ) -> Agent:
+    model_id = model_id or agent_settings.gpt_4
+
     additional_context = ""
     if user_id:
         additional_context += "<context>"
@@ -26,7 +29,11 @@ def get_scholar(
         agent_id="scholar",
         user_id=user_id,
         session_id=session_id,
-        model=OpenAIChat(id=model_id),
+        model=OpenAIChat(
+            id=model_id,
+            max_tokens=agent_settings.default_max_completion_tokens,
+            temperature=agent_settings.default_temperature,
+        ),
         # Tools available to the agent
         tools=[DuckDuckGoTools()],
         # Storage for the agent

agents/settings.py

@@ -0,0 +1,18 @@
+from pydantic_settings import BaseSettings
+
+
+class AgentSettings(BaseSettings):
+    """Agent settings that can be set using environment variables.
+
+    Reference: https://pydantic-docs.helpmanual.io/usage/settings/
+    """
+
+    gpt_4_mini: str = "gpt-4o-mini"
+    gpt_4: str = "gpt-4o"
+    embedding_model: str = "text-embedding-3-small"
+    default_max_completion_tokens: int = 16000
+    default_temperature: float = 0
+
+
+# Create an TeamSettings object
+agent_settings = AgentSettings()

api/routes/playground.py

@@ -4,8 +4,8 @@
 
 from agents.sage import get_sage
 from agents.scholar import get_scholar
-from teams.finance_researcher_team import get_finance_researcher_team
-from teams.multi_language_team import get_multi_language_team
+from teams.finance_researcher import get_finance_researcher_team
+from teams.multi_language import get_multi_language_team
 from workflows.blog_post_generator import get_blog_post_generator
 from workflows.investment_report_generator import get_investment_report_generator
 from workspace.dev_resources import dev_fastapi

api/routes/teams.py

@@ -0,0 +1,98 @@
+from enum import Enum
+from typing import AsyncGenerator, List, Optional
+
+from agno.team import Team
+from fastapi import APIRouter, HTTPException, status
+from fastapi.responses import StreamingResponse
+from pydantic import BaseModel
+
+from teams.operator import TeamType, get_available_teams, get_team
+from utils.log import logger
+
+######################################################
+## Router for the Agent Interface
+######################################################
+
+teams_router = APIRouter(prefix="/teams", tags=["Teams"])
+
+
+class Model(str, Enum):
+    gpt_4o = "gpt-4o"
+    o3_mini = "o3-mini"
+
+
+@teams_router.get("", response_model=List[str])
+async def list_teams():
+    """
+    Returns a list of all available team IDs.
+
+    Returns:
+        List[str]: List of team identifiers
+    """
+    return get_available_teams()
+
+
+async def chat_response_streamer(team: Team, message: str) -> AsyncGenerator:
+    """
+    Stream team responses chunk by chunk.
+
+    Args:
+        team: The team instance to interact with
+        message: User message to process
+
+    Yields:
+        Text chunks from the team response
+    """
+    run_response = await team.arun(message, stream=True)
+    async for chunk in run_response:
+        # chunk.content only contains the text response from the Agent.
+        # For advanced use cases, we should yield the entire chunk
+        # that contains the tool calls and intermediate steps.
+        yield chunk.content
+
+
+class RunRequest(BaseModel):
+    """Request model for an running an team"""
+
+    message: str
+    stream: bool = True
+    model: Model = Model.gpt_4o
+    user_id: Optional[str] = None
+    session_id: Optional[str] = None
+
+
+@teams_router.post("/{team_id}/runs", status_code=status.HTTP_200_OK)
+async def run_team(team_id: TeamType, body: RunRequest):
+    """
+    Sends a message to a specific team and returns the response.
+
+    Args:
+        team_id: The ID of the team to interact with
+        body: Request parameters including the message
+
+    Returns:
+        Either a streaming response or the complete team response
+    """
+    logger.debug(f"RunRequest: {body}")
+
+    try:
+        team: Team = get_team(
+            model_id=body.model.value,
+            team_id=team_id,
+            user_id=body.user_id,
+            session_id=body.session_id,
+        )
+    except Exception as e:
+        raise HTTPException(status_code=status.HTTP_404_NOT_FOUND, detail=f"Team not found: {str(e)}")
+
+    if body.stream:
+        return StreamingResponse(
+            chat_response_streamer(team, body.message),
+            media_type="text/event-stream",
+        )
+    else:
+        response = await team.arun(body.message, stream=False)
+        # response.content only contains the text response from the Agent.
+        # For advanced use cases, we should yield the entire response
+        # that contains the tool calls and intermediate steps.
+        return response.content

api/routes/v1_router.py

@@ -3,8 +3,10 @@
 from api.routes.agents import agents_router
 from api.routes.playground import playground_router
 from api.routes.status import status_router
+from api.routes.teams import teams_router
 
 v1_router = APIRouter(prefix="/v1")
 v1_router.include_router(status_router)
 v1_router.include_router(agents_router)
+v1_router.include_router(teams_router)
 v1_router.include_router(playground_router)

pyproject.toml

@@ -6,12 +6,11 @@ readme = "README.md"
 authors = [{ name = "Agno", email = "hello@agno.com" }]
 
 dependencies = [
-  "agno[aws]==1.3.5",
+  "agno[aws]==1.4.6",
   "aiofiles",
   "alembic",
   "beautifulsoup4",
   "duckduckgo-search",
-  "exa_py",
   "fastapi[standard]",
   "googlesearch-python",
   "lxml_html_clean",
@@ -20,10 +19,7 @@ dependencies = [
   "pgvector",
   "psycopg[binary]",
   "pycountry",
-  "pypdf",
   "sqlalchemy",
-  "streamlit",
-  "tiktoken",
   "typer",
   "yfinance",
 ]

requirements.txt

@@ -1,19 +1,15 @@
 # This file was autogenerated by uv via the following command:
 #    ./scripts/generate_requirements.sh
-agno==1.3.5
+agno==1.4.6
 agno-aws==0.0.1
 agno-docker==0.0.1
 aiofiles==24.1.0
 alembic==1.15.1
-altair==5.5.0
 annotated-types==0.7.0
 anyio==4.9.0
-attrs==25.3.0
 beautifulsoup4==4.13.3
-blinker==1.9.0
 boto3==1.37.19
 botocore==1.37.19
-cachetools==5.5.2
 certifi==2025.1.31
 charset-normalizer==3.4.1
 click==8.1.8
@@ -23,7 +19,6 @@ docker==7.1.0
 docstring-parser==0.16
 duckduckgo-search==7.5.3
 email-validator==2.2.0
-exa-py==1.9.1
 fastapi==0.115.12
 fastapi-cli==0.0.7
 feedparser==6.0.11
@@ -37,58 +32,44 @@ httpcore==1.0.7
 httptools==0.6.4
 httpx==0.28.1
 idna==3.10
-iniconfig==2.1.0
 jinja2==3.1.6
 jiter==0.9.0
 jmespath==1.0.1
 joblib==1.4.2
-jsonschema==4.23.0
-jsonschema-specifications==2024.10.1
 lxml==5.3.1
 lxml-html-clean==0.4.2
 mako==1.3.9
 markdown-it-py==3.0.0
 markupsafe==3.0.2
 mdurl==0.1.2
 multitasking==0.0.11
-narwhals==1.32.0
 newspaper4k==0.9.3.1
 nltk==3.9.1
 numpy==2.2.4
 openai==1.68.2
-packaging==24.2
 pandas==2.2.3
 peewee==3.17.9
 pgvector==0.4.0
 pillow==11.1.0
 platformdirs==4.3.7
-pluggy==1.5.0
 primp==0.14.0
-protobuf==5.29.4
 psycopg==3.2.6
 psycopg-binary==3.2.6
-pyarrow==19.0.1
 pycountry==24.6.1
 pydantic==2.10.6
 pydantic-core==2.27.2
 pydantic-settings==2.8.1
-pydeck==0.9.1
 pygments==2.19.1
-pypdf==5.4.0
-pytest==8.3.5
-pytest-mock==3.14.0
 python-dateutil==2.9.0.post0
 python-dotenv==1.1.0
 python-multipart==0.0.20
 pytz==2025.2
 pyyaml==6.0.2
-referencing==0.36.2
 regex==2024.11.6
 requests==2.32.3
 requests-file==2.1.0
 rich==13.9.4
 rich-toolkit==0.13.2
-rpds-py==0.23.1
 s3transfer==0.11.4
 sgmllib3k==1.0.0
 shellingham==1.5.4
@@ -98,13 +79,8 @@ sniffio==1.3.1
 soupsieve==2.6
 sqlalchemy==2.0.39
 starlette==0.46.1
-streamlit==1.43.2
-tenacity==9.0.0
-tiktoken==0.9.0
 tldextract==5.2.0
-toml==0.10.2
 tomli==2.2.1
-tornado==6.4.2
 tqdm==4.67.1
 typer==0.15.2
 typing-extensions==4.12.2