high level chat working

src/crewai/agent.py

@@ -136,10 +136,8 @@ class Agent(BaseAgent):
         self._set_knowledge()
         self.agent_ops_agent_name = self.role
 
-        self.llm = create_llm(self.llm, default_model="gpt-4o-mini")
+        self.llm = create_llm(self.llm)
-        self.function_calling_llm = create_llm(
+        self.function_calling_llm = create_llm(self.function_calling_llm)
-            self.function_calling_llm, default_model="gpt-4o-mini"
-        )
 
         if not self.agent_executor:
             self._setup_agent_executor()

src/crewai/cli/constants.py

@@ -158,6 +158,8 @@ MODELS = {
     ],
 }
 
+DEFAULT_LLM_MODEL = "gpt-4o-mini"
+
 JSON_URL = "https://raw.githubusercontent.com/BerriAI/litellm/main/model_prices_and_context_window.json"
 
 

src/crewai/cli/crew_chat.py

@@ -1,7 +1,3 @@
-import json
-import subprocess
-from typing import cast
-
 import click
 
 from crewai.cli.fetch_chat_llm import fetch_chat_llm
@@ -20,20 +16,15 @@ def run_chat():
     # 1) Fetch CrewInputs
     click.secho("Gathering crew inputs via `fetch_crew_inputs()`...", fg="cyan")
     try:
-        crew_inputs: ChatInputs = fetch_crew_inputs()
+        crew_inputs = fetch_crew_inputs()
+        click.echo(f"CrewInputs: {crew_inputs}")
+        if not crew_inputs:
+            click.secho("Error: Failed to fetch crew inputs. Exiting.", fg="red")
+            return
     except Exception as e:
         click.secho(f"Error fetching crew inputs: {e}", fg="red")
         return
 
-    # Check for mandatory fields
-    if not crew_inputs.crew_name:
-        click.secho("Error: Crew name is missing. Exiting.", fg="red")
-        return
-
-    if not crew_inputs.crew_description:
-        click.secho("Error: Crew description is missing. Exiting.", fg="red")
-        return
-
     # 2) Generate a tool schema from the crew inputs
     crew_tool_schema = generate_crew_tool_schema(crew_inputs)
 
@@ -85,7 +76,7 @@ def run_chat():
     # 6) Main chat loop
     while True:
         try:
-            user_input = click.prompt("You: ", type=str)
+            user_input = click.prompt("You", type=str)
             if user_input.strip().lower() in ["exit", "quit"]:
                 click.echo("Exiting chat. Goodbye!")
                 break

src/crewai/cli/fetch_chat_llm.py

@@ -42,29 +42,39 @@ def fetch_chat_llm() -> LLM:
     llm_instance = None
 
     try:
-        # 1) Run the subprocess
         result = subprocess.run(command, capture_output=True, text=True, check=True)
-        stdout_str = result.stdout.strip()
+        stdout_lines = result.stdout.strip().splitlines()
 
-        # 2) Attempt to parse stdout as JSON
+        # Find the line that contains the JSON data
-        if stdout_str:
+        json_line = next(
-            try:
+            (
-                llm_data = json.loads(stdout_str)
+                line
-                llm_instance = LLM.from_dict(llm_data)
+                for line in stdout_lines
-            except json.JSONDecodeError as e:
+                if line.startswith("{") and line.endswith("}")
-                raise RuntimeError(
+            ),
-                    f"Unable to parse JSON from `fetch_chat_llm` output: {e}"
+            None,
-                ) from e
+        )
+
+        if not json_line:
+            raise RuntimeError(
+                "No valid JSON output received from `fetch_chat_llm` command."
+            )
+
+        try:
+            llm_data = json.loads(json_line)
+            llm_instance = LLM.from_dict(llm_data)
+        except json.JSONDecodeError as e:
+            raise RuntimeError(
+                f"Unable to parse JSON from `fetch_chat_llm` output: {e}\nOutput: {repr(json_line)}"
+            ) from e
 
     except subprocess.CalledProcessError as e:
-        # Subprocess error means the script failed
         raise RuntimeError(f"An error occurred while fetching chat LLM: {e}") from e
     except Exception as e:
         raise RuntimeError(
             f"An unexpected error occurred while fetching chat LLM: {e}"
         ) from e
 
-    # Verify that we have a valid LLM
     if not llm_instance:
         raise RuntimeError("Failed to create a valid LLM from `fetch_chat_llm` output.")
 

src/crewai/cli/fetch_crew_inputs.py

@@ -1,5 +1,6 @@
 import json
 import subprocess
+from typing import Optional
 
 import click
 from packaging import version
@@ -9,7 +10,7 @@ from crewai.cli.version import get_crewai_version
 from crewai.types.crew_chat import ChatInputs
 
 
-def fetch_crew_inputs() -> ChatInputs:
+def fetch_crew_inputs() -> Optional[ChatInputs]:
     """
     Fetch the crew's ChatInputs (a structure containing crew_description and input fields)
     by running "uv run fetch_chat_inputs", which prints JSON representing a ChatInputs object.
@@ -37,22 +38,37 @@ def fetch_crew_inputs() -> ChatInputs:
 
     try:
         result = subprocess.run(command, capture_output=True, text=True, check=True)
-        stdout_str = result.stdout.strip()
+        stdout_lines = result.stdout.strip().splitlines()
 
-        if not stdout_str:
+        # Find the line that contains the JSON data
-            return ChatInputs(crew_name=crew_name)
+        json_line = next(
+            (
+                line
+                for line in stdout_lines
+                if line.startswith("{") and line.endswith("}")
+            ),
+            None,
+        )
+
+        if not json_line:
+            click.echo(
+                "No valid JSON output received from `fetch_chat_inputs` command.",
+                err=True,
+            )
+            return None
 
         try:
-            raw_data = json.loads(stdout_str)
+            raw_data = json.loads(json_line)
             chat_inputs = ChatInputs(**raw_data)
             if crew_name:
                 chat_inputs.crew_name = crew_name
             return chat_inputs
         except json.JSONDecodeError as e:
             click.echo(
-                f"Unable to parse JSON from `fetch_chat_inputs` output: {e}", err=True
+                f"Unable to parse JSON from `fetch_chat_inputs` output: {e}\nOutput: {repr(json_line)}",
+                err=True,
             )
-            return ChatInputs(crew_name=crew_name)
+            return None
 
     except subprocess.CalledProcessError as e:
         click.echo(f"An error occurred while fetching chat inputs: {e}", err=True)
@@ -67,4 +83,4 @@ def fetch_crew_inputs() -> ChatInputs:
     except Exception as e:
         click.echo(f"An unexpected error occurred: {e}", err=True)
 
-    return ChatInputs(crew_name=crew_name)
+    return None

src/crewai/cli/templates/crew/pyproject.toml

@@ -14,7 +14,7 @@ run_crew = "{{folder_name}}.main:run"
 train = "{{folder_name}}.main:train"
 replay = "{{folder_name}}.main:replay"
 test = "{{folder_name}}.main:test"
-fetch_inputs = "{{folder_name}}.main:fetch_inputs"
+fetch_chat_inputs = "{{folder_name}}.main:fetch_chat_inputs"
 fetch_chat_llm = "{{folder_name}}.main:fetch_chat_llm"
 
 [build-system]

src/crewai/llm.py

@@ -7,13 +7,17 @@ import warnings
 from contextlib import contextmanager
 from typing import Any, Dict, List, Optional, Union
 
+# Load environment variables from .env file
 import litellm
-from litellm import ModelResponse, get_supported_openai_params
+from dotenv import load_dotenv
+from litellm import get_supported_openai_params
 
 from crewai.utilities.exceptions.context_window_exceeding_exception import (
     LLMContextLengthExceededException,
 )
 
+load_dotenv()
+
 
 class FilteredStream:
     def __init__(self, original_stream):
@@ -111,7 +115,6 @@ class LLM:
         api_version: Optional[str] = None,
         api_key: Optional[str] = None,
         callbacks: List[Any] = [],
-        **kwargs,
     ):
         self.model = model
         self.timeout = timeout
@@ -133,11 +136,9 @@ class LLM:
         self.api_key = api_key
         self.callbacks = callbacks
         self.context_window_size = 0
-        self.kwargs = kwargs
 
         # For safety, we disable passing init params to next calls
         litellm.drop_params = True
-        litellm.set_verbose = False
 
         self.set_callbacks(callbacks)
         self.set_env_callbacks()
@@ -166,7 +167,6 @@ class LLM:
             "api_version": self.api_version,
             "api_key": self.api_key,
             "callbacks": self.callbacks,
-            "kwargs": self.kwargs,
         }
 
     @classmethod
@@ -248,12 +248,13 @@ class LLM:
                     "api_key": self.api_key,
                     "stream": False,
                     "tools": tools,  # pass the tool schema
-                    **self.kwargs,
                 }
 
                 # remove None values
                 params = {k: v for k, v in params.items() if v is not None}
 
+                print(f"Params: {params}")
+
                 response = litellm.completion(**params)
                 response_message = response.choices[0].message
                 text_response = response_message.content or ""
@@ -283,7 +284,7 @@ class LLM:
                         messages.append(
                             {
                                 "tool_call_id": tool_call.id,
-                                "role": "tool",
+                                "role": "function",
                                 "name": function_name,
                                 "content": str(result),
                             }

src/crewai/types/crew_chat.py

@@ -13,8 +13,11 @@ class ChatInputField(BaseModel):
         }
     """
 
-    name: str
+    name: str = Field(..., description="The name of the input field")
-    description: Optional[str] = None
+    description: str = Field(
+        ...,
+        description="A short description of the input field",
+    )
 
 
 class ChatInputs(BaseModel):
@@ -31,6 +34,11 @@ class ChatInputs(BaseModel):
         }
     """
 
-    crew_name: Optional[str] = Field(default="Crew")
+    crew_name: str = Field(..., description="The name of the crew")
-    crew_description: Optional[str] = None
+    crew_description: str = Field(
-    inputs: List[ChatInputField] = Field(default_factory=list)
+        ...,
+        description="A description of the crew's purpose",
+    )
+    inputs: List[ChatInputField] = Field(
+        default_factory=list, description="A list of input fields for the crew"
+    )

src/crewai/utilities/llm_utils.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, Optional, Union
 
 from packaging import version
 
-from crewai.cli.constants import ENV_VARS, LITELLM_PARAMS
+from crewai.cli.constants import DEFAULT_LLM_MODEL, ENV_VARS, LITELLM_PARAMS
 from crewai.cli.utils import read_toml
 from crewai.cli.version import get_crewai_version
 from crewai.llm import LLM
@@ -11,7 +11,6 @@ from crewai.llm import LLM
 
 def create_llm(
     llm_value: Union[str, LLM, Any, None] = None,
-    default_model: str = "gpt-4o-mini",
 ) -> Optional[LLM]:
     """
     Creates or returns an LLM instance based on the given llm_value.
@@ -45,7 +44,7 @@ def create_llm(
 
     # 3) If llm_value is None, parse environment variables or use default
     if llm_value is None:
-        return _llm_via_environment_or_fallback(default_model)
+        return _llm_via_environment_or_fallback()
 
     # 4) Otherwise, attempt to extract relevant attributes from an unknown object (like a config)
     #    e.g. follow the approach used in agent.py
@@ -104,17 +103,17 @@ def create_chat_llm(default_model: str = "gpt-4") -> Optional[LLM]:
         )
 
     # After checks, simply call create_llm with None (meaning "use env or fallback"):
-    return create_llm(None, default_model=default_model)
+    return create_llm(None)
 
 
-def _llm_via_environment_or_fallback(
+def _llm_via_environment_or_fallback() -> Optional[LLM]:
-    default_model: str = "gpt-4o-mini",
-) -> Optional[LLM]:
     """
     Helper function: if llm_value is None, we load environment variables or fallback default model.
     """
     model_name = (
-        os.environ.get("OPENAI_MODEL_NAME") or os.environ.get("MODEL") or default_model
+        os.environ.get("OPENAI_MODEL_NAME")
+        or os.environ.get("MODEL")
+        or DEFAULT_LLM_MODEL
     )
     llm_params = {"model": model_name}