Release/v0.3.0

.cursor/rules/pytest.mdc

@@ -77,8 +77,8 @@ from pipelex.config_pipelex import get_config
 
 from pipelex.core.pipe import PipeAbstract, update_job_metadata_for_pipe
 from pipelex.core.pipes.pipe_output import PipeOutput, PipeOutputType
-from pipelex.core.pipes.pipe_run_params import PipeRunParams
-from pipelex.core.pipes.pipe_run_params import PipeRunParams
+from pipelex.pipe_run.pipe_run_params import PipeRunParams
+from pipelex.pipe_run.pipe_run_params import PipeRunParams
 from pipelex.pipe_works.pipe_router_protocol import PipeRouterProtocol
 ```
 

.env.example

@@ -1,3 +1 @@
-PYRIGHT_PYTHON_FORCE_VERSION=1.1.398
-
 PIPELEX_INFERENCE_API_KEY=

.pipelex/inference/backends.toml

@@ -2,48 +2,56 @@
 endpoint = "https://inference.pipelex.com/v1"
 api_key = "${PIPELEX_INFERENCE_API_KEY}"
 
-[blackboxai]
-enabled = false
-endpoint = "https://api.blackbox.ai/v1"
-api_key = "${BLACKBOX_API_KEY}"
-
-[openai]
-enabled = false
-api_key = "${OPENAI_API_KEY}"
-
 [azure_openai]
 enabled = false
 endpoint = "${AZURE_API_BASE}"
 api_key = "${AZURE_API_KEY}"
 api_version = "${AZURE_API_VERSION}"
 
+[bedrock]
+enabled = false
+aws_region = "${AWS_REGION}"
+
+[google]
+enabled = false
+api_key = "${GOOGLE_API_KEY}"
+
+[vertexai]
+enabled = false
+gcp_project_id = "${GCP_PROJECT_ID}"
+gcp_location = "${GCP_LOCATION}"
+gcp_credentials_file_path = "${GCP_CREDENTIALS_FILE_PATH}"
+
+[openai]
+enabled = false
+api_key = "${OPENAI_API_KEY}"
+
 [anthropic]
 enabled = false
 api_key = "${ANTHROPIC_API_KEY}"
 claude_4_tokens_limit = 8192
 
-[ollama]
+[mistral]
 enabled = false
-endpoint = "http://localhost:11434/v1"
+api_key = "${MISTRAL_API_KEY}"
 
 [xai]
 enabled = false
 endpoint = "https://api.x.ai/v1"
 api_key = "${XAI_API_KEY}"
 
-[bedrock]
+[ollama]
 enabled = false
-aws_region = "${AWS_REGION}"
+endpoint = "http://localhost:11434/v1"
 
-[vertexai]
+[blackboxai]
 enabled = false
-gcp_project_id = "${GCP_PROJECT_ID}"
-gcp_location = "${GCP_LOCATION}"
-gcp_credentials_file_path = "${GCP_CREDENTIALS_FILE_PATH}"
+endpoint = "https://api.blackbox.ai/v1"
+api_key = "${BLACKBOX_API_KEY}"
 
-[mistral]
+[fal]
 enabled = false
-api_key = "${MISTRAL_API_KEY}"
+api_key = "${FAL_API_KEY}"
 
 [internal] # software-only backend, runs internally, without AI
 enabled = true

.pipelex/inference/backends/anthropic.toml

@@ -1,6 +1,32 @@
-default_sdk = "anthropic"
-default_prompting_target = "anthropic"
+################################################################################
+# Anthropic Backend Configuration
+################################################################################
+#
+# This file defines the model specifications for Anthropic Claude models.
+# It contains model definitions for various Claude language models
+# accessible through the Anthropic API.
+#
+# Configuration structure:
+# - Each model is defined in its own section with the model name as the header
+# - Headers with dots must be quoted (e.g., ["claude-3.5-sonnet"])
+# - Model costs are in USD per million tokens (input/output)
+#
+################################################################################
 
+################################################################################
+# MODEL DEFAULTS
+################################################################################
+
+[defaults]
+model_type = "llm"
+sdk = "anthropic"
+prompting_target = "anthropic"
+
+################################################################################
+# LANGUAGE MODELS
+################################################################################
+
+# --- Claude 3 Series ----------------------------------------------------------
 [claude-3-haiku]
 model_id = "claude-3-haiku-20240307"
 max_tokens = 4096
@@ -17,22 +43,7 @@ outputs = ["text", "structured"]
 max_prompt_images = 100
 costs = { input = 15.0, output = 75.0 }
 
-["claude-3.5-sonnet"]
-model_id = "claude-3-5-sonnet-20240620"
-max_tokens = 8192
-inputs = ["text", "images"]
-outputs = ["text", "structured"]
-max_prompt_images = 100
-costs = { input = 3.0, output = 15.0 }
-
-["claude-3.5-sonnet-v2"]
-model_id = "claude-3-5-sonnet-20241022"
-max_tokens = 8192
-inputs = ["text", "images"]
-outputs = ["text", "structured"]
-max_prompt_images = 100
-costs = { input = 3.0, output = 15.0 }
-
+# --- Claude 3.7 Series --------------------------------------------------------
 ["claude-3.7-sonnet"]
 model_id = "claude-3-7-sonnet-20250219"
 max_tokens = 8192
@@ -41,6 +52,7 @@ outputs = ["text", "structured"]
 max_prompt_images = 100
 costs = { input = 3.0, output = 15.0 }
 
+# --- Claude 4 Series ----------------------------------------------------------
 [claude-4-sonnet]
 model_id = "claude-sonnet-4-20250514"
 max_tokens = 64000
@@ -57,6 +69,7 @@ outputs = ["text", "structured"]
 max_prompt_images = 100
 costs = { input = 3.0, output = 15.0 }
 
+# --- Claude 4.1 Series --------------------------------------------------------
 ["claude-4.1-opus"]
 model_id = "claude-opus-4-1-20250805"
 max_tokens = 32000
@@ -65,3 +78,11 @@ outputs = ["text", "structured"]
 max_prompt_images = 100
 costs = { input = 3.0, output = 15.0 }
 
+# --- Claude 4.5 Series --------------------------------------------------------
+["claude-4.5-sonnet"]
+model_id = "claude-sonnet-4-5-20250929"
+max_tokens = 64000
+inputs = ["text", "images"]
+outputs = ["text", "structured"]
+max_prompt_images = 100
+costs = { input = 3.0, output = 15.0 }

.pipelex/inference/backends/azure_openai.toml

@@ -1,6 +1,32 @@
-default_sdk = "azure_openai"
-default_prompting_target = "openai"
+################################################################################
+# Azure OpenAI Backend Configuration
+################################################################################
+#
+# This file defines the model specifications for Azure OpenAI models.
+# It contains model definitions for OpenAI models deployed on Azure
+# accessible through the Azure OpenAI API.
+#
+# Configuration structure:
+# - Each model is defined in its own section with the model name as the header
+# - Headers with dots must be quoted (e.g., ["gpt-4.1"])
+# - Model costs are in USD per million tokens (input/output)
+#
+################################################################################
 
+################################################################################
+# MODEL DEFAULTS
+################################################################################
+
+[defaults]
+model_type = "llm"
+sdk = "azure_openai"
+prompting_target = "openai"
+
+################################################################################
+# LANGUAGE MODELS
+################################################################################
+
+# --- GPT-4o Series ------------------------------------------------------------
 [gpt-4o]
 model_id = "gpt-4o-2024-11-20"
 inputs = ["text", "images"]
@@ -13,6 +39,7 @@ inputs = ["text", "images"]
 outputs = ["text", "structured"]
 costs = { input = 0.15, output = 0.6 }
 
+# --- GPT-4.1 Series -----------------------------------------------------------
 ["gpt-4.1"]
 model_id = "gpt-4.1-2025-04-14"
 inputs = ["text", "images"]
@@ -31,6 +58,7 @@ inputs = ["text", "images"]
 outputs = ["text", "structured"]
 costs = { input = 0.1, output = 0.4 }
 
+# --- o Series ----------------------------------------------------------------
 [o1-mini]
 model_id = "o1-mini-2024-09-12"
 inputs = ["text"]
@@ -49,6 +77,7 @@ inputs = ["text"]
 outputs = ["text", "structured"]
 costs = { input = 1.1, output = 4.4 }
 
+# --- GPT-5 Series -------------------------------------------------------------
 [gpt-5-mini]
 model_id = "gpt-5-mini-2025-08-07"
 inputs = ["text", "images"]

.pipelex/inference/backends/bedrock.toml

@@ -1,13 +1,40 @@
-default_sdk = "bedrock_aioboto3"
-default_prompting_target = "anthropic"
+################################################################################
+# AWS Bedrock Backend Configuration
+################################################################################
+#
+# This file defines the model specifications for AWS Bedrock models.
+# It contains model definitions for various language models
+# accessible through the AWS Bedrock service.
+#
+# Configuration structure:
+# - Each model is defined in its own section with the model name as the header
+# - Headers with dots must be quoted (e.g., ["claude-3.5-sonnet"])
+# - Model costs are in USD per million tokens (input/output)
+#
+################################################################################
 
+################################################################################
+# MODEL DEFAULTS
+################################################################################
+
+[defaults]
+model_type = "llm"
+sdk = "bedrock_aioboto3"
+prompting_target = "anthropic"
+
+################################################################################
+# LANGUAGE MODELS
+################################################################################
+
+# --- Mistral Models -----------------------------------------------------------
 [bedrock-mistral-large]
 model_id = "mistral.mistral-large-2407-v1:0"
 max_tokens = 8192
 inputs = ["text"]
 outputs = ["text"]
 costs = { input = 4.0, output = 12.0 }
 
+# --- Meta Llama Models --------------------------------------------------------
 [bedrock-meta-llama-3-3-70b-instruct]
 model_id = "us.meta.llama3-3-70b-instruct-v1:0"
 max_tokens = 8192
@@ -16,6 +43,7 @@ outputs = ["text"]
 # TODO: find out the actual cost per million tokens for llama3 on bedrock
 costs = { input = 3.0, output = 15.0 }
 
+# --- Amazon Nova Models -------------------------------------------------------
 [bedrock-nova-pro]
 model_id = "us.amazon.nova-pro-v1:0"
 max_tokens = 5120
@@ -24,28 +52,7 @@ outputs = ["text"]
 # TODO: find out the actual cost per million tokens for nova on bedrock
 costs = { input = 3.0, output = 15.0 }
 
-################################################################################
-# Anthropic Models
-################################################################################
-
-["claude-3.5-sonnet"]
-sdk = "bedrock_anthropic"
-model_id = "us.anthropic.claude-3-5-sonnet-20240620-v1:0"
-max_tokens = 8192
-inputs = ["text", "images"]
-outputs = ["text", "structured"]
-max_prompt_images = 100
-costs = { input = 3.0, output = 15.0 }
-
-["claude-3.5-sonnet-v2"]
-sdk = "bedrock_anthropic"
-model_id = "anthropic.claude-3-5-sonnet-20241022-v2:0"
-max_tokens = 8192
-inputs = ["text", "images"]
-outputs = ["text", "structured"]
-max_prompt_images = 100
-costs = { input = 3.0, output = 15.0 }
-
+# --- Claude LLMs --------------------------------------------------------------
 ["claude-3.7-sonnet"]
 sdk = "bedrock_anthropic"
 model_id = "us.anthropic.claude-3-7-sonnet-20250219-v1:0"
@@ -82,3 +89,13 @@ outputs = ["text", "structured"]
 max_prompt_images = 100
 costs = { input = 3.0, output = 15.0 }
 
+# anthropic.claude-sonnet-4-5-20250929-v1:0,Anthropic,arn:aws:bedrock:us-west-2::foundation-model/anthropic.claude-sonnet-4-5-20250929-v1:0,
+
+["claude-4.5-sonnet"]
+sdk = "bedrock_anthropic"
+model_id = "us.anthropic.claude-sonnet-4-5-20250929-v1:0"
+max_tokens = 8192
+inputs = ["text", "images"]
+outputs = ["text", "structured"]
+max_prompt_images = 100
+costs = { input = 3.0, output = 15.0 }