more configs for chat

shinkai-bin/shinkai-node/src/llm_provider/providers/ollama.rs

@@ -1,7 +1,7 @@
 use crate::llm_provider::execution::chains::inference_chain_trait::{FunctionCall, LLMInferenceResponse};
 use crate::llm_provider::llm_stopper::LLMStopper;
 use crate::llm_provider::providers::shared::ollama_api::{
- ollama_prepare_messages, ollama_conversation_prepare_messages_with_tooling, OllamaAPIStreamingResponse,
+ ollama_conversation_prepare_messages_with_tooling, ollama_prepare_messages, OllamaAPIStreamingResponse,
 };
 use crate::managers::model_capabilities_manager::PromptResultEnum;
 
@@ -105,8 +105,11 @@ impl LLMService for Ollama {
  }
  }
 
- // Conditionally add functions to the payload if tools_json is not empty
- if !tools_json.is_empty() {
+ // Add this line to extract the use_tools flag from the config
+ let use_tools = config.as_ref().map_or(true, |c| c.use_tools.unwrap_or(true));
+
+ // Conditionally add tools to the payload if use_tools is true
+ if use_tools && !tools_json.is_empty() {
  payload["tools"] = serde_json::Value::Array(tools_json);
  }
 

shinkai-bin/shinkai-node/src/llm_provider/providers/openai.rs

@@ -4,9 +4,7 @@ use std::sync::Arc;
 use super::super::error::LLMProviderError;
 use super::shared::openai_api::{openai_prepare_messages, MessageContent, OpenAIResponse};
 use super::LLMService;
-use crate::llm_provider::execution::chains::inference_chain_trait::{
- LLMInferenceResponse, FunctionCall,
-};
+use crate::llm_provider::execution::chains::inference_chain_trait::{FunctionCall, LLMInferenceResponse};
 use crate::llm_provider::llm_stopper::LLMStopper;
 use crate::managers::model_capabilities_manager::PromptResultEnum;
 use async_trait::async_trait;
@@ -100,8 +98,11 @@ impl LLMService for OpenAI {
  "max_tokens": result.remaining_tokens,
  });
 
- // Conditionally add functions to the payload if tools_json is not empty
- if !tools_json.is_empty() {
+ // Add this line to extract the use_tools flag from the config
+ let use_tools = config.as_ref().map_or(true, |c| c.use_tools.unwrap_or(true));
+
+ // Conditionally add tools to the payload if use_tools is true
+ if use_tools && !tools_json.is_empty() {
  payload["functions"] = serde_json::Value::Array(tools_json);
  }
 

shinkai-bin/shinkai-node/src/network/v2_api/api_v2_commands_jobs.rs

@@ -704,6 +704,8 @@ impl Node {
  top_p: None,
  stream: None,
  other_model_params: None,
+ use_tools: None,
+ web_search: None,
  });
  let _ = res.send(Ok(config)).await;
  Ok(())

shinkai-bin/shinkai-node/src/network/v2_api/api_v2_commands_prompts.rs

@@ -179,7 +179,7 @@ impl Node {
  let start_time = Instant::now();
 
  // Perform the internal search using LanceShinkaiDb
- match lance_db.read().await.prompt_vector_search(&query, 5).await {
+ match lance_db.read().await.prompt_vector_search(&query, 10).await {
  Ok(prompts) => {
  // Set embeddings to None before returning
  let prompts_without_embeddings: Vec<CustomPrompt> = prompts

shinkai-libs/shinkai-lancedb/Cargo.toml

@@ -11,7 +11,7 @@ uuid = { version = "1.6.1", features = ["v4"] }
 shinkai_tools_primitives = { workspace = true }
 shinkai_vector_resources = { workspace = true }
 shinkai_message_primitives = { workspace = true }
-shinkai_tools_runner = { version = "0.7.14", features = ["built-in-tools"] }
+shinkai_tools_runner = { version = "0.7.15", features = ["built-in-tools"] }
 regex = "1"
 base64 = "0.22.0"
 lancedb = "0.10.0"

shinkai-libs/shinkai-lancedb/src/lance_db/shinkai_prompt_db.rs

@@ -90,7 +90,7 @@ impl LanceShinkaiDb {
  Ok(())
  }
 
- fn convert_batch_to_prompt(batch: &RecordBatch) -> Option<CustomPrompt> {
+ fn convert_batch_to_prompt(batch: &RecordBatch) -> Vec<CustomPrompt> {
  let name_array = batch
  .column_by_name(ShinkaiPromptSchema::name_field())
  .unwrap()
@@ -134,13 +134,15 @@ impl LanceShinkaiDb {
  .downcast_ref::<FixedSizeListArray>()
  .unwrap();
 
- if name_array.len() > 0 {
- let embedding = if vector_array.is_null(0) {
+ let mut prompts = Vec::new();
+
+ for i in 0..name_array.len() {
+ let embedding = if vector_array.is_null(i) {
  None
  } else {
  Some(
  vector_array
- .value(0)
+ .value(i)
  .as_any()
  .downcast_ref::<Float32Array>()
  .unwrap()
@@ -149,18 +151,18 @@ impl LanceShinkaiDb {
  )
  };
 
- Some(CustomPrompt {
- name: name_array.value(0).to_string(),
- prompt: prompt_array.value(0).to_string(),
- is_system: is_system_array.value(0),
- is_enabled: is_enabled_array.value(0),
- version: version_array.value(0).to_string(),
- is_favorite: is_favorite_array.value(0),
+ prompts.push(CustomPrompt {
+ name: name_array.value(i).to_string(),
+ prompt: prompt_array.value(i).to_string(),
+ is_system: is_system_array.value(i),
+ is_enabled: is_enabled_array.value(i),
+ version: version_array.value(i).to_string(),
+ is_favorite: is_favorite_array.value(i),
  embedding,
- })
- } else {
- None
+ });
  }
+
+ prompts
  }
 
  pub async fn get_prompt(&self, name: &str) -> Result<Option<CustomPrompt>, ShinkaiLanceDBError> {
@@ -188,7 +190,8 @@ impl LanceShinkaiDb {
  .map_err(|e| ShinkaiLanceDBError::DatabaseError(e.to_string()))?;
 
  for batch in results {
- if let Some(prompt) = Self::convert_batch_to_prompt(&batch) {
+ let prompts = Self::convert_batch_to_prompt(&batch);
+ for prompt in prompts {
  return Ok(Some(prompt));
  }
  }
@@ -281,11 +284,8 @@ impl LanceShinkaiDb {
  let mut prompts = Vec::new();
  let mut res = query;
  while let Some(Ok(batch)) = res.next().await {
- for _i in 0..batch.num_rows() {
- if let Some(prompt) = Self::convert_batch_to_prompt(&batch) {
- prompts.push(prompt);
- }
- }
+ let prompts_batch = Self::convert_batch_to_prompt(&batch);
+ prompts.extend(prompts_batch);
  }
 
  Ok(prompts)
@@ -311,7 +311,12 @@ impl LanceShinkaiDb {
  let fts_query_builder = self
  .prompt_table
  .query()
- .full_text_search(FullTextSearchQuery::new(query.to_owned()))
+ .full_text_search(FullTextSearchQuery {
+ columns: vec!["prompt".to_string()],
+ query: query.to_owned(),
+ limit: Some(num_results as i64),
+ wand_factor: Some(1.0),
+ })
  .select(Select::columns(&[
  ShinkaiPromptSchema::name_field(),
  ShinkaiPromptSchema::prompt_field(),
@@ -357,16 +362,14 @@ impl LanceShinkaiDb {
 
  let mut fts_res = fts_query;
  while let Some(Ok(batch)) = fts_res.next().await {
- if let Some(prompt) = Self::convert_batch_to_prompt(&batch) {
- fts_results.push(prompt);
- }
+ let prompts = Self::convert_batch_to_prompt(&batch);
+ fts_results.extend(prompts);
  }
 
  let mut vector_res = vector_query;
  while let Some(Ok(batch)) = vector_res.next().await {
- if let Some(prompt) = Self::convert_batch_to_prompt(&batch) {
- vector_results.push(prompt);
- }
+ let prompts = Self::convert_batch_to_prompt(&batch);
+ vector_results.extend(prompts);
  }
 
  // Merge results using interleave and remove duplicates
@@ -399,6 +402,21 @@ impl LanceShinkaiDb {
  }
  }
 
+ // Continue to add results from the remaining iterator if needed
+ while combined_results.len() < num_results as usize {
+ if let Some(fts_item) = fts_iter.next() {
+ if seen.insert(fts_item.name.clone()) {
+ combined_results.push(fts_item);
+ }
+ } else if let Some(vector_item) = vector_iter.next() {
+ if seen.insert(vector_item.name.clone()) {
+ combined_results.push(vector_item);
+ }
+ } else {
+ break;
+ }
+ }
+
  Ok(combined_results)
  }
 
@@ -422,11 +440,8 @@ impl LanceShinkaiDb {
  let mut prompts = Vec::new();
  let mut res = query;
  while let Some(Ok(batch)) = res.next().await {
- for _i in 0..batch.num_rows() {
- if let Some(prompt) = Self::convert_batch_to_prompt(&batch) {
- prompts.push(prompt);
- }
- }
+ let prompts_batch = Self::convert_batch_to_prompt(&batch);
+ prompts.extend(prompts_batch);
  }
 
  Ok(prompts)

shinkai-libs/shinkai-message-primitives/src/schemas/job_config.rs

@@ -13,4 +13,6 @@ pub struct JobConfig {
  pub top_p: Option<f64>,
  pub stream: Option<bool>,
  pub other_model_params: Option<Value>,
+ pub use_tools: Option<bool>,
+ pub web_search: Option<bool>,
 }