Ṣẹda opo gigun ti epo gbigbe data | B4N1

Ṣẹda opo gigun ti epo gbigbe data

3 months ago · b4n1 Read time: 6 min

** Orchestrating AI-Agbara DevOps pẹlu DSPy ati LangChain: Apẹrẹ Apẹrẹ fun Iwadii Iṣẹlẹ Aifọwọyi ***

Ni ala-ilẹ oni-nọmba ti o yara ti ode oni, awọn ẹgbẹ DevOps dojukọ ipenija idiju kan ti o pọ si: idamo ati yanju awọn iṣẹlẹ daradara ati imunadoko. Bi iwọn didun ati iyara ti awọn idasilẹ sọfitiwia ti yara, iṣeeṣe ti awọn aṣiṣe ati awọn irufin aabo n dagba. Lati duro niwaju ohun ti tẹ, awọn ajo gbọdọ gba awọn ilana imotuntun ti o lo agbara ti oye Artificial (AI) lati ṣe adaṣe adaṣe iṣẹlẹ ati ipinnu.

Ninu àpilẹkọ yii, a yoo lọ sinu awọn alaye imuse imọ-ẹrọ ti lilo DSPy ati LangChain lati ṣẹda faaji iwọn fun iwadii isẹlẹ adaṣe. Nipa apapọ awọn agbara ti awọn imọ-ẹrọ gige-eti meji wọnyi, a yoo ṣe afihan bi a ṣe le kọ eto ti o lagbara ati ti o munadoko ti o mu imudara ati imunado DevOps pọ si.

** Oye DSPy ati LangChain ***

Ṣaaju ki a to lọ sinu imuse imọ-ẹrọ, jẹ ki a ṣafihan ni ṣoki DSPy ati LangChain.

DSPy

DSPy jẹ ile-ikawe Python ti o pese wiwo ipele giga fun kikọ ati gbigbe awọn ohun elo AI-agbara ṣiṣẹ. O funni ni ọpọlọpọ awọn ẹya, pẹlu:

** Ṣiṣẹ Awoṣe ***: DSPy gba ọ laaye lati sin awọn awoṣe AI bi API, ṣiṣe ki o rọrun lati ṣepọ wọn sinu awọn ohun elo ti o wa tẹlẹ. ** Isakoso awoṣe ***: DSPy n pese awọn irinṣẹ fun iṣakoso awọn awoṣe AI, pẹlu imuṣiṣẹ awoṣe, ibojuwo, ati ikede. ** Isopọpọ data ***: DSPy n jẹ ki isọpọ ailopin ṣiṣẹ pẹlu ọpọlọpọ awọn orisun data, pẹlu awọn data data, APIs, ati awọn ọna ṣiṣe faili.

LangChain

LangChain jẹ ile-ikawe Python ti o pese ilana fun kikọ awọn ohun elo AI ibaraẹnisọrọ. O funni ni ọpọlọpọ awọn ẹya, pẹlu:

** Awọn atọkun ibaraenisọrọ ***: LangChain jẹ ki ẹda awọn atọkun ibaraẹnisọrọ, gẹgẹbi awọn iwiregbe ati awọn oluranlọwọ ohun.

  • ** Ṣiṣẹda Ede Adayeba (NLP) ***: LangChain n pese awọn irinṣẹ fun awọn iṣẹ ṣiṣe NLP, pẹlu iyasọtọ ọrọ, itupalẹ itara, ati idanimọ nkan.
  • ** Ṣiṣakoso awọn aworan oye ***: LangChain jẹ ki ẹda ati iṣakoso awọn aworan oye, eyiti o ṣe pataki fun awọn ohun elo AI ibaraẹnisọrọ.

** Ṣiṣe ile-iṣẹ Iṣaṣewọn ***

Lati kọ faaji ti iwọn fun iwadii isẹlẹ adaṣe, a yoo darapọ awọn agbara ti DSPy ati LangChain. Apẹrẹ wa yoo ni awọn paati wọnyi:

  1. ** Data Ingestion ***: A yoo lo DSPy lati ingest data lati orisirisi awọn orisun, pẹlu àkọọlẹ, metiriki, ati APIs.
  2. ** Ṣiṣeto data ***: A yoo lo DSPy lati ṣe ilana data ti a fi sinu, lilo awọn awoṣe AI lati ṣe idanimọ awọn iṣẹlẹ ti o pọju.
  3. ** Wiwa Iṣẹlẹ ***: A yoo lo LangChain lati ṣẹda wiwo ibaraẹnisọrọ fun wiwa iṣẹlẹ, gbigba awọn olumulo laaye lati ṣe ajọṣepọ pẹlu eto naa ati pese aaye fun iwadii iṣẹlẹ.
  4. **Iṣakoso Aworan Imọye ***: A yoo lo LangChain lati ṣẹda ati ṣakoso awọn aworan oye, eyiti yoo tọju alaye nipa awọn iṣẹlẹ, pẹlu awọn okunfa wọn, awọn ipa, ati awọn ipinnu.
  5. ** Ipinnu ***: A yoo lo DSPy lati lo awọn awoṣe AI lati yanju awọn iṣẹlẹ, fifin iwọn imọ lati sọ fun ṣiṣe ipinnu.

** imuse Imọ-ẹrọ ***

Jẹ ki a lọ sinu awọn alaye imuse imọ-ẹrọ ti faaji wa.

Data Ingestion

A yoo lo DSPy lati jijẹ data lati oriṣiriṣi awọn orisun, pẹlu awọn akọọlẹ, awọn metiriki, ati awọn API. A yoo ṣẹda opo gigun ti epo jijẹ data nipa lilo kilasi 'DataPipeline' ti DSPy, eyiti yoo mu sisẹ data ati ibi ipamọ.

`` Python gbe wọle dspy bi dsp

opo = dsp.DataPipeline()

Ṣafikun awọn orisun data si opo gigun ti epo

pipeline.add_source ("awọn akọọlẹ", dsp.LogSource()) pipeline.add_source ("metiriki", dsp.MetricSource()) pipeline.add_source ("api", dsp.APISource ())

Bẹrẹ opo gigun ti epo

pipeline.bẹrẹ ()


### Ṣiṣẹda data

A yoo lo DSPy lati ṣe ilana data ingested, lilo awọn awoṣe AI lati ṣe idanimọ awọn iṣẹlẹ ti o pọju. A yoo ṣẹda opo gigun ti epo ti n ṣatunṣe data nipa lilo kilasi 'DataPipeline' ti DSPy, eyiti yoo mu sisẹ data ati ibi ipamọ.

`` Python
gbe wọle dspy bi dsp

# Ṣẹda opo gigun ti iṣelọpọ data
opo = dsp.DataPipeline()

# Ṣafikun awọn awoṣe AI si opo gigun ti epo
pipeline.add_model ("iwari_iṣẹlẹ", dsp.IncidentDetectionModel())
pipeline.add_model ("anomaly_detection", dsp.AnomalyDetectionModel ())

# Bẹrẹ opo gigun ti epo
pipeline.bẹrẹ ()

Iwari isẹlẹ

A yoo lo LangChain lati ṣẹda wiwo ibaraẹnisọrọ fun wiwa iṣẹlẹ, gbigba awọn olumulo laaye lati ṣe ajọṣepọ pẹlu eto naa ati pese aaye fun iwadii iṣẹlẹ.

`` Python gbe wọle langchain bi lc

Ṣẹda wiwo ibaraẹnisọrọ kan

ni wiwo = lc.ConversationalInterface ()

Ṣafikun chatbot kan si wiwo naa

interface.add_chatbot ("iṣẹlẹ_detection", lc.Chatbot ())

Bẹrẹ wiwo naa

interface.bẹrẹ ()


### Imọ Aworan Management

A yoo lo LangChain lati ṣẹda ati ṣakoso aworan oye kan, eyiti yoo tọju alaye nipa awọn iṣẹlẹ, pẹlu awọn okunfa wọn, awọn ipa, ati awọn ipinnu.

`` Python
gbe wọle langchain bi lc

# Ṣẹda aworan oye kan
aworan = lc.KnowledgeGraph()

# Ṣafikun awọn apa si ayaworan naa
graph.add_node ("iṣẹlẹ1", lc.Node())
graph.add_node ("iṣẹlẹ2", lc.Node())

# Ṣafikun awọn egbegbe si ayaworan naa
graph.add_edge ("iṣẹlẹ1", "iṣẹlẹ2", lc.Edge ())

Ipinnu

A yoo lo DSPy lati lo awọn awoṣe AI lati yanju awọn iṣẹlẹ, ni lilo iwọn imo lati sọ fun ṣiṣe ipinnu.

`` Python gbe wọle dspy bi dsp

Ṣẹda opo gigun ti o ga

opo = dsp.DataPipeline()

Ṣafikun awọn awoṣe AI si opo gigun ti epo

pipeline.add_model ("ipinnu_iṣẹlẹ", dsp.IncidentResolutionModel())

Bẹrẹ opo gigun ti epo

pipeline.bẹrẹ ()


** Top 5-10 Awọn aṣẹ ti a lo julọ / awọn snippets ***

Eyi ni oke 5-10 awọn aṣẹ ti a lo julọ/snippets fun DSPy ati LangChain:

### DSPy

* `dsp.DataPipeline()`: Ṣẹda opo gigun ti epo fun data jijẹ ati sisẹ.
* `dsp.add_source()`: Ṣafikun orisun data kan si opo gigun ti epo.
* `dsp.add_model()`: Ṣe afikun awoṣe AI kan si opo gigun ti epo.
* `dsp.start()`: Bẹrẹ opo gigun ti epo.
* `dsp.stop()`: Da opo gigun ti epo duro.

### LangChain

* `lc.ConversationalInterface()`: Ṣẹda wiwo ibaraẹnisọrọ fun wiwa iṣẹlẹ.
* `lc.add_chatbot ()`: Ṣe afikun chatbot kan si wiwo.
* `lc.start()`: Bẹrẹ ni wiwo.
* `lc.KnowledgeGraph()`: Ṣẹda a imo awonya fun isẹlẹ isakoso.
* `lc.add_node()`: Ṣafikun ipade kan si awọnyaya.
* `lc.add_edge()`: Ṣafikun eti kan si awọnyaya.

** Iworan ***

Eyi ni iwoye ti faaji wa nipa lilo Chart.js:

`` json
{
  "type": "pieChart",
  "data": {
    "labels": ["Gbigba data", "Ṣiṣe data", "Iwadi Iṣẹlẹ", "Iṣakoso Aworan Imo", "Ipinnu"],
    "awọn ipilẹ data": [
      {
        "label": "Àwọn ohun èlò ìkọ́lé",
        "data": [30, 20, 20, 15, 15],
        "awọ abẹlẹ": [
          "rgba (255, 99, 132, 0.2)",
          "rgba (54, 162, 235, 0.2)",
          "rgba (255, 206, 86, 0.2)",
          "rgba (75, 192, 192, 0.2)",
          "rgba (153, 102, 255, 0.2)"
        ],
        "Awọ aala": [
          "rgba (255, 99, 132, 1)",
          "rgba (54, 162, 235, 1)",
          "rgba (255, 206, 86, 1)",
          "rgba (75, 192, 192, 1)",
          "rgba (153, 102, 255, 1)"
        ],
        "AalaWidth": 1
      }
    ]
  },
  "awọn aṣayan": {
    "akọle": {
      "ifihan": otitọ,
      "ọrọ": "Awọn ohun elo ile-iṣẹ"
    },
    "Àlàyé": {
      "ifihan": otitọ
    }
  }
}

Wiwo yii ṣe afihan awọn paati marun ti faaji wa, pẹlu jijẹ data ati awọn paati sisẹ ti o gba ipin ti o tobi julọ.

Ipari

Ninu àpilẹkọ yii, a ti ṣe afihan bi o ṣe le kọ faaji ti iwọn fun iwadii isẹlẹ adaṣe ni lilo DSPy ati LangChain. Nipa apapọ awọn agbara ti awọn imọ-ẹrọ gige-eti meji wọnyi, a ti ṣẹda eto to lagbara ati lilo daradara ti o mu ṣiṣe ati imunadoko DevOps pọ si. A ti tun pese apẹẹrẹ imuse ti o wulo, pẹlu awọn snippets koodu ati iwoye ti faaji. Nipa gbigba faaji yii, awọn ẹgbẹ le mu ilọsiwaju awọn akoko esi iṣẹlẹ wọn, dinku akoko isunmọ, ati mu igbẹkẹle eto gbogbogbo pọ si.

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